fam <- read.table("C:/Users/minal/OneDrive/Desktop/gen_data/02_activities/data/gwa.qc.A1.fam", header = FALSE)
+nrow(fam)
+
+[1] 4000 # The dataset contains 4000 samples
+
+
+
+
+
+
+
+
+Assignment #1
+Assignment 1
+You only need to write lines of code for each question. When answering questions that ask you to identify or interpret something, the length of your response doesn’t matter. For example, if the answer is just ‘yes,’ ‘no,’ or a number, you can just give that answer without adding anything else.
+We will go through comparable code and concepts in the live learning session. If you run into trouble, start by using the help help() function in R, to get information about the datasets and function in question. The internet is also a great resource when coding (though note that no outside searches are required by the assignment!). If you do incorporate code from the internet, please cite the source within your code (providing a URL is sufficient).
+Please bring questions that you cannot work out on your own to office hours, work periods or share with your peers on Slack. We will work with you through the issue.
+You will need to install PLINK and run the analyses. Please follow the OS-specific setup guide in SETUP.md. PLINK is a free, open-source whole genome association analysis toolset, designed to perform a range of basic, large-scale analyses in a computationally efficient manner.
Question 1: Data inspection
+Before fitting any models, it is essential to understand the data. Use R or bash code to answer the following questions about the gwa.qc.A1.fam, gwa.qc.A1.bim, and gwa.qc.A1.bed files, available at the following Google Drive link: https://drive.google.com/drive/folders/11meVqGCY5yAyI1fh-fAlMEXQt0VmRGuz?usp=drive_link. Please download all three files from this link and place them in 02_activities/data/.
-
+
- Read the .fam file. How many samples does the dataset contain? +
+
+
+
+-
+
- What is the ‘variable type’ of the response variable (i.e.Continuous or binary)? +
+
+
+
+
+fam <- read.table("C:/Users/minal/OneDrive/Desktop/gen_data/02_activities/data/gwa.qc.A1.fam", header = FALSE)
+head(fam$V6)
+
+[1] -0.6944381 1.8538454 2.0826368 2.7387147 1.3411404 0.4167786unique(fam$V6)
+
+ [1] -0.694438130 1.853845361 2.082636778 2.738714739 1.341140356
+ [6] 0.416778587 2.382971233 1.514299288 0.718686391 2.089041362
+ [11] 1.433708345 1.033029984 1.975368955 3.209670788 2.493291214
+ [16] 3.079400042 1.671769648 2.049343898 1.322094772 1.258426470
+ [21] 2.102163139 1.566221015 2.581470920 1.730205789 2.004985294
+ [26] -0.058513492 1.238375706 2.315751569 0.985770460 1.829232363
+ [31] 1.722300677 2.180546731 2.335088328 -0.693529930 3.260521823
+ [36] 3.310500156 0.506915444 1.509406726 1.218114308 3.507849744
+ [41] 3.346117587 2.506476654 2.439118421 1.807498169 1.895426988
+ [46] 2.377298644 2.529290450 2.744653693 1.100191754 2.167363329
+ [51] 3.342415951 2.793413766 1.156579496 1.035552521 1.479569922
+ [56] 1.838068420 -0.014366565 2.522184384 1.806915341 2.207659351
+ [61] 2.205528359 0.623251317 2.531756939 4.097813272 3.762014272
+ [66] 0.431761345 2.215890581 1.675112896 0.883731594 4.641487155
+ [71] 0.374082541 3.468537269 2.267154935 1.785755057 1.435838996
+ [76] 2.587247596 -2.006701444 0.253630770 0.599780453 0.469739488
+ [81] -0.123851232 0.654743493 2.611123660 1.634531315 4.117327350
+ [86] 0.174426236 3.304140663 2.238053247 1.044512311 0.019296285
+ [91] 0.625495638 2.437928630 2.347273022 3.310032389 1.780590239
+ [96] 1.974598297 2.058363015 1.018402087 1.509081317 2.731016109
+ [101] 1.748453585 0.979299431 1.188656047 -0.524088559 1.042040892
+ [106] 1.323044405 2.356660710 0.870997127 2.837386141 2.726655362
+ [111] 1.460346978 2.840649132 2.132147695 2.151303710 2.299044642
+ [116] 4.138514697 1.642086374 2.659968880 2.955879243 1.920681131
+ [121] 3.351828590 1.292746404 0.994527391 3.427501649 3.049818271
+ [126] 2.726717085 1.931537280 1.995914985 1.078576579 4.007170275
+ [131] 2.401770283 3.192948689 3.219229017 0.842491512 1.088879188
+ [136] 2.057716182 2.173508086 1.371332202 1.531674015 2.013047259
+ [141] 1.068673134 3.115767261 0.510361633 2.791354444 -0.210818675
+ [146] 1.148166585 2.148778987 1.136915662 1.842871611 -0.553895831
+ [151] 1.925520229 0.103274418 0.811968988 2.301112277 3.526507795
+ [156] 3.198984996 3.671754550 1.357815837 3.057257121 2.195575784
+ [161] 2.248137549 1.679840250 1.404687806 0.261494520 1.907313649
+ [166] -0.145578698 1.285916570 0.242850692 1.824798829 1.691437229
+ [171] 0.360192806 1.485242646 2.465706067 0.708295055 2.153754677
