#Input data
dataku <- read.csv("file:///D:/Skripsi/databaru.csv" ,
header= TRUE, sep=",")
sampel = (dataku$sample)
str(dataku)
## 'data.frame': 54 obs. of 242 variables:
## $ sample : Factor w/ 54 levels "GSM514737","GSM514738",..: 1 2 3 4 5 6 7 8 9 10 ...
## $ X216671_x_at : num 11 11.3 11.5 11.5 11.5 ...
## $ X1562738_a_at : num 3.9 3.84 4.02 3.45 3.2 ...
## $ X1565866_a_at : num 4.57 4.67 5.18 4.74 5.12 ...
## $ X221057_at : num 4.09 4.36 4.13 4.12 4.4 ...
## $ X213964_x_at : num 4.39 3.8 4.41 4.21 4.39 ...
## $ X230156_x_at : num 4 3.6 3.53 3.42 4.16 ...
## $ X1553113_s_at : num 3.85 3.44 3.35 3.64 3.8 ...
## $ X226746_s_at : num 5.67 6.99 6.52 6.27 6.2 ...
## $ X235547_at : num 4.23 4.47 4.55 4.21 4.18 ...
## $ X214384_s_at : num 4.9 5.45 4.96 4.37 5.26 ...
## $ X212768_s_at : num 3.59 3.37 4.24 3.99 4.22 ...
## $ X213684_s_at : num 4.3 4.01 4.05 4.2 3.77 ...
## $ X242497_at : num 6.76 6.49 7.19 6.97 7.15 ...
## $ X230790_x_at : num 5.6 5.16 5.52 5.57 5.54 ...
## $ X217494_s_at : num 4.95 4.87 4.8 4.38 4.5 ...
## $ X238992_at : num 3.96 3.54 3.82 3.77 3.99 ...
## $ X213817_at : num 5.47 5.58 5.38 4.91 5.18 ...
## $ X208325_s_at : num 7.7 7.41 7.72 7.16 7.83 ...
## $ X226836_at : num 6.39 5.76 6.35 6.26 6.03 ...
## $ X224673_at : num 7.45 7.25 7.6 7.31 7.26 ...
## $ X228985_at : num 5.16 5.15 5.07 4.6 4.96 ...
## $ X225830_at : num 5.01 4.32 5.06 4.89 5.13 ...
## $ X214683_s_at : num 7.4 6.26 6.89 6.88 7.06 ...
## $ X230559_x_at : num 3.52 3.62 4.03 3.4 3.63 ...
## $ X225537_at : num 6.17 5.61 5.3 5.25 5.48 ...
## $ X203634_s_at : num 4.88 4.65 4.4 4.08 4.12 ...
## $ X228324_at : num 4.11 4.27 4.03 3.83 4.35 ...
## $ X1553749_at : num 3.61 3.65 3.66 3.6 3.5 ...
## $ X234464_s_at : num 5.58 5.57 5.84 5.5 5.51 ...
## $ X1554704_at : num 4.85 5.05 4.75 4.78 4.59 ...
## $ X240050_s_at : num 3.85 3.96 3.91 3.72 3.84 ...
## $ X1559129_a_at : num 5.54 5.42 5.21 4.76 5.18 ...
## $ X227310_at : num 3.96 3.69 3.89 3.78 3.99 ...
## $ X217547_x_at : num 3.63 3.16 3.31 3.62 4.01 ...
## $ X214395_x_at : num 5.93 6.61 6.53 6.36 6.41 ...
## $ X219599_at : num 7.55 6.6 7.16 7.41 7.01 ...
## $ X201437_s_at : num 4.63 5 4.75 4.85 4.53 ...
## $ X231035_s_at : num 6.65 7 7.29 7.17 7.16 ...
## $ X208939_at : num 6.57 5.39 5.54 5.35 5.67 ...
## $ X226099_at : num 4.14 3.76 4.23 4.2 3.98 ...
## $ X230126_s_at : num 5.01 5.6 5.94 5.6 5.84 ...
## $ X231548_at : num 6.67 6.32 6.47 6.17 6.38 ...
## $ X214052_x_at : num 5.21 4.98 5.49 5.04 5.14 ...
## $ X213582_at : num 5.6 5.41 6.01 5.48 5.84 ...
## $ X216563_at : num 3.85 3.73 4 3.99 4.42 ...
## $ X241621_at : num 3.5 3.54 3.97 3.72 3.79 ...
## $ X211074_at : num 11.2 12.4 12.4 11.5 12.2 ...
## $ X212477_at : num 4.34 4.28 4.57 4.1 4.31 ...
## $ X227553_at : num 5.77 5.52 5.99 5.58 5.55 ...
## $ X224321_at : num 6.74 7.75 7.13 7.23 7.37 ...
