0

次のようにdata.frameを初期化しています:

combdat <- data.frame(matrix(nrow=50), check.names=FALSE)

ループで、追加の列に入力したいと思います。これは次のように発生します。

combdat[,mkr] <- mkrgeno

ここで、mkr は特定の文字で、mkrgeno は同じサイズのベクトルです。ただし、同じ mkr の特定の値があります。私はそれらを保持する必要があります。今のところ、それらは上書きされます。check.names=FALSE を設定しましたが

誰か私にアドバイスがありますか。ありがとう

リッチ


わかりましたありがとうございました。質問をより詳細に尋ねてみます。

マーカーに関する特定の情報を含むリストmarkerinfoがあります:

> markerinfo
marker chr      pos        lod   pheno
1   c1m22   1 213.2983  9.1495699 RAPGEF2
2   c4m14   4 131.0000  8.5438345 CACNA1E
3    c1m8   1  63.0000  9.0002544  CACNB3
4   c3m22   3 228.0000  7.1775450   RASA2
5   c1m31   1 305.0000  6.4748053  CACNG6
6   c3m22   3 230.3826  6.5638616   PRKCG
7   c4m11   4 103.0000  6.3592497 CACNA1B
8   c4m26   4 256.0000  8.5450810 CACNA1F
9   c4m14   4 139.0000  5.3257424  CACNG3
10   c2m1   2   0.0000  7.8765658 CACNA1G
11   c2m2   2  13.0000 10.0825268   PRKCA
12  c2m16   2 159.0000  9.2080541 CACNA1D
13  c4m20   4 191.7279  7.2340899    SOS2
14   c2m3   2  16.0000  5.9131295  CACNG5
15  c3m22   3 230.3826  6.7322605 CACNA1A
16   c3m8   3  75.4555  1.1470464 RASGRF1
17   c3m8   3  70.0000  1.9991043    MRAS
18  c1m30   1 288.2238  1.8443845   RRAS2
19  c4m16   4 157.0000  2.1455832 RASGRP3
20  c3m30   3 320.0000  1.9721441    HRAS
21  c1m10   1  90.0000  1.8833757 RASGRF2
22  c3m16   3 161.6888  2.1163401    NRAS
23  c3m20   3 201.9852  2.6265899 RASGRP1
24  c3m30   3 319.4977  1.3677933    KRAS
25  c3m22   3 230.3826  0.7012214 RASGRP2

