[1] "###############################"
[1] "####DENISOVA###########"
[1] "###############################"
[1] "###############################"
[1] "####AFRICAN####DENISOVA###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  PopulationMat[, pop] and DenisovaMat[, 12] 
t = -95.8415, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 -0.2784773 -0.2677316 
sample estimates:
      cor 
-0.273113 

[1] "==========0============="

	Spearman's rank correlation rho

data:  PopulationMat[, pop] and DenisovaMat[, 12] 
S = 2.923488e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
       rho 
-0.1851163 

[1] "==========0============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.09388155 0.10506543 
sample estimates:
odds ratio 
0.09931312 

[1] "==========0============="
[1] "###############################"
[1] "###############################"
[1] "####AD MIX AMERICAN####DENISOVA###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  PopulationMat[, pop] and DenisovaMat[, 12] 
t = 4.0533, df = 113961, p-value = 5.053e-05
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.006200655 0.017810712 
sample estimates:
       cor 
0.01200609 

[1] "==========5.05292004058244e-05============="

	Spearman's rank correlation rho

data:  PopulationMat[, pop] and DenisovaMat[, 12] 
S = 2.246334e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
       rho 
0.08938695 

[1] "==========8.01562270362143e-201============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.0003875
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 1.077085 1.292608 
sample estimates:
odds ratio 
  1.180843 

[1] "==========0.000387499265248055============="
[1] "###############################"
[1] "###############################"
[1] "####ASIAN####DENISOVA###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  PopulationMat[, pop] and DenisovaMat[, 12] 
t = 116.0249, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.319831 0.330216 
sample estimates:
      cor 
0.3250333 

[1] "==========0============="

	Spearman's rank correlation rho

data:  PopulationMat[, pop] and DenisovaMat[, 12] 
S = 1.953336e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.2081615 

[1] "==========0============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 13.66887 15.45629 
sample estimates:
odds ratio 
  14.53473 

[1] "==========0============="
[1] "###############################"
[1] "###############################"
[1] "####EUROPEAN####DENISOVA###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  PopulationMat[, pop] and DenisovaMat[, 12] 
t = 25.348, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.06910063 0.08064727 
sample estimates:
       cor 
0.07487646 

[1] "==========0============="

	Spearman's rank correlation rho

data:  PopulationMat[, pop] and DenisovaMat[, 12] 
S = 2.240868e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
       rho 
0.09160264 

[1] "==========7.72116668541538e-211============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 2.328313 2.779456 
sample estimates:
odds ratio 
  2.545467 

[1] "==========2.71004034578505e-80============="
[1] "###############################"
[1] "###############################"
[1] "####NEANDERTAL###########"
[1] "###############################"
[1] "###############################"
[1] "####AFRICAN####NEANDERTAL###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  PopulationMat[, pop] and NeanderMat[, 12] 
t = -174.8457, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 -0.4644757 -0.4553200 
sample estimates:
       cor 
-0.4599101 

[1] "==========0============="

	Spearman's rank correlation rho

data:  PopulationMat[, pop] and NeanderMat[, 12] 
S = 3.094942e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
     rho 
-0.25462 

[1] "==========0============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.03573338 0.03988137 
sample estimates:
odds ratio 
  0.037771 

[1] "==========0============="
[1] "###############################"
[1] "###############################"
[1] "####AD MIX AMERICAN####NEANDERTAL###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  PopulationMat[, pop] and NeanderMat[, 12] 
t = 31.2979, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.08655693 0.09806970 
sample estimates:
      cor 
0.0923164 

[1] "==========0============="

	Spearman's rank correlation rho

data:  PopulationMat[, pop] and NeanderMat[, 12] 
S = 2.167645e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.1212854 

[1] "==========0============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 2.538624 2.903084 
sample estimates:
odds ratio 
  2.715401 

[1] "==========9.45592195708443e-160============="
[1] "###############################"
[1] "###############################"
[1] "####ASIAN####NEANDERTAL###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  PopulationMat[, pop] and NeanderMat[, 12] 
t = 136.6448, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.3702048 0.3801819 
sample estimates:
      cor 
0.3752042 

[1] "==========0============="

	Spearman's rank correlation rho

data:  PopulationMat[, pop] and NeanderMat[, 12] 
S = 1.757145e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.2876928 

[1] "==========0============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 18.78830 21.20144 
sample estimates:
odds ratio 
   19.9622 

[1] "==========0============="
[1] "###############################"
[1] "###############################"
[1] "####EUROPEAN####NEANDERTAL###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  PopulationMat[, pop] and NeanderMat[, 12] 
t = 109.6593, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.3036860 0.3141895 
sample estimates:
      cor 
0.3089472 

[1] "==========0============="

	Spearman's rank correlation rho

data:  PopulationMat[, pop] and NeanderMat[, 12] 
S = 2.00622e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.1867234 

