******Results of the Case-control Association tests ****** There are 320 individuals from 20 independent families. 120 of the individuals are affected, 200 of the individuals are unaffected, and 0 of the individuals are of unknown phenotype. The prevalence value used in the RM test statistic is 0.050000 **************************************** Analysis of Marker 1: SNP_1 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.094329 pvalue = 0.758744 df = 1 ***************************************** RCHI test RCHI statistic value = 1.617607 pvalue = 0.203426 df = 1 ***************************************** RW test RW statistic value = 2.151880 pvalue = 0.142395 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5941 sd = 0.0404 freq = 0.5476 sd = 0.0447 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346 allele 2 : freq = 0.4059 sd = 0.0404 freq = 0.4524 sd = 0.0447 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6083 freq = 0.5450 freq = 0.0000 freq = 0.5687 allele 2 : freq = 0.3917 freq = 0.4550 freq = 0.0000 freq = 0.4313 ***************************************** **************************************** Analysis of Marker 2: SNP_2 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.541780 pvalue = 0.11087 df = 1 ***************************************** RCHI test RCHI statistic value = 0.644251 pvalue = 0.422176 df = 1 ***************************************** RW test RW statistic value = 1.260533 pvalue = 0.26155 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3891 sd = 0.0401 freq = 0.3565 sd = 0.0430 freq = 0.0000 sd = 0.0000 freq = 0.3600 sd = 0.0339 allele 2 : freq = 0.6109 sd = 0.0401 freq = 0.6435 sd = 0.0430 freq = 0.0000 sd = 0.0000 freq = 0.6400 sd = 0.0339 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4042 freq = 0.3650 freq = 0.0000 freq = 0.3797 allele 2 : freq = 0.5958 freq = 0.6350 freq = 0.0000 freq = 0.6203 ***************************************** **************************************** Analysis of Marker 3: SNP_3 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.666274 pvalue = 0.102496 df = 1 ***************************************** RCHI test RCHI statistic value = 5.426881 pvalue = 0.0198291 df = 1 ***************************************** RW test RW statistic value = 5.819110 pvalue = 0.015853 df = 1 Frequency of allele 1 is increased in the controls (quasi-score associated to this allele is -34.4000) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4591 sd = 0.0410 freq = 0.5798 sd = 0.0443 freq = 0.0000 sd = 0.0000 freq = 0.5100 sd = 0.0353 allele 2 : freq = 0.5409 sd = 0.0410 freq = 0.4202 sd = 0.0443 freq = 0.0000 sd = 0.0000 freq = 0.4900 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4708 freq = 0.5875 freq = 0.0000 freq = 0.5437 allele 2 : freq = 0.5292 freq = 0.4125 freq = 0.0000 freq = 0.4562 ***************************************** **************************************** Analysis of Marker 4: SNP_4 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.102133 pvalue = 0.749285 df = 1 ***************************************** RCHI test RCHI statistic value = 0.055954 pvalue = 0.813009 df = 1 ***************************************** RW test RW statistic value = 1.754061 pvalue = 0.185367 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3876 sd = 0.0401 freq = 0.3685 sd = 0.0433 freq = 0.0000 sd = 0.0000 freq = 0.3850 sd = 0.0344 allele 2 : freq = 0.6124 sd = 0.0401 freq = 0.6315 sd = 0.0433 freq = 0.0000 sd = 0.0000 freq = 0.6150 sd = 0.0344 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3958 freq = 0.4075 freq = 0.0000 freq = 0.4031 allele 2 : freq = 0.6042 freq = 0.5925 freq = 0.0000 freq = 0.5969 ***************************************** **************************************** Analysis of Marker 5: SNP_5 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 7.560758 pvalue = 0.00596529 df = 1 Frequency of allele 1 is increased in the cases (quasi-score associated to this allele is 28.9263) ***************************************** RCHI test RCHI statistic value = 3.378319 pvalue = 0.0660594 df = 1 ***************************************** RW test RW statistic value = 5.568675 pvalue = 0.0182846 df = 1 Frequency of allele 1 is increased in the cases (quasi-score associated to this allele is 26.2000) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2250 sd = 0.0343 freq = 0.1500 sd = 0.0321 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266 allele 2 : freq = 0.7750 sd = 0.0343 freq = 0.8500 sd = 0.0321 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2292 freq = 0.1575 freq = 0.0000 freq = 0.1844 allele 2 : freq = 0.7708 freq = 0.8425 freq = 0.0000 freq = 0.8156 ***************************************** **************************************** Analysis of Marker 6: SNP_6 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.976915 pvalue = 0.322962 df = 1 ***************************************** RCHI test RCHI statistic value = 0.009979 pvalue = 0.920427 df = 1 ***************************************** RW test RW statistic value = 0.299519 pvalue = 0.584184 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4679 sd = 0.0410 freq = 0.4742 sd = 0.0448 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353 allele 2 : freq = 0.5321 sd = 0.0410 freq = 0.5258 sd = 0.0448 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4500 freq = 0.4550 freq = 0.0000 freq = 0.4531 allele 2 : freq = 0.5500 freq = 0.5450 freq = 0.0000 freq = 0.5469 ***************************************** **************************************** Analysis of Marker 7: SNP_7 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.431746 pvalue = 0.511133 df = 1 ***************************************** RCHI test RCHI statistic value = 1.025777 pvalue = 0.311153 df = 1 ***************************************** RW test RW statistic value = 0.628332 pvalue = 0.427968 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7229 sd = 0.0368 freq = 0.6863 sd = 0.0417 freq = 0.0000 sd = 0.0000 freq = 0.7150 sd = 0.0319 allele 2 : freq = 0.2771 sd = 0.0368 freq = 0.3137 sd = 0.0417 freq = 0.0000 sd = 0.0000 freq = 0.2850 sd = 0.0319 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7292 freq = 0.6825 freq = 0.0000 freq = 0.7000 allele 2 : freq = 0.2708 freq = 0.3175 freq = 0.0000 freq = 0.3000 ***************************************** **************************************** Analysis of Marker 8: SNP_8 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.591587 pvalue = 0.2071 df = 1 ***************************************** RCHI test RCHI statistic value = 0.891104 pvalue = 0.345178 df = 1 ***************************************** RW test RW statistic value = 4.399916 pvalue = 0.0359407 df = 1 Frequency of allele 1 is increased in the cases (quasi-score associated to this allele is 29.0000) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6568 sd = 0.0391 freq = 0.5927 sd = 0.0441 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342 allele 2 : freq = 0.3432 sd = 0.0391 freq = 0.4073 sd = 0.0441 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6583 freq = 0.6125 freq = 0.0000 freq = 0.6297 allele 2 : freq = 0.3417 freq = 0.3875 freq = 0.0000 freq = 0.3703 ***************************************** **************************************** Analysis of Marker 9: SNP_9 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.038005 pvalue = 0.845434 df = 1 ***************************************** RCHI test RCHI statistic value = 0.003284 pvalue = 0.954305 df = 1 ***************************************** RW test RW statistic value = 0.674125 pvalue = 0.411617 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2444 sd = 0.0353 freq = 0.2387 sd = 0.0383 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308 allele 2 : freq = 0.7556 sd = 0.0353 freq = 0.7613 sd = 0.0383 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2500 freq = 0.2525 freq = 0.0000 freq = 0.2516 allele 2 : freq = 0.7500 freq = 0.7475 freq = 0.0000 freq = 0.7484 ***************************************** **************************************** Analysis of Marker 10: SNP_10 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.867182 pvalue = 0.351737 df = 1 ***************************************** RCHI test RCHI statistic value = 0.040639 pvalue = 0.840237 df = 1 ***************************************** RW test RW statistic value = 0.442874 pvalue = 0.505739 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4329 sd = 0.0408 freq = 0.4121 sd = 0.0442 freq = 0.0000 sd = 0.0000 freq = 0.4400 sd = 0.0351 allele 2 : freq = 0.5671 sd = 0.0408 freq = 0.5879 sd = 0.0442 freq = 0.0000 sd = 0.0000 freq = 0.5600 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4125 freq = 0.4225 freq = 0.0000 freq = 0.4188 allele 2 : freq = 0.5875 freq = 0.5775 freq = 0.0000 freq = 0.5813 ***************************************** **************************************** Analysis of Marker 11: SNP_11 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.041034 pvalue = 0.839472 df = 1 ***************************************** RCHI test RCHI statistic value = 3.410574 pvalue = 0.0647799 df = 1 ***************************************** RW test RW statistic value = 0.485456 pvalue = 0.485961 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3926 sd = 0.0402 freq = 0.3597 sd = 0.0431 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345 allele 2 : freq = 0.6074 sd = 0.0402 freq = 0.6403 sd = 0.0431 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3875 freq = 0.3000 freq = 0.0000 freq = 0.3328 allele 2 : freq = 0.6125 freq = 0.7000 freq = 0.0000 freq = 0.6672 ***************************************** **************************************** Analysis of Marker 12: SNP_12 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.256708 pvalue = 0.612391 df = 1 ***************************************** RCHI test RCHI statistic value = 0.290778 pvalue = 0.589723 df = 1 ***************************************** RW test RW statistic value = 0.283941 pvalue = 0.594129 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7444 sd = 0.0359 freq = 0.7145 sd = 0.0406 freq = 0.0000 sd = 0.0000 freq = 0.7300 sd = 0.0314 allele 2 : freq = 0.2556 sd = 0.0359 freq = 0.2855 sd = 0.0406 freq = 0.0000 sd = 0.0000 freq = 0.2700 sd = 0.0314 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7417 freq = 0.7175 freq = 0.0000 freq = 0.7266 allele 2 : freq = 0.2583 freq = 0.2825 freq = 0.0000 freq = 0.2734 ***************************************** **************************************** Analysis of Marker 13: SNP_13 