## $ X230699_at : num 5.53 5.3 5.4 5.65 5.69 ...
## $ X1554283_at : num 4.32 4.31 4.1 4.09 4.39 ...
## $ X213552_at : num 4.41 4.2 3.69 4.13 4.37 ...
## $ X202318_s_at : num 5.77 6.15 6.33 6.02 6.22 ...
## $ X232125_at : num 4.65 3.65 3.65 3.88 4.25 ...
## $ X62987_r_at : num 11.6 11.7 11.7 11.7 11.7 ...
## $ X231951_at : num 9.43 9.81 9.58 9.88 9.62 ...
## $ X210007_s_at : num 4.53 4.75 4.5 4.4 4.96 ...
## $ X1563498_s_at : num 3.92 3.91 3.56 4.24 4.41 ...
## $ X228193_s_at : num 4.91 4.73 5.11 5.04 4.52 ...
## $ X242685_at : num 3.13 3.45 3.33 3.7 3.33 ...
## $ X227244_s_at : num 5 4.97 5.46 5.07 5.12 ...
## $ X220132_s_at : num 5.36 4.73 5.06 5.36 5.12 ...
## $ X213951_s_at : num 6.19 6.36 6.42 6.64 5.99 ...
## $ X213826_s_at : num 7.22 7.46 7.71 7.1 7.31 ...
## $ X1552980_at : num 5.36 4.99 5.64 5.32 5.46 ...
## $ X213831_at : num 9.7 9.71 9.57 9.7 9.69 ...
## $ X209480_at : num 8.56 8.35 8.4 8.33 8.71 ...
## $ X209728_at : num 10.6 10.7 10.2 10.2 10.4 ...
## $ X221919_at : num 5.44 5.53 5.69 5.43 5.68 ...
## $ X209657_s_at : num 5.09 4.4 4.92 4.59 5.27 ...
## $ X228520_s_at : num 6.42 6.04 6.65 5.9 5.94 ...
## $ X206638_at : num 4 4.96 4.12 4.39 3.81 ...
## $ X1558700_s_at : num 4.24 4.16 4.01 4.5 4.4 ...
## $ X200602_at : num 4.66 4.79 5.35 5.27 5.47 ...
## $ X207688_s_at : num 4.68 5.27 5.29 5.05 5.89 ...
## $ X214723_x_at : num 4.39 3.89 4.12 4.03 4.75 ...
## $ X231735_s_at : num 8.68 8.73 9.06 8.83 8.78 ...
## $ X1562364_at : num 5.3 5 5.52 5.59 5.4 ...
## $ X1554597_at : num 6.68 6.15 6.39 6.07 6.43 ...
## $ X206123_at : num 9.5 9.31 9.49 9.61 9.57 ...
## $ X1562481_at : num 4.46 4.02 4.63 4.28 4 ...
## $ X232197_x_at : num 3.59 3.71 3.87 3.5 3.42 ...
## $ X228938_at : num 6 5.95 5.77 6.25 5.85 ...
## $ X214057_at : num 7.15 7.03 7.99 7.28 7.41 ...
## $ X1560145_at : num 6.44 5.79 6.16 6.08 5.81 ...
## $ X221589_s_at : num 4.93 4.41 4.57 4.47 4.78 ...
## $ X232001_at : num 7.54 7.03 6.8 7.09 7.46 ...
## $ X229543_at : num 3.67 3.91 3.82 3.84 3.86 ...
## $ X1558688_at : num 12.7 12.8 12.9 13 13 ...
## $ X1553575_at : num 7.68 7.85 8.11 7.75 7.97 ...
## $ X228933_at : num 4.53 4.65 4.67 4.14 4.95 ...
## $ X229143_at : num 4.43 4.75 4.57 4.57 4.55 ...
## $ X229204_at : num 7.23 7.23 7.34 7.08 7.06 ...
## $ X209525_at : num 4.41 4.57 4.82 4.99 4.49 ...
## $ X222968_at : num 5.85 5.86 5.63 5.3 5.22 ...
## $ X222487_s_at : num 4.02 4.66 4.52 4.88 4.75 ...
## $ X230535_s_at : num 5.75 6.22 5.96 5.19 5.88 ...
## [list output truncated]
dim(dataku)
## [1] 54 242
head(dataku)