+ [176] -1.030929629 3.480148455 1.490442424 -0.692611348 2.346240474
+ [181] 3.095545112 1.129041297 1.801703473 1.061099821 1.384751005
+ [186] 0.780210165 1.892249324 0.102955250 1.492011179 2.100254841
+ [191] 2.697571797 0.393302126 1.321786007 1.262540798 1.217333229
+ [196] -0.100920393 1.652407884 0.985878837 3.026327588 -0.463205499
+ [201] 2.731473528 1.724238998 1.651770950 2.838135449 0.890834180
+ [206] 1.892707703 2.097820198 2.390617452 0.349449074 2.408120599
+ [211] 1.880484703 1.038536319 1.736916337 -0.559819349 2.186028229
+ [216] 1.327516000 2.623907430 1.568061721 3.066206512 1.075616886
+ [221] 0.817854142 2.236680319 2.342407452 2.284577464 3.120133683
+ [226] 1.078001737 2.853302085 1.557323463 2.709542532 2.801843461
+ [231] 2.695516592 2.822305372 2.859986522 1.324729804 0.902415026
+ [236] 3.188001430 2.368579728 1.024975577 0.781750370 1.578860416
+ [241] 3.066653014 1.181859018 -0.764796782 1.701477289 2.335529464
+ [246] 1.667863777 2.378341148 3.448943969 2.385706312 2.861593620
+ [251] 1.530349386 -0.317939800 2.334187496 2.955702655 4.383430878
+ [256] 2.207483571 -0.197977730 3.847997213 2.557736612 2.933921399
+ [261] 1.753645808 1.263703524 0.808443120 2.371870400 1.453968215
+ [266] 2.908903376 -0.108387020 -0.029709200 2.994608257 2.709902967
+ [271] 1.926632472 1.940933863 3.124260707 2.124666543 0.652523738
+ [276] 3.043848605 2.100930938 2.494120078 1.930340127 1.425774722
+ [281] 1.854863666 2.799554323 1.664877805 0.670860251 1.909973109
+ [286] 3.783266537 -0.200325139 2.762722590 1.970838417 2.945919226
+ [291] 2.194765920 2.706943276 2.429795682 2.744446381 1.786103094
+ [296] 1.645024255 2.624597012 3.579593237 1.020394645 0.953786897
+ [301] 2.565905608 3.238821453 1.312282781 1.585104579 3.110143291
+ [306] 2.004163369 3.716853042 2.110491758 2.558766539 1.816662684
+ [311] 0.023732867 1.102436498 2.702764527 1.630442305 2.618130832
+ [316] 2.375206716 2.993039927 1.016023942 1.559019723 3.050515894
+ [321] 2.844940182 1.476171861 3.604799179 2.149667539 1.320989092
+ [326] 1.285455448 0.678643548 -0.058815922 0.678709951 3.449832158
+ [331] 3.776384521 2.443058454 1.942625610 1.312929440 3.940311425
+ [336] 2.152427991 2.524270397 4.235004153 2.298337150 0.537469769
+ [341] 2.525743354 2.338030573 2.406142266 1.532481270 0.614829981
+ [346] 1.710305030 1.346656867 1.127818894 3.218320924 0.268510317
+ [351] 0.615796059 2.926446019 1.077265584 1.883019584 2.214150966
+ [356] 2.944378437 1.026355235 3.227128432 2.933304818 2.780203045
+ [361] 1.185259571 2.868228784 3.885233302 3.068855779 2.299368873
+ [366] 1.494790681 3.177930603 0.567652089 2.455684920 1.680997962
+ [371] 0.545867318 3.289920945 1.077261928 2.675635539 1.774605512
+ [376] 1.755039292 1.249466902 1.605290763 0.199205239 3.394314347
+ [381] 0.860253991 3.121594215 3.120291774 1.645153793 0.678071685
+ [386] 1.228437724 1.995058990 2.520112811 1.508758545 0.280150964
+ [391] 2.035979617 0.899866286 0.685218418 1.182444692 0.667062528
+ [396] 2.831444811 1.251555031 1.564861954 1.878870189 2.399027229
+ [401] 2.365121668 3.382648500 2.928825518 1.923482255 0.936677691
+ [406] 3.870428068 3.207714949 4.152316471 3.840582504 2.329402834
+ [411] 1.866467502 2.082233874 1.835601116 2.143850418 3.364769795
+ [416] 1.962193731 1.543623633 1.365137406 1.996928675 2.088613113
+ [421] 0.300135661 -0.171641102 3.625745609 2.214860105 1.036725289
+ [426] 2.876905335 1.353958746 1.497098941 1.333517324 0.707993809
+ [431] 0.330356951 3.570959072 1.447920048 3.001205977 0.954537829
+ [436] 1.862152214 2.431437692 1.280544452 1.882409554 1.593091663
+ [441] -0.850181603 2.409744036 3.639852276 1.479409811 1.780423628
+ [446] 1.777619257 1.045520739 1.564019714 1.682522049 0.328216622
+ [451] 1.051102947 2.092540093 2.491426290 1.777657735 3.083721958
+ [456] 1.915009438 0.765235446 3.276415290 0.812836900 -0.891856059
+ [461] 1.676607789 1.038019892 1.831607448 1.239052628 0.334411394
+ [466] 1.098696145 -0.809609715 1.610306995 1.774002397 1.425556599
+ [471] 3.211797002 1.246899057 1.121624008 -0.305767860 0.825725927
+ [476] 0.603409395 0.500145249 3.767707516 3.569615463 2.258333484
+ [481] 1.761094865 0.806523421 1.549627622 2.496386387 1.760422764
+ [486] 1.458460061 1.881076124 1.733107628 3.099816093 1.549171085
+ [491] 0.914360939 2.740287227 0.542231567 4.325177404 1.082174121
+ [496] 1.691177053 0.009434676 2.234156025 1.295861028 1.390699864
+ [501] 1.114845453 2.751997389 2.360513128 2.718573392 1.443067662
+ [506] 2.820915464 3.148531901 -0.399967711 3.700911428 1.248309270
