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

	Pearson's product-moment correlation

data:  PopulationMat[, pop] and DenisovaMat[, 12] 
t = -56.4529, df = 160586, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 -0.1442896 -0.1346981 
sample estimates:
       cor 
-0.1394972 

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

	Spearman's rank correlation rho

data:  PopulationMat[, pop] and DenisovaMat[, 12] 
S = 7.668769e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
       rho 
-0.1110603 

[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:
 0.2728302 0.3010362 
sample estimates:
odds ratio 
 0.2865778 

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

	Pearson's product-moment correlation

data:  PopulationMat[, pop] and DenisovaMat[, 12] 
t = 6.5542, df = 160586, p-value = 5.612e-11
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.01146331 0.02124257 
sample estimates:
       cor 
0.01635333 

[1] "==========5.61182211811229e-11============="

	Spearman's rank correlation rho

data:  PopulationMat[, pop] and DenisovaMat[, 12] 
S = 6.432396e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
       rho 
0.06806687 

[1] "==========3.39058095481196e-164============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.00386
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 1.030197 1.168999 
sample estimates:
odds ratio 
  1.097818 

[1] "==========0.00386031424922727============="
[1] "###############################"
[1] "###############################"
[1] "####ASIAN###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  PopulationMat[, pop] and DenisovaMat[, 12] 
t = 62.7879, df = 160586, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.1500172 0.1595647 
sample estimates:
      cor 
0.1547945 

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

	Spearman's rank correlation rho

data:  PopulationMat[, pop] and DenisovaMat[, 12] 
S = 5.98753e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.1325196 

[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:
 4.423302 4.958965 
sample estimates:
odds ratio 
  4.684225 

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

	Pearson's product-moment correlation

data:  PopulationMat[, pop] and DenisovaMat[, 12] 
t = 29.9623, df = 160586, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.06969533 0.07942282 
sample estimates:
       cor 
0.07456085 

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

	Spearman's rank correlation rho

data:  PopulationMat[, pop] and DenisovaMat[, 12] 
S = 6.245234e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
       rho 
0.09518311 

[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:
 2.185612 2.455974 
sample estimates:
odds ratio 
  2.317433 

[1] "==========2.77530242252935e-152============="
[1] "###############################"
[1] "###############################"
[1] "####NEANDERTAL###########"
[1] "###############################"
[1] "###############################"
[1] "####AFRICAN###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  PopulationMat[, pop] and NeanderMat[, 12] 
t = -161.1011, df = 160586, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 -0.3772065 -0.3687855 
sample estimates:
       cor 
-0.3730037 

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

	Spearman's rank correlation rho

data:  PopulationMat[, pop] and NeanderMat[, 12] 
S = 8.28276e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
-0.200016 

[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:
 0.06373279 0.06931534 
sample estimates:
odds ratio 
0.06647877 

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

	Pearson's product-moment correlation

data:  PopulationMat[, pop] and NeanderMat[, 12] 
t = 33.8106, df = 160586, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.07921509 0.08892783 
sample estimates:
       cor 
0.08407346 

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

	Spearman's rank correlation rho

data:  PopulationMat[, pop] and NeanderMat[, 12] 
S = 6.153966e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.1084062 

[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:
 2.056667 2.268687 
sample estimates:
odds ratio 
   2.16057 

[1] "==========2.55989026704698e-185============="
[1] "###############################"
[1] "###############################"
[1] "####ASIAN###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  PopulationMat[, pop] and NeanderMat[, 12] 
t = 135.5229, df = 160586, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.3159682 0.3247462 
sample estimates:
      cor 
0.3203641 

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

	Spearman's rank correlation rho

data:  PopulationMat[, pop] and NeanderMat[, 12] 
S = 5.315652e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.2298621 

[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:
 13.36977 14.78596 
sample estimates:
odds ratio 
  14.05683 

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

	Pearson's product-moment correlation

data:  PopulationMat[, pop] and NeanderMat[, 12] 
t = 108.2106, df = 160586, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.2561306 0.2652477 
sample estimates:
     cor 
0.260695 

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

	Spearman's rank correlation rho

data:  PopulationMat[, pop] and NeanderMat[, 12] 
S = 5.567658e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
      rho 
0.1933511 

[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:
 7.182681 7.864227 
sample estimates:
odds ratio 
  7.516188 

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

	Pearson's product-moment correlation

data:  PopulationMat[, pop] and AncestMat[, 12] 
t = -11.9338, df = 160586, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 -0.03465282 -0.02487961 
sample estimates:
        cor 
-0.02976693 

[1] "==========8.14103892530757e-33============="