[1] "==========0============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 11.88013 13.50336 
sample estimates:
odds ratio 
  12.66953 

[1] "==========0============="
[1] "###############################"
[1] "###############################"
[1] "####ANCESTOR###########"
[1] "###############################"
[1] "###############################"
[1] "####AFRICAN####ANCESTOR###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  PopulationMat[, pop] and AncestMat[, 12] 
t = -5.3432, df = 113961, p-value = 9.149e-08
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 -0.02162979 -0.01002097 
sample estimates:
        cor 
-0.01582592 

[1] "==========9.14948715434911e-08============="

	Spearman's rank correlation rho

data:  PopulationMat[, pop] and AncestMat[, 12] 
S = 2.707123e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
        rho 
-0.09740656 

[1] "==========2.94878273824614e-238============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.001168
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.7464619 0.9306795 
sample estimates:
odds ratio 
 0.8325297 

[1] "==========0.00116837589121304============="
[1] "###############################"
[1] "###############################"
[1] "####AD MIX AMERICAN####ANCESTOR###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  PopulationMat[, pop] and AncestMat[, 12] 
t = 3.887, df = 113961, p-value = 0.0001015
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.005708142 0.017318334 
sample estimates:
       cor 
0.01151363 

[1] "==========0.000101531367513896============="

	Spearman's rank correlation rho

data:  PopulationMat[, pop] and AncestMat[, 12] 
S = 2.141703e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.1318019 

[1] "==========0============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.3479
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.8307168 1.0634710 
sample estimates:
odds ratio 
 0.9413852 

[1] "==========0.347864371542357============="
[1] "###############################"
[1] "###############################"
[1] "####ASIAN####ANCESTOR###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  PopulationMat[, pop] and AncestMat[, 12] 
t = -3.0551, df = 113961, p-value = 0.00225
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 -0.014854753 -0.003243973 
sample estimates:
         cor 
-0.009049668 

[1] "==========0.00225020989936031============="

	Spearman's rank correlation rho

data:  PopulationMat[, pop] and AncestMat[, 12] 
S = 2.471937e+14, p-value = 0.4851
alternative hypothesis: true rho is not equal to 0 
sample estimates:
         rho 
-0.002067817 

[1] "==========0.485142674578535============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 9.103e-08
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 1.248333 1.599230 
sample estimates:
odds ratio 
  1.415079 

[1] "==========9.10316759404917e-08============="
[1] "###############################"
[1] "###############################"
[1] "####EUROPEAN####ANCESTOR###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  PopulationMat[, pop] and AncestMat[, 12] 
t = 11.7301, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.02892653 0.04052426 
sample estimates:
       cor 
0.03472657 

[1] "==========0============="

	Spearman's rank correlation rho

data:  PopulationMat[, pop] and AncestMat[, 12] 
S = 2.244067e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
       rho 
0.09030595 

[1] "==========6.02139971424212e-205============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 1.59e-06
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 1.222163 1.598089 
sample estimates:
odds ratio 
  1.400085 

[1] "==========1.59045862078264e-06============="
[1] "###############################"
[1] "###############################"
[1] "####DENISOVA 2###########"
[1] "###############################"
[1] "###############################"
[1] "####AFRICAN####DENISOVA 2###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.08358347 0.09977473 
sample estimates:
odds ratio 
0.09130637 

[1] "==========0============="
[1] "###############################"
[1] "###############################"
[1] "####AD MIX AMERICAN####DENISOVA 2###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.0487
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.9971836 1.3657991 
sample estimates:
odds ratio 
  1.169988 

[1] "==========0.0486992898390597============="
[1] "###############################"
[1] "###############################"
[1] "####ASIAN####DENISOVA 2###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 12.80339 15.37113 
sample estimates:
odds ratio 
  14.02957 

[1] "==========0============="
[1] "###############################"
[1] "###############################"
[1] "####EUROPEAN####DENISOVA 2###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 2.396326 3.179906 
sample estimates:
odds ratio 
  2.765596 

[1] "==========3.85071303384795e-37============="
[1] "###############################"
[1] "###############################"
[1] "####DENISOVA 3###########"
[1] "###############################"
[1] "###############################"
[1] "####AFRICAN####DENISOVA 3###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.08971687 0.10696655 
sample estimates:
odds ratio 
0.09794895 

[1] "==========0============="
[1] "###############################"
[1] "###############################"
[1] "####AD MIX AMERICAN####DENISOVA 3###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.05193
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.9860333 1.6045634 
sample estimates:
odds ratio 
  1.266502 

[1] "==========0.0519254971677243============="
[1] "###############################"
[1] "###############################"
[1] "####ASIAN####DENISOVA 3###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 13.22229 15.92202 
sample estimates:
odds ratio 
  14.51364 

[1] "==========0============="
[1] "###############################"
[1] "###############################"
[1] "####EUROPEAN####DENISOVA 3###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 2.349048 3.241670 
sample estimates:
odds ratio 
  2.766345 