別の data.frame は遺伝子型です。

 c3m1 c3m2 c3m3 c3m4 c3m5 c3m6 c3m7 c3m8 c3m9 c3m10 c3m11 c3m12 c3m13 c3m14 c3m15 c3m16 c3m17 c3m18 c3m19 c3m20 c3m21 c3m22 c3m23 c3m24 c3m25 c3m26 c3m27 c3m28
V1     2    2    2    2    2    2    2    2    2     2     2     2     2     2     2     2     2     2     2     2     2     2     1     1     1     2     2     2
V2     1    1    1    1    1    1    2    2    2     2     2     2     2     2     2     2     2     2     2     2     2     2     2     2     2     1     1     1
V3     2    2    2    2    2    2    2    2    2     2     2     2     2     2     2     2     2     2     2     2     2     2     2     2     2     2     2     2
V4     1    1    1    1    2    2    1    1    1     1     1     1     2     2     2     1     1     1     1     1     1     1     1     1     1     1     1     1
V5     1    1    1    1    1    1    1    1    1     1     1     1     2     2     2     2     2     2     2     1     1     1     1     1     1     1     1     1
V6     1    1    1    1    1    1    2    2    2     2     2     2     2     2     2     2     1     1     1     1     1     1     1     1     1     1     1     1
V7     2    1    1    1    1    1    1    1    1     1     1     1     2     2     2     2     2     2     2     2     1     1     1     1     2     2     2     2
V8     2    2    2    2    2    2    2    1    1     2     2     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1
V9     2    2    2    2    2    1    1    1    1     1     2     2     2     2     2     2     2     2     2     1     1     1     1     1     2     2     2     2
V10    2    1    1    1    1    2    2    2    2     2     2     2     2     2     2     2     2     1     1     1     2     2     2     2     2     2     2     2
V11    1    2    2    2    2    2    2    2    2     2     2     1     1     1     1     1     1     1     1     1     1     1     2     2     2     2     2     2
V12    1    1    1    1    1    1    1    1    1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1
V13    2    2    2    2    2    2    2    2    2     2     2     2     2     2     2     2     2     2     1     1     1     1     1     1     1     1     1     1
V14    1    2    2    2    2    2    2    2    2     2     2     2     2     2     2     1     1     1     1     1     1     1     1     2     2     2     2     2
V15    1    1    1    1    1    1    1    1    1     1     1     1     1     1     1     1     1     1     2     2     2     2     2     2     2     1     1     1
V16    1    1    1    1    1    1    1    1    1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1
V17    1    1    1    1    1    1    1    2    2     2     2     2     2     2     2     2     2     2     2     2     2     2     2     2     2     2     2     1
V18    1    1    1    1    1    1    1    1    1     1     2     2     2     2     2     1     1     1     1     1     1     1     1     2     2     2     2     2
V19    2    2    2    2    2    2    2    2    2     2     2     2     1     1     2     2     2     2     2     2     2     2     2     2     2     2     2     2
V20    1    1    1    1    2    2    2    2    1     1     1     1     1     1     1     1     1     1     1     1     2     2     2     2     2     1     1     1
V21    2    2    2    2    2    2    2    1    1     1     1     1     1     1     2     2     2     2     1     1     1     1     1     1     1     1     1     1
V22    1    1    2    2    2    2    2    1    1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1
V23    2    2    2    2    1    1    1    1    1     2     2     2     2     2     2     2     2     1     1     1     1     1     1     1     1     1     2     2
V24    2    2    2    2    2    2    2    2    2     2     2     1     1     1     1     1     1     1     1     2     2     2     2     2     2     2     2     2
V25    1    1    1    1    1    1    1    1    1     1     1     2     2     2     2     2     2     2     2     2     2     2     2     2     2     2     2     2
V26    1    1    1    1    1    1    1    1    1     1     1     2     2     2     2     1     1     1     1     1     1     1     1     1     1     1     1     1
V27    2    2    2    2    2    2    2    2    2     2     2     2     2     2     2     2     2     2     2     2     2     2     2     2     2     1     1     1
V28    2    2    2    2    2    2    2    2    2     2     1     1     1     1     1     1     1     1     1     1     2     1     1     1     2     2     2     2
V29    2    2    2    2    1    1    1    1    1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1