	Spearman's rank correlation rho

data:  PopulationMat[, pop] and AncestMat[, 12] 
S = 7.350685e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
        rho 
-0.06497597 

[1] "==========8.99096612863471e-150============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 9.979e-07
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.8006987 0.9088270 
sample estimates:
odds ratio 
 0.8527671 

[1] "==========9.97889947313013e-07============="
[1] "###############################"
[1] "###############################"
[1] "####AD MIX AMERICAN###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  PopulationMat[, pop] and AncestMat[, 12] 
t = 2.2428, df = 160586, p-value = 0.02491
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.000705738 0.010487307 
sample estimates:
        cor 
0.005596656 

[1] "==========0.0249114913032598============="

	Spearman's rank correlation rho

data:  PopulationMat[, pop] and AncestMat[, 12] 
S = 6.491157e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
       rho 
0.05955349 

[1] "==========4.26724233215597e-126============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.3122
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.9083906 1.0305698 
sample estimates:
odds ratio 
 0.9678758 

[1] "==========0.312184321923054============="
[1] "###############################"
[1] "###############################"
[1] "####ASIAN###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  PopulationMat[, pop] and AncestMat[, 12] 
t = 4.077, df = 160586, p-value = 4.564e-05
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.005282727 0.015063591 
sample estimates:
      cor 
0.0101734 

[1] "==========4.56390802419104e-05============="

	Spearman's rank correlation rho

data:  PopulationMat[, pop] and AncestMat[, 12] 
S = 6.564724e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
       rho 
0.04889503 

[1] "==========1.38809938848948e-85============="

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 2.19e-08
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 1.163325 1.364394 
sample estimates:
odds ratio 
  1.260564 

[1] "==========2.18970456297442e-08============="
[1] "###############################"
[1] "###############################"
[1] "####EUROPEAN###########"
[1] "###############################"

	Pearson's product-moment correlation

data:  PopulationMat[, pop] and AncestMat[, 12] 
t = 15.0455, df = 160586, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
 0.03263374 0.04240185 
sample estimates:
       cor 
0.03751869 

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

	Spearman's rank correlation rho

data:  PopulationMat[, pop] and AncestMat[, 12] 
S = 6.436217e+14, p-value < 2.2e-16
alternative hypothesis: true rho is not equal to 0 
sample estimates:
       rho 
0.06751325 

[1] "==========1.45642562053106e-161============="

	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:
 1.372771 1.560928 
sample estimates:
odds ratio 
  1.464305 

[1] "==========2.08771910997045e-29============="
[1] "###############################"
[1] "###############################"
[1] "####DENISOVA 2###########"
[1] "###############################"
[1] "###############################"
[1] "####AFRICAN###########"
[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:
 0.2288133 0.2648134 
sample estimates:
odds ratio 
 0.2460869 

[1] "==========1.77764717843512e-250============="
[1] "###############################"
[1] "###############################"
[1] "####AD MIX AMERICAN###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.2377
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.9583628 1.1800940 
sample estimates:
odds ratio 
  1.064596 

[1] "==========0.237712740250966============="
[1] "###############################"
[1] "###############################"
[1] "####ASIAN###########"
[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:
 5.001494 5.885885 
sample estimates:
odds ratio 
  5.428121 

[1] "==========1.94710636252654e-272============="
[1] "###############################"
[1] "###############################"
[1] "####EUROPEAN###########"
[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:
 2.184707 2.617649 
sample estimates:
odds ratio 
  2.392968 

[1] "==========8.86238724733413e-68============="
[1] "###############################"
[1] "###############################"
[1] "####DENISOVA 3###########"
[1] "###############################"
[1] "###############################"
[1] "####AFRICAN###########"
[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:
 0.2435019 0.2804579 
sample estimates:
odds ratio 
 0.2613039 

[1] "==========1.33707814595772e-251============="
[1] "###############################"
[1] "###############################"
[1] "####AD MIX AMERICAN###########"
[1] "###############################"

	Fisher's Exact Test for Count Data

data:  conf 
p-value = 0.3413
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.9125029 1.2749402 
sample estimates:
odds ratio 
   1.08196 

[1] "==========0.341292122415414============="
[1] "###############################"
[1] "###############################"
[1] "####ASIAN###########"
[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:
 5.361355 6.378497 
sample estimates:
odds ratio 
  5.850305 

[1] "==========1.35246355128737e-254============="
[1] "###############################"
[1] "###############################"
[1] "####EUROPEAN###########"
[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:
 2.115295 2.603442 
sample estimates:
odds ratio 
  2.349068 

[1] "==========2.57802837760391e-49============="
[1] "###############################"