Last updated: 2019-04-03

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Knit directory: Comparative_eQTL/analysis/

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genotype data from this study (as vcf-files) was merged with that from deManuel et al 2016 (after LiftOver to PanTro5) which contains 65 chimp whole-genome genotype data spanning all of 4 recognized sub-species. Snps were pruned to get variants in approximate equilibrium. Genotype matrix was PCA transformed and plotted below. See Admixture results for a different analysis from the same pruned genotype matrix.

library(plyr)
library(tidyverse)
library(knitr)
library(reshape2)
library(ggrepel)
PCs <- read.table("../output/PopulationStructure/pca.eigenvec", header=T)
kable(head(PCs))
FID IID PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10 PC11 PC12 PC13 PC14 PC15 PC16 PC17 PC18 PC19 PC20
Pan_troglodytes_ThisStudy 549 -0.1086080 -0.0185367 0.0047385 -0.0162971 -0.0311260 0.0000395 0.0580742 0.0030003 0.0049427 -0.0146798 0.0007913 0.0000136 0.0018131 0.0443707 0.0005986 -0.0045199 0.0042858 -0.0054122 0.0049457 0.0040508
Pan_troglodytes_ThisStudy 570 -0.0945861 -0.0228424 -0.0139375 0.1784300 0.0561001 -0.0123242 -0.1530910 0.0069772 -0.0475961 0.2593960 -0.0499002 0.0451386 0.0244429 -0.0397052 -0.0247859 0.1374960 -0.0456096 0.3216140 -0.1129810 -0.1112110
Pan_troglodytes_ThisStudy 389 -0.1102000 -0.0206677 0.0032202 0.0154353 -0.1000540 0.0067056 -0.3743740 -0.0264212 0.0008181 0.0115340 0.0012632 -0.0003830 -0.0065716 -0.0203393 0.0044067 -0.0078456 0.0226097 -0.0235458 0.0019568 0.0015674
Pan_troglodytes_ThisStudy 456 -0.1080520 -0.0178848 0.0044265 -0.0109278 -0.0180761 -0.0001380 0.0346550 0.0027620 0.0022740 -0.0061954 0.0012627 -0.0010709 0.0001944 -0.0083610 -0.0012457 0.0000329 -0.0084463 0.0036722 0.0055043 0.0061112
Pan_troglodytes_ThisStudy 623 -0.1098180 -0.0207351 0.0041487 -0.0187801 -0.0988228 0.0098866 -0.2848930 -0.0250151 0.0174731 -0.0801156 0.0183987 -0.0171209 -0.0141164 0.0079797 0.0116067 -0.0583678 0.0340296 -0.1413580 0.0494442 0.0492784
Pan_troglodytes_ThisStudy 438 -0.1081380 -0.0178263 0.0044915 -0.0116550 -0.0195512 -0.0007298 0.0396553 0.0037245 0.0014656 -0.0086023 0.0023694 -0.0018639 -0.0017371 0.0041872 -0.0013800 -0.0000295 -0.0043911 -0.0012766 0.0051678 0.0062231
PCs$Subspecies <- mapvalues(PCs$FID, from=c("Pan_troglodytes_schweinfurthii", "Pan_troglodytes_ellioti", "Pan_troglodytes_ThisStudy", "Pan_troglodytes", "Pan_troglodytes_troglodytes", "Pan_troglodytes_verus"), to=c("Eastern", "Nigeria\nCameroon", "This Study", "Eastern", "Central", "Western"))