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.011331 pvalue = 0.0826844 df = 1 ***************************************** RCHI test RCHI statistic value = 2.022068 pvalue = 0.155028 df = 1 ***************************************** RW test RW statistic value = 0.154419 pvalue = 0.694347 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8891 sd = 0.0258 freq = 0.8532 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252 allele 2 : freq = 0.1109 sd = 0.0258 freq = 0.1468 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8833 freq = 0.8325 freq = 0.0000 freq = 0.8516 allele 2 : freq = 0.1167 freq = 0.1675 freq = 0.0000 freq = 0.1484 ***************************************** **************************************** Analysis of Marker 14: SNP_14 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.371852 pvalue = 0.241494 df = 1 ***************************************** RCHI test RCHI statistic value = 1.568838 pvalue = 0.210376 df = 1 ***************************************** RW test RW statistic value = 0.863076 pvalue = 0.352879 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4091 sd = 0.0404 freq = 0.4508 sd = 0.0447 freq = 0.0000 sd = 0.0000 freq = 0.4300 sd = 0.0350 allele 2 : freq = 0.5909 sd = 0.0404 freq = 0.5492 sd = 0.0447 freq = 0.0000 sd = 0.0000 freq = 0.5700 sd = 0.0350 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4000 freq = 0.4625 freq = 0.0000 freq = 0.4391 allele 2 : freq = 0.6000 freq = 0.5375 freq = 0.0000 freq = 0.5609 ***************************************** **************************************** Analysis of Marker 15: SNP_15 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.433335 pvalue = 0.510357 df = 1 ***************************************** RCHI test RCHI statistic value = 0.369115 pvalue = 0.543487 df = 1 ***************************************** RW test RW statistic value = 0.262221 pvalue = 0.608598 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3279 sd = 0.0386 freq = 0.3444 sd = 0.0427 freq = 0.0000 sd = 0.0000 freq = 0.3500 sd = 0.0337 allele 2 : freq = 0.6721 sd = 0.0386 freq = 0.6556 sd = 0.0427 freq = 0.0000 sd = 0.0000 freq = 0.6500 sd = 0.0337 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3333 freq = 0.3625 freq = 0.0000 freq = 0.3516 allele 2 : freq = 0.6667 freq = 0.6375 freq = 0.0000 freq = 0.6484 ***************************************** **************************************** Analysis of Marker 16: SNP_16 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.587967 pvalue = 0.207617 df = 1 ***************************************** RCHI test RCHI statistic value = 0.231584 pvalue = 0.630352 df = 1 ***************************************** RW test RW statistic value = 0.378724 pvalue = 0.538287 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4844 sd = 0.0411 freq = 0.4565 sd = 0.0447 freq = 0.0000 sd = 0.0000 freq = 0.4550 sd = 0.0352 allele 2 : freq = 0.5156 sd = 0.0411 freq = 0.5435 sd = 0.0447 freq = 0.0000 sd = 0.0000 freq = 0.5450 sd = 0.0352 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4917 freq = 0.4675 freq = 0.0000 freq = 0.4766 allele 2 : freq = 0.5083 freq = 0.5325 freq = 0.0000 freq = 0.5234 ***************************************** **************************************** Analysis of Marker 17: SNP_17 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.114295 pvalue = 0.29115 df = 1 ***************************************** RCHI test RCHI statistic value = 0.292148 pvalue = 0.588848 df = 1 ***************************************** RW test RW statistic value = 1.529041 pvalue = 0.216256 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2424 sd = 0.0352 freq = 0.2669 sd = 0.0397 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308 allele 2 : freq = 0.7576 sd = 0.0352 freq = 0.7331 sd = 0.0397 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2292 freq = 0.2525 freq = 0.0000 freq = 0.2437 allele 2 : freq = 0.7708 freq = 0.7475 freq = 0.0000 freq = 0.7562 ***************************************** **************************************** Analysis of Marker 18: SNP_18 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.180530 pvalue = 0.277248 df = 1 ***************************************** RCHI test RCHI statistic value = 0.563737 pvalue = 0.452758 df = 1 ***************************************** RW test RW statistic value = 0.186174 pvalue = 0.66612 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6029 sd = 0.0402 freq = 0.6298 sd = 0.0434 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342 allele 2 : freq = 0.3971 sd = 0.0402 freq = 0.3702 sd = 0.0434 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5958 freq = 0.6325 freq = 0.0000 freq = 0.6188 allele 2 : freq = 0.4042 freq = 0.3675 freq = 0.0000 freq = 0.3812 ***************************************** **************************************** Analysis of Marker 19: SNP_19 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.250525 pvalue = 0.616706 df = 1 ***************************************** RCHI test RCHI statistic value = 0.191428 pvalue = 0.661731 df = 1 ***************************************** RW test RW statistic value = 0.148074 pvalue = 0.700383 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2712 sd = 0.0366 freq = 0.2653 sd = 0.0396 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308 allele 2 : freq = 0.7288 sd = 0.0366 freq = 0.7347 sd = 0.0396 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2667 freq = 0.2475 freq = 0.0000 freq = 0.2547 allele 2 : freq = 0.7333 freq = 0.7525 freq = 0.0000 freq = 0.7453 ***************************************** **************************************** Analysis of Marker 20: SNP_20 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.870238 pvalue = 0.171448 df = 1 ***************************************** RCHI test RCHI statistic value = 3.455250 pvalue = 0.0630512 df = 1 ***************************************** RW test RW statistic value = 2.817808 pvalue = 0.0932236 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8462 sd = 0.0297 freq = 0.9161 sd = 0.0249 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234 allele 2 : freq = 0.1538 sd = 0.0297 freq = 0.0839 sd = 0.0249 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8542 freq = 0.9125 freq = 0.0000 freq = 0.8906 allele 2 : freq = 0.1458 freq = 0.0875 freq = 0.0000 freq = 0.1094 ***************************************** **************************************** Analysis of Marker 21: SNP_21 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.000821 pvalue = 0.977139 df = 1 ***************************************** RCHI test RCHI statistic value = 0.948148 pvalue = 0.330191 df = 1 ***************************************** RW test RW statistic value = 0.712608 pvalue = 0.39858 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8800 sd = 0.0267 freq = 0.8927 sd = 0.0278 freq = 0.0000 sd = 0.0000 freq = 0.8800 sd = 0.0230 allele 2 : freq = 0.1200 sd = 0.0267 freq = 0.1073 sd = 0.0278 freq = 0.0000 sd = 0.0000 freq = 0.1200 sd = 0.0230 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8833 freq = 0.9125 freq = 0.0000 freq = 0.9016 allele 2 : freq = 0.1167 freq = 0.0875 freq = 0.0000 freq = 0.0984 ***************************************** **************************************** Analysis of Marker 22: SNP_22 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.015931 pvalue = 0.899559 df = 1 ***************************************** RCHI test RCHI statistic value = 0.129211 pvalue = 0.719252 df = 1 ***************************************** RW test RW statistic value = 0.322705 pvalue = 0.569986 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1709 sd = 0.0310 freq = 0.1500 sd = 0.0321 freq = 0.0000 sd = 0.0000 freq = 0.1750 sd = 0.0269 allele 2 : freq = 0.8291 sd = 0.0310 freq = 0.8500 sd = 0.0321 freq = 0.0000 sd = 0.0000 freq = 0.8250 sd = 0.0269 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1708 freq = 0.1575 freq = 0.0000 freq = 0.1625 allele 2 : freq = 0.8292 freq = 0.8425 freq = 0.0000 freq = 0.8375 ***************************************** **************************************** Analysis of Marker 23: SNP_23 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.166298 pvalue = 0.683423 df = 1 ***************************************** RCHI test RCHI statistic value = 0.018522 pvalue = 0.891744 df = 1 ***************************************** RW test RW statistic value = 0.090670 pvalue = 0.763327 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5956 sd = 0.0404 freq = 0.6048 sd = 0.0439 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346 allele 2 : freq = 0.4044 sd = 0.0404 freq = 0.3952 sd = 0.0439 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6167 freq = 0.6100 freq = 0.0000 freq = 0.6125 allele 2 : freq = 0.3833 freq = 0.3900 freq = 0.0000 freq = 0.3875 ***************************************** **************************************** Analysis of Marker 24: SNP_24 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.827134 pvalue = 0.0926836 df = 1 ***************************************** RCHI test RCHI statistic value = 4.191896 pvalue = 0.0406177 df = 1 ***************************************** RW test RW statistic value = 0.045017 pvalue = 0.831972 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6432 sd = 0.0394 freq = 0.5782 sd = 0.0443 freq = 0.0000 sd = 0.0000 freq = 0.6000 sd = 0.0346 allele 2 : freq = 0.3568 sd = 0.0394 freq = 0.4218 sd = 0.0443 freq = 0.0000 sd = 0.0000 freq = 0.4000 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6417 freq = 0.5400 freq = 0.0000 freq = 0.5781 allele 2 : freq = 0.3583 freq = 0.4600 freq = 0.0000 freq = 0.4219 ***************************************** **************************************** Analysis of Marker 25: SNP_25 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.476881 pvalue = 0.115531 df = 1 ***************************************** RCHI test RCHI statistic value = 3.217389 pvalue = 0.0728597 df = 1 ***************************************** RW test RW statistic value = 2.285647 pvalue = 0.130576 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4762 sd = 0.0411 freq = 0.5573 sd = 0.0446 freq = 0.0000 sd = 0.0000 freq = 0.5150 sd = 0.0353 allele 2 : freq = 0.5238 sd = 0.0411 freq = 0.4427 sd = 0.0446 freq = 0.0000 sd = 0.0000 freq = 0.4850 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4750 freq = 0.5650 freq = 0.0000 freq = 0.5312 allele 2 : freq = 0.5250 freq = 0.4350 freq = 0.0000 freq = 0.4688 ***************************************** **************************************** Analysis