+ [511] 1.256171653 0.833352575 0.634215300 1.922819775 1.633589989
+ [516] 1.158896234 2.061809708 2.102451350 3.559292006 1.594974914
+ [521] 1.175562400 1.137204658 1.252437631 2.174733711 2.910410387
+ [526] 1.335235488 -1.940405135 1.954554706 3.488654941 2.351584053
+ [531] 3.272280095 3.608537464 1.533850613 1.410789258 1.210505287
+ [536] 0.464111162 2.873385987 2.099980817 1.111901693 1.856961164
+ [541] 3.687446070 0.874552138 2.708285413 3.326176646 2.344108754
+ [546] 0.216337456 1.304591236 1.226664385 0.789128859 3.534488061
+ [551] 3.163240239 0.363738685 3.403020764 1.728918364 2.086572081
+ [556] 3.117345327 2.212440966 3.124556354 2.153435550 2.327053332
+ [561] 3.033980251 -0.353315330 2.995613394 0.378220571 1.434415101
+ [566] 4.239449413 2.312921588 2.654329218 3.939204628 2.860185085
+ [571] 2.310879104 2.934968329 2.716487793 2.092143364 0.155205006
+ [576] 2.988127887 0.542145610 1.793349841 1.263913256 1.404892024
+ [581] 3.189845170 1.408439034 2.225203319 2.040203201 3.670287975
+ [586] 3.342710937 0.924186990 2.755537973 1.658831882 0.829559652
+ [591] 2.519810344 2.141501649 1.040394757 3.076282128 1.092519160
+ [596] 2.257072966 1.390608751 3.888533313 2.600580294 2.987824626
+ [601] 2.731066999 2.609655913 2.190609470 1.057177105 1.302351747
+ [606] 1.193674731 0.696145256 1.697215805 1.204549534 2.147036528
+ [611] 0.645526035 1.525829823 2.574064916 1.283501267 0.945212156
+ [616] 2.529312040 3.819763174 1.402369340 4.736095389 2.513710792
+ [621] 2.104634376 0.906219092 1.801724797 0.396460781 0.300888572
+ [626] 2.823011663 2.967963251 2.169436341 -0.019844734 1.006005101
+ [631] 2.639513765 3.549134824 0.289995316 1.436516551 0.654968650
+ [636] 1.464995726 0.767662486 3.901729850 1.477136095 2.265545160
+ [641] 1.423009243 1.824100183 2.766608654 0.685656054 2.539682194
+ [646] 1.472029387 2.739249824 2.471321048 2.418761725 1.021413903
+ [651] 2.262268975 3.584420246 1.418564409 2.467999002 2.124674682
+ [656] 4.129801686 5.326807923 1.342083987 0.479397052 0.646175370
+ [661] 1.279172668 2.287844003 0.412431670 1.683302010 0.772601892
+ [666] 2.226882832 1.319977038 3.367460977 0.757070672 1.011853611
+ [671] 1.215070328 2.487414656 1.668081501 1.395490763 4.007654495
+ [676] 3.194841449 2.620177211 2.146974007 1.268136195 -1.141618580
+ [681] 0.977361269 3.169663945 2.188122346 3.244364978 3.403518170
+ [686] 2.815717800 0.891435138 1.620071594 2.739638622 1.968687114
+ [691] 3.305984014 2.344883158 2.742411052 2.330388383 1.605246561
+ [696] 1.590944723 1.206500878 3.380229557 0.880526113 1.046455235
+ [701] 0.815626283 0.130602709 1.313302512 2.021314066 2.867300860
+ [706] 2.187652960 3.204651909 0.448201441 1.874552615 0.948098546
+ [711] -0.527040023 1.125284552 3.375675510 -0.076865569 -0.932342605
+ [716] 2.627053673 1.393690012 1.367860469 1.718833157 2.643367153
+ [721] 1.768516540 0.996956431 1.893223686 1.876918429 1.230027437
+ [726] 1.418898135 -0.454594215 2.521765450 1.091402836 1.867116890
+ [731] 1.304534186 3.158838039 -1.143137286 1.385498803 3.929063957
+ [736] 1.730604547 3.733207605 0.427484949 3.275684628 2.424798131
+ [741] 1.019540402 1.441342288 2.576544924 1.467044894 3.526979777
+ [746] 3.894384870 1.519326725 0.768645679 3.100528943 2.592045550
+ [751] 2.002028075 2.109144194 0.661183419 1.796887046 2.006765986
+ [756] 3.268559368 2.151134828 0.609944681 3.115758321 2.398489660
+ [761] 2.238852338 -0.971623548 1.776008472 1.129792321 2.457107381
+ [766] 2.786908845 1.248169232 1.499728955 1.052838987 0.978502719
+ [771] 2.014111969 1.946946856 3.108678665 2.159920651 2.498698751
+ [776] -0.255466602 0.221040891 2.299717170 2.036050032 1.364718778
+ [781] 1.184439463 0.161205728 1.167810084 1.381980254 2.558047895
+ [786] 2.881420765 3.141311953 2.794967117 1.356979560 1.275361130
+ [791] 0.845106102 2.364356069 2.997935805 3.254961785 0.176618991
+ [796] 0.666572623 0.709690341 1.391824960 1.536242213 1.714921745
+ [801] 2.810557788 1.890963844 2.107235959 2.648267643 1.564742134
+ [806] 2.165389660 -0.066219795 4.433295778 1.048896989 1.158799825
+ [811] 2.689361582 2.496898040 -0.026973862 4.065329353 1.350547607
+ [816] 3.091101547 1.397653290 1.353361005 3.255405335 2.027703001
+ [821] 2.250686109 0.659020547 2.751857605 2.625392005 3.386624195
+ [826] 0.286780784 0.477995668 1.310790699 1.229196084 3.617157687
+ [831] 0.021809537 1.565263471 1.222856944 3.192218330 4.007883711
+ [836] 2.017702602 0.659254470 1.324340639 2.581196171 0.037212011
+ [841] 1.323140969 3.730925014 2.023245838 4.094914885 1.844057220