V30    2    2    2    1    1    1    2    2    2     2     2     2     2     2     2     2     2     2     2     2     2     2     2     2     1     1     1     1
V31    2    2    2    2    2    1    1    1    1     1     1     2     2     2     2     2     2     2     2     2     2     2     2     2     2     2     2     2
V32    1    1    1    1    1    1    1    1    2     1     1     2     2     2     2     2     1     1     1     1     1     1     1     1     1     1     1     1
V33    2    1    1    1    1    1    1    2    2     1     1     1     1     1     1     1     1     2     2     2     2     2     2     2     2     1     1     1
V34    1    2    2    1    1    1    1    1    1     1     1     1     1     2     2     2     1     1     1     1     1     1     1     1     1     1     1     2
V35    1    1    1    1    1    1    2    2    2     2     1     1     2     1     1     1     1     1     1     1     1     2     2     2     1     1     1     1
V36    1    1    1    1    2    2    1    2    1     1     1     1     1     1     1     2     2     2     2     2     2     2     2     2     2     1     1     1
V37    2    2    2    1    1    2    1    1    1     1     1     1     1     1     1     1     2     2     2     2     2     2     2     2     2     2     1     1
V38    2    2    2    2    2    2    2    2    1     1     2     2     2     2     2     2     2     2     2     1     1     1     1     1     1     1     1     1
V39    2    2    2    2    2    2    2    2    2     2     2     1     1     1     1     1     1     1     2     2     2     2     2     2     2     2     2     1
V40    2    2    2    2    2    2    2    2    2     1     1     1     1     1     1     2     2     2     2     2     2     2     2     2     2     1     1     1
V41    2    2    2    2    2    2    2    2    2     2     2     2     1     1     1     1     1     1     1     1     1     1     1     1     1     2     2     2
V42    2    2    2    1    1    1    1    1    1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     2     2     2     2     2
V43    2    2    2    2    2    2    2    2    2     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1
V44    2    2    2    2    2    1    1    1    1     1     1     1     1     1     2     2     2     2     2     1     1     1     1     1     1     1     1     1
V45    2    1    1    1    2    2    2    2    2     2     2     2     2     2     1     1     1     2     2     2     2     2     2     2     2     2     2     1
V46    2    2    2    2    2    2    2    2    2     2     2     1     2     2     2     2     2     2     2     2     2     2     2     2     2     2     2     1
V47    1    2    1    1    1    1    1    1    1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1     1
V48    1    1    1    1    1    1    1    2    2     2     2     2     2     2     1     1     1     1     1     1     1     1     1     1     1     2     2     2
V49    2    2    2    2    2    1    1    1    1     1     1     1     2     2     2     2     2     2     2     2     2     2     2     2     2     1     1     1
V50    1    1    1    1    1    1    1    1    2     2     2     2     2     2     2     2     2     2     2     2     1     2     2     2     2     2     2     2
    c3m29 c3m30 c3m31 c3m32
V1      2     2     2     2
V2      1     1     1     1
V3      2     2     2     1
V4      1     1     1     1
V5      1     1     2     2
V6      1     1     1     2
V7      2     2     2     2
V8      1     1     1     1
V9      2     2     2     2
V10     2     2     2     2
V11     2     2     2     2
V12     1     2     2     2
V13     2     2     2     2
V14     2     2     2     2
V15     1     1     1     1
V16     1     1     1     1
V17     1     1     1     1
V18     2     2     2     2
V19     2     1     1     1
V20     1     1     1     1
V21     2     2     2     2
V22     1     1     1     1
V23     2     2     2     2
V24     2     2     2     2
V25     2     2     2     2
V26     1     1     1     1
V27     1     1     1     1
V28     2     2     1     1
V29     1     1     1     1
V30     1     1     2     2
V31     2     2     2     2
V32     1     1     2     2
V33     1     1     2     2
V34     1     1     1     1
V35     1     1     1     1
V36     1     1     1     1
V37     1     1     1     1
V38     1     2     2     2
V39     1     1     1     1
V40     1     1     1     1
V41     2     2     2     2
V42     2     1     1     1
V43     1     1     1     1
V44     1     1     1     1
V45     2     2     2     2
V46     1     1     2     2
V47     2     2     2     2
V48     2     2     2     2
V49     2     2     2     1
V50     2     2     2     2

