| tags: [ Genomic Data PCA PLINK ] categories: [Coding Experiments ]
Performing PCA on filtered NIES genomic data
Introduction
After addressing the missing genotype filtering issue, the PCA on the final data set will need to be repeated. Performing a PCA will reveal population structure and will reveal any underlying genetic structures in the genomic data.
Methods and Results
Note: I forgot to change the paternal and maternal IDs before I re-did the merge and it seemed to be causing issues with the PCA. I changed the paternal and maternal IDs in the final data set (nies_miss_filtered) ONLY.
1. Run PCA
plink1.9 --bfile nies_miss_filtered --pca 180 var-wts --out plink_output/nies_mergedsnp_pca The count is modified to 180 to capture all PCs with an eigenvalue > 1 and the var-wts modifier will generate a file that includes variant contributions (i.e. membership coefficients).
2. Load eigenvalue file
nies_mergedsnp_pca_eigenval <- read.table('C:/Users/Martha/Documents/Honours/Project/honours.project/Data/plink_output/nies_mergedsnp_pca.eigenval', header = F)
head(nies_mergedsnp_pca_eigenval)## V1
## 1 5.48553
## 2 4.65242
## 3 4.19170
## 4 3.99730
## 5 3.69793
## 6 3.481823. Generate screeplot
barplot(nies_mergedsnp_pca_eigenval$V1,
names.arg = 1:nrow(nies_mergedsnp_pca_eigenval),
main = "NIES PCA Eigenvalue",
xlab = "Principal Components",
ylab = "Eigenvalue",
col ="lightskyblue2")
lines(x = 1:nrow(nies_mergedsnp_pca_eigenval), nies_mergedsnp_pca_eigenval$V1,
type = "b", pch = 19, col = "red")
There are 124 PCs with eigenvalue >1.
4. Load eigenvector file
nies_mergedsnp_pca_eigenvec <- read.table('C:/Users/Martha/Documents/Honours/Project/honours.project/Data/plink_output/nies_mergedsnp_pca.eigenvec', header = F)
head(nies_mergedsnp_pca_eigenvec)## V1 V2 V3 V4 V5 V6 V7
## 1 1 110150 0.0580533 -0.02181010 -0.00780063 -0.01339780 -0.0159969
## 2 1 110160 0.0603027 -0.02610870 0.00123163 -0.01550290 -0.0283369
## 3 1 110500 -0.0627142 -0.00597684 0.01986040 0.02116970 -0.0201570
## 4 1 110650 -0.1213000 -0.00551570 -0.10189800 -0.04138730 0.0418274
## 5 1 110820 -0.0124270 -0.00744404 -0.02447650 0.00310853 -0.0316200
## 6 1 111280 0.0734706 -0.02527090 -0.01060830 -0.02471250 -0.0204686
## V8 V9 V10 V11 V12 V13
## 1 -0.01048690 -0.012945600 0.00388005 0.00648779 0.00957051 -0.00660300
## 2 -0.01289850 -0.018414400 0.00813571 -0.01661600 0.03049390 -0.00272608
## 3 0.01639690 -0.012247800 0.00849990 -0.05850000 0.05549920 -0.00372680
## 4 0.00875482 0.024374700 -0.02105260 0.03956000 -0.01939270 0.00260395
## 5 -0.00792899 -0.000714059 -0.00782901 0.03126400 0.03276160 -0.04951610
## 6 -0.01038480 -0.012323000 0.00349920 -0.00311082 0.01847910 -0.00294400
## V14 V15 V16 V17 V18 V19
## 1 0.00593293 -0.000588801 0.00309164 -0.00858625 -0.00260197 0.0149693
## 