[1] "==========7.12213310530182e-29============="
[1] "###############################"
[1] "###############################"
[1] "###############################"
[1] "###############################"
[1] "###############################"
[1] "###############################"
[1] "###############################"
[1] "###############################"
[1] "###############################"
[1] "###############################"
[1] "###############################"
[1] "###############################"
[1] "###############################"
[1] "###############################"
[1] "####DENISOVA###########"
[1] "###############################"
[1] "###############################"
[1] "####HapMapAfricans####DENISOVA###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
t = -18.3646, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 -0.06010719 -0.04852972 
sample estimates:
        cor 
-0.05432028 

[1] "==========3.24045165062491e-75============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
S = 2.437831e+14, p-value = 7.202e-05
alternative hypothesis: true rho is not equal to 0 
sample estimates:
       rho 
0.01175835 

[1] "==========7.20159904999506e-05============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.5349927 0.6027932 
sample estimates:
odds ratio 
 0.5680146 

[1] "==========3.04033307990071e-85============="
[1] "###############################"
[1] "###############################"
[1] "####CEPHEuropean####DENISOVA###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
t = 18.9475, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.05024943 0.06182470 
sample estimates:
       cor 
0.05603895 

[1] "==========0============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
S = 2.285396e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
       rho 
0.07355179 

[1] "==========1.85604279391598e-136============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 2.169147 3.120575 
sample estimates:
odds ratio 
  2.609465 

[1] "==========2.49462973074551e-21============="
[1] "###############################"
[1] "###############################"
[1] "####HanChineseBeijing####DENISOVA###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
t = 56.4841, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.1593729 0.1706684 
sample estimates:
      cor 
0.1650261 

[1] "==========0============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
S = 2.151827e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.1276976 

[1] "==========0============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 6.765547 8.269441 
sample estimates:
odds ratio 
  7.480219 

[1] "==========3.28786238144888e-257============="
[1] "###############################"
[1] "###############################"
[1] "####HanChineseSouth####DENISOVA###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
t = 46.8803, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.1318505 0.1432426 
sample estimates:
      cor 
0.1375511 

[1] "==========0============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
S = 2.181992e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.1154697 

[1] "==========0============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 5.879718 7.263443 
sample estimates:
odds ratio 
  6.538762 

[1] "==========3.21005513854934e-202============="
[1] "###############################"
[1] "###############################"
[1] "####Colombian####DENISOVA###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
t = 0.6978, df = 113961, p-value = 0.4853
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 -0.003738828  0.007872854 
sample estimates:
        cor 
0.002067083 

[1] "==========0.485297670095037============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
S = 2.278922e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
       rho 
0.07617638 

[1] "==========2.97790749201362e-146============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.7691
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.8435242 1.2435936 
sample estimates:
odds ratio 
  1.028461 

[1] "==========0.769141584428419============="
[1] "###############################"
[1] "###############################"
[1] "####HapMapFinnish####DENISOVA###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
t = 20.1149, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.05369268 0.06526333 
sample estimates:
    cor 
0.05948 

[1] "==========0============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
S = 2.277128e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
       rho 
0.07690355 

[1] "==========4.999434672452e-149============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 2.592975 3.542891 
sample estimates:
odds ratio 
  3.037099 

[1] "==========1.95658936822225e-36============="
[1] "###############################"
[1] "###############################"
[1] "####British####DENISOVA###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
t = 20.14, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.05376658 0.06533713 
sample estimates:
       cor 
0.05955386 

[1] "==========0============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
S = 2.297055e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
       rho 
0.06882553 

[1] "==========1.08226472050767e-119============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 2.354362 3.305835 
sample estimates:
odds ratio 
  2.796757 

[1] "==========2.71710250418298e-27============="
[1] "###############################"
[1] "###############################"
[1] "####Iberian####DENISOVA###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
t = 9.068, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.02104950 0.03265286 
sample estimates:
       cor 
0.02685208 

[1] "==========0============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
S = 2.359616e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.0434646 

[1] "==========8.69311122828545e-49============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.001307
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 1.407655 4.365101 
sample estimates:
odds ratio 
  2.558671 

[1] "==========0.0013068439817828============="
[1] "###############################"
[1] "###############################"
[1] "####Japanese####DENISOVA###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
t = 45.7365, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.1285508 0.1399533 
sample estimates:
      cor 
0.1342565 

[1] "==========0============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
S = 2.168051e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.1211208 

[1] "==========0============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 6.061330 7.622704 
sample estimates:
odds ratio 
  6.801074 

[1] "==========1.36204454852907e-179============="
[1] "###############################"
[1] "###############################"
[1] "####KOREAN####DENISOVA###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
t = 102.6007, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.2854709 0.2961007 
sample estimates:
      cor 
0.2907948 

[1] "==========0============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
S = 1.960655e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.2051946 