## sample X216671_x_at X1562738_a_at X1565866_a_at X221057_at
## 1 GSM514737 11.03524 3.900094 4.568587 4.092823
## 2 GSM514738 11.28329 3.839818 4.671037 4.364913
## 3 GSM514739 11.49579 4.024019 5.175035 4.127306
## 4 GSM514740 11.47500 3.450468 4.737689 4.124238
## 5 GSM514741 11.47334 3.200125 5.122944 4.404533
## 6 GSM514742 11.15582 3.138268 5.095908 4.217661
## X213964_x_at X230156_x_at X1553113_s_at X226746_s_at X235547_at
## 1 4.388659 3.997078 3.846021 5.674073 4.225162
## 2 3.797805 3.601215 3.440797 6.987558 4.466731
## 3 4.411868 3.534582 3.349497 6.515071 4.550468
## 4 4.208121 3.419962 3.639953 6.272661 4.210992
## 5 4.387170 4.158220 3.803968 6.197169 4.183926
## 6 4.149331 3.325083 3.632247 5.931276 4.257388
## X214384_s_at X212768_s_at X213684_s_at X242497_at X230790_x_at
## 1 4.903450 3.587801 4.300989 6.763878 5.604847
## 2 5.445815 3.369883 4.014897 6.492054 5.158656
## 3 4.960762 4.244512 4.053045 7.186097 5.524681
## 4 4.366681 3.991007 4.198842 6.969761 5.565819
## 5 5.260839 4.215770 3.767181 7.154392 5.543823
## 6 4.579939 5.638916 4.487803 6.630450 5.488110
## X217494_s_at X238992_at X213817_at X208325_s_at X226836_at X224673_at
## 1 4.954125 3.955241 5.466253 7.702690 6.391387 7.448027
## 2 4.872018 3.537780 5.582575 7.411505 5.756651 7.249571
## 3 4.800037 3.821023 5.382863 7.720639 6.349981 7.599764
## 4 4.381648 3.770343 4.912503 7.161937 6.262451 7.311629
## 5 4.496130 3.988838 5.177215 7.826759 6.025127 7.259183
## 6 4.072273 4.208968 5.838244 6.775187 6.653094 7.465191
## X228985_at X225830_at X214683_s_at X230559_x_at X225537_at X203634_s_at
## 1 5.163696 5.013517 7.395201 3.519144 6.173324 4.876347
## 2 5.149536 4.317398 6.255437 3.616936 5.610011 4.646503
## 3 5.074102 5.060310 6.885373 4.028473 5.298232 4.398177
## 4 4.601477 4.893476 6.881907 3.401023 5.253050 4.082194
## 5 4.957743 5.127484 7.062347 3.632471 5.482401 4.115714
## 6 5.630147 4.546424 7.772427 4.138841 5.909036 4.076287
## X228324_at X1553749_at X234464_s_at X1554704_at X240050_s_at
## 1 4.110351 3.610601 5.576689 4.851263 3.851502
## 2 4.266695 3.648428 5.571536 5.052163 3.956373
## 3 4.030001 3.661559 5.839049 4.750035 3.908899
## 4 3.834485 3.599229 5.498021 4.780423 3.720031
## 5 4.353321 3.501682 5.505728 4.593421 3.839799
## 6 4.775601 3.473817 5.842043 4.876864 3.595638
## X1559129_a_at X227310_at X217547_x_at X214395_x_at X219599_at
## 1 5.538565 3.961169 3.625031 5.932426 7.551969
## 2 5.415982 3.689053 3.164815 6.610468 6.595908
## 3 5.212804 3.885691 3.312961 6.527454 7.164144
## 4 4.762895 3.775441 3.618466 6.355502 7.411649
## 5 5.178579 3.987482 4.014154 6.405308 7.007769
## 6 4.931067 3.817688 3.381368 6.518154 7.384347
## X201437_s_at X231035_s_at X208939_at X226099_at X230126_s_at X231548_at
## 1 4.628857 6.652110 6.569220 4.135388 5.005349 6.666328
## 2 5.001016 7.004208 5.386432 3.761261 5.595097 6.323409
## 3 4.751914 7.290746 5.541893 4.229620 5.941802 6.470407
## 4 4.846269 7.172316 5.348231 4.201566 5.595245 6.174649
## 5 4.531271 7.156486 5.666606 3.976781 5.844101 6.378791
## 6 5.637688 6.615067 6.099025 4.540935 5.494042 6.141350