および名前を持つ別のもの:表現型

> phenotype
        RAPGEF2      CACNA1E       CACNB3        RASA2      CACNG6        PRKCG     CACNA1B      CACNA1F     CACNG3     CACNA1G        PRKCA     CACNA1D         SOS2
1  -0.247595001  0.053503367 -0.236269632 -0.198393959  0.30226149  0.034393665  0.13201747 -0.055123952 -0.4775578 -0.16406024 -0.601510801 -0.74241018  0.003437553
2   0.076554542 -0.296400594 -0.204362787 -0.083725326 -0.51309205  0.008746035  0.49724817 -0.141674911 -1.5563250 -0.28751925 -0.152694444 -0.83115868 -0.520475369
3  -0.327202333  0.001312523  0.013790261  0.074576720  0.23008238 -0.050573176 -1.04673228 -0.330784609  0.5481467 -0.84388147 -0.743829290 -0.55692338 -0.542878574
4  -0.007847655 -0.138671725 -0.149620332 -0.819362934 -0.11386931 -0.041000430 -0.16221890  0.157342905 -0.4304658 -0.04136305  0.140892816 -1.43966569 -0.502489598
5  -0.288891373 -0.453451438 -0.203315372 -0.432877782 -0.32638230 -0.079509208 -1.07767644 -0.239044759 -2.6685509 -0.34506117 -0.601583079  0.06418028 -0.447845591
6  -0.819438873 -0.186128793  0.010946957 -0.541158848 -0.05467246 -0.091256991 -0.14121849  0.120465369 -0.7412188 -1.45824366 -0.742750372 -0.65559390 -0.024424118
7   0.056713692  0.099570795 -0.140081980 -0.249675499 -0.54844575 -0.142449430 -0.17804642 -0.193517791 -2.8180865 -0.37995253  0.521983735 -0.13506427 -0.496292115
8  -0.415822882 -0.234501809  0.045971377 -0.501303875  0.10064320 -0.123989099 -0.18390119 -0.272184476 -2.3932719 -0.17459784  0.041698873 -0.58292029 -0.030478251
9   0.216626060 -0.055785714  0.102465484 -0.296597579 -0.63187464 -0.043925124 -0.73290772  0.086194905  1.2253629 -0.26787759 -0.186213820  0.21540883 -0.409209752
10 -0.172889555 -0.359033332  0.059976873 -0.122362142 -0.57597543 -0.039439871 -0.37358470  0.046816519 -0.2194930  0.44557540 -0.008582745  0.04681091 -0.151858633
11 -0.799370277 -0.390225142  0.092905430 -0.539360659 -0.46040156 -0.080978159 -1.35509517 -0.183647290 -2.0786691 -0.53105091 -0.537946690  0.15503760 -0.250068125
12  0.165948180  0.084380299  0.072471995 -0.257986088 -0.31888913 -0.113180297  0.09108201  0.081261902  0.4084345 -0.32413522 -0.410390899 -0.52705454 -1.311315609
13 -0.151699952 -0.345160750  0.024127039 -0.199062545 -0.35710011 -0.101713530 -1.52298182 -0.131191677 -1.4151031  0.13075608 -0.112750159 -0.09761248 -0.448443675
14 -0.064050378  0.058414370 -0.049131860 -0.438722188  0.46253165 -0.085058699 -0.48949571  0.312177213 -0.4383044 -0.13332403 -0.952470633 -0.10016991 -0.738450721
15 -0.252830650 -0.021360957 -0.054884002 -0.132821999  0.24029851  0.032595174 -0.28201065 -0.134742072 -1.2429264 -0.20965743 -0.266581307 -0.65461311 -0.026886166
16 -0.302939138 -0.237659778 -0.173316135 -0.433111666 -0.49102642 -0.169569976 -0.14919939 -0.024873565 -1.7566415 -0.11697234  0.250150721 -1.00971694 -0.314707578
17 -0.027397752 -0.220213983 -0.020104605 -0.260175395  0.36690904 -0.015439485 -1.64675598 -0.341331701  1.1341947  0.19718194  0.040220128  0.21718090 -1.082049767
18 -0.084826002  0.075130631  0.085664240 -0.516533930  0.05420691 -0.111368755 -0.54866864 -0.246852143 -0.1673859  0.54867571 -0.491091471 -0.64419595 -0.417058365
19  0.076420274 -0.198417039 -0.209613388  0.275960810  0.20461276 -0.016330089 -2.44087703  0.016533904 -0.9745876 -0.32916054 -0.886846124 -0.03904152  0.423648190
20 -0.341758547  0.027599210 -0.238241196 -0.122481806 -0.53322283 -0.041335840 -0.09748360  0.109385536  0.7184183 -0.42004508 -0.297868841  0.02331034 -0.176874436
21 -0.729225854 -0.366947864 -0.151319971 -0.766507590 -0.93109904 -0.120188998 -0.82125694 -0.069669901 -1.8344670  0.19827344 -0.121866097 -0.64905504 -0.309849450
22 -0.375156253  0.023848706 -0.084361744 -0.444354626 -0.66319529 -0.062962171 -1.20604478  0.168518715 -1.5501544  0.47227482 -0.209564431 -0.47454099 -0.057838134
23 -0.254021124  0.169933007 -0.110124957 -0.321290108 -0.25074586 -0.002748504 -1.67191531 -0.213003128 -0.6702960  0.06601284  0.419818706 -0.24339589 -0.900376250