+ [846] 2.719307341 1.430970565 1.605828031 1.228297108 1.955229673
+ [851] 2.317124761 2.649228235 3.144907152 3.455616650 2.098441297
+ [856] 2.858467362 1.076699440 3.194114706 2.223407742 -0.246710900
+ [861] 2.366493517 1.366128195 3.153869367 1.977654205 1.754403488
+ [866] 2.546865558 2.786321252 2.040586724 2.832697257 3.827690178
+ [871] 2.609646045 -0.110971290 3.800183859 1.073647825 1.275679353
+ [876] 3.589583019 1.609480695 1.729517452 1.469130793 1.346412269
+ [881] 1.824565846 2.044188923 0.261233979 2.724626397 0.671869748
+ [886] 3.318855641 3.124800757 2.521691621 4.412108655 -0.297471539
+ [891] 2.410528649 -0.002139037 0.253064117 3.004727893 3.189787890
+ [896] 0.829168440 1.350453663 2.456340775 1.659727787 3.162788438
+ [901] 1.677288513 0.668660090 1.923936649 2.791168716 0.481596298
+ [906] 0.856779986 2.003556889 1.291206606 2.676046944 2.800008252
+ [911] 0.888041200 1.327940555 2.444398735 3.990883583 2.748809471
+ [916] 2.052232804 1.201164860 1.002967635 0.837150303 2.095742694
+ [921] 3.788494747 1.483942861 1.245734984 3.365169692 2.497523426
+ [926] 2.791880766 0.895266184 0.323826809 1.825848220 3.663463538
+ [931] 3.094437616 3.748025713 1.643780682 2.899934843 3.054147802
+ [936] 1.724873885 2.251751767 3.090082444 2.137253953 2.592584154
+ [941] 0.940245550 2.231293361 2.048125289 2.132462570 2.172839008
+ [946] 2.678538065 3.986868908 0.533472078 1.148210676 1.250273113
+ [951] 2.569290252 1.588810909 2.577932389 1.158621922 -0.814049610
+ [956] 1.531930036 0.734205143 1.842316855 3.544312235 2.278360840
+ [961] 1.365502730 1.989801494 0.861025692 2.032288733 1.653516073
+ [966] 2.535795379 2.202185294 0.734506949 2.384152728 2.849300059
+ [971] 1.199865856 0.459898066 2.950513257 1.589733998 2.961319492
+ [976] 1.203441857 1.475155735 4.426034843 0.208238691 1.106607276
+ [981] 0.282600582 3.323911499 3.703970797 1.540217029 2.566569284
+ [986] 2.887735521 2.096475233 2.387254402 2.491968350 2.869773141
+ [991] 3.712856670 2.430868826 3.247981924 2.240282456 1.747191067
+ [996] 2.247494359 -1.178268247 1.484504866 3.074494522 3.337468970
+[1001] 2.413719736 0.313359945 2.998551435 1.235554445 2.244049876
+[1006] 0.737312622 0.241169436 3.376680990 1.379833571 2.077585762
+[1011] 0.895540986 2.572268663 1.892939379 1.510733002 1.733085108
+[1016] 1.277081759 0.926438000 1.098794014 0.692137440 1.508465834
+[1021] 1.102849671 1.508930209 3.383353735 2.396558826 1.543422930
+[1026] 2.225899308 -0.689723166 1.872653917 2.579212604 2.892757344
+[1031] 1.589352746 2.754575807 1.849474222 3.451767899 1.849382590
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+[3261] 4.169370082 1.933593496 1.323177369 2.722022712 -0.007680486
+[3266] 1.013479083 1.508785615 2.285254944 1.847518597 2.268125101
+[3271] 3.881140866 1.109060727 2.488911141 3.384687899 0.631443582
+[3276] 4.223102861 0.676643337 2.096921059 2.120473623 2.918029620
+[3281] 2.283920775 1.602321262 1.464966603 3.945840583 3.281013316
+[3286] 2.565084342 1.512568798 2.997717451 2.409768930 3.491687682
+[3291] 2.431783641 0.696590841 2.946451872 3.151435999 0.415852715
+[3296] 1.192767155 1.945635455 1.467734586 2.529787867 2.604534022
+[3301] 1.724593230 1.483661780 2.332507167 2.860452724 1.970517223
+[3306] 1.054675826 1.365064584 0.773395218 3.045517334 3.153871441
+[3311] 3.216829182 0.654209936 1.630787227 1.882681484 2.852638306
+[3316] 1.015763050 2.787268936 1.656440604 -0.675042833 0.687805179
+[3321] 2.080559019 0.498997940 3.306271689 -0.071507950 0.359176155
+[3326] 2.037721246 1.447090756 2.764469058 3.345640719 1.727408028
+[3331] 1.236448858 1.653313681 3.063182562 1.499298938 1.980747812
+[3336] 2.411578873 3.659517871 -0.830977214 2.764050094 3.475113212
+[3341] 1.365488433 2.489761413 1.837781044 1.380615397 2.128028106
+[3346] 3.879276583 0.481141381 1.324237853 3.911626467 2.338134784
+[3351] 3.486128988 0.849144160 1.809703231 2.377107833 1.740049680
+[3356] 1.214029056 1.355503093 1.293403032 0.883153369 3.333988860
+[3361] 0.944740407 3.467271978 1.369081706 1.348474532 2.772825389
+[3366] 3.122879029 2.056797292 1.757467353 2.876919149 0.390211877
+[3371] 0.571551745 1.588271201 4.009665112 2.240464603 1.975490718
+[3376] 2.041121886 0.196173120 1.451939079 2.298424159 1.460403175
+[3381] 2.024752888 1.872966459 2.232604879 3.342327227 1.700935375
+[3386] 0.481736076 4.640412599 2.004674547 1.620823479 2.472014616
+[3391] 4.126992556 0.816360022 2.780198486 0.918496346 1.255559180
+[3396] 2.180397223 2.358895938 3.031560907 1.857988637 2.532774965
+[3401] 2.778067353 2.326119886 3.180608701 4.466709331 1.979009411
