title: R data.frame columns with the same name check.names=FALSE not working
body: <p>Im initializing a data.frame as the following:</p>
  
  <pre><code>combdat &lt;- data.frame(matrix(nrow=50), check.names=FALSE)
  </code></pre>
  
  <p>In a loop I want now to fill in additional columns. This happens like this:</p>
  
  <pre><code>combdat[,mkr] &lt;- mkrgeno
  </code></pre>
  
  <p>Where mkr is a certain character and mkrgeno a vector of the same size. However there are certain values for mkr which are the same. I need to keep them. Right now they will just be overwritten. Athough I set check.names=FALSE</p>
  
  <p>Do anybody has an advice for me.
  Thanks</p>
  
  <p>Rich    </p>
  
  <hr>
  
  <p>Ok thank you I will try to ask my question in more detail.</p>
  
  <p>Im having the list markerinfo with certain information about the markers:</p>
  
  <pre><code>&gt; 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
  </code></pre>
  
  <p>Another data.frame is genotypes:</p>
  
  <pre><code> 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
  </code></pre>
  
  <p>and another one with the name: phenotype</p>
  
  <pre><code>&gt; 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
  </code></pre>
  
  <p>And now I want to create a new data.frame which is a combination of genotype and phenotype. In particular that one column is the genotype of the first marker (in markerinfo) and the next column is the corresponding phenotype in phenotypes. I want to do this of course for all markers in markerinfo. However as you can see there are a few markers in duplicate form. Nevertheless these should be considered as different markers and still have a column. I need this alternating form because of the further processing of the data.</p>
  
  <p>Thanks in advance if this can help you answer my question</p>