of Marker 26: SNP_26 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.606359 pvalue = 0.057559 df = 1 ***************************************** RCHI test RCHI statistic value = 1.562148 pvalue = 0.211351 df = 1 ***************************************** RW test RW statistic value = 0.663684 pvalue = 0.415262 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4879 sd = 0.0411 freq = 0.4202 sd = 0.0443 freq = 0.0000 sd = 0.0000 freq = 0.4350 sd = 0.0351 allele 2 : freq = 0.5121 sd = 0.0411 freq = 0.5798 sd = 0.0443 freq = 0.0000 sd = 0.0000 freq = 0.5650 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4875 freq = 0.4250 freq = 0.0000 freq = 0.4484 allele 2 : freq = 0.5125 freq = 0.5750 freq = 0.0000 freq = 0.5516 ***************************************** **************************************** Analysis of Marker 27: SNP_27 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.308793 pvalue = 0.252613 df = 1 ***************************************** RCHI test RCHI statistic value = 0.298703 pvalue = 0.584697 df = 1 ***************************************** RW test RW statistic value = 1.144688 pvalue = 0.284664 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6668 sd = 0.0388 freq = 0.7065 sd = 0.0409 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328 allele 2 : freq = 0.3332 sd = 0.0388 freq = 0.2935 sd = 0.0409 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6542 freq = 0.6800 freq = 0.0000 freq = 0.6703 allele 2 : freq = 0.3458 freq = 0.3200 freq = 0.0000 freq = 0.3297 ***************************************** **************************************** Analysis of Marker 28: SNP_28 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.055581 pvalue = 0.813621 df = 1 ***************************************** RCHI test RCHI statistic value = 0.074090 pvalue = 0.785473 df = 1 ***************************************** RW test RW statistic value = 1.778238 pvalue = 0.182366 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6147 sd = 0.0400 freq = 0.6113 sd = 0.0438 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345 allele 2 : freq = 0.3853 sd = 0.0400 freq = 0.3887 sd = 0.0438 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6042 freq = 0.6175 freq = 0.0000 freq = 0.6125 allele 2 : freq = 0.3958 freq = 0.3825 freq = 0.0000 freq = 0.3875 ***************************************** **************************************** Analysis of Marker 29: SNP_29 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.060887 pvalue = 0.805099 df = 1 ***************************************** RCHI test RCHI statistic value = 0.320455 pvalue = 0.571335 df = 1 ***************************************** RW test RW statistic value = 0.060906 pvalue = 0.80507 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7768 sd = 0.0342 freq = 0.7597 sd = 0.0384 freq = 0.0000 sd = 0.0000 freq = 0.7750 sd = 0.0295 allele 2 : freq = 0.2232 sd = 0.0342 freq = 0.2403 sd = 0.0384 freq = 0.0000 sd = 0.0000 freq = 0.2250 sd = 0.0295 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7792 freq = 0.7550 freq = 0.0000 freq = 0.7641 allele 2 : freq = 0.2208 freq = 0.2450 freq = 0.0000 freq = 0.2359 ***************************************** **************************************** Analysis of Marker 30: SNP_30 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.003403 pvalue = 0.953479 df = 1 ***************************************** RCHI test RCHI statistic value = 0.119808 pvalue = 0.729243 df = 1 ***************************************** RW test RW statistic value = 0.025746 pvalue = 0.872521 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3712 sd = 0.0397 freq = 0.3452 sd = 0.0427 freq = 0.0000 sd = 0.0000 freq = 0.3700 sd = 0.0341 allele 2 : freq = 0.6288 sd = 0.0397 freq = 0.6548 sd = 0.0427 freq = 0.0000 sd = 0.0000 freq = 0.6300 sd = 0.0341 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3667 freq = 0.3500 freq = 0.0000 freq = 0.3563 allele 2 : freq = 0.6333 freq = 0.6500 freq = 0.0000 freq = 0.6438 ***************************************** **************************************** Analysis of Marker 31: SNP_31 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.036575 pvalue = 0.848333 df = 1 ***************************************** RCHI test RCHI statistic value = 0.023861 pvalue = 0.877239 df = 1 ***************************************** RW test RW statistic value = 0.025322 pvalue = 0.873568 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3835 sd = 0.0400 freq = 0.3758 sd = 0.0435 freq = 0.0000 sd = 0.0000 freq = 0.3700 sd = 0.0341 allele 2 : freq = 0.6165 sd = 0.0400 freq = 0.6242 sd = 0.0435 freq = 0.0000 sd = 0.0000 freq = 0.6300 sd = 0.0341 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3750 freq = 0.3675 freq = 0.0000 freq = 0.3703 allele 2 : freq = 0.6250 freq = 0.6325 freq = 0.0000 freq = 0.6297 ***************************************** **************************************** Analysis of Marker 32: SNP_32 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.405423 pvalue = 0.524302 df = 1 ***************************************** RCHI test RCHI statistic value = 0.507489 pvalue = 0.476228 df = 1 ***************************************** RW test RW statistic value = 2.118774 pvalue = 0.145503 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8315 sd = 0.0308 freq = 0.7984 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.8250 sd = 0.0269 allele 2 : freq = 0.1685 sd = 0.0308 freq = 0.2016 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.1750 sd = 0.0269 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8375 freq = 0.8100 freq = 0.0000 freq = 0.8203 allele 2 : freq = 0.1625 freq = 0.1900 freq = 0.0000 freq = 0.1797 ***************************************** **************************************** Analysis of Marker 33: SNP_33 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.119272 pvalue = 0.729825 df = 1 ***************************************** RCHI test RCHI statistic value = 0.734238 pvalue = 0.391513 df = 1 ***************************************** RW test RW statistic value = 0.130401 pvalue = 0.718016 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2850 sd = 0.0371 freq = 0.2903 sd = 0.0408 freq = 0.0000 sd = 0.0000 freq = 0.2900 sd = 0.0321 allele 2 : freq = 0.7150 sd = 0.0371 freq = 0.7097 sd = 0.0408 freq = 0.0000 sd = 0.0000 freq = 0.7100 sd = 0.0321 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2958 freq = 0.2575 freq = 0.0000 freq = 0.2719 allele 2 : freq = 0.7042 freq = 0.7425 freq = 0.0000 freq = 0.7281 ***************************************** **************************************** Analysis of Marker 34: SNP_34 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.101548 pvalue = 0.749979 df = 1 ***************************************** RCHI test RCHI statistic value = 0.000324 pvalue = 0.985634 df = 1 ***************************************** RW test RW statistic value = 0.045146 pvalue = 0.831735 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3126 sd = 0.0381 freq = 0.3153 sd = 0.0417 freq = 0.0000 sd = 0.0000 freq = 0.2950 sd = 0.0322 allele 2 : freq = 0.6874 sd = 0.0381 freq = 0.6847 sd = 0.0417 freq = 0.0000 sd = 0.0000 freq = 0.7050 sd = 0.0322 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3042 freq = 0.3050 freq = 0.0000 freq = 0.3047 allele 2 : freq = 0.6958 freq = 0.6950 freq = 0.0000 freq = 0.6953 ***************************************** **************************************** Analysis of Marker 35: SNP_35 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.278015 pvalue = 0.598005 df = 1 ***************************************** RCHI test RCHI statistic value = 0.745907 pvalue = 0.387775 df = 1 ***************************************** RW test RW statistic value = 1.009133 pvalue = 0.315111 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6806 sd = 0.0383 freq = 0.6484 sd = 0.0429 freq = 0.0000 sd = 0.0000 freq = 0.6550 sd = 0.0336 allele 2 : freq = 0.3194 sd = 0.0383 freq = 0.3516 sd = 0.0429 freq = 0.0000 sd = 0.0000 freq = 0.3450 sd = 0.0336 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6667 freq = 0.6250 freq = 0.0000 freq = 0.6406 allele 2 : freq = 0.3333 freq = 0.3750 freq = 0.0000 freq = 0.3594 ***************************************** **************************************** Analysis of Marker 36: SNP_36 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.049650 pvalue = 0.823674 df = 1 ***************************************** RCHI test RCHI statistic value = 0.032391 pvalue = 0.857173 df = 1 ***************************************** RW test RW statistic value = 0.273002 pvalue = 0.601325 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2176 sd = 0.0339 freq = 0.2008 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.2200 sd = 0.0293 allele 2 : freq = 0.7824 sd = 0.0339 freq = 0.7992 sd = 0.0360 freq = 0.0000 sd = 0.0000 freq = 0.7800 sd = 0.0293 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2250 freq = 0.2175 freq = 0.0000 freq = 0.2203 allele 2 : freq = 0.7750 freq = 0.7825 freq = 0.0000 freq = 0.7797 ***************************************** **************************************** Analysis of Marker 37: SNP_37 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.443225 pvalue = 0.50557 df = 1 ***************************************** RCHI test RCHI statistic value = 0.396154 pvalue = 0.529082 df = 1 ***************************************** RW test RW statistic value = 2.171522 pvalue = 0.140587 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8300 sd = 0.0309 freq = 0.8508 sd = 0.0320 freq = 0.0000 sd = 0.0000 freq = 0.8500 sd = 0.0252 allele 2 : freq = 0.1700 sd = 0.0309 freq = 0.1492 sd = 0.0320 freq = 0.0000 sd = 0.0000 freq = 0.1500 sd = 0.0252 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8375 freq = 0.8600 freq = 0.0000 freq = 0.8516 allele 2 : freq = 0.1625 freq = 0.1400 freq = 0.0000 freq = 0.1484 ***************************************** **************************************** Analysis of Marker 38: SNP_38 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.011195 pvalue = 0.915737 df = 1 ***************************************** RCHI test RCHI statistic value = 0.023039 pvalue = 0.879356 df = 1 ***************************************** RW test RW statistic value = 0.001819 pvalue = 0.965985 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4253 sd = 0.0407 freq = 0.4234 sd = 0.0444 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348 allele 2 : freq = 0.5747 sd = 0.0407 freq = 0.5766 sd = 0.0444 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4125 