[1] "==========0============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 23.60837 28.29533 
sample estimates:
odds ratio 
  25.84219 

[1] "==========0============="
[1] "###############################"
[1] "###############################"
[1] "####Luhya####DENISOVA###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
t = -35.7194, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 -0.11096044 -0.09947727 
sample estimates:
       cor 
-0.1052224 

[1] "==========6.88888097743776e-278============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
S = 2.641647e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
        rho 
-0.07086422 

[1] "==========8.70576230102371e-127============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.3698880 0.4088458 
sample estimates:
odds ratio 
 0.3888997 

[1] "==========1.22319899348565e-302============="
[1] "###############################"
[1] "###############################"
[1] "####MapMapMexican####DENISOVA###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
t = 10.7936, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.02615610 0.03775597 
sample estimates:
       cor 
0.03195711 

[1] "==========0============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
S = 2.257325e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.0849313 

[1] "==========1.96710522742476e-181============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 5.211e-10
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 1.498755 2.128959 
sample estimates:
odds ratio 
  1.791754 

[1] "==========5.21078493778242e-10============="
[1] "###############################"
[1] "###############################"
[1] "####PuertoRican####DENISOVA###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
t = -1.9475, df = 113961, p-value = 0.05147
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 -1.157443e-02  3.691667e-05 
sample estimates:
        cor 
-0.00576895 

[1] "==========0.0514747548925085============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
S = 2.28185e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
       rho 
0.07498923 

[1] "==========8.85338229397568e-142============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.002857
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.6468320 0.9184495 
sample estimates:
odds ratio 
 0.7734199 

[1] "==========0.00285693941250176============="
[1] "###############################"
[1] "###############################"
[1] "####Toscan####DENISOVA###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
t = 12.5179, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.03125667 0.04285246 
sample estimates:
       cor 
0.03705581 

[1] "==========0============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
S = 2.291341e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
       rho 
0.07114188 

[1] "==========9.06662347359748e-128============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 2.111005 2.904231 
sample estimates:
odds ratio 
  2.481598 

[1] "==========1.37304453808272e-24============="
[1] "###############################"
[1] "###############################"
[1] "####Yoruba####DENISOVA###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
t = -31.8479, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 -0.09967599 -0.08816669 
sample estimates:
        cor 
-0.09392448 

[1] "==========1.33187949316754e-221============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and DenisovaMat[, 12] 
S = 2.607198e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
       rho 
-0.0568992 

[1] "==========2.34774705003168e-82============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.3941982 0.4360079 
sample estimates:
odds ratio 
 0.4145773 

[1] "==========1.20573764829284e-264============="
[1] "###############################"
[1] "###############################"
[1] "####NEANDERTAL###########"
[1] "###############################"
[1] "###############################"
[1] "####HapMapAfricans####NEANDERTAL###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
t = -32.3876, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 -0.10125141 -0.08974558 
sample estimates:
        cor 
-0.09550169 

[1] "==========4.53949402673368e-229============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
S = 2.508534e+14, p-value = 1.153e-08
alternative hypothesis: true rho is not equal to 0 
sample estimates:
        rho 
-0.01690322 

[1] "==========1.15252395253014e-08============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.3598688 0.4083688 
sample estimates:
odds ratio 
 0.3834785 

[1] "==========3.47316415290511e-236============="
[1] "###############################"
[1] "###############################"
[1] "####CEPHEuropean####NEANDERTAL###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
t = 77.0749, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.2170621 0.2280986 
sample estimates:
      cor 
0.2225875 

[1] "==========0============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
S = 2.06159e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.1642779 

[1] "==========0============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 11.39652 14.68017 
sample estimates:
odds ratio 
  12.93595 

[1] "==========3.62053884640185e-279============="
[1] "###############################"
[1] "###############################"
[1] "####HanChineseBeijing####NEANDERTAL###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
t = 104.4266, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.2902135 0.3008112 
sample estimates:
      cor 
0.2955215 

[1] "==========0============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
S = 1.916819e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.2229646 

[1] "==========0============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 20.78797 25.04277 
sample estimates:
odds ratio 
  22.82472 

[1] "==========0============="
[1] "###############################"
[1] "###############################"
[1] "####HanChineseSouth####NEANDERTAL###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
t = 84.208, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.2365555 0.2474871 
sample estimates:
     cor 
0.242029 

[1] "==========0============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
S = 1.946602e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.2108912 

[1] "==========0============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 15.67101 18.94680 
sample estimates:
odds ratio 
  17.23073 

[1] "==========0============="
[1] "###############################"
[1] "###############################"
[1] "####Colombian####NEANDERTAL###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
t = 19.5176, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.05193125 0.06350430 
sample estimates:
       cor 
0.05771971 

[1] "==========0============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
S = 2.184023e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.1146463 

[1] "==========0============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 1.780998 2.356674 
sample estimates:
odds ratio 
  2.052385 