+[3406] 1.497340087 -0.975099450 2.536752868 -0.348187915 2.222124079
+[3411] 3.417211393 2.150373716 3.808074212 1.496786902 1.711369984
+[3416] 2.845680432 2.241165168 1.633270508 2.077740858 1.866696657
+[3421] 3.459864248 4.096503722 0.188037212 3.067954482 2.254588895
+[3426] 1.420425853 2.553230354 1.048619523 2.331290165 0.785046594
+[3431] 0.596486213 -0.022725521 0.262738092 2.558969059 2.564359812
+[3436] 3.156729449 1.491310038 3.506333050 1.971165713 0.947080658
+[3441] -0.440291778 1.804932085 1.986054236 2.268000912 4.185383656
+[3446] 1.218453420 0.112656775 0.476606322 2.799754130 0.009228082
+[3451] 2.487611945 2.595311785 1.532617508 1.097790769 1.142984055
+[3456] 5.221735496 3.289029240 3.033435586 1.832462119 2.503569396
+[3461] 1.673412820 1.564368843 4.776324984 2.416340941 2.036728889
+[3466] 1.547245464 2.019278809 0.289644076 1.822625406 3.831018619
+[3471] 2.177141407 1.687520370 2.304805493 2.658781437 3.330955593
+[3476] 3.198034337 1.387438600 3.007848526 1.812215363 0.793061272
+[3481] 3.247368127 2.701407498 2.246935825 2.439797668 0.634281275
+[3486] 1.353527598 -0.741178760 0.461639618 1.509373928 3.601381180
+[3491] 4.621975309 3.195883051 1.318686162 2.727818437 1.938426525
+[3496] 2.508459210 0.971699546 0.632783752 3.080337115 0.679204103
+[3501] 2.450202318 1.653952362 3.564987134 2.897724870 2.646203800
+[3506] 1.016397470 1.860290479 2.510282288 0.701086392 2.852751785
+[3511] 2.076265886 1.641772369 0.347270085 1.121202625 0.622022337
+[3516] 0.789408072 2.717839015 0.735399668 4.089023147 0.976471596
+[3521] 0.590307465 2.336571828 2.746559297 1.903467326 2.311139744
+[3526] -0.149468871 0.760466486 1.481608671 2.157945094 1.110211971
+[3531] 2.806406858 2.844971294 3.501151906 1.663528916 1.314942333
+[3536] 2.391867254 3.441558425 2.906856636 1.957028361 0.577295683
+[3541] 0.441161762 3.386046860 1.860776740 1.040048856 3.167719277
+[3546] 2.419769138 1.614802580 1.072872063 3.005719584 -0.036199503
+[3551] 2.920064348 2.135313542 2.196823215 1.083529818 0.457658232
+[3556] 2.017131462 0.858758476 2.124553822 1.333263131 2.667083428
+[3561] 3.399487792 2.362858390 -0.915811505 -0.017617117 0.277181188
+[3566] 1.783092566 1.297620129 1.873898634 1.857023979 0.242569722
+[3571] 1.685767630 0.370105498 2.176759981 2.179786781 0.294584902
+[3576] 2.777195926 -0.166359923 -0.018231967 2.261976521 1.797139692
+[3581] 2.468178262 2.685415464 0.024256671 0.671107731 2.720478658
+[3586] 2.562700859 2.435460423 2.173607388 0.769414519 2.122620752
+[3591] 0.300977491 2.155449520 2.021707744 1.159814992 1.113006337
+[3596] 1.770408860 1.182670964 -0.263204539 2.484586343 2.339724512
+[3601] 1.844429118 2.411221862 2.578795739 1.647792645 0.624681377
+[3606] 2.274649767 2.723029759 2.024111060 1.435318151 1.295358935
+[3611] 2.423110110 3.345564752 3.443860712 1.719062130 1.530304986
+[3616] 1.776098866 -0.587255252 1.778152463 2.571339752 1.523263217
+[3621] 2.657761704 2.615801303 2.028696989 2.288342318 3.676021351
+[3626] 1.919300584 2.492471047 2.679351610 2.002558620 3.610442119
+[3631] 2.199717455 1.130105614 1.816946214 1.316929404 0.308898353
+[3636] 0.814214713 4.228499954 3.972023770 1.693085159 2.409418267
+[3641] 1.705982271 1.265340450 2.506171958 1.055077149 2.087730657
+[3646] 2.102857742 2.818831094 1.859435408 0.963746653 3.292056020
+[3651] 2.376663779 2.572732737 0.919753918 1.564292778 -0.227473603
+[3656] 1.066805822 2.922525381 3.532853168 1.731510641 2.512457178
+[3661] 2.011847889 1.572157036 2.558159638 3.636415381 1.144523413
+[3666] 3.134634866 2.951463951 1.571812645 0.899892068 -2.175237472
+[3671] 3.196363069 0.470053911 2.732527913 3.469041908 -0.048363219
+[3676] 3.227662256 2.584198244 2.018518980 3.900786143 3.088562578
+[3681] 2.538769892 0.372019865 1.572537048 2.293642461 3.999785471
+[3686] 1.835259933 2.741511220 4.528983788 3.085496404 2.977063729
+[3691] 2.406021141 2.299747462 1.898737492 1.098111631 2.001983525
+[3696] 1.423106608 1.708194831 2.164433808 4.180962407 2.240012501
+[3701] 2.482398272 2.069966116 0.759023991 2.892663630 2.522659374
+[3706] 2.658662185 0.359769357 2.211204211 1.698397585 1.722692986
+[3711] 1.795861718 0.157965859 0.927675758 1.468179238 1.740026888
+[3716] 0.043945585 2.663095419 2.034464982 1.422425866 3.453403807
+[3721] 3.447469301 3.370947890 2.826184390 1.944582455 0.475119178
+[3726] 2.002419776 1.795302319 1.355376639 1.295774517 2.194958381
+[3731] 2.629834026 1.573731964 1.734463388 0.961681918 1.737039793
+[3736] 0.197191354 2.237427453 0.722857744 2.909945510 1.720443712