24 -0.115377716 -0.069793465 -0.082424787 -0.207820569 -0.62402649 -0.057047717 -0.28566344 -0.343388680 -0.9703774 -0.05548410 -0.226484770 -0.73331271 -0.699834400
25 -0.049844861 -0.005899354 -0.014298567 -0.058495200 -1.32936915 -0.080242402  0.21312235 -0.469668455  0.3296792 -0.40816963  0.169496411 -0.06951457  0.678321997
26 -0.722770403  0.103085237 -0.107956995 -0.453234395 -0.79713145 -0.010894595 -0.02192121 -0.183129347 -0.4671715 -0.24454782  0.140808502 -0.16672267 -0.297979736
27  0.177156038 -0.352948087  0.126134036  0.009680394 -0.53116648  0.083284652 -2.56881648  0.040743856 -1.3867899 -0.30346968 -0.943847562 -1.27918873  0.074066589
28  0.031014348 -0.096368514 -0.191044463 -0.150761960 -0.34080995 -0.082406406  0.81100676  0.081447585 -0.4011565  0.46952945 -0.126056643 -0.39482906  0.487768932
29 -0.175479066 -0.406803418  0.060241581 -0.630242987 -0.04177606 -0.099102694 -1.77644280 -0.220901308 -1.0807459  0.25538082 -0.127072554 -0.28244767  0.077844220
30  0.067184617  0.135066792  0.061038582 -0.005188869 -0.28276832  0.002666423  1.11312551 -0.261943690  0.9199570 -0.65210434 -0.308977705 -0.74132895 -0.089614346
31  0.077892704 -0.235195609 -0.067162872 -0.207711784  0.02699528 -0.005653163 -1.61297664 -0.338387970 -0.2485027 -0.10887056  0.343968213  0.09719695 -0.452561385
32  0.142403286 -0.026388719 -0.065678040 -0.362428853 -0.19390021 -0.130526170 -1.21100755 -0.350326700 -1.2818116 -0.72894545 -0.654865598 -0.75242740 -0.379810157
33 -0.001080476 -0.290697156  0.011388500  0.139363744  0.27888665 -0.100895638  0.39220173 -0.346996776 -0.7863979 -0.52910994 -0.558958463  0.31595835 -0.710613795
34  0.224116945 -0.185072933  0.086483429 -0.348059767 -0.25522243 -0.126570401 -2.48462353 -0.402525824 -1.8282210 -0.71284302  0.003787240  0.33055507 -0.485361798
35 -0.254131666 -0.181962657  0.134810146 -0.144177046 -0.42946649  0.006665253 -1.31883436 -0.233832760 -0.8644715  0.02096703 -0.386481233 -0.72159749  0.091061479
36  0.078173409  0.069614224 -0.027333201 -0.338889055 -0.08953657 -0.048366331 -1.05945722 -0.005647055 -0.5515289 -0.99689326 -0.499325729  0.25250542 -0.630618039
37 -0.383263187  0.050446587  0.042835279 -0.187032348  0.10888308 -0.044352563 -0.14934550 -0.123438315  1.1205628 -0.59339281 -0.824166347 -0.50010055  0.362946526
38  0.155765532 -0.095113895 -0.028232352 -0.341382444 -0.28993519 -0.063198747 -0.74942280 -0.262175258  0.3796110 -0.64149439  0.038476888 -0.15428205 -0.070443511
39 -0.352871059 -0.154463839 -0.040044333 -0.215973910 -0.70080752 -0.030485881 -1.59167190 -0.018228487 -2.7482696 -0.81423002 -0.990327664  0.02797165 -0.961506882
40 -0.027887194 -0.500539888  0.101565681  0.026081728 -0.37318368  0.030271868 -1.56720146  0.114323657 -0.9604690 -0.83847006 -0.616284751 -0.22106937 -0.817229295
41 -0.116324675  0.141997059  0.011066622 -0.637030608 -0.06816308 -0.139064501 -0.21884155 -0.133162057  0.3200013  0.40302112  0.196245908 -0.44456908 -0.060186732
42 -0.011563437 -0.097908807  0.010180963 -0.356297511  0.25810039 -0.053495480 -1.23448236 -0.075325095 -2.1873328  0.25853977  0.024608949 -0.24320912 -0.865864499
43 -0.473180079 -0.175778274 -0.153653640 -0.492266908 -0.72545341 -0.089492114 -1.52409341 -0.113111386 -1.8098738 -0.23081989 -0.143859625 -0.33247673 -0.930370376
44 -0.301982544 -0.276093471 -0.172829397 -0.165867999 -0.09716023 -0.074000281 -1.29494575 -0.284384336 -0.3640354 -0.98837691 -0.583165895 -0.22244048 -0.389223572
45 -0.035837132  0.089487455  0.043398895 -0.261321417 -0.14740720  0.086069259  0.50424191 -0.435393685 -0.6916679  0.08837666 -0.764933697 -0.15527777 -0.180500006
46 -0.283577759  0.033526022 -0.053893390 -0.276804767 -0.38757922  0.049021497  1.11676571 -0.165603000 -1.4368988  0.08869823  0.165745244 -0.43123024 -0.409150399
47 -0.579455295  0.045838903 -0.174331523 -0.503703045 -0.51013334 -0.018538629  0.24724654 -0.382273065 -0.2014670 -0.67669484 -0.653328789  0.46375442 -0.481676959