[1] "==========5.0338378441679e-21============="
[1] "###############################"
[1] "###############################"
[1] "####HapMapFinnish####NEANDERTAL###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
t = 77.6756, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.2187142 0.2297421 
sample estimates:
      cor 
0.2242353 

[1] "==========0============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
S = 2.023834e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.1795832 

[1] "==========0============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 14.75157 18.53560 
sample estimates:
odds ratio 
  16.54221 

[1] "==========0============="
[1] "###############################"
[1] "###############################"
[1] "####British####NEANDERTAL###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
t = 80.9175, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.2275974 0.2385783 
sample estimates:
      cor 
0.2330953 

[1] "==========0============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
S = 2.043486e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.1716169 

[1] "==========0============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 13.73001 17.47375 
sample estimates:
odds ratio 
  15.48552 

[1] "==========0============="
[1] "###############################"
[1] "###############################"
[1] "####Iberian####NEANDERTAL###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
t = 28.4885, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.07832351 0.08985313 
sample estimates:
       cor 
0.08409114 

[1] "==========0============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
S = 2.21119e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.1036334 

[1] "==========1.40474891453482e-269============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
  4.577027 10.361899 
sample estimates:
odds ratio 
  6.939485 

[1] "==========3.94711725161511e-17============="
[1] "###############################"
[1] "###############################"
[1] "####Japanese####NEANDERTAL###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
t = 99.5345, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.2774591 0.2881421 
sample estimates:
      cor 
0.2828094 

[1] "==========0============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
S = 1.930364e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.2174739 

[1] "==========0============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 20.56902 25.40723 
sample estimates:
odds ratio 
  22.84191 

[1] "==========0============="
[1] "###############################"
[1] "###############################"
[1] "####KOREAN####NEANDERTAL###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
t = 66.5149, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.1877219 0.1988997 
sample estimates:
     cor 
0.193317 

[1] "==========0============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
S = 1.858429e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.2466347 

[1] "==========0============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
  9.253958 11.091510 
sample estimates:
odds ratio 
  10.13408 

[1] "==========0============="
[1] "###############################"
[1] "###############################"
[1] "####Luhya####NEANDERTAL###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
t = -58.8414, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 -0.1773433 -0.1660739 
sample estimates:
       cor 
-0.1717142 

[1] "==========0============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
S = 2.759088e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
       rho 
-0.1184723 

[1] "==========0============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.1952538 0.2161436 
sample estimates:
odds ratio 
 0.2054494 

[1] "==========0============="
[1] "###############################"
[1] "###############################"
[1] "####MapMapMexican####NEANDERTAL###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
t = 34.004, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.09447042 0.10596553 
sample estimates:
      cor 
0.1002213 

[1] "==========0============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
S = 2.172574e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.1192875 

[1] "==========0============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 4.420146 5.635597 
sample estimates:
odds ratio 
  4.994957 

[1] "==========6.98903256184245e-116============="
[1] "###############################"
[1] "###############################"
[1] "####PuertoRican####NEANDERTAL###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
t = 8.4112, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.01910539 0.03070991 
sample estimates:
       cor 
0.02490849 

[1] "==========0============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
S = 2.20905e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
     rho 
0.104501 

[1] "==========4.23161832306114e-274============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.127
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.9653161 1.2826641 
sample estimates:
odds ratio 
  1.115031 

[1] "==========0.126967943952974============="
[1] "###############################"
[1] "###############################"
[1] "####Toscan####NEANDERTAL###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
t = 69.1204, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.1950116 0.2061561 
sample estimates:
      cor 
0.2005904 

[1] "==========0============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
S = 2.076522e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.1582248 

[1] "==========0============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
  9.380475 11.707899 
sample estimates:
odds ratio 
  10.48504 

[1] "==========4.09888242273481e-298============="
[1] "###############################"
[1] "###############################"
[1] "####Yoruba####NEANDERTAL###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
t = -55.2856, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 -0.1672656 -0.1559572 
sample estimates:
       cor 
-0.1616167 

[1] "==========0============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and NeanderMat[, 12] 
S = 2.715098e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
       rho 
-0.1006396 

[1] "==========2.84089674312307e-254============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.2121796 0.2353314 
sample estimates:
odds ratio 
 0.2234815 

[1] "==========0============="
[1] "###############################"
[1] "###############################"
[1] "####ANCESTOR###########"
[1] "###############################"
[1] "###############################"
[1] "####HapMapAfricans####ANCESTOR###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
t = 1.394, df = 113961, p-value = 0.1633
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 -0.001676652  0.009934882 
sample estimates:
        cor 
0.004129254 

[1] "==========0.16332936510337============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
S = 2.281374e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
       rho 
0.07518243 

[1] "==========1.67468602773179e-142============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.6654
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.9220427 1.0520390 
sample estimates:
odds ratio 
 0.9850756 