+[3741] 0.489508474 2.162405209 1.927191160 3.368291796 1.383484905
+[3746] 2.912173172 2.136063221 1.217926389 3.346851718 2.050675987
+[3751] 0.959114063 3.156746522 3.949903804 2.044792956 0.961877549
+[3756] 1.602293322 1.375540038 2.239598876 2.721385714 1.605092855
+[3761] 3.455175158 1.099539939 1.041064532 0.974161121 0.108106971
+[3766] 0.393117541 1.740237340 2.033058274 1.346255131 2.287088204
+[3771] 0.099744738 0.049358224 0.796591477 1.871258866 1.519363920
+[3776] 0.492441499 1.701296194 3.783675735 0.482529531 2.646321113
+[3781] 1.964236500 1.557551383 4.260375164 1.255032776 4.922849902
+[3786] 0.627770808 -0.576730253 2.811893672 1.743012471 1.910398239
+[3791] 2.216832352 2.440836499 1.823731016 4.247426202 1.493836378
+[3796] 1.057148229 3.350836797 0.196989926 1.657187352 0.736739371
+[3801] 2.859262961 2.074016781 1.333865750 2.567358146 2.298975231
+[3806] 1.888543508 1.239529342 2.109264457 0.663797668 2.214229707
+[3811] 3.037478491 1.601350845 1.018846476 1.898625681 2.381438384
+[3816] 1.786479595 1.144546838 3.631067377 2.578493102 2.695829550
+[3821] 1.102991026 2.667597608 2.337733467 -1.543865785 0.128829774
+[3826] 2.502826943 1.897086396 -0.179195142 1.478077458 2.249300549
+[3831] 1.355244541 1.287812070 3.020831926 1.562783895 1.685355012
+[3836] 4.196534029 2.824979508 0.839408901 3.999127565 0.681634610
+[3841] 3.015271506 1.776082027 2.194772944 1.812298112 0.768185327
+[3846] 2.354107855 1.659614366 1.364719501 3.478871846 2.250220906
+[3851] 3.421229180 0.652472027 1.117170224 0.285964915 2.942685707
+[3856] 0.972233468 1.345849344 2.723644128 2.044220813 1.337925285
+[3861] 2.009624487 1.932512826 3.861295080 3.151701886 2.446049774
+[3866] -0.300903501 0.901270029 2.255772279 2.727545891 1.103344376
+[3871] 1.288437572 0.833169563 -0.572180354 3.008780039 1.561072850
+[3876] 2.081424078 1.563093392 0.606901409 2.792722208 2.618119004
+[3881] 1.539593273 1.152736816 4.365382376 3.247836542 1.982595434
+[3886] 1.465533779 1.459825685 0.823261961 0.056992403 3.072574767
+[3891] 1.465310949 2.120166823 2.510458561 1.299370790 1.803371062
+[3896] 2.115943520 2.410706436 -0.106773137 1.034127930 0.230118551
+[3901] 0.647062522 1.878672351 2.163581189 3.331088649 1.838497926
+[3906] 1.669851625 1.607699771 3.447460395 1.228072411 1.965055514
+[3911] 2.144572269 0.531540271 2.804693883 4.059926402 1.507595886
+[3916] 2.863279956 3.290160325 0.740429215 0.513128271 0.513392632
+[3921] 2.278906076 1.427822148 1.251685788 1.936062756 2.906787533
+[3926] 2.618211156 0.828728263 1.635341876 4.121141812 1.302693329
+[3931] 1.103946602 1.850404058 1.153250184 1.684511361 2.618351518
+[3936] 1.071955121 1.995777958 1.488187644 0.410240012 1.259283046
+[3941] 1.462409421 2.173325316 0.560423478 1.884714271 0.751006408
+[3946] 4.140458995 1.793244069 1.225137892 2.216311036 0.535053521
+[3951] 0.478460576 3.183607060 2.094318554 1.891558512 2.437425305
+[3956] 1.197585211 0.572653464 0.262836302 1.801774354 0.851853963
+[3961] 2.214844309 0.876795069 2.974828256 1.602691955 3.823117420
+[3966] 3.192662619 2.169309599 1.105424099 0.203320852 2.372429213
+[3971] 1.624611911 -0.127232763 0.707475896 3.200847916 -1.029698830
+[3976] 2.102372173 -0.776985194 2.068228234 1.139866988 1.630073796
+[3981] 0.615501345 2.193273400 -0.708950257 0.445528694 1.483704102
+[3986] 3.005934380 3.179665223 2.081869716 1.344246133 2.532178239
+[3991] 0.848357003 1.247300773 0.869393374 0.825096270 4.298838832
+[3996] 0.972865400 2.328812589 1.640779696 3.301833427 2.763848937 # The variable type is continuous-
+
- Read the .bim file. How many SNPs does the dataset contain? +
+
+
+
+bim <- read.table("C:/Users/minal/OneDrive/Desktop/gen_data/02_activities/data/gwa.qc.A1.bim", header = FALSE)
+nrow(bim)
+
+[1] 101083 # The dataset conatins 101083 SNPs Question 2: Allele Frequency Estimation
+-
+
- Load the genotype matrix for SNPs rs1861, rs3813199, rs3128342, and rs11804831 using additive coding. What are the allele frequencies (AFs) for these four SNPs? +
+
+
+plink2 --bfile ../data/gwa.qc.A1 --export A --out ../data/gwa.qc.A1_additive
+
+PLINK v2.0.0-a.7 64-bit (10 Jan 2026) cog-genomics.org/plink/2.0/
+(C) 2005-2026 Shaun Purcell, Christopher Chang GNU General Public License v3
+Logging to ../data/gwa.qc.A1_additive.log.
+Options in effect:
+ --bfile ../data/gwa.qc.A1
+ --export A
+ --out ../data/gwa.qc.A1_additive
+
+Start time: Mon Mar 16 23:01:30 2026
+16108 MiB RAM detected; reserving 8054 MiB for main workspace.
+Using up to 12 threads (change this with --threads).