2 -0.00317803 -0.008996640 -0.02629710 -0.01435460 -0.01107970 0.0888328
## 3 0.01591510 -0.009341670 -0.00302872 -0.05892730 -0.06463570 0.0745986
## 4 -0.02714940 0.000537460 -0.01113080 0.01490040 0.03649120 0.0237077
## 5 0.03871610 0.003605940 0.03906190 -0.06576060 -0.00262143 -0.0934364
## 6 0.00394709 -0.022009200 -0.00119686 -0.00976863 0.01805600 0.0165097
## V20 V21 V22 V23 V24
## 1 -0.005934760 -0.00208618 -3.29184e-03 -0.00658050 -0.00800942
## 2 -0.011911400 -0.05967270 -2.91357e-02 -0.00700849 -0.09652530
## 3 -0.022431900 -0.06561370 -1.49645e-03 0.08740310 0.10013700
## 4 -0.000991943 -0.03240350 -1.97088e-05 -0.00295890 -0.00546874
## 5 -0.004635140 -0.00310451 -2.30620e-02 0.02301510 -0.03129290
## 6 -0.013334700 0.00156326 1.86692e-02 -0.01120950 -0.02313320
## V25 V26 V27 V28 V29 V30
## 1 -0.00463907 0.01396930 -0.001245380 -0.00106755 -0.00783984 0.00217777
## 2 0.11622200 -0.06482740 0.032276300 0.00755965 0.02632220 0.03814950
## 3 0.01200850 -0.05191590 -0.015575600 -0.03646400 0.06959300 -0.02495550
## 4 0.01132850 0.00295416 0.000606828 0.00620507 -0.02301050 0.01666500
## 5 -0.00762375 0.03222100 0.037171900 -0.12920700 0.00528434 0.04090880
## 6 0.01525300 0.04073370 -0.025054900 -0.01336830 -0.02046330 0.00141455
## V31 V32 V33 V34 V35 V36
## 1 -0.00782729 -0.00240342 0.0174927 -0.00870952 0.00520303 -0.01150820
## 2 -0.02293870 -0.00390053 -0.0347669 0.00917760 -0.01337650 0.00912830
## 3 0.02795900 0.03207720 0.0281315 0.00851524 0.00803930 0.00143664
## 4 0.00582874 -0.00296321 -0.0457396 -0.08751990 -0.00906126 -0.02864310
## 5 -0.00262458 -0.08845570 -0.0794186 -0.00865573 -0.00783652 0.01948510
## 6 0.01693450 0.01753910 0.0882141 0.02257800 0.08313920 -0.10071400
## V37 V38 V39 V40 V41 V42
## 1 0.01617970 -0.00581790 0.00115008 -0.00664286 -0.00557068 0.00963309
## 2 0.00118579 0.02002830 0.02335850 0.01875990 -0.00397718 0.01018800
## 3 -0.01614540 -0.17845600 -0.04332030 -0.23522600 0.05695340 -0.15193500
## 4 0.01501750 0.00980803 0.00568763 0.00319338 0.00312568 -0.02486890
## 5 -0.01003610 0.03723760 -0.05217610 -0.01213090 0.00819801 0.03638850
## 6 0.08159660 -0.00227000 -0.30616400 -0.10026200 -0.70026500 -0.14530300
## V43 V44 V45 V46 V47 V48
## 1 0.01045060 0.00242226 -0.01406610 0.00634299 -0.00195383 0.00157447
## 2 -0.00253252 -0.00293676 0.00384136 0.00597699 -0.00489726 -0.00622170
## 3 0.06158300 -0.04812370 0.01945250 0.01432440 0.02020720 -0.00229730
## 4 -0.01407990 -0.01548830 0.00325367 -0.00451456 -0.00689999 -0.00298612
## 5 0.02401120 -0.01671840 0.01413850 -0.01193280 -0.02145040 0.02439760
## 6 -0.29851300 -0.30788400 0.13692500 0.23115300 -0.15269900 0.00966720
## V49 V50 V51 V52 V53 V54
## 1 0.00337618 0.01240300 -0.00425539 -0.00485039 0.00122091 0.00164213
## 2 -0.03244820 0.00178894 -0.00358877 0.01135150 -0.00307234 -0.00485710
## 3 -0.08335380 -0.03811870 -0.12540100 -0.14672400 0.02024600 0.01596100
## 4 -0.00536638 -0.01639000 0.00312845 0.04265300 0.03169380 0.01940930
## 5 -0.01935800 -0.03202100 -0.02432510 0.01735530 0.01533200 0.02006330
## 6 0.12562500 -0.02361540 0.02880490 -0.01318460 0.08401570 -0.02934090
## V55 V56 V57 V58 V59 V60
## 1 0.00690449 0.01910110 0.00412265 -0.01580070 0.0104596 0.00498214
## 2 0.00820774 -0.00250109 -0.00528773 -0.00916875 0.0214467 0.01299530
## 3 -0.02925380 0.01802110 0.08061020 -0.08222120 0.0303873 0.03521750
## 4 -0.01341600 0.02796420 0.00967232 0.01937110 -0.0516484 -0.18781600
## 5 0.00293897 0.03627790 -0.00294191 0.06370170 0.0428291 0.06877990
## 6 -0.03870670 0.01597550 0.00235369 0.09853200 -0.0521655 0.00671212
## V61 V62 V63 V64 V65 V66
## 1 0.00880112 -0.01114290 0.00636398 0.01324840 0.00389913 0.01120740
## 2 0.05021760 -0.00141409 0.05050970 0.03640430 -0.02779430 0.00517638
## 3 0.01256570 0.03476970 -0.01369090 -0.00310447 0.03363490 -0.02376850
## 4 0.03322760 0.10737200 0.00588210 -0.00902759 0.07114620 0.02218740
## 5 -0.01453880 -0.02876180 0.00914536 0.01292470 0.00486764 -0.01540110
## 6 -0.04543700 0.06673130 0.02010830 -0.02291080 -0.02526520 -0.02677710
## V67 V68 V69 V70 V71 V72
## 1 0.0146682 0.00522434 -0.00914312 -0.01146890 0.00885911 0.000108119
## 2 0.0251600 0.02821230 -0.04985000 -0.00434802 0.08090540 -0.117711000
## 3 -0.0370360 -0.05922970 -0.03449760 0.02741540 0.01229940 0.012229300
## 4 0.0650385 0.01137480 0.00902250 -0.10260600 0.00837667 0.005941700
## 5 0.0206996 0.04067020 -0.04720190 0.01477110 -0.01549600 0.021433000
## 6 -0.0315374 0.00880754 0.02105490 0.00660042 0.00338457 0.008695640
## V73 V74 V75 V76 V77 V78
## 1 0.010066100 -0.0223144 -0.0273216 -0.0150315 0.0156034 0.0171533
## 2 0.166257000 -0.0256179 0.0682009 0.0214916 -0.0672570 -0.0131806
## 3 0.000053434 -0.0463886 0.0028018 0.0325513 0.0210180 0.0140566
## 4 0.094069800 0.0647535 0.0523219 -0.1143650 0.0283962 0.0847421
## 5 -0.026934700 0.0126614 0.0190672 -0.1262400 -0.0239081 -0.0534103
## 6 0.006987970 0.0102255 0.0284900 0.0192278 -0.0206665 -0.0100639
## V79 V80 V81 V82 V83 V84
## 1 -0.008136860 0.00962546 0.00982921 0.01156120 0.02129050 -0.01751680
## 2 0.021038700 0.00138233 0.01509810 -0.01608150 -0.01731750 0.02469600
## 3 0.028249800 -0.01641900 -0.03046390 0.02027460 0.02883530 -0.00740610
## 4 -0.000906123 -0.01156610 -0.10494700 0.07667300 -0.00524314 -0.00236648
## 5 0.040599400 0.00601000 0.04847380 -0.07806990 -0.04116620 -0.01521740
## 6 -0.002312770 0.00287455 0.00178415 -0.00225482 -0.00821111 0.00309447
## V85 V86 V87 V88 V89 V90
## 1 0.00457159 -0.00408645 -0.00457461 0.0181709 0.01745590 0.00212766
## 2 -0.00471093 0.00867787 0.03015190 -0.0342671 