[1] "==========0.665367879768498============="
[1] "###############################"
[1] "###############################"
[1] "####CEPHEuropean####ANCESTOR###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
t = 7.4889, df = 113961, p-value = 6.994e-14
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.01637475 0.02798077 
sample estimates:
       cor 
0.02217851 

[1] "==========6.99440505513849e-14============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
S = 2.299882e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
       rho 
0.06767943 

[1] "==========8.53583275658744e-116============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.101
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.9332135 1.6984700 
sample estimates:
odds ratio 
  1.272227 

[1] "==========0.101032777211887============="
[1] "###############################"
[1] "###############################"
[1] "####HanChineseBeijing####ANCESTOR###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
t = 6.1451, df = 113961, p-value = 8.018e-10
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.01239571 0.02400360 
sample estimates:
       cor 
0.01820027 

[1] "==========8.01840371877915e-10============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
S = 2.316202e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
       rho 
0.06106376 

[1] "==========1.38245689501511e-94============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.1914
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.9182223 1.4385102 
sample estimates:
odds ratio 
  1.155931 

[1] "==========0.191361774846141============="
[1] "###############################"
[1] "###############################"
[1] "####HanChineseSouth####ANCESTOR###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
t = 4.633, df = 113961, p-value = 3.607e-06
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.007917685 0.019527230 
sample estimates:
       cor 
0.01372292 

[1] "==========3.60741930771624e-06============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
S = 2.325058e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
       rho 
0.05747402 

[1] "==========5.42055562209355e-84============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.359
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.8716237 1.3963215 
sample estimates:
odds ratio 
  1.110272 

[1] "==========0.359006282835752============="
[1] "###############################"
[1] "###############################"
[1] "####Colombian####ANCESTOR###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
t = 3.4231, df = 113961, p-value = 0.0006194
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.004333887 0.015944425 
sample estimates:
      cor 
0.0101395 

[1] "==========0.000619378842849905============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
S = 2.179226e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.1165908 

[1] "==========0============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.2032
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.6374168 1.0840924 
sample estimates:
odds ratio 
 0.8382817 

[1] "==========0.203183700500443============="
[1] "###############################"
[1] "###############################"
[1] "####HapMapFinnish####ANCESTOR###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
t = 9.5009, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.02233078 0.03393332 
sample estimates:
     cor 
0.028133 

[1] "==========0============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
S = 2.298858e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.0680946 

[1] "==========3.3667370070249e-117============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.00294
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 1.137109 1.883860 
sample estimates:
odds ratio 
  1.474118 

[1] "==========0.00294042551682006============="
[1] "###############################"
[1] "###############################"
[1] "####British####ANCESTOR###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
t = 8.6848, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.01991513 0.03151918 
sample estimates:
       cor 
0.02571802 

[1] "==========0============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
S = 2.299922e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
       rho 
0.06766344 

[1] "==========9.66387644303212e-116============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 7.898e-05
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 1.306199 2.160320 
sample estimates:
odds ratio 
  1.691647 

[1] "==========7.89793548051425e-05============="
[1] "###############################"
[1] "###############################"
[1] "####Iberian####ANCESTOR###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
t = 4.7538, df = 113961, p-value = 1.998e-06
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.008275511 0.019884941 
sample estimates:
      cor 
0.0140807 

[1] "==========1.99822677249273e-06============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
S = 2.343388e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
       rho 
0.05004308 

[1] "==========4.19304666568485e-64============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.4557
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.5012801 3.1402372 
sample estimates:
odds ratio 
  1.396327 

[1] "==========0.455670900617191============="
[1] "###############################"
[1] "###############################"
[1] "####Japanese####ANCESTOR###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
t = 7.3282, df = 113961, p-value = 2.349e-13
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.01589886 0.02750513 
sample estimates:
       cor 
0.02170273 

[1] "==========2.34923192010683e-13============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
S = 2.309634e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.0637262 

[1] "==========7.38228565234231e-103============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.00249
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 1.129606 1.793391 
sample estimates:
odds ratio 
   1.43181 

[1] "==========0.00249045847096876============="
[1] "###############################"
[1] "###############################"
[1] "####KOREAN####ANCESTOR###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
t = -12.7521, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 -0.04354440 -0.03194921 
sample estimates:
        cor 
-0.03774808 

[1] "==========3.21686307672447e-37============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
S = 2.555519e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
        rho 
-0.03594996 

[1] "==========6.4887119578788e-34============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.004451
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 1.091606 1.631437 
sample estimates:
odds ratio 
  1.340466 

[1] "==========0.00445075470498225============="
[1] "###############################"
[1] "###############################"
[1] "####Luhya####ANCESTOR###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
t = -8.2349, df = 113961, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 -0.03018815 -0.01858332 
sample estimates:
        cor 
-0.02438655 

[1] "==========1.81599371282493e-16============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
S = 2.48694e+14, p-value = 0.00594
alternative hypothesis: true rho is not equal to 0 
sample estimates:
         rho 
-0.008149305 