freq = 0.4050 freq = 0.0000 freq = 0.4078 allele 2 : freq = 0.5875 freq = 0.5950 freq = 0.0000 freq = 0.5922 ***************************************** **************************************** Analysis of Marker 39: SNP_39 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.050690 pvalue = 0.821867 df = 1 ***************************************** RCHI test RCHI statistic value = 0.336850 pvalue = 0.561653 df = 1 ***************************************** RW test RW statistic value = 5.000869 pvalue = 0.0253346 df = 1 Frequency of allele 1 is increased in the cases (quasi-score associated to this allele is 32.0000) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5018 sd = 0.0411 freq = 0.4629 sd = 0.0448 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354 allele 2 : freq = 0.4982 sd = 0.0411 freq = 0.5371 sd = 0.0448 freq = 0.0000 sd = 0.0000 freq = 0.5000 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5042 freq = 0.4750 freq = 0.0000 freq = 0.4859 allele 2 : freq = 0.4958 freq = 0.5250 freq = 0.0000 freq = 0.5141 ***************************************** **************************************** Analysis of Marker 40: SNP_40 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.095282 pvalue = 0.757567 df = 1 ***************************************** RCHI test RCHI statistic value = 0.009979 pvalue = 0.920427 df = 1 ***************************************** RW test RW statistic value = 1.703184 pvalue = 0.191872 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5600 sd = 0.0408 freq = 0.5363 sd = 0.0448 freq = 0.0000 sd = 0.0000 freq = 0.5600 sd = 0.0351 allele 2 : freq = 0.4400 sd = 0.0408 freq = 0.4637 sd = 0.0448 freq = 0.0000 sd = 0.0000 freq = 0.4400 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5500 freq = 0.5450 freq = 0.0000 freq = 0.5469 allele 2 : freq = 0.4500 freq = 0.4550 freq = 0.0000 freq = 0.4531 ***************************************** **************************************** Analysis of Marker 41: SNP_41 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.992144 pvalue = 0.158117 df = 1 ***************************************** RCHI test RCHI statistic value = 2.127903 pvalue = 0.144639 df = 1 ***************************************** RW test RW statistic value = 0.197124 pvalue = 0.657053 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8182 sd = 0.0317 freq = 0.7855 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.7950 sd = 0.0285 allele 2 : freq = 0.1818 sd = 0.0317 freq = 0.2145 sd = 0.0369 freq = 0.0000 sd = 0.0000 freq = 0.2050 sd = 0.0285 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8250 freq = 0.7650 freq = 0.0000 freq = 0.7875 allele 2 : freq = 0.1750 freq = 0.2350 freq = 0.0000 freq = 0.2125 ***************************************** **************************************** Analysis of Marker 42: SNP_42 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.522358 pvalue = 0.217263 df = 1 ***************************************** RCHI test RCHI statistic value = 0.548584 pvalue = 0.458897 df = 1 ***************************************** RW test RW statistic value = 0.526928 pvalue = 0.467901 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3579 sd = 0.0394 freq = 0.3677 sd = 0.0433 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342 allele 2 : freq = 0.6421 sd = 0.0394 freq = 0.6323 sd = 0.0433 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3417 freq = 0.3775 freq = 0.0000 freq = 0.3641 allele 2 : freq = 0.6583 freq = 0.6225 freq = 0.0000 freq = 0.6359 ***************************************** **************************************** Analysis of Marker 43: SNP_43 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.514816 pvalue = 0.218406 df = 1 ***************************************** RCHI test RCHI statistic value = 2.590491 pvalue = 0.107507 df = 1 ***************************************** RW test RW statistic value = 1.840295 pvalue = 0.174916 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5526 sd = 0.0409 freq = 0.6097 sd = 0.0438 freq = 0.0000 sd = 0.0000 freq = 0.5550 sd = 0.0351 allele 2 : freq = 0.4474 sd = 0.0409 freq = 0.3903 sd = 0.0438 freq = 0.0000 sd = 0.0000 freq = 0.4450 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5250 freq = 0.6050 freq = 0.0000 freq = 0.5750 allele 2 : freq = 0.4750 freq = 0.3950 freq = 0.0000 freq = 0.4250 ***************************************** **************************************** Analysis of Marker 44: SNP_44 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.703587 pvalue = 0.401581 df = 1 ***************************************** RCHI test RCHI statistic value = 0.002723 pvalue = 0.958383 df = 1 ***************************************** RW test RW statistic value = 0.435257 pvalue = 0.509421 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3621 sd = 0.0395 freq = 0.3839 sd = 0.0437 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342 allele 2 : freq = 0.6379 sd = 0.0395 freq = 0.6161 sd = 0.0437 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3500 freq = 0.3475 freq = 0.0000 freq = 0.3484 allele 2 : freq = 0.6500 freq = 0.6525 freq = 0.0000 freq = 0.6516 ***************************************** **************************************** Analysis of Marker 45: SNP_45 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.547760 pvalue = 0.0596259 df = 1 ***************************************** RCHI test RCHI statistic value = 0.801658 pvalue = 0.370598 df = 1 ***************************************** RW test RW statistic value = 1.984394 pvalue = 0.158928 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7932 sd = 0.0333 freq = 0.7629 sd = 0.0382 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304 allele 2 : freq = 0.2068 sd = 0.0333 freq = 0.2371 sd = 0.0382 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8000 freq = 0.7625 freq = 0.0000 freq = 0.7766 allele 2 : freq = 0.2000 freq = 0.2375 freq = 0.0000 freq = 0.2234 ***************************************** **************************************** Analysis of Marker 46: SNP_46 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.555893 pvalue = 0.109884 df = 1 ***************************************** RCHI test RCHI statistic value = 0.569332 pvalue = 0.450524 df = 1 ***************************************** RW test RW statistic value = 1.470829 pvalue = 0.225215 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3535 sd = 0.0393 freq = 0.3105 sd = 0.0416 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328 allele 2 : freq = 0.6465 sd = 0.0393 freq = 0.6895 sd = 0.0416 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3583 freq = 0.3225 freq = 0.0000 freq = 0.3359 allele 2 : freq = 0.6417 freq = 0.6775 freq = 0.0000 freq = 0.6641 ***************************************** **************************************** Analysis of Marker 47: SNP_47 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.045368 pvalue = 0.83133 df = 1 ***************************************** RCHI test RCHI statistic value = 0.012936 pvalue = 0.909447 df = 1 ***************************************** RW test RW statistic value = 0.516922 pvalue = 0.472158 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0971 sd = 0.0243 freq = 0.0903 sd = 0.0257 freq = 0.0000 sd = 0.0000 freq = 0.1000 sd = 0.0212 allele 2 : freq = 0.9029 sd = 0.0243 freq = 0.9097 sd = 0.0257 freq = 0.0000 sd = 0.0000 freq = 0.9000 sd = 0.0212 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.0958 freq = 0.0925 freq = 0.0000 freq = 0.0938 allele 2 : freq = 0.9042 freq = 0.9075 freq = 0.0000 freq = 0.9062 ***************************************** **************************************** Analysis of Marker 48: SNP_48 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.079053 pvalue = 0.778585 df = 1 ***************************************** RCHI test RCHI statistic value = 1.355646 pvalue = 0.244293 df = 1 ***************************************** RW test RW statistic value = 0.050094 pvalue = 0.822899 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2347 sd = 0.0349 freq = 0.2202 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.2350 sd = 0.0300 allele 2 : freq = 0.7653 sd = 0.0349 freq = 0.7798 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.7650 sd = 0.0300 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2375 freq = 0.1900 freq = 0.0000 freq = 0.2078 allele 2 : freq = 0.7625 freq = 0.8100 freq = 0.0000 freq = 0.7922 ***************************************** **************************************** Analysis of Marker 49: SNP_49 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.017818 pvalue = 0.893811 df = 1 ***************************************** RCHI test RCHI statistic value = 0.027477 pvalue = 0.868344 df = 1 ***************************************** RW test RW statistic value = 0.003123 pvalue = 0.955433 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5038 sd = 0.0411 freq = 0.4863 sd = 0.0449 freq = 0.0000 sd = 0.0000 freq = 0.4950 sd = 0.0354 allele 2 : freq = 0.4962 sd = 0.0411 freq = 0.5137 sd = 0.0449 freq = 0.0000 sd = 0.0000 freq = 0.5050 sd = 0.0354 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4917 freq = 0.5000 freq = 0.0000 freq = 0.4969 allele 2 : freq = 0.5083 freq = 0.5000 freq = 0.0000 freq = 0.5031 ***************************************** **************************************** Analysis of Marker 50: SNP_50 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.001927 pvalue = 0.964983 df = 1 ***************************************** RCHI test RCHI statistic value = 0.219820 pvalue = 0.639177 df = 1 ***************************************** RW test RW statistic value = 0.045277 pvalue = 0.831495 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3279 sd = 0.0386 freq = 0.3040 sd = 0.0413 freq = 0.0000 sd = 0.0000 freq = 0.3200 sd = 0.0330 allele 2 : freq = 0.6721 sd = 0.0386 freq = 0.6960 sd = 0.0413 freq = 0.0000 sd = 0.0000 freq = 0.6800 sd = 0.0330 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3167 freq = 0.2950 freq = 0.0000 freq = 0.3031 allele 2 : freq = 0.6833 freq = 0.7050 freq = 0.0000 freq = 0.6969 ***************************************** **************************************** Analysis of Marker 51: SNP_51 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.457030 pvalue = 0.499015 df = 1 ***************************************** RCHI test RCHI statistic value = 1.264951 pvalue = 0.260716 df = 1 ***************************************** RW test RW statistic value = 0.011455 pvalue = 0.914767 