48 -0.308546234 -0.047014302 -0.005449878 -0.350135893 -0.16086990 -0.090971861  0.11738860 -0.360362823 -0.3117357 -0.92804263 -0.430577252  0.38097823 -0.426938081
49 -0.165320629 -0.436561117 -0.022108887 -0.412614936  0.20412609  0.003279052 -0.77152209  0.211526672 -0.5851201 -0.18290809 -0.284230585  0.30449400 -0.666071768
50 -0.142082710  0.195017303 -0.121702032  0.077439475 -0.47426071  0.055089372 -0.82942407 -0.249394753  0.5139078 -0.52850805 -0.707774591  0.02486043 -0.529796003
        CACNG5     CACNA1A     RASGRF1       MRAS       RRAS2      RASGRP3        HRAS      RASGRF2       NRAS     RASGRP1         KRAS    RASGRP2
1  -1.08126573 -0.10466468  0.16163511  5.2884330   1.4807031  1.367194844  -5.3632946  8.854311810  -1.590394  5.46299955   3.39043935 -0.6188210
2  -0.20103987  0.02859079 -4.04956365  6.8065804   9.7156082  2.358011759   7.5529682 -1.371397362   5.512496  2.38105873  -4.31024938 -2.9758226
3  -0.56279304 -0.49473575  0.93100155 13.3018509   4.7819748 -0.830227776   7.1269586  1.639458379   5.579675  1.92566166 -10.04349925 -3.9823054
4  -0.17721434 -0.13495743 -4.18967059  7.7963292   2.4795673  0.849823268  16.4843104  1.625120794   2.538493 -1.96693411  -1.06650587  2.9583095
5  -0.21284845 -0.41776136 11.57622331  7.8696230  25.3334550  0.525216862  21.7506102  1.804542827  27.144583  1.33103943  14.91107071  4.3580818
6   0.26966929 -0.57921249 -3.81118227 -1.7711352   2.6537342  2.381451473   0.3413279  0.002745248  11.787951 -2.72785260   5.81449916  1.1492321
7  -0.05721931 -0.61373510  3.20661730 17.0161591   8.3848898  9.128073635  10.0460744  7.427485748   6.423633  8.58609614   5.14330065  0.2455554
8  -0.23483474 -0.30007284  7.44882239 -4.1520715   2.5809601  0.007694412  14.4026853  6.009882772   1.973626  5.85650616  -4.99508071  1.4778224
9  -0.30401185 -0.23601064  0.61950230  2.1421284  15.4745282 -0.515190084   5.7490335 -3.364087292  12.305191  0.68371891   0.70766236  0.7915359
10  0.03069795  0.17789637  5.48077430  0.1797954   1.5320631 -0.612153126 -11.1569228  2.314820314   5.364269 -1.03632032   7.25132489  3.9454336
11 -0.67484374 -0.24910596  2.32388243 17.9765927   0.9794240 10.700691074   7.1050062  4.714036496  15.891228 -4.31287607   7.62253612  5.1733717
12 -0.23985708 -0.38664533  5.49113542  6.9358357  20.5868853 -0.490459011  19.0955840 -0.187311045 -11.228341 -2.01774050   2.46021292  2.9611938
13 -0.17565650 -0.26472802 -3.66145265 12.2382531  18.9846037 -1.676584866  15.2614596  4.241818360  11.685053 -1.41970648  -8.67808713  5.7914843
14 -0.66123979 -0.73403494 -1.47051990 -9.4605317   7.9187982  1.649205050   5.5260746  2.236724615  -5.689584  0.08904104  -7.61932439 -2.3718501
15 -0.25993662 -0.36155808  0.47540397  0.2766627 -12.6713829  3.527719828  16.7505891 -4.031521995  -6.139259  1.16441221  -6.18252342  1.0479288
16 -0.03146197 -0.45563938  7.13155463 -8.8844448  10.2941475  6.470602700  11.8131578  2.036032005  -3.021039  1.27196373  16.98691230  5.9919408
17  0.15062972 -0.14899016 -5.17104361 27.1526356  10.6209803  8.107969651  11.0779712  5.968404297  13.698359  2.93330073  20.28969711 -1.1704762
18 -0.25937867 -0.39833982 -0.43088475 -5.6251327  11.3899990 -0.318345728   3.1713730  0.760007843   5.409240 -3.68088307 -10.11778528  4.8975433
19 -0.87451283 -0.05959917 -2.53664942 29.4869423  19.1536567 -4.591416100  27.3860278  3.156809354   7.025175  4.72109032  26.79484568  2.0115602
20 -0.67964587  0.27642731 -7.18238442  5.0073861   9.8321189  0.380995576   1.9077432 -0.585178489  -3.439573  2.59522601  -8.74681890 -0.6800699
21 -0.49629567 -0.56934938  2.23942230 22.8194269   5.2645346 -2.428571330   6.1776451  2.611162565  18.775754  1.10296129  12.87445853 -4.3216192
22  0.00724720 -0.70303883 -1.43444204  1.8773895   9.1167518  3.582722007   9.7741579  0.028240658   4.460745  2.27952502  14.99544664 -0.9230170
23 -0.10643328 -0.67769320  6.75704004  3.0189378  -0.9081308  2.255448682   9.2941211  2.151332408  -2.619788  1.16186606  -5.75794077  3.8895972