[1] "==========0.005939712791134============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.2053
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.8992238 1.0233096 
sample estimates:
odds ratio 
 0.9591232 

[1] "==========0.205318288976249============="
[1] "###############################"
[1] "###############################"
[1] "####MapMapMexican####ANCESTOR###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
t = 0.8481, df = 113961, p-value = 0.3964
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 -0.003293686  0.008317973 
sample estimates:
        cor 
0.002512228 

[1] "==========0.396393280584017============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
S = 2.225194e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.0979564 

[1] "==========6.07256384611646e-241============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.0193
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.4877074 0.9492115 
sample estimates:
odds ratio 
 0.6897444 

[1] "==========0.0193013535196166============="
[1] "###############################"
[1] "###############################"
[1] "####PuertoRican####ANCESTOR###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
t = 2.6356, df = 113961, p-value = 0.0084
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.002001345 0.013612368 
sample estimates:
       cor 
0.00780712 

[1] "==========0.0083995998192683============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
S = 2.169169e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.1206678 

[1] "==========0============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.3078
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.9101414 1.3222299 
sample estimates:
odds ratio 
   1.10126 

[1] "==========0.307846289728565============="
[1] "###############################"
[1] "###############################"
[1] "####Toscan####ANCESTOR###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
t = 7.0455, df = 113961, p-value = 1.858e-12
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.01506204 0.02666872 
sample estimates:
       cor 
0.02086608 

[1] "==========1.85806925401266e-12============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
S = 2.276164e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
       rho 
0.07729429 

[1] "==========1.57322758500017e-150============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.04787
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.9902054 1.6500589 
sample estimates:
odds ratio 
  1.287805 

[1] "==========0.0478731251794013============="
[1] "###############################"
[1] "###############################"
[1] "####Yoruba####ANCESTOR###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
t = 3.5297, df = 113961, p-value = 0.0004163
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.004649585 0.016260047 
sample estimates:
       cor 
0.01045517 

[1] "==========0.000416257649060281============="

	Spearman's rank correlation rho

data:  SubPopulationMat[, pop] and AncestMat[, 12] 
S = 2.365866e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.0409311 

[1] "==========1.84342088033899e-43============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.1535
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.8970917 1.0176733 
sample estimates:
odds ratio 
 0.9554197 

[1] "==========0.153501612441728============="
[1] "###############################"
[1] "###############################"
[1] "####DENISOVA 2###########"
[1] "###############################"
[1] "###############################"
[1] "####HapMapAfricans####DENISOVA 2###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.4594046 0.5691118 
sample estimates:
odds ratio 
 0.5117506 

[1] "==========9.2362083693879e-40============="
[1] "###############################"
[1] "###############################"
[1] "####CEPHEuropean####DENISOVA 2###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 8.255e-10
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 2.018112 3.623094 
sample estimates:
odds ratio 
  2.730213 

[1] "==========8.25475961789995e-10============="
[1] "###############################"
[1] "###############################"
[1] "####HanChineseBeijing####DENISOVA 2###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
  8.744249 11.432061 
sample estimates:
odds ratio 
  10.00974 

[1] "==========1.06908491884408e-165============="
[1] "###############################"
[1] "###############################"
[1] "####HanChineseSouth####DENISOVA 2###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
  7.807799 10.365401 
sample estimates:
odds ratio 
  9.009087 

[1] "==========2.47768738197364e-136============="
[1] "###############################"
[1] "###############################"
[1] "####Colombian####DENISOVA 2###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.3567
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.5639661 1.1922973 
sample estimates:
odds ratio 
 0.8345649 

[1] "==========0.356691438305587============="
[1] "###############################"
[1] "###############################"
[1] "####HapMapFinnish####DENISOVA 2###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 1.265e-13
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 2.255362 3.764145 
sample estimates:
odds ratio 
  2.934675 

[1] "==========1.26470914372999e-13============="
[1] "###############################"
[1] "###############################"
[1] "####British####DENISOVA 2###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 1.986e-14
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 2.408895 4.071754 
sample estimates:
odds ratio 
  3.155544 

[1] "==========1.98624738023902e-14============="
[1] "###############################"
[1] "###############################"
[1] "####Iberian####DENISOVA 2###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.001891
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 1.590948 7.738997 
sample estimates:
odds ratio 
  3.783799 

[1] "==========0.00189123298557861============="
[1] "###############################"
[1] "###############################"
[1] "####Japanese####DENISOVA 2###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
  7.516126 10.238116 
sample estimates:
odds ratio 
  8.787722 

[1] "==========1.07606191395031e-111============="
[1] "###############################"
[1] "###############################"
[1] "####KOREAN####DENISOVA 2###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 12.37239 15.71135 
sample estimates:
odds ratio 
  13.94846 