0.01375430 0.04829120
## 3 -0.02373860 -0.04686160 -0.02421930 0.0196338 0.03499210 -0.00401268
## 4 0.03022330 -0.15827700 -0.00225803 0.0568574 0.06251270 0.04089830
## 5 -0.17776800 -0.09685540 -0.05043750 0.0261205 0.19505900 -0.01687070
## 6 0.00259575 0.02041260 0.01660500 -0.0047839 -0.00140185 0.00417252
## V91 V92 V93 V94 V95 V96
## 1 0.02184280 -0.00967006 0.01123210 -0.000299601 -0.01688730 -0.00264460
## 2 0.00522579 -0.03001530 -0.02092030 0.017658800 -0.08505740 0.04929710
## 3 0.01808690 0.01877150 0.00950924 -0.007053430 0.01569400 -0.00395051
## 4 0.03609610 -0.08461420 0.05794560 0.022976800 -0.01925530 0.04648220
## 5 0.07233380 0.10162100 0.02064050 0.022698100 0.08363990 -0.00336410
## 6 0.00670400 -0.00246764 -0.00505919 0.005006050 0.00545145 -0.00900900
## V97 V98 V99 V100 V101 V102
## 1 0.00462763 -0.01831480 0.022564000 -0.00284203 0.00865470 -0.05006000
## 2 -0.07607840 0.15477800 -0.075241500 0.02399970 0.01290660 -0.05024880
## 3 0.01919240 -0.00483976 0.033116500 -0.02065310 -0.03759220 0.00472340
## 4 -0.06316070 -0.16117100 0.026668400 0.03465200 -0.03016840 0.01521690
## 5 0.05518850 0.10920800 -0.017930600 -0.16920700 -0.14847900 -0.13024400
## 6 -0.00461421 0.01825110 0.000887915 -0.00697237 -0.00212243 0.00367182
## V103 V104 V105 V106 V107
## 1 -0.068075500 0.02510520 0.13952800 -0.00413094 0.00630122
## 2 -0.000255193 0.12302400 -0.00539848 -0.01039540 0.02018690
## 3 -0.001421450 0.00088267 -0.02221840 0.03299920 -0.00390762
## 4 0.028593000 -0.01139920 0.04093560 -0.00938868 -0.00720572
## 5 0.198864000 -0.05879400 0.12358000 -0.06155320 -0.02708440
## 6 0.005995210 -0.00996802 -0.01659920 0.01602410 -0.00120011
## V108 V109 V110 V111 V112 V113
## 1 -0.032489400 0.06817740 -0.03171390 0.01951640 0.01232290 0.05196460
## 2 -0.012184300 -0.05497160 -0.03218070 -0.04555290 -0.02661560 0.01424140
## 3 0.000472951 -0.00335946 0.01623950 -0.02141890 0.02024450 -0.02069300
## 4 -0.024008500 -0.02658030 0.00166353 -0.03345550 0.00416706 -0.06799350
## 5 0.095998500 -0.01631460 0.00351234 0.03254430 -0.05519100 0.01142940
## 6 -0.002547700 -0.01080140 0.01687360 0.00703329 -0.00206468 -0.00497138
## V114 V115 V116 V117 V118 V119
## 1 -0.02699800 0.06150460 0.02418310 0.04262860 0.13165200 -0.16303800
## 2 0.04955760 0.04940340 -0.08022640 0.07110660 -0.01719100 0.04071160
## 3 0.00913006 -0.00540506 -0.02094380 -0.01465740 0.01247950 -0.02158340
## 4 -0.03477620 -0.03173170 -0.05694930 -0.07467990 -0.06334620 -0.03725600
## 5 -0.06990980 -0.03009870 -0.06511780 0.05388050 -0.00609493 0.02029200
## 6 -0.00834490 -0.00286578 0.00278953 -0.00274628 0.00113293 -0.00317027
## V120 V121 V122 V123 V124
## 1 0.06842750 -0.044383300 0.019167900 0.14649500 -0.24960800
## 2 -0.04587240 0.028600900 -0.000525909 0.02063370 -0.01125590