24  0.35597240  0.06858421 -1.72085135 10.4151256  -0.1591937  1.167127427   4.6532448  0.296189520 -10.270647 -0.35558702  16.91723551 -1.0866788
25  0.10449039  0.22289001  6.69617230  6.2155570  10.8483718 -1.374067174   3.7386102  1.255906864   5.792042  6.56478190   5.65215300  4.2867125
26  0.11049705 -0.26850303 -2.60011742  1.7766863  -7.9563835 -1.795606943   2.2133029 -4.103202628   5.503321 -1.80881337   6.71979360  5.2476183
27 -0.43247910  0.06570798  3.12944595 26.3058088  23.7036553  1.572823145  41.4230817 -3.123108372  44.661343  6.00690771  12.20911459  9.3681238
28 -0.06832140 -0.47558618 -0.05898754 10.2791424  -1.2785850 -1.881395391  -7.0972730  0.283137062  11.300423 -5.42201881   7.69205240  3.6647710
29 -0.14796844 -0.31242843 -7.13439956  8.8376481  13.4659132  1.461275344   4.1133381  2.784203145  12.496497  0.41425657   6.27234388  3.2425929
30  0.33267383  0.07562561  4.30418636 11.5135055  -5.5710269  0.595018978  20.2956727 -1.999030542  23.338891  1.79473828  25.14227894  3.5624672
31 -0.13135999  0.03429504  3.12945679 -1.7988365  -0.8664450 -0.925567331  -3.7275570 -3.950239410   7.792904 -2.94586593  -4.80659759 -5.1385471
32 -0.65278805 -0.24207506 -0.80329023 -1.5381825  -7.0147661 -1.371024797  11.1363243 -0.703554423   9.848548  0.77097874  -0.01193523  2.0874871
33 -0.27298162  0.36527044 -0.44873371 -3.2108142  15.4038635  5.626084802   7.3734731 -0.818813872  -2.329578 -1.22258273   5.73140635  7.6681611
34  0.24697363  0.04004560  3.55251026 10.9369448  17.4436080  4.964061402  -4.1149183 -0.594522702  30.979488  1.34426338  10.79636312  3.7373761
35 -0.23005566  0.07016680  8.61098096  7.2749938   6.1983372 -1.931047305  11.2845415 -0.255800684 -12.768165  0.65177004   7.72055325 -9.8395187
36  0.07745730 -0.07007581  4.21970890 16.3408506  13.6502613 -2.764005594   4.7150426 -3.352393845   7.726116  1.05046858 -11.41243533 -2.5015196
37 -0.68399493  0.23974508 -0.17544534 -5.5184731   5.8961029 -4.510778693  17.5402976  4.658695314   3.495335  4.32696570   6.21866892  2.9641552
38 -0.04013683 -0.78642712 -3.96729208  3.4475599  -1.2403075  2.536697158  -7.7241472  4.334766041  -9.963346 -0.64687173  17.34032967  1.8524765
39 -0.44495174 -0.19879868  1.92668453  6.8470802  21.4526006  0.455531935  27.9513567 -1.370725185   1.955942  3.59422972  24.79601058 -4.6690074
40 -0.13325651 -0.17514241 -2.82513210 21.0013199  -2.2907174 -1.494103403  18.4596623  2.297606605  -2.724228  2.31410400   0.75443901  0.1896653
41 -0.04049955 -0.30950401  1.08764034 12.0828373   3.2890383  5.742280231 -11.8575537  1.698274301  -2.021231  1.42562103   0.06413767  2.3617709
42  0.11173966 -0.66458170  7.85442282  9.1662041  30.2460296  1.990946110  16.4452737  5.687569677  11.302004  8.06994470  23.60159352 -3.6748499
43  0.22047452 -0.53158026  0.50466780 19.9152823   8.9427850 -0.637162403  11.3976456  4.603380514   8.462772 -1.49806588  15.98236455  2.5163547
44 -0.36319770 -0.22408093  2.86754885  1.5941018  -7.0354188  0.740816157   5.6042852 -1.145312539  -4.309770 -4.60556357   8.99063162  4.1639967
45 -0.45275458 -0.08379418 -5.95422943 16.4861889  15.9877620 -0.807411042   8.0873218  4.025147480  -3.494243  1.36140592   0.17167116  0.5730415
46 -0.02849445 -0.22411911  3.18637465  7.3235045  12.1141402 -2.049762449  -5.7373841  1.660312041  16.389530  4.32823877   2.31488480 -1.0958932
47 -0.46860175 -0.13260285  4.40493794  8.4949938   3.9516605 -1.243255229  -1.6795379 -0.013959038   4.140808 -3.39817037   4.27670204 -1.6862091
48 -0.41927264 -0.70467223  3.69590189 -6.4179034  -2.8701968  2.692561594  20.7038768  0.392052464  -2.993030  1.25742496  -5.18694095 -6.7182529
49 -0.02718469 -0.35311492  1.12532546  0.4862352   0.3023580 -1.603408864   1.2115986  0.845596944   9.048511  3.92056012  -8.67131197 -2.3896462
50 -0.32380034  0.06106854  3.30870522 -4.9429947  15.9727621 -0.159746543   7.7858779  1.608172511   4.614853  1.15746997  -3.63746568 -1.5704711