[1] "==========1.40467508575169e-270============="
[1] "###############################"
[1] "###############################"
[1] "####Luhya####DENISOVA 2###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.2973004 0.3541294 
sample estimates:
odds ratio 
 0.3245309 

[1] "==========3.4222747334198e-147============="
[1] "###############################"
[1] "###############################"
[1] "####MapMapMexican####DENISOVA 2###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.0003746
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 1.292735 2.349998 
sample estimates:
odds ratio 
  1.761371 

[1] "==========0.000374595655349601============="
[1] "###############################"
[1] "###############################"
[1] "####PuertoRican####DENISOVA 2###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.5455
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.677717 1.198126 
sample estimates:
odds ratio 
 0.9099812 

[1] "==========0.545450346070509============="
[1] "###############################"
[1] "###############################"
[1] "####Toscan####DENISOVA 2###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 4.865e-12
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 2.070999 3.439406 
sample estimates:
odds ratio 
  2.687911 

[1] "==========4.8650169166641e-12============="
[1] "###############################"
[1] "###############################"
[1] "####Yoruba####DENISOVA 2###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.3095125 0.3698064 
sample estimates:
odds ratio 
 0.3384024 

[1] "==========1.47274332794816e-135============="
[1] "###############################"
[1] "###############################"
[1] "####DENISOVA 3###########"
[1] "###############################"
[1] "###############################"
[1] "####HapMapAfricans####DENISOVA 3###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 1.431e-09
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.5459147 0.7455281 
sample estimates:
odds ratio 
 0.6395851 

[1] "==========1.4312194295119e-09============="
[1] "###############################"
[1] "###############################"
[1] "####CEPHEuropean####DENISOVA 3###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.2597
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.6620598 3.1080679 
sample estimates:
odds ratio 
  1.551573 

[1] "==========0.259745194634531============="
[1] "###############################"
[1] "###############################"
[1] "####HanChineseBeijing####DENISOVA 3###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
  8.907355 13.877945 
sample estimates:
odds ratio 
  11.15927 

[1] "==========2.30541384475131e-65============="
[1] "###############################"
[1] "###############################"
[1] "####HanChineseSouth####DENISOVA 3###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
  8.052366 12.167073 
sample estimates:
odds ratio 
  9.930233 

[1] "==========6.44734593677028e-69============="
[1] "###############################"
[1] "###############################"
[1] "####Colombian####DENISOVA 3###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.1797
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.283380 1.191551 
sample estimates:
odds ratio 
 0.6230972 

[1] "==========0.179714639116434============="
[1] "###############################"
[1] "###############################"
[1] "####HapMapFinnish####DENISOVA 3###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.0006907
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 1.466386 4.156663 
sample estimates:
odds ratio 
  2.551667 

[1] "==========0.000690704117227562============="
[1] "###############################"
[1] "###############################"
[1] "####British####DENISOVA 3###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.2132
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.6808389 2.9008573 
sample estimates:
odds ratio 
  1.505269 

[1] "==========0.21323047068002============="
[1] "###############################"
[1] "###############################"
[1] "####Iberian####DENISOVA 3###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.06835
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
  0.6610836 10.3592672 
sample estimates:
odds ratio 
  3.325456 

[1] "==========0.0683484779324296============="
[1] "###############################"
[1] "###############################"
[1] "####Japanese####DENISOVA 3###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
  6.565164 10.948444 
sample estimates:
odds ratio 
  8.526852 

[1] "==========1.16196180219092e-40============="
[1] "###############################"
[1] "###############################"
[1] "####KOREAN####DENISOVA 3###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 11.91000 15.35357 
sample estimates:
odds ratio 
  13.53379 

[1] "==========5.69224119469039e-232============="
[1] "###############################"
[1] "###############################"
[1] "####Luhya####DENISOVA 3###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.4031952 0.4889390 
sample estimates:
odds ratio 
 0.4442332 

[1] "==========4.88671055752714e-69============="
[1] "###############################"
[1] "###############################"
[1] "####MapMapMexican####DENISOVA 3###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.004241
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 1.247174 3.152648 
sample estimates:
odds ratio 
  2.036036 

[1] "==========0.00424120891642918============="
[1] "###############################"
[1] "###############################"
[1] "####PuertoRican####DENISOVA 3###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.407
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.7706514 1.7008247 
sample estimates:
odds ratio 
  1.167498 

[1] "==========0.407021823450877============="
[1] "###############################"
[1] "###############################"
[1] "####Toscan####DENISOVA 3###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.8534
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.449768 2.094526 
sample estimates:
odds ratio 
  1.050582 

[1] "==========0.853409000952498============="
[1] "###############################"
[1] "###############################"
[1] "####Yoruba####DENISOVA 3###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value < 2.2e-16
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.4267816 0.5230046 
sample estimates:
odds ratio 
 0.4727772 

[1] "==========4.03394796840758e-54============="
[1] "###############################"