title: Labelling in Principal component analysis in R
body: <p>This is a continuation of the following post.</p>
  
  <p><a href="https://stackoverflow.com/questions/30405247/principal-component-in-r">how to color points in 17 colors based on principal component?</a></p>
  
  <pre><code>This is as.fumeric function 
  
  as.fumeric &lt;- function(x,levels=unique(x)) as.numeric(factor(x,levels=levels))
  
  
  cols=as.fumeric(gtex_pm$tissue)
  plot(pc_gtex$x[,1],pc_gtex$x[,2],col=cols, main = "PCA", xlab = "PC1", ylab = "PC2")
  legend("topleft", col=1:17, legend = paste(unique(gtex_pm$tissue), 1:17), pch = 20, bty='n', cex=1.5)
  </code></pre>
  
  <p>Once i have the plot with 17 levels,the legend created displays 17 levels,but the colors for them repeat after 1 to 8.So the 9th label has the same color as the first.
  Also,Is there any better way to add the group labels on the PCA plot.I have 17 unique groups.Either 2 groups are being assigned the same color because of "cols" variable or because of plotting "legend".The levels in cols are 17 .</p>
  
  <p>I can not post the picture due to a low reputation.The details of the data are in the linked post pasted above.</p>
  
  <p>This is the input data:</p>
  
  <pre><code>   SRR1069514   0   0.0009995   5.773065971 1.644998088 0.142367241 0.176471143 0.195566784 0.0009995   0.025667747 3.380994674 1.762502288 0   0.077886539 0   0.002995509 0.01093994  2.110576771 1.38829236  2.26186726  0.431132855 3.108480433 3.96347629  0   0   0.41012092  3.48452699  1.68565794  0   1.425034189 1.87456758  2.590542128 0   0   0   1.941471742 0.961646434 0   1.17711535  0.058268908 0   0.260824618 3.08534443  1.10426296  0.242946179 0.0009995   0   0   0   0.0009995   1.560247668 1.517541898 0.016857117 0.767326579 0.0009995   3.0191069   0   2.607050533 1.446683661 2.288384744 2.62082062  0.19309663  0   0   0.234281296 0   1.415610416 2.328837464 0.008959741 0.911479175 0.375005901 0.660107327 3.184739763 1.16064768  0.001998003 0.138891999 2.219855445 3.1011278   1.81872592  2.98229236  2.4114395   3.24528404  0   1.54734972  0.406131553 0.029558802 0.003992021 0.693647056 2.07581 2.8357982   0.0009995   0.082501222 1.09661029  2.75829962  0.635518068 3.11484775  0.01291623  3.40837159  0   
     SRR1071717   0   0   0.0009995   4.99519673  1.626491667 0.100749903 0.327863862 0.09531018  0   0.056380333 3.328196489 1.541373182 0   0.091667189 0.044973366 0   0.033434776 1.953311265 1.56444055  1.79142608  0.993622075 3.206236281 3.82609468  0   0   2.565487674 3.2202349   1.1304339   0   1.092258815 1.80203978  2.645394351 0   0   0.0009995   1.681200279 2.047434746 0   0.948176921 0.006975614 0.014888613 0.298622013 2.49667052  1.01884732  0.38662202  0   0   0   0   0.0009995   0.941958479 1.752845376 0.017839918 0.216722984 0.051643233 3.0505518   0   2.034444176 0.988053098 2.235804059 1.89686995  0.090754363 0   0   0.198850859 0   1.585554972 2.274905524 0   0.04305949  0.056380333 0.044016885 0.771496147 1.195436473 0   0.368801124 1.974636427 2.7700856   2.00120969  2.88875935  2.2651947   2.66242502  0   0.429181635 0.04018179  0.034401427 0   0.242161557 1.9907469   2.1384177   0.0009995   0.008959741 0.99916021  2.3892214   0.086177696 3.16821391  0   3.2038434   0
     SRR1073069   2.19544522  1.32866525  0.0009995   4.50198508  1.159707388 0.141499562 0.265436464 0.026641931 2.3330173   0.028587457 3.140698044 1.537297235 0.012916225 0.023716527 0   0.002995509 0.049742092 2.071157322 1.02460688  2.11818137  0.359072069 2.419656765 3.5065479   0.137149838 2.121902193 0.305276381 2.95958683  1.49939981  3.14397985  1.001366904 1.450911    1.39475844  1.930071085 1.140074079 0.037295785 1.609437912 0.412109651 0.870456196 0.943516718 0.013902905 0   0.152721087 2.88836976  1.482967248 0.272314595 2.061532121 0.552159487 2.394890764 1.391033116 0.443402947 1.593714952 1.285921387 0.00796817  0.371563556 0.020782539 3.1946651   1.26327891  2.212003715 1.46672161  2.140183804 2.71997877  0.294161039 0.018821754 0.0009995   0.179818427 1.893714192 1.731478538 2.502255288 0.013902905 0.752830183 0.347129531 0.407463111 2.467082065 0.558472277 1.563812734 0.022739487 1.608837732 2.8176816   1.30670988  2.44495233  1.81107178  3.03254625  0.569283193 0.948176921 0.101653654 0.036331929 0   0.786182047 1.9867779   3.5039946   2.463427618 0.008959741 0.76360564  2.20640453  0.514618422 2.87964779  1.11021142  3.18750899  1.22436349
     SRR1074410   2.69022562  1.70055751  0.013902905 3.314622273 0.503196597 0.4940863   0.044016885 0.023716527 1.753884517 0.03246719  2.767324893 1.666385193 0.009950331 0.05259245  0   0   0.017839918 1.575260461 0.76779072  2.22202559  0.83377831  2.198113071 3.57953881  0.051643233 2.207284913 0.072320662 3.04414141  1.39177929  2.851746423 0.982452934 1.33210213  1.888583654 1.871340532 1.238664044 0.03246719  1.734659877 0.486737828 0.412109651 1.126551657 0.035367144 0   0.213497174 2.76032635  1.131402111 0.572108852 2.102425378 0.291175962 1.85159947  0.943516718 0.283674051 1.232560261 0.982078472 0   0.223943232 0.035367144 2.9064091   1.583299255 2.376671636 1.185095749 2.07681309  2.20794469  0.877549904 0.151002874 0   0.107059072 3.038312721 1.486365915 2.633829402 0   0.403463105 0.195566784 0.285930539 1.296643139 0.48796633  1.664115474 0.054488185 1.884034745 2.3757426   1.71036863  2.61732284  1.9348492   3.1138708   1.220239777 0.322807874 0.12398598  0.004987542 0.002995509 0.446607051 1.939317    3.8484227   2.78346684  0.025667747 0.78253074  2.03352848  0.181487876 2.7091163   1.00430161  3.1429015   1.24875495
  </code></pre>
  
  <p>The group table:</p>
  
  <pre><code>head(gtex_pm)
  
       sample   tissue
  
     1 SRR1069514 Prostate
     2 SRR1071717  Bladder
     3 SRR1073069 Prostate
     4 SRR1074410 Prostate
  </code></pre>