kable(head(PCs))
FID IID PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9 PC10 PC11 PC12 PC13 PC14 PC15 PC16 PC17 PC18 PC19 PC20 Subspecies
Pan_troglodytes_ThisStudy 549 -0.1086080 -0.0185367 0.0047385 -0.0162971 -0.0311260 0.0000395 0.0580742 0.0030003 0.0049427 -0.0146798 0.0007913 0.0000136 0.0018131 0.0443707 0.0005986 -0.0045199 0.0042858 -0.0054122 0.0049457 0.0040508 This Study
Pan_troglodytes_ThisStudy 570 -0.0945861 -0.0228424 -0.0139375 0.1784300 0.0561001 -0.0123242 -0.1530910 0.0069772 -0.0475961 0.2593960 -0.0499002 0.0451386 0.0244429 -0.0397052 -0.0247859 0.1374960 -0.0456096 0.3216140 -0.1129810 -0.1112110 This Study
Pan_troglodytes_ThisStudy 389 -0.1102000 -0.0206677 0.0032202 0.0154353 -0.1000540 0.0067056 -0.3743740 -0.0264212 0.0008181 0.0115340 0.0012632 -0.0003830 -0.0065716 -0.0203393 0.0044067 -0.0078456 0.0226097 -0.0235458 0.0019568 0.0015674 This Study
Pan_troglodytes_ThisStudy 456 -0.1080520 -0.0178848 0.0044265 -0.0109278 -0.0180761 -0.0001380 0.0346550 0.0027620 0.0022740 -0.0061954 0.0012627 -0.0010709 0.0001944 -0.0083610 -0.0012457 0.0000329 -0.0084463 0.0036722 0.0055043 0.0061112 This Study
Pan_troglodytes_ThisStudy 623 -0.1098180 -0.0207351 0.0041487 -0.0187801 -0.0988228 0.0098866 -0.2848930 -0.0250151 0.0174731 -0.0801156 0.0183987 -0.0171209 -0.0141164 0.0079797 0.0116067 -0.0583678 0.0340296 -0.1413580 0.0494442 0.0492784 This Study
Pan_troglodytes_ThisStudy 438 -0.1081380 -0.0178263 0.0044915 -0.0116550 -0.0195512 -0.0007298 0.0396553 0.0037245 0.0014656 -0.0086023 0.0023694 -0.0018639 -0.0017371 0.0041872 -0.0013800 -0.0000295 -0.0043911 -0.0012766 0.0051678 0.0062231 This Study
eigenvals <- read.table("../output/PopulationStructure/pca.eigenval", header=F)
kable(head(eigenvals))
V1
26.37000
7.61469
5.18840
1.83704
1.78864
1.56717
#Get rid of clutter by only labeling individuals in this study
PCs$Label <- PCs$IID
PCs$Label[PCs$FID != "Pan_troglodytes_ThisStudy"] <- ""
Warning in `[<-.factor`(`*tmp*`, PCs$FID != "Pan_troglodytes_ThisStudy", :
invalid factor level, NA generated
ggplot(PCs, aes(x=PC1, y=PC2, label=Label, color=Subspecies)) +
  geom_point() +
  geom_text_repel(size=2)
Warning: Removed 59 rows containing missing values (geom_text_repel).

ggplot(PCs, aes(x=PC2, y=PC3, label=Label, color=Subspecies)) +
  geom_point() +
  geom_text_repel(size=2)
Warning: Removed 59 rows containing missing values (geom_text_repel).

ggplot(PCs, aes(x=PC4, y=PC5, label=Label, color=Subspecies)) +
  geom_point() +
  geom_text_repel(size=2)
Warning: Removed 59 rows containing missing values (geom_text_repel).

ggplot(PCs, aes(x=PC6, y=PC7, label=Label, color=Subspecies)) +
  geom_point() +
  geom_text_repel(size=2)
Warning: Removed 59 rows containing missing values (geom_text_repel).

Conclusion from this (and admixture analysis) is that most individuals in this cohort are Western chimps, and a fair number have recent admixture with Central chimp. Will include this population structure information in modeling.

Subspecies admixture seems to be captured in the first 3 PCs. Looking at the smaller PCs, samples are not seperated by subspecies, but I notice a few samples still cluster tightly together, which seem to correspond to closely related samples as plotted in kinship analysis.



sessionInfo()
R version 3.5.1 (2018-07-02)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS  10.14

Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] ggrepel_0.8.0   reshape2_1.4.3  knitr_1.22      forcats_0.4.0  
 [5] stringr_1.4.0   dplyr_0.8.0.1   purrr_0.3.2     readr_1.3.1    
 [9] tidyr_0.8.2     tibble_2.1.1    ggplot2_3.1.0   tidyverse_1.2.1
[13] plyr_1.8.4     

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.1       highr_0.8        cellranger_1.1.0 pillar_1.3.1    
 [5] compiler_3.5.1   git2r_0.24.0     workflowr_1.2.0  tools_3.5.1     
 [9] digest_0.6.18    lubridate_1.7.4  jsonlite_1.6     evaluate_0.13   
[13] nlme_3.1-137     gtable_0.3.0     lattice_0.20-38  pkgconfig_2.0.2 
[17] rlang_0.3.3      cli_1.1.0        rstudioapi_0.10  yaml_2.2.0      
[21] haven_2.1.0      xfun_0.6         withr_2.1.2      xml2_1.2.0      
[25] httr_1.4.0       hms_0.4.2        generics_0.0.2   fs_1.2.6        
[29] rprojroot_1.3-2  grid_3.5.1       tidyselect_0.2.5 glue_1.3.1      
[33] R6_2.4.0         readxl_1.1.0     rmarkdown_1.11   modelr_0.1.4    
[37] magrittr_1.5     backports_1.1.3  scales_1.0.0     htmltools_0.3.6 
[41] rvest_0.3.2      assertthat_0.2.1 colorspace_1.4-1 labeling_0.3    
[45] stringi_1.4.3    lazyeval_0.2.2   munsell_0.5.0    broom_0.5.1     
[49] crayon_1.3.4