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6835 sd = 0.0383 freq = 0.6839 sd = 0.0418 freq = 0.0000 sd = 0.0000 freq = 0.6850 sd = 0.0328 allele 2 : freq = 0.3165 sd = 0.0383 freq = 0.3161 sd = 0.0418 freq = 0.0000 sd = 0.0000 freq = 0.3150 sd = 0.0328 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6708 freq = 0.7225 freq = 0.0000 freq = 0.7031 allele 2 : freq = 0.3292 freq = 0.2775 freq = 0.0000 freq = 0.2969 ***************************************** **************************************** Analysis of Marker 52: SNP_52 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.001706 pvalue = 0.967051 df = 1 ***************************************** RCHI test RCHI statistic value = 1.280614 pvalue = 0.257785 df = 1 ***************************************** RW test RW statistic value = 0.483233 pvalue = 0.486962 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2847 sd = 0.0371 freq = 0.2532 sd = 0.0391 freq = 0.0000 sd = 0.0000 freq = 0.2850 sd = 0.0319 allele 2 : freq = 0.7153 sd = 0.0371 freq = 0.7468 sd = 0.0391 freq = 0.0000 sd = 0.0000 freq = 0.7150 sd = 0.0319 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2792 freq = 0.2300 freq = 0.0000 freq = 0.2484 allele 2 : freq = 0.7208 freq = 0.7700 freq = 0.0000 freq = 0.7516 ***************************************** **************************************** Analysis of Marker 53: SNP_53 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.285684 pvalue = 0.256845 df = 1 ***************************************** RCHI test RCHI statistic value = 0.061792 pvalue = 0.803685 df = 1 ***************************************** RW test RW statistic value = 1.362611 pvalue = 0.243085 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9471 sd = 0.0184 freq = 0.9306 sd = 0.0228 freq = 0.0000 sd = 0.0000 freq = 0.9300 sd = 0.0180 allele 2 : freq = 0.0529 sd = 0.0184 freq = 0.0694 sd = 0.0228 freq = 0.0000 sd = 0.0000 freq = 0.0700 sd = 0.0180 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.9458 freq = 0.9400 freq = 0.0000 freq = 0.9422 allele 2 : freq = 0.0542 freq = 0.0600 freq = 0.0000 freq = 0.0578 ***************************************** **************************************** Analysis of Marker 54: SNP_54 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.301998 pvalue = 0.582633 df = 1 ***************************************** RCHI test RCHI statistic value = 0.581600 pvalue = 0.445686 df = 1 ***************************************** RW test RW statistic value = 0.328233 pvalue = 0.566701 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4729 sd = 0.0411 freq = 0.5081 sd = 0.0449 freq = 0.0000 sd = 0.0000 freq = 0.4800 sd = 0.0353 allele 2 : freq = 0.5271 sd = 0.0411 freq = 0.4919 sd = 0.0449 freq = 0.0000 sd = 0.0000 freq = 0.5200 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4667 freq = 0.5050 freq = 0.0000 freq = 0.4906 allele 2 : freq = 0.5333 freq = 0.4950 freq = 0.0000 freq = 0.5094 ***************************************** **************************************** Analysis of Marker 55: SNP_55 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.684713 pvalue = 0.0549134 df = 1 ***************************************** RCHI test RCHI statistic value = 1.953677 pvalue = 0.162191 df = 1 ***************************************** RW test RW statistic value = 1.196710 pvalue = 0.27398 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5618 sd = 0.0408 freq = 0.5024 sd = 0.0449 freq = 0.0000 sd = 0.0000 freq = 0.5350 sd = 0.0353 allele 2 : freq = 0.4382 sd = 0.0408 freq = 0.4976 sd = 0.0449 freq = 0.0000 sd = 0.0000 freq = 0.4650 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5875 freq = 0.5175 freq = 0.0000 freq = 0.5437 allele 2 : freq = 0.4125 freq = 0.4825 freq = 0.0000 freq = 0.4562 ***************************************** **************************************** Analysis of Marker 56: SNP_56 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.230669 pvalue = 0.631028 df = 1 ***************************************** RCHI test RCHI statistic value = 0.099470 pvalue = 0.752467 df = 1 ***************************************** RW test RW statistic value = 1.130619 pvalue = 0.287643 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5168 sd = 0.0411 freq = 0.5581 sd = 0.0446 freq = 0.0000 sd = 0.0000 freq = 0.5300 sd = 0.0353 allele 2 : freq = 0.4832 sd = 0.0411 freq = 0.4419 sd = 0.0446 freq = 0.0000 sd = 0.0000 freq = 0.4700 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5167 freq = 0.5325 freq = 0.0000 freq = 0.5266 allele 2 : freq = 0.4833 freq = 0.4675 freq = 0.0000 freq = 0.4734 ***************************************** **************************************** Analysis of Marker 57: SNP_57 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.024060 pvalue = 0.876733 df = 1 ***************************************** RCHI test RCHI statistic value = 0.182280 pvalue = 0.669421 df = 1 ***************************************** RW test RW statistic value = 2.372098 pvalue = 0.123521 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3418 sd = 0.0390 freq = 0.3637 sd = 0.0432 freq = 0.0000 sd = 0.0000 freq = 0.3600 sd = 0.0339 allele 2 : freq = 0.6582 sd = 0.0390 freq = 0.6363 sd = 0.0432 freq = 0.0000 sd = 0.0000 freq = 0.6400 sd = 0.0339 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3667 freq = 0.3875 freq = 0.0000 freq = 0.3797 allele 2 : freq = 0.6333 freq = 0.6125 freq = 0.0000 freq = 0.6203 ***************************************** **************************************** Analysis of Marker 58: SNP_58 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.473234 pvalue = 0.224836 df = 1 ***************************************** RCHI test RCHI statistic value = 0.683352 pvalue = 0.408435 df = 1 ***************************************** RW test RW statistic value = 0.239322 pvalue = 0.624696 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3191 sd = 0.0383 freq = 0.3758 sd = 0.0435 freq = 0.0000 sd = 0.0000 freq = 0.3400 sd = 0.0335 allele 2 : freq = 0.6809 sd = 0.0383 freq = 0.6242 sd = 0.0435 freq = 0.0000 sd = 0.0000 freq = 0.6600 sd = 0.0335 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3083 freq = 0.3475 freq = 0.0000 freq = 0.3328 allele 2 : freq = 0.6917 freq = 0.6525 freq = 0.0000 freq = 0.6672 ***************************************** **************************************** Analysis of Marker 59: SNP_59 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.124140 pvalue = 0.724587 df = 1 ***************************************** RCHI test RCHI statistic value = 0.501058 pvalue = 0.479035 df = 1 ***************************************** RW test RW statistic value = 0.012079 pvalue = 0.912486 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2853 sd = 0.0371 freq = 0.2919 sd = 0.0408 freq = 0.0000 sd = 0.0000 freq = 0.2850 sd = 0.0319 allele 2 : freq = 0.7147 sd = 0.0371 freq = 0.7081 sd = 0.0408 freq = 0.0000 sd = 0.0000 freq = 0.7150 sd = 0.0319 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2917 freq = 0.2600 freq = 0.0000 freq = 0.2719 allele 2 : freq = 0.7083 freq = 0.7400 freq = 0.0000 freq = 0.7281 ***************************************** **************************************** Analysis of Marker 60: SNP_60 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.681373 pvalue = 0.409114 df = 1 ***************************************** RCHI test RCHI statistic value = 0.000000 pvalue = 1 df = 1 ***************************************** RW test RW statistic value = 0.183755 pvalue = 0.668166 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7471 sd = 0.0358 freq = 0.7435 sd = 0.0392 freq = 0.0000 sd = 0.0000 freq = 0.7600 sd = 0.0302 allele 2 : freq = 0.2529 sd = 0.0358 freq = 0.2565 sd = 0.0392 freq = 0.0000 sd = 0.0000 freq = 0.2400 sd = 0.0302 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7375 freq = 0.7375 freq = 0.0000 freq = 0.7375 allele 2 : freq = 0.2625 freq = 0.2625 freq = 0.0000 freq = 0.2625 ***************************************** **************************************** Analysis of Marker 61: SNP_61 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.069963 pvalue = 0.791391 df = 1 ***************************************** RCHI test RCHI statistic value = 0.558321 pvalue = 0.454937 df = 1 ***************************************** RW test RW statistic value = 0.005899 pvalue = 0.93878 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7335 sd = 0.0364 freq = 0.7065 sd = 0.0409 freq = 0.0000 sd = 0.0000 freq = 0.7250 sd = 0.0316 allele 2 : freq = 0.2665 sd = 0.0364 freq = 0.2935 sd = 0.0409 freq = 0.0000 sd = 0.0000 freq = 0.2750 sd = 0.0316 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7292 freq = 0.6950 freq = 0.0000 freq = 0.7078 allele 2 : freq = 0.2708 freq = 0.3050 freq = 0.0000 freq = 0.2922 ***************************************** **************************************** Analysis of Marker 62: SNP_62 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.403083 pvalue = 0.525501 df = 1 ***************************************** RCHI test RCHI statistic value = 0.342352 pvalue = 0.558475 df = 1 ***************************************** RW test RW statistic value = 0.202182 pvalue = 0.652965 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3868 sd = 0.0401 freq = 0.3927 sd = 0.0439 freq = 0.0000 sd = 0.0000 freq = 0.4050 sd = 0.0347 allele 2 : freq = 0.6132 sd = 0.0401 freq = 0.6073 sd = 0.0439 freq = 0.0000 sd = 0.0000 freq = 0.5950 sd = 0.0347 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3833 freq = 0.3550 freq = 0.0000 freq = 0.3656 allele 2 : freq = 0.6167 freq = 0.6450 freq = 0.0000 freq = 0.6344 ***************************************** **************************************** Analysis of Marker 63: SNP_63 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.000023 pvalue = 0.996153 df = 1 ***************************************** RCHI test RCHI statistic value = 0.320797 pvalue = 0.571129 df = 1 ***************************************** RW test RW statistic value = 0.010254 pvalue = 0.919341 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6179 sd = 0.0400 freq = 0.6282 sd = 0.0434 freq = 0.0000 sd = 0.0000 freq = 0.6100 sd = 0.0345 allele 2 : freq = 0.3821 sd = 0.0400 freq = 0.3718 sd = 0.0434 freq = 0.0000 sd = 0.0000 freq = 0.3900 sd = 0.0345 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6125 freq = 0.6400 freq = 0.0000 freq = 0.6297 allele 2 : freq = 0.3875 freq = 0.3600 freq = 0.0000 freq = 0.3703 ***************************************** **************************************** Analysis of Marker 64: SNP_64 