## 3 0.00915690 0.004296840 -0.008668290 -0.00450780 -0.04789140
## 4 0.00642140 -0.059385600 -0.015295900 0.02130460 -0.04922690
## 5 -0.00237306 -0.000535242 -0.021844900 0.04308430 -0.00855428
## 6 0.00137092 0.002995040 0.000962721 -0.00738091 0.00734140
## V125 V126 V127 V128 V129
## 1 -0.19129100 0.390730000 0.178652000 0.073308300 -0.04382930
## 2 -0.05310810 0.009346700 0.015126400 -0.025005900 0.05899090
## 3 -0.01254080 -0.012677200 -0.060179100 -0.052547800 -0.01116910
## 4 -0.00252294 -0.061113200 0.041647700 0.039890000 0.01900570
## 5 0.02669190 -0.002728450 0.049494300 0.018860200 0.01723320
## 6 -0.00109346 0.000644824 -0.000498865 -0.000839896 -0.00804003
## V130 V131 V132 V133 V134
## 1 0.10033500 -0.478367000 0.324151000 -0.12891800 0.01354240
## 2 -0.01896500 0.023762900 -0.007318970 0.01999910 -0.00149277
## 3 0.00314394 -0.015922400 0.014662100 0.01883330 0.02075710
## 4 0.04161340 -0.003076160 -0.003657620 -0.00500664 0.00861792
## 5 0.01307070 0.028648500 0.029492200 0.00191751 0.00435353
## 6 -0.00181600 0.000960612 -0.000100017 0.00194846 0.00428462
## V135 V136 V137 V138 V139 V140
## 1 0.05209730 -0.00478589 -0.11858600 -0.13287300 0.12610600 0.0705684
## 2 0.02003470 0.00124692 -0.01390430 -0.03611690 0.01483050 -0.0464841
## 3 0.02073970 0.01858150 -0.02646090 -0.00623113 -0.01226930 -0.0203073
## 4 0.00199488 0.01170620 0.01032170 -0.04124960 -0.01553880 -0.0124197
## 5 -0.03089050 -0.02281130 0.02113440 -0.00439903 -0.01456160 0.0495630
## 6 -0.00354532 -0.00864431 -0.00446856 -0.00517413 -0.00214382 0.0013762
## V141 V142 V143 V144 V145 V146
## 1 0.12247700 -7.38478e-02 -0.032232500 0.0769023 0.15929500 -0.20513100
## 2 0.02524720 2.41657e-03 -0.040413700 0.0627728 0.01970590 0.08143080
## 3 -0.01342990 -5.44775e-03 0.000967213 0.0136930 -0.00351556 0.05391820
## 4 0.02441970 5.22873e-02 0.012021900 -0.0139247 -0.02080860 0.00457880
## 5 0.02199570 2.73086e-02 -0.013581500 0.0256259 -0.00720759 0.03005100
## 6 -0.00764995 -4.77188e-05 0.002664110 -0.0030741 0.00204634 -0.00052989
## V147 V148 V149 V150 V151 V152
## 1 0.052119000 -0.02522370 0.09477110 0.05137340 0.054656000 -0.04817710
## 2 0.006748520 0.00869137 -0.06372070 0.07520740 0.048658000 0.07498410
## 3 0.003322480 0.01871520 0.00471530 -0.01615590 0.035514100 0.00825111
## 4 0.030539200 -0.01881560 -0.01218860 -0.00649297 0.012409300 0.01321870
## 5 0.009736080 -0.00659521 -0.02035260 -0.03510660 0.000679085 -0.01974010
## 6 -0.000997563 0.00389109 -0.00242497 -0.00129399 0.002954580 0.01004160
## V153 V154 V155 V156 V157
## 1 -0.06625430 -0.019998800 0.02961120 -0.01644810 -8.84433e-03
## 2 0.06864840 0.124158000 -0.01050020 -0.05891040 1.54492e-01
## 3 0.03240720 0.013901900 0.03792000 0.01376910 -4.95837e-02
## 4 -0.05507040 0.026160500 0.00533067 -0.07011790 1.67534e-02
## 5 0.01166580 0.009774090 0.01829380 -0.01534050 -4.88636e-04
## 6 -0.00168715 -0.000869744 -0.00493961 0.00243669 8.10003e-06
## V158 V159 V160 V161 V162
## 1 -0.039019700 -0.017672700 -0.057368500 0.00775504 0.02659430
## 2 -0.074140600 0.096408900 -0.038436500 0.05198080 0.08380840
## 3 -0.024275200 -0.020752900 -0.028232300 0.02196050 0.01363410
## 4 0.020681400 0.000902287 -0.049579200 -0.04381270 -0.03362120
## 5 -0.000308501 -0.009178990 -0.022717600 0.02129490 -0.00697893
## 6 0.005115700 -0.005565500 -0.000724328 -0.00258916 0.00450059
## V163 V164 V165 V166 V167 V168
## 1 0.01042740 0.060763100 -0.01092560 0.02810950 0.00643299 0.02917300
## 2 -0.16714100 0.005338340 0.04283570 0.07471760 0.07143240 -0.08232050
## 3 0.00653668 -0.013609600 0.00092289 -0.01984740 -0.01534040 -0.01668310
## 4 0.03618720 0.014015900 -0.02508620 -0.03684450 0.02077830 -0.00119209
## 5 0.00160157 0.029267200 0.01807740 0.00986753 -0.00593741 0.00466225
## 6 -0.00152874 -0.000754018 0.00638870 -0.00140111 -0.00168477 0.00152801
## V169 V170 V171 V172 V173 V174
## 1 0.04545880 -0.02023620 -0.03157790 0.02090030 0.011116700 0.06602600
## 2 0.15246000 0.01855330 -0.05902410 -0.07257110 0.027449300 -0.02702810
## 3 -0.01548680 -0.00400023 0.01357240 0.00114033 -0.000496046 -0.00995036
## 4 0.02537400 0.02701610 -0.00830635 0.00754541 -0.004043270 -0.06484790
## 5 -0.02529580 -0.02000870 -0.00121372 0.00755906 -0.004868680 -0.00732274
## 6 0.00356159 0.00189407 -0.00244621 0.00309933 0.001073780 0.00776754
## V175 V176 V177 V178 V179 V180
## 1 0.02915790 -0.03298980 0.00165833 -0.04564290 -0.023814200 -0.00564948
## 2 -0.06474470 0.09401120 -0.12200500 -0.03669680 0.071505100 0.14759900
## 3 -0.02230090 -0.01658990 -0.00931276 0.02469480 0.054522300 -0.00649999
## 4 -0.03232290 -0.01633540 -0.00014721 -0.01572870 -0.031833700 -0.03190570
## 5 0.00424838 -0.00318330 0.01250620 0.01063030 -0.000175706 -0.00199057
## 6 0.00444232 0.00265844 0.00114818 0.00352842 -0.001934140 -0.00453990
## V181 V182
## 1 0.00960140 -0.02056120
## 2 0.02908570 0.17446100
## 3 -0.00341861 -0.02695520
## 4 0.01715600 -0.03955110
## 5 -0.00452073 -0.00969280
## 6 0.00728620 -0.003135015. Generate plots based on eigenvectors
plot(nies_mergedsnp_pca_eigenvec$V3, nies_mergedsnp_pca_eigenvec$V4, xlab = "PC1", ylab = "PC2", main = "PC1 vs PC2 eigenvectors") #PC1 vs PC2
plot(nies_mergedsnp_pca_eigenvec$V4, nies_mergedsnp_pca_eigenvec$V5, xlab = "PC2", ylab = "PC3", main = "PC2 vs PC3 eigenvectors") #PC1 vs PC2
plot(nies_mergedsnp_pca_eigenvec$V4, nies_mergedsnp_pca_eigenvec$V6, xlab = "PC2", ylab = "PC4", main = "PC2 vs PC4 eigenvectors") 
Note: the PCA plots have changed. The clustering that appeared from the first set of merged files no longer appear in the above PCA plots.