そして今、遺伝子型と表現型の組み合わせである新しい data.frame を作成したいと思います。特に、1 つの列は (markerinfo の) 最初のマーカーの遺伝子型であり、次の列は表現型の対応する表現型です。もちろん、markerinfo のすべてのマーカーに対してこれを行いたいと思います。ただし、ご覧のとおり、いくつかのマーカーが重複しています。それにもかかわらず、これらは異なるマーカーと見なされるべきであり、それでも列があります。データをさらに処理するために、この代替形式が必要です。

これが私の質問に答えるのに役立つ場合は、事前に感謝します

4

1 に答える 1

1

あなたのことを正しく理解できたかどうかわかりません。最小限の再現可能な例を作成する方法、特に の使用方法を学ぶ必要がありますdput

私は data.frames markerinfogenotypeを呼び出し、phenotypeテスト用にデータのごく一部のみを使用しました。私のソリューションが機能するには、markerinfo の各遺伝子型と表現型が対応する data.frames に存在する必要があります。(したがって、テストに使用した削減されたデータセットで機能するように、markerinfo の表現型を変更する必要がありました。)

result <- lapply(seq_along(markerinfo$marker),function(i) {
  x <- as.character(markerinfo$marker[i]) 
  res <- cbind(genotype[,x],phenotype[,as.character(markerinfo[i,"pheno"])])
  colnames(res) <- c(paste('geno',x,sep="_"),paste('pheno',as.character(markerinfo[i,"pheno"]),sep="_"))
  res
  }
)

result <- do.call('cbind',result) #combine lists

head(result)
     geno_c3m22 pheno_CACNA1E geno_c3m22 pheno_CACNA1F geno_c3m16 pheno_CACNA1G geno_c3m20 pheno_RAPGEF2
[1,]          2   0.053503367          2   -0.05512395          2   -0.16406024          2  -0.247595001
[2,]          2  -0.296400594          2   -0.14167491          2   -0.28751925          2   0.076554542
[3,]          2   0.001312523          2   -0.33078461          2   -0.84388147          2  -0.327202333
[4,]          1  -0.138671725          1    0.15734291          1   -0.04136305          1  -0.007847655
[5,]          1  -0.453451438          1   -0.23904476          2   -0.34506117          1  -0.288891373
[6,]          1  -0.186128793          1    0.12046537          2   -1.45824366          1  -0.819438873
#this is a matrix, use as.data.frame to turn it into a data.frame
于 2012-12-08T08:32:56.740 に答える