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.467599 pvalue = 0.225725 df = 1 ***************************************** RCHI test RCHI statistic value = 2.176064 pvalue = 0.140173 df = 1 ***************************************** RW test RW statistic value = 3.749425 pvalue = 0.0528257 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1021 sd = 0.0249 freq = 0.1573 sd = 0.0327 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234 allele 2 : freq = 0.8979 sd = 0.0249 freq = 0.8427 sd = 0.0327 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1042 freq = 0.1550 freq = 0.0000 freq = 0.1359 allele 2 : freq = 0.8958 freq = 0.8450 freq = 0.0000 freq = 0.8641 ***************************************** **************************************** Analysis of Marker 65: SNP_65 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.033664 pvalue = 0.854424 df = 1 ***************************************** RCHI test RCHI statistic value = 0.585411 pvalue = 0.444199 df = 1 ***************************************** RW test RW statistic value = 2.993534 pvalue = 0.0835976 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7021 sd = 0.0376 freq = 0.7266 sd = 0.0400 freq = 0.0000 sd = 0.0000 freq = 0.7000 sd = 0.0324 allele 2 : freq = 0.2979 sd = 0.0376 freq = 0.2734 sd = 0.0400 freq = 0.0000 sd = 0.0000 freq = 0.3000 sd = 0.0324 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7083 freq = 0.7425 freq = 0.0000 freq = 0.7297 allele 2 : freq = 0.2917 freq = 0.2575 freq = 0.0000 freq = 0.2703 ***************************************** **************************************** Analysis of Marker 66: SNP_66 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.257690 pvalue = 0.262089 df = 1 ***************************************** RCHI test RCHI statistic value = 0.034480 pvalue = 0.85269 df = 1 ***************************************** RW test RW statistic value = 1.116038 pvalue = 0.290773 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1562 sd = 0.0299 freq = 0.1734 sd = 0.0340 freq = 0.0000 sd = 0.0000 freq = 0.1700 sd = 0.0266 allele 2 : freq = 0.8438 sd = 0.0299 freq = 0.8266 sd = 0.0340 freq = 0.0000 sd = 0.0000 freq = 0.8300 sd = 0.0266 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1458 freq = 0.1525 freq = 0.0000 freq = 0.1500 allele 2 : freq = 0.8542 freq = 0.8475 freq = 0.0000 freq = 0.8500 ***************************************** **************************************** Analysis of Marker 67: SNP_67 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.370994 pvalue = 0.542463 df = 1 ***************************************** RCHI test RCHI statistic value = 0.396276 pvalue = 0.529019 df = 1 ***************************************** RW test RW statistic value = 0.001955 pvalue = 0.964733 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1003 sd = 0.0247 freq = 0.1210 sd = 0.0293 freq = 0.0000 sd = 0.0000 freq = 0.1100 sd = 0.0221 allele 2 : freq = 0.8997 sd = 0.0247 freq = 0.8790 sd = 0.0293 freq = 0.0000 sd = 0.0000 freq = 0.8900 sd = 0.0221 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1000 freq = 0.1200 freq = 0.0000 freq = 0.1125 allele 2 : freq = 0.9000 freq = 0.8800 freq = 0.0000 freq = 0.8875 ***************************************** **************************************** Analysis of Marker 68: SNP_68 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.064372 pvalue = 0.799715 df = 1 ***************************************** RCHI test RCHI statistic value = 0.293677 pvalue = 0.587874 df = 1 ***************************************** RW test RW statistic value = 0.069440 pvalue = 0.792154 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8265 sd = 0.0311 freq = 0.7976 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.8250 sd = 0.0269 allele 2 : freq = 0.1735 sd = 0.0311 freq = 0.2024 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.1750 sd = 0.0269 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8167 freq = 0.7950 freq = 0.0000 freq = 0.8031 allele 2 : freq = 0.1833 freq = 0.2050 freq = 0.0000 freq = 0.1969 ***************************************** **************************************** Analysis of Marker 69: SNP_69 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.308616 pvalue = 0.57853 df = 1 ***************************************** RCHI test RCHI statistic value = 0.534339 pvalue = 0.464788 df = 1 ***************************************** RW test RW statistic value = 1.700077 pvalue = 0.192278 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3556 sd = 0.0394 freq = 0.3935 sd = 0.0439 freq = 0.0000 sd = 0.0000 freq = 0.3800 sd = 0.0343 allele 2 : freq = 0.6444 sd = 0.0394 freq = 0.6065 sd = 0.0439 freq = 0.0000 sd = 0.0000 freq = 0.6200 sd = 0.0343 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3667 freq = 0.4025 freq = 0.0000 freq = 0.3891 allele 2 : freq = 0.6333 freq = 0.5975 freq = 0.0000 freq = 0.6109 ***************************************** **************************************** Analysis of Marker 70: SNP_70 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.020943 pvalue = 0.884934 df = 1 ***************************************** RCHI test RCHI statistic value = 0.221256 pvalue = 0.638085 df = 1 ***************************************** RW test RW statistic value = 0.674435 pvalue = 0.41151 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5662 sd = 0.0408 freq = 0.5702 sd = 0.0445 freq = 0.0000 sd = 0.0000 freq = 0.5600 sd = 0.0351 allele 2 : freq = 0.4338 sd = 0.0408 freq = 0.4298 sd = 0.0445 freq = 0.0000 sd = 0.0000 freq = 0.4400 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5667 freq = 0.5900 freq = 0.0000 freq = 0.5813 allele 2 : freq = 0.4333 freq = 0.4100 freq = 0.0000 freq = 0.4188 ***************************************** **************************************** Analysis of Marker 71: SNP_71 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.306213 pvalue = 0.253081 df = 1 ***************************************** RCHI test RCHI statistic value = 0.208921 pvalue = 0.647614 df = 1 ***************************************** RW test RW statistic value = 0.833913 pvalue = 0.361143 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4029 sd = 0.0403 freq = 0.3565 sd = 0.0430 freq = 0.0000 sd = 0.0000 freq = 0.3800 sd = 0.0343 allele 2 : freq = 0.5971 sd = 0.0403 freq = 0.6435 sd = 0.0430 freq = 0.0000 sd = 0.0000 freq = 0.6200 sd = 0.0343 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4125 freq = 0.3900 freq = 0.0000 freq = 0.3984 allele 2 : freq = 0.5875 freq = 0.6100 freq = 0.0000 freq = 0.6016 ***************************************** **************************************** Analysis of Marker 72: SNP_72 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.634222 pvalue = 0.20112 df = 1 ***************************************** RCHI test RCHI statistic value = 2.520148 pvalue = 0.1124 df = 1 ***************************************** RW test RW statistic value = 0.198925 pvalue = 0.65559 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8453 sd = 0.0297 freq = 0.8129 sd = 0.0350 freq = 0.0000 sd = 0.0000 freq = 0.8250 sd = 0.0269 allele 2 : freq = 0.1547 sd = 0.0297 freq = 0.1871 sd = 0.0350 freq = 0.0000 sd = 0.0000 freq = 0.1750 sd = 0.0269 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8500 freq = 0.7875 freq = 0.0000 freq = 0.8109 allele 2 : freq = 0.1500 freq = 0.2125 freq = 0.0000 freq = 0.1891 ***************************************** **************************************** Analysis of Marker 73: SNP_73 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.600952 pvalue = 0.438215 df = 1 ***************************************** RCHI test RCHI statistic value = 0.926733 pvalue = 0.335713 df = 1 ***************************************** RW test RW statistic value = 0.533267 pvalue = 0.465236 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8768 sd = 0.0270 freq = 0.8484 sd = 0.0322 freq = 0.0000 sd = 0.0000 freq = 0.8700 sd = 0.0238 allele 2 : freq = 0.1232 sd = 0.0270 freq = 0.1516 sd = 0.0322 freq = 0.0000 sd = 0.0000 freq = 0.1300 sd = 0.0238 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8833 freq = 0.8500 freq = 0.0000 freq = 0.8625 allele 2 : freq = 0.1167 freq = 0.1500 freq = 0.0000 freq = 0.1375 ***************************************** **************************************** Analysis of Marker 74: SNP_74 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.635441 pvalue = 0.104503 df = 1 ***************************************** RCHI test RCHI statistic value = 3.264434 pvalue = 0.0707975 df = 1 ***************************************** RW test RW statistic value = 0.205766 pvalue = 0.650106 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2976 sd = 0.0376 freq = 0.2468 sd = 0.0387 freq = 0.0000 sd = 0.0000 freq = 0.2600 sd = 0.0310 allele 2 : freq = 0.7024 sd = 0.0376 freq = 0.7532 sd = 0.0387 freq = 0.0000 sd = 0.0000 freq = 0.7400 sd = 0.0310 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2958 freq = 0.2175 freq = 0.0000 freq = 0.2469 allele 2 : freq = 0.7042 freq = 0.7825 freq = 0.0000 freq = 0.7531 ***************************************** **************************************** Analysis of Marker 75: SNP_75 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.679645 pvalue = 0.409709 df = 1 ***************************************** RCHI test RCHI statistic value = 1.471473 pvalue = 0.225113 df = 1 ***************************************** RW test RW statistic value = 0.822621 pvalue = 0.364415 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2691 sd = 0.0365 freq = 0.2097 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.2500 sd = 0.0306 allele 2 : freq = 0.7309 sd = 0.0365 freq = 0.7903 sd = 0.0366 freq = 0.0000 sd = 0.0000 freq = 0.7500 sd = 0.0306 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2667 freq = 0.2150 freq = 0.0000 freq = 0.2344 allele 2 : freq = 0.7333 freq = 0.7850 freq = 0.0000 freq = 0.7656 ***************************************** **************************************** Analysis of Marker 76: SNP_76 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 6.361505 pvalue = 0.0116623 df = 1 Frequency of allele 1 is increased in the controls (quasi-score associated to this allele is -28.3579) ***************************************** RCHI test RCHI statistic value = 0.960127 pvalue = 0.327155 df = 1 ***************************************** RW test RW statistic value = 0.048010 pvalue = 0.826563 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7706 sd = 0.0346 freq = 0.8185 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.8150 