+4000 samples (2000 females, 2000 males; 4000 founders) loaded from
+../data/gwa.qc.A1.fam.
+101083 variants loaded from ../data/gwa.qc.A1.bim.
+1 quantitative phenotype loaded (4000 values).
+
+--export A pass 1/1: loading... 0%64% writing... 0%1%2%3%4%5%6%7%8%9%10%11%12%13%14%15%16%17%18%19%20%21%22%23%24%25%26%27%28%29%30%31%32%33%34%35%36%37%38%39%40%41%42%43%44%45%46%47%48%49%50%51%52%53%54%55%56%57%58%59%60%61%62%63%64%65%66%67%68%69%70%71%72%73%74%75%76%77%78%79%80%81%82%83%84%85%86%87%88%89%90%91%92%93%94%95%96%97%98%99% done.
+--export A: ../data/gwa.qc.A1_additive.raw written.
+End time: Mon Mar 16 23:01:32 2026
+
+
+
+library(data.table)
+
+# Load the genotype matrix (additive coding)
+geno <- fread("C:/Users/minal/OneDrive/Desktop/gen_data/02_activities/data/gwa.qc.A1_additive.raw")
+
+# Select the 4 SNPs using exact column names
+geno_sub <- geno[, .(rs1861_C, rs3813199_G, rs3128342_C, rs11804831_T)]
+
+# Calculate allele frequencies (divide by 2 because additive coding is 0,1,2)
+af <- colMeans(geno_sub, na.rm = TRUE) / 2
+af
+
+ rs1861_C rs3813199_G rs3128342_C rs11804831_T
+ 0.9460141 0.9430874 0.6948789 0.8456588 # Allele frequencies for the 4 SNPs:
+# rs1861_C = 0.9460141
+# rs3813199_G = 0.9430874
+# rs3128342_C = 0.6948789
+# rs11804831_T = 0.8456588-
+
- What are the minor allele frequencies (MAFs) for these four SNPs? +
+
+
+
+ # MAF is the smaller of AF and 1-AF
+maf <- pmin(af, 1 - af)
+maf
+
+ rs1861_C rs3813199_G rs3128342_C rs11804831_T
+ 0.05398587 0.05691262 0.30512109 0.15434124 # Minor Allele Frequencies for the 4 SNPs:
+# rs1861_C = 0.05398587
+# rs3813199_G = 0.05691262
+# rs3128342_C = 0.30512109
+# rs11804831_T = 0.15434124Question 3: Hardy–Weinberg Equilibrium (HWE) Test
+-
+
- Conduct the Hardy–Weinberg Equilibrium (HWE) test for all SNPs in the .bim file. Then, load the file containing the HWE p-value results and display the first few rows of the resulting data frame. +
+
+
+plink2 --bfile ../data/gwa.qc.A1 --hardy --out ../data/gwa.qc.A1_hwe
+
+PLINK v2.0.0-a.7 64-bit (10 Jan 2026) cog-genomics.org/plink/2.0/
+(C) 2005-2026 Shaun Purcell, Christopher Chang GNU General Public License v3
+Logging to ../data/gwa.qc.A1_hwe.log.
+Options in effect:
+ --bfile ../data/gwa.qc.A1
+ --hardy
+ --out ../data/gwa.qc.A1_hwe
+
+Start time: Mon Mar 16 23:01:38 2026
+16108 MiB RAM detected; reserving 8054 MiB for main workspace.
+Using up to 12 threads (change this with --threads).
+4000 samples (2000 females, 2000 males; 4000 founders) loaded from
+../data/gwa.qc.A1.fam.
+101083 variants loaded from ../data/gwa.qc.A1.bim.
+1 quantitative phenotype loaded (4000 values).
+Calculating allele frequencies... 0%64%done.
+--hardy: 0%1%2%3%4%5%6%7%8%9%10%11%12%13%14%15%16%17%18%19%20%21%22%23%24%25%26%27%28%29%30%31%32%33%34%35%36%37%38%39%40%41%42%43%44%45%46%47%48%49%50%51%52%53%54%55%56%57%58%59%60%61%62%63%64%65%66%67%68%69%70%71%72%73%74%75%76%77%78%79%80%81%82%83%84%85%86%87%88%89%90%91%92%93%94%95%96%97%98%99%
+--hardy: Autosomal Hardy-Weinberg report (founders only) written to
+../data/gwa.qc.A1_hwe.hardy .