sd = 0.0275 allele 2 : freq = 0.2294 sd = 0.0346 freq = 0.1815 sd = 0.0346 freq = 0.0000 sd = 0.0000 freq = 0.1850 sd = 0.0275 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7542 freq = 0.7950 freq = 0.0000 freq = 0.7797 allele 2 : freq = 0.2458 freq = 0.2050 freq = 0.0000 freq = 0.2203 ***************************************** **************************************** Analysis of Marker 77: SNP_77 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.283137 pvalue = 0.594652 df = 1 ***************************************** RCHI test RCHI statistic value = 0.562373 pvalue = 0.453306 df = 1 ***************************************** RW test RW statistic value = 1.459157 pvalue = 0.227064 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5991 sd = 0.0403 freq = 0.5750 sd = 0.0444 freq = 0.0000 sd = 0.0000 freq = 0.5950 sd = 0.0347 allele 2 : freq = 0.4009 sd = 0.0403 freq = 0.4250 sd = 0.0444 freq = 0.0000 sd = 0.0000 freq = 0.4050 sd = 0.0347 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5750 freq = 0.5375 freq = 0.0000 freq = 0.5516 allele 2 : freq = 0.4250 freq = 0.4625 freq = 0.0000 freq = 0.4484 ***************************************** **************************************** Analysis of Marker 78: SNP_78 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.747673 pvalue = 0.387214 df = 1 ***************************************** RCHI test RCHI statistic value = 2.146950 pvalue = 0.142853 df = 1 ***************************************** RW test RW statistic value = 1.254642 pvalue = 0.262668 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4324 sd = 0.0407 freq = 0.3702 sd = 0.0434 freq = 0.0000 sd = 0.0000 freq = 0.4100 sd = 0.0348 allele 2 : freq = 0.5676 sd = 0.0407 freq = 0.6298 sd = 0.0434 freq = 0.0000 sd = 0.0000 freq = 0.5900 sd = 0.0348 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4292 freq = 0.3575 freq = 0.0000 freq = 0.3844 allele 2 : freq = 0.5708 freq = 0.6425 freq = 0.0000 freq = 0.6156 ***************************************** **************************************** Analysis of Marker 79: SNP_79 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.229819 pvalue = 0.0723087 df = 1 ***************************************** RCHI test RCHI statistic value = 4.980733 pvalue = 0.0256311 df = 1 ***************************************** RW test RW statistic value = 4.025837 pvalue = 0.0448084 df = 1 Frequency of allele 1 is increased in the controls (quasi-score associated to this allele is -19.2000) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8153 sd = 0.0319 freq = 0.8839 sd = 0.0288 freq = 0.0000 sd = 0.0000 freq = 0.8550 sd = 0.0249 allele 2 : freq = 0.1847 sd = 0.0319 freq = 0.1161 sd = 0.0288 freq = 0.0000 sd = 0.0000 freq = 0.1450 sd = 0.0249 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8250 freq = 0.9000 freq = 0.0000 freq = 0.8719 allele 2 : freq = 0.1750 freq = 0.1000 freq = 0.0000 freq = 0.1281 ***************************************** **************************************** Analysis of Marker 80: SNP_80 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.198095 pvalue = 0.138181 df = 1 ***************************************** RCHI test RCHI statistic value = 3.241505 pvalue = 0.0717947 df = 1 ***************************************** RW test RW statistic value = 4.465367 pvalue = 0.0345887 df = 1 Frequency of allele 1 is increased in the controls (quasi-score associated to this allele is -29.8000) ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3576 sd = 0.0394 freq = 0.4266 sd = 0.0444 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346 allele 2 : freq = 0.6424 sd = 0.0394 freq = 0.5734 sd = 0.0444 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3583 freq = 0.4475 freq = 0.0000 freq = 0.4141 allele 2 : freq = 0.6417 freq = 0.5525 freq = 0.0000 freq = 0.5859 ***************************************** **************************************** Analysis of Marker 81: SNP_81 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.312816 pvalue = 0.251886 df = 1 ***************************************** RCHI test RCHI statistic value = 0.490570 pvalue = 0.483673 df = 1 ***************************************** RW test RW statistic value = 1.519725 pvalue = 0.217661 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2112 sd = 0.0336 freq = 0.1694 sd = 0.0337 freq = 0.0000 sd = 0.0000 freq = 0.1950 sd = 0.0280 allele 2 : freq = 0.7888 sd = 0.0336 freq = 0.8306 sd = 0.0337 freq = 0.0000 sd = 0.0000 freq = 0.8050 sd = 0.0280 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2208 freq = 0.1925 freq = 0.0000 freq = 0.2031 allele 2 : freq = 0.7792 freq = 0.8075 freq = 0.0000 freq = 0.7969 ***************************************** **************************************** Analysis of Marker 82: SNP_82 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.001336 pvalue = 0.970848 df = 1 ***************************************** RCHI test RCHI statistic value = 0.000422 pvalue = 0.983611 df = 1 ***************************************** RW test RW statistic value = 0.076738 pvalue = 0.781767 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8188 sd = 0.0317 freq = 0.8089 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.7950 sd = 0.0285 allele 2 : freq = 0.1812 sd = 0.0317 freq = 0.1911 sd = 0.0353 freq = 0.0000 sd = 0.0000 freq = 0.2050 sd = 0.0285 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7958 freq = 0.7950 freq = 0.0000 freq = 0.7953 allele 2 : freq = 0.2042 freq = 0.2050 freq = 0.0000 freq = 0.2047 ***************************************** **************************************** Analysis of Marker 83: SNP_83 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.748035 pvalue = 0.387099 df = 1 ***************************************** RCHI test RCHI statistic value = 2.219476 pvalue = 0.136279 df = 1 ***************************************** RW test RW statistic value = 0.510896 pvalue = 0.474751 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1159 sd = 0.0263 freq = 0.1516 sd = 0.0322 freq = 0.0000 sd = 0.0000 freq = 0.1350 sd = 0.0242 allele 2 : freq = 0.8841 sd = 0.0263 freq = 0.8484 sd = 0.0322 freq = 0.0000 sd = 0.0000 freq = 0.8650 sd = 0.0242 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1208 freq = 0.1750 freq = 0.0000 freq = 0.1547 allele 2 : freq = 0.8792 freq = 0.8250 freq = 0.0000 freq = 0.8453 ***************************************** **************************************** Analysis of Marker 84: SNP_84 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.063594 pvalue = 0.800903 df = 1 ***************************************** RCHI test RCHI statistic value = 0.275252 pvalue = 0.599831 df = 1 ***************************************** RW test RW statistic value = 0.017599 pvalue = 0.894463 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3318 sd = 0.0387 freq = 0.3403 sd = 0.0426 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332 allele 2 : freq = 0.6682 sd = 0.0387 freq = 0.6597 sd = 0.0426 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3250 freq = 0.3500 freq = 0.0000 freq = 0.3406 allele 2 : freq = 0.6750 freq = 0.6500 freq = 0.0000 freq = 0.6594 ***************************************** **************************************** Analysis of Marker 85: SNP_85 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.173012 pvalue = 0.677449 df = 1 ***************************************** RCHI test RCHI statistic value = 0.614516 pvalue = 0.433093 df = 1 ***************************************** RW test RW statistic value = 0.000287 pvalue = 0.986483 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7518 sd = 0.0355 freq = 0.7968 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.7700 sd = 0.0298 allele 2 : freq = 0.2482 sd = 0.0355 freq = 0.2032 sd = 0.0361 freq = 0.0000 sd = 0.0000 freq = 0.2300 sd = 0.0298 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.7625 freq = 0.7950 freq = 0.0000 freq = 0.7828 allele 2 : freq = 0.2375 freq = 0.2050 freq = 0.0000 freq = 0.2172 ***************************************** **************************************** Analysis of Marker 86: SNP_86 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.267952 pvalue = 0.604709 df = 1 ***************************************** RCHI test RCHI statistic value = 0.215483 pvalue = 0.642504 df = 1 ***************************************** RW test RW statistic value = 0.020242 pvalue = 0.886863 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8071 sd = 0.0325 freq = 0.8081 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.8100 sd = 0.0277 allele 2 : freq = 0.1929 sd = 0.0325 freq = 0.1919 sd = 0.0354 freq = 0.0000 sd = 0.0000 freq = 0.1900 sd = 0.0277 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.8208 freq = 0.8025 freq = 0.0000 freq = 0.8094 allele 2 : freq = 0.1792 freq = 0.1975 freq = 0.0000 freq = 0.1906 ***************************************** **************************************** Analysis of Marker 87: SNP_87 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.108679 pvalue = 0.292369 df = 1 ***************************************** RCHI test RCHI statistic value = 0.211115 pvalue = 0.645895 df = 1 ***************************************** RW test RW statistic value = 0.010386 pvalue = 0.918826 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1388 sd = 0.0284 freq = 0.1468 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.1250 sd = 0.0234 allele 2 : freq = 0.8612 sd = 0.0284 freq = 0.8532 sd = 0.0318 freq = 0.0000 sd = 0.0000 freq = 0.8750 sd = 0.0234 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1458 freq = 0.1300 freq = 0.0000 freq = 0.1359 allele 2 : freq = 0.8542 freq = 0.8700 freq = 0.0000 freq = 0.8641 ***************************************** **************************************** Analysis of Marker 88: SNP_88 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.046990 pvalue = 0.828387 df = 1 ***************************************** RCHI test RCHI statistic value = 0.817152 pvalue = 0.366014 df = 1 ***************************************** RW test RW statistic value = 0.008633 pvalue = 0.92597 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2050 sd = 0.0332 freq = 0.2040 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.2000 sd = 0.0283 allele 2 : freq = 0.7950 sd = 0.0332 freq = 0.7960 sd = 0.0362 freq = 0.0000 sd = 0.0000 freq = 0.8000 sd = 0.0283 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1917 freq = 0.1575 freq = 0.0000 freq = 0.1703 allele 2 : freq = 0.8083 freq = 0.8425 freq = 0.0000 freq = 0.8297 ***************************************** **************************************** Analysis of Marker 89: SNP_89 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.165891 pvalue = 0.68379 df = 1 ***************************************** RCHI test RCHI statistic value = 1.509371 pvalue = 0.219235 df = 1 ***************************************** RW test RW statistic value = 0.000783 pvalue = 0.977673 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4212 sd = 0.0406 freq = 0.4653 sd = 0.0448 freq = 0.0000 sd = 0.0000 freq = 0.4400 sd = 0.0351 allele 2 : freq = 0.5788 sd = 0.0406 freq = 0.5347 sd = 0.0448 freq = 0.0000 sd = 0.0000 freq = 0.5600 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4333 freq = 0.4950 freq = 0.0000 freq = 0.4719 allele 2 : freq = 0.5667 freq = 0.5050 freq = 0.0000 freq = 0.5281 ***************************************** **************************************** Analysis of Marker 90: SNP_90 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 2.783493 pvalue = 0.0952402 df = 1 ***************************************** RCHI test RCHI statistic value = 3.377770 pvalue = 0.0660814 df = 1 ***************************************** RW test RW statistic value = 2.106048 pvalue = 0.146718 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2915 sd = 0.0374 freq = 0.2194 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.2550 sd = 0.0308 allele 2 : freq = 0.7085 sd = 0.0374 freq = 0.7806 sd = 0.0372 freq = 0.0000 sd = 0.0000 freq = 0.7450 sd = 0.0308 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2917 freq = 0.2125 freq = 0.0000 freq = 0.2422 allele 2 : freq = 0.7083 freq = 0.7875 freq = 0.0000 freq = 0.7578 ***************************************** **************************************** Analysis of Marker 91: SNP_91 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.798376 pvalue = 0.371579 df = 1 ***************************************** RCHI test RCHI statistic value = 1.575358 pvalue = 0.209431 df = 1 ***************************************** RW test RW statistic value = 0.257262 pvalue = 0.612008 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3318 sd = 0.0387 freq = 0.3831 sd = 0.0437 freq = 0.0000 sd = 0.0000 freq = 0.3500 sd = 0.0337 allele 2 : freq = 0.6682 sd = 0.0387 freq = 0.6169 sd = 0.0437 freq = 0.0000 sd = 0.0000 freq = 0.6500 sd = 0.0337 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3292 freq = 0.3900 freq = 0.0000 freq = 0.3672 allele 2 : freq = 0.6708 freq = 0.6100 freq = 0.0000 freq = 0.6328 ***************************************** **************************************** Analysis of Marker 92: SNP_92 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 3.338971 pvalue = 0.0676569 df = 1 ***************************************** RCHI test RCHI statistic value = 4.450831 pvalue = 0.0348843 df = 1 ***************************************** RW test RW statistic value = 0.291386 pvalue = 0.589334 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1997 sd = 0.0329 freq = 0.2806 sd = 0.0403 freq = 0.0000 sd = 0.0000 freq = 0.2450 sd = 0.0304 allele 2 : freq = 0.8003 sd = 0.0329 freq = 0.7194 sd = 0.0403 freq = 0.0000 sd = 0.0000 freq = 0.7550 sd = 0.0304 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2042 freq = 0.2975 freq = 0.0000 freq = 0.2625 allele 2 : freq = 0.7958 freq = 0.7025 freq = 0.0000 freq = 0.7375 ***************************************** **************************************** Analysis of Marker 93: SNP_93 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.833672 pvalue = 0.361213 df = 1 ***************************************** RCHI test RCHI statistic value = 0.022352 pvalue = 0.881155 df = 1 ***************************************** RW test RW statistic value = 0.636922 pvalue = 0.424828 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4856 sd = 0.0411 freq = 0.4750 sd = 0.0448 freq = 0.0000 sd = 0.0000 freq = 0.4900 sd = 0.0353 allele 2 : freq = 0.5144 sd = 0.0411 freq = 0.5250 sd = 0.0448 freq = 0.0000 sd = 0.0000 freq = 0.5100 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4625 freq = 0.4700 freq = 0.0000 freq = 0.4672 allele 2 : freq = 0.5375 freq = 0.5300 freq = 0.0000 freq = 0.5328 ***************************************** **************************************** Analysis of Marker 94: SNP_94 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.866870 pvalue = 0.351823 df = 1 ***************************************** RCHI test RCHI statistic value = 0.445656 pvalue = 0.504405 df = 1 ***************************************** RW test RW statistic value = 1.200610 pvalue = 0.2732 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6559 sd = 0.0391 freq = 0.6887 sd = 0.0416 freq = 0.0000 sd = 0.0000 freq = 0.6700 sd = 0.0332 allele 2 : freq = 0.3441 sd = 0.0391 freq = 0.3113 sd = 0.0416 freq = 0.0000 sd = 0.0000 freq = 0.3300 sd = 0.0332 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6458 freq = 0.6775 freq = 0.0000 freq = 0.6656 allele 2 : freq = 0.3542 freq = 0.3225 freq = 0.0000 freq = 0.3344 ***************************************** **************************************** Analysis of Marker 95: SNP_95 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.019157 pvalue = 0.889918 df = 1 ***************************************** RCHI test RCHI statistic value = 0.020462 pvalue = 0.886254 df = 1 ***************************************** RW test RW statistic value = 1.311917 pvalue = 0.252048 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1371 sd = 0.0283 freq = 0.1266 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.1400 sd = 0.0245 allele 2 : freq = 0.8629 sd = 0.0283 freq = 0.8734 sd = 0.0299 freq = 0.0000 sd = 0.0000 freq = 0.8600 sd = 0.0245 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.1375 freq = 0.1425 freq = 0.0000 freq = 0.1406 allele 2 : freq = 0.8625 freq = 0.8575 freq = 0.0000 freq = 0.8594 ***************************************** **************************************** Analysis of Marker 96: SNP_96 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.359382 pvalue = 0.548849 df = 1 ***************************************** RCHI test RCHI statistic value = 0.217094 pvalue = 0.641263 df = 1 ***************************************** RW test RW statistic value = 0.003385 pvalue = 0.953605 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3676 sd = 0.0397 freq = 0.3597 sd = 0.0431 freq = 0.0000 sd = 0.0000 freq = 0.3950 sd = 0.0346 allele 2 : freq = 0.6324 sd = 0.0397 freq = 0.6403 sd = 0.0431 freq = 0.0000 sd = 0.0000 freq = 0.6050 sd = 0.0346 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.3750 freq = 0.3525 freq = 0.0000 freq = 0.3609 allele 2 : freq = 0.6250 freq = 0.6475 freq = 0.0000 freq = 0.6391 ***************************************** **************************************** Analysis of Marker 97: SNP_97 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.523471 pvalue = 0.469365 df = 1 ***************************************** RCHI test RCHI statistic value = 1.077308 pvalue = 0.299301 df = 1 ***************************************** RW test RW statistic value = 0.378987 pvalue = 0.538146 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2676 sd = 0.0364 freq = 0.2363 sd = 0.0381 freq = 0.0000 sd = 0.0000 freq = 0.2600 sd = 0.0310 allele 2 : freq = 0.7324 sd = 0.0364 freq = 0.7637 sd = 0.0381 freq = 0.0000 sd = 0.0000 freq = 0.7400 sd = 0.0310 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.2750 freq = 0.2300 freq = 0.0000 freq = 0.2469 allele 2 : freq = 0.7250 freq = 0.7700 freq = 0.0000 freq = 0.7531 ***************************************** **************************************** Analysis of Marker 98: SNP_98 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.392167 pvalue = 0.531163 df = 1 ***************************************** RCHI test RCHI statistic value = 0.198792 pvalue = 0.655697 df = 1 ***************************************** RW test RW statistic value = 0.522274 pvalue = 0.469873 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6438 sd = 0.0394 freq = 0.6153 sd = 0.0437 freq = 0.0000 sd = 0.0000 freq = 0.6250 sd = 0.0342 allele 2 : freq = 0.3562 sd = 0.0394 freq = 0.3847 sd = 0.0437 freq = 0.0000 sd = 0.0000 freq = 0.3750 sd = 0.0342 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.6417 freq = 0.6200 freq = 0.0000 freq = 0.6281 allele 2 : freq = 0.3583 freq = 0.3800 freq = 0.0000 freq = 0.3719 ***************************************** **************************************** Analysis of Marker 99: SNP_99 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 0.758672 pvalue = 0.383744 df = 1 ***************************************** RCHI test RCHI statistic value = 0.515694 pvalue = 0.472684 df = 1 ***************************************** RW test RW statistic value = 0.437680 pvalue = 0.508244 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4265 sd = 0.0407 freq = 0.4315 sd = 0.0445 freq = 0.0000 sd = 0.0000 freq = 0.4400 sd = 0.0351 allele 2 : freq = 0.5735 sd = 0.0407 freq = 0.5685 sd = 0.0445 freq = 0.0000 sd = 0.0000 freq = 0.5600 sd = 0.0351 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4167 freq = 0.4525 freq = 0.0000 freq = 0.4391 allele 2 : freq = 0.5833 freq = 0.5475 freq = 0.0000 freq = 0.5609 ***************************************** **************************************** Analysis of Marker 100: SNP_100 **************************************** There are 120 affected individuals, 200 unaffected individuals, and 0 individuals of unknown phenotype available. ***************************************** RM test RM statistic value = 1.416997 pvalue = 0.233898 df = 1 ***************************************** RCHI test RCHI statistic value = 1.953677 pvalue = 0.162191 df = 1 ***************************************** RW test RW statistic value = 2.210097 pvalue = 0.13711 df = 1 ***************************************** allele frequency estimates using the Best Linear Unbiased Estimator (BLUE) in cases unaffected controls unknown controls all sample allele 1 : freq = 0.4994 sd = 0.0411 freq = 0.5653 sd = 0.0445 freq = 0.0000 sd = 0.0000 freq = 0.5300 sd = 0.0353 allele 2 : freq = 0.5006 sd = 0.0411 freq = 0.4347 sd = 0.0445 freq = 0.0000 sd = 0.0000 freq = 0.4700 sd = 0.0353 ***************************************** allele frequency estimates using naive counting in cases unaffected controls unknown controls all sample allele 1 : freq = 0.5000 freq = 0.5700 freq = 0.0000 freq = 0.5437 allele 2 : freq = 0.5000 freq = 0.4300 freq = 0.0000 freq = 0.4562 *****************************************