+End time: Mon Mar 16 23:01:39 2026
+
+
+ # Load the HWE results
+library(data.table)
+hwe <- fread("C:/Users/minal/OneDrive/Desktop/gen_data/02_activities/data/gwa.qc.A1_hwe.hardy")
+head(hwe)
+
+ #CHROM ID A1 AX HOM_A1_CT HET_A1_CT TWO_AX_CT O(HET_A1)
+ <int> <char> <char> <char> <int> <int> <int> <num>
+1: 1 rs3737728 G A 1713 1841 428 0.462330
+2: 1 rs1320565 C T 3368 589 19 0.148139
+3: 1 rs3813199 G A 3531 428 12 0.107781
+4: 1 rs11804831 T C 2820 1061 81 0.267794
+5: 1 rs3766178 T C 2391 1378 214 0.345970
+6: 1 rs3128342 C A 1927 1655 382 0.417508
+ E(HET_A1) P
+ <num> <num>
+1: 0.447932 0.0437892
+2: 0.145262 0.2734290
+3: 0.107347 1.0000000
+4: 0.261040 0.1133540
+5: 0.350629 0.4158770
+6: 0.424044 0.3302730-
+
- What are the HWE p-values for SNPs rs1861, rs3813199, rs3128342, and rs11804831? +
+
+
+
+library(data.table)
+
+# Load HWE results
+hwe <- fread("C:/Users/minal/OneDrive/Desktop/gen_data/02_activities/data/gwa.qc.A1_hwe.hardy")
+
+# Filter for our 4 SNPs and show their p-values
+snps <- c("rs1861", "rs3813199", "rs3128342", "rs11804831")
+hwe[ID %in% snps, .(ID, P)]
+
+ ID P
+ <char> <num>
+1: rs3813199 1.000000
+2: rs11804831 0.113354
+3: rs3128342 0.330273
+4: rs1861 0.274719 # HWE p-values for the 4 SNPs:
+# rs1861 = 0.274719
+# rs3813199 = 1.000000
+# rs3128342 = 0.330273
+# rs11804831 = 0.113354Question 4: Genetic Association Test
+-
+
- Conduct a linear regression to test the association between SNP rs1861 and the phenotype. What is the p-value? +
+
+
+
+library(data.table)
+
+# Load genotype and phenotype data
+geno <- fread("C:/Users/minal/OneDrive/Desktop/gen_data/02_activities/data/gwa.qc.A1_additive.raw")
+fam <- read.table("C:/Users/minal/OneDrive/Desktop/gen_data/02_activities/data/gwa.qc.A1.fam", header = FALSE)
+
+# Extract phenotype (column 6) and rs1861 genotype
+phenotype <- fam$V6
+rs1861 <- geno$rs1861_C
+
+# Fit linear regression
+model_add <- lm(phenotype ~ rs1861)
+summary(model_add)
+
+
+Call:
+lm(formula = phenotype ~ rs1861)
+
+Residuals:
+ Min 1Q Median 3Q Max
+-3.5439 -0.6850 0.0021 0.6993 3.3268
+
+Coefficients:
+ Estimate Std. Error t value Pr(>|t|)
+(Intercept) 0.05238 0.09486 0.552 0.581
+rs1861 0.97382 0.04943 19.703 <2e-16 ***
+---
+Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
+
+Residual standard error: 1.003 on 3962 degrees of freedom
+ (36 observations deleted due to missingness)
+Multiple R-squared: 0.08924, Adjusted R-squared: 0.08901
+F-statistic: 388.2 on 1 and 3962 DF, p-value: < 2.2e-16 # p-value for rs1861 = <2e-16-
+
- How would you interpret the beta coefficient from this regression? +
+
+
+# The beta coefficient for rs1861 is 0.97382-
+
- Plot the scatterplot of phenotype versus the genotype of SNP rs1861. Add the regression line to the plot. +
+
+
+library(data.table)
+
+# Reload data
+geno <- fread("C:/Users/minal/OneDrive/Desktop/gen_data/02_activities/data/gwa.qc.A1_additive.raw")
+fam <- read.table("C:/Users/minal/OneDrive/Desktop/gen_data/02_activities/data/gwa.qc.A1.fam", header = FALSE)
+phenotype <- fam$V6
+rs1861 <- geno$rs1861_C
+model_add <- lm(phenotype ~ rs1861)
+
+# Plot scatterplot with regression line
+plot(rs1861, phenotype,
+ xlab = "Genotype of rs1861 (additive coding)",
+ ylab = "Phenotype",
+ main = "Phenotype vs rs1861 Genotype")
+abline(model_add, col = "red")
+
+
+
+
+
+
-
+
- Convert the genotype coding for rs1861 to recessive coding. +
+
+
+# Recessive coding: only 2 copies of allele = 1, everything else = 0
+rs1861_rec <- ifelse(rs1861 == 2, 1, 0)
+table(rs1861_rec)
+
+rs1861_rec
+ 0 1
+ 413 3551 -
+
- Conduct a linear regression to test the association between the recessive-coded rs1861 and the phenotype. What is the p-value? +
+
+
+
+## Linear regression with recessive coding
+model_rec <- lm(phenotype ~ rs1861_rec)
+summary(model_rec)
+
+
+Call:
+lm(formula = phenotype ~ rs1861_rec)
+
+Residuals:
+ Min 1Q Median 3Q Max
+-3.5437 -0.6892 0.0015 0.7016 3.3270
+
+Coefficients:
+ Estimate Std. Error t value Pr(>|t|)
+(Intercept) 0.99231 0.04945 20.07 <2e-16 ***
+rs1861_rec 1.00754 0.05224 19.29 <2e-16 ***
+---
+Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
+
+Residual standard error: 1.005 on 3962 degrees of freedom
+ (36 observations deleted due to missingness)
+Multiple R-squared: 0.08582, Adjusted R-squared: 0.08559
+F-statistic: 372 on 1 and 3962 DF, p-value: < 2.2e-16# Answer: p-value shown in rs1861_rec row under Pr(>|t|)
+ # p-value for recessive model = <2e-16 -
+
- Plot the scatterplot of phenotype versus the recessive-coded genotype of rs1861. Add the regression line to the plot. +
+
+
+# Plot scatterplot with recessive coding and regression line
+plot(rs1861_rec, phenotype,
+ xlab = "Genotype of rs1861 (recessive coding)",
+ ylab = "Phenotype",
+ main = "Phenotype vs rs1861 Recessive Genotype")
+abline(model_rec, col = "blue")
+
+
+
+
+
+
-
+
- Which model fits better? Justify your answer. +
+
+
+
+
+summary(model_add)$r.squared
+
+[1] 0.08923678summary(model_rec)$r.squared
+
+[1] 0.08582295# The additive model fits better.
+# Additive R-squared = 0.08924
+# Recessive R-squared = 0.08582
+# Higher R-squared means better fitCriteria
+| Criteria | +Complete | +Incomplete | +
|---|---|---|
| Data Inspection | +Correct sample/SNP counts and variable type identified. | +Missing or incorrect counts or variable type. | +
| Allele Frequency Estimation | +Correct allele and minor allele frequencies computed. | +Frequencies missing or wrong. | +
| Hardy–Weinberg Equilibrium Test | +Correct PLINK command and p-value extraction in R. | +PLINK command or extraction incorrect/missing. | +
| Genetic Association Test | +Correct regressions, plots, coding, and interpretation. | +Regression, plots, or interpretation missing/incomplete. | +
Submission Information
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+Note:
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++
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+
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