## X214052_x_at X213582_at X216563_at X241621_at X211074_at X212477_at
## 1 5.210584 5.601526 3.853609 3.504369 11.21438 4.338136
## 2 4.982424 5.405460 3.725323 3.537717 12.44077 4.284818
## 3 5.490412 6.014104 4.002171 3.972312 12.40623 4.574449
## 4 5.037759 5.475902 3.987390 3.715240 11.52307 4.102631
## 5 5.141782 5.835930 4.421978 3.789234 12.18357 4.310725
## 6 5.531210 5.860268 4.124487 3.522961 10.22403 4.325814
## X227553_at X224321_at X230699_at X1554283_at X213552_at X202318_s_at
## 1 5.773410 6.741876 5.526956 4.315031 4.405230 5.773276
## 2 5.522639 7.748698 5.298612 4.310534 4.195542 6.147466
## 3 5.991038 7.134851 5.403608 4.099845 3.685103 6.334777
## 4 5.577002 7.232568 5.650346 4.091661 4.131079 6.016703
## 5 5.547008 7.373964 5.689253 4.393770 4.371374 6.223509
## 6 5.660619 6.738725 5.215214 4.060454 4.314053 6.298900
## X232125_at X62987_r_at X231951_at X210007_s_at X1563498_s_at
## 1 4.650233 11.57725 9.433411 4.531536 3.915250
## 2 3.648428 11.68896 9.810697 4.753675 3.911706
## 3 3.645995 11.69482 9.579063 4.496183 3.561161
## 4 3.881307 11.73762 9.884634 4.399476 4.242040
## 5 4.246278 11.71210 9.619396 4.963877 4.412085
## 6 3.643435 11.55109 9.767578 4.961408 4.667662
## X228193_s_at X242685_at X227244_s_at X220132_s_at X213951_s_at
## 1 4.913270 3.126847 4.995494 5.359131 6.191723
## 2 4.730452 3.445666 4.969064 4.730452 6.358256
## 3 5.114841 3.329672 5.464779 5.057490 6.419065
## 4 5.040897 3.698925 5.067047 5.356656 6.635764
## 5 4.520046 3.332740 5.117541 5.118410 5.992815
## 6 5.152212 3.474038 4.860549 4.853037 6.977804
## X213826_s_at X1552980_at X213831_at X209480_at X209728_at X221919_at
## 1 7.219597 5.359762 9.704738 8.561157 10.60576 5.441272
## 2 7.455883 4.989631 9.711077 8.353473 10.69205 5.532944
## 3 7.707088 5.641522 9.565671 8.401436 10.20276 5.685043
## 4 7.097236 5.315286 9.696828 8.333331 10.18361 5.430635
## 5 7.314604 5.457356 9.693618 8.710299 10.44160 5.676631
## 6 6.760126 5.339817 8.821694 8.656878 10.60018 5.502271
## X209657_s_at X228520_s_at X206638_at X1558700_s_at X200602_at
## 1 5.094304 6.423503 4.004194 4.238551 4.657009
## 2 4.396660 6.042881 4.960186 4.163922 4.793713
## 3 4.915765 6.649534 4.124715 4.013228 5.349418
## 4 4.594763 5.903326 4.387631 4.499470 5.272439
## 5 5.274378 5.942364 3.806141 4.397469 5.473170
## 6 5.893857 6.671968 4.348915 5.154516 5.161873
## X207688_s_at X214723_x_at X231735_s_at X1562364_at X1554597_at
## 1 4.676087 4.390421 8.684168 5.303412 6.676598
## 2 5.267626 3.886801 8.728240 5.002389 6.145305
## 3 5.289701 4.123864 9.057076 5.519337 6.386872
## 4 5.054038 4.033635 8.827052 5.594535 6.067617
## 5 5.888063 4.749086 8.782078 5.399084 6.434116
## 6 5.831523 3.999550 9.392400 5.598560 6.536111
## X206123_at X1562481_at X232197_x_at X228938_at X214057_at X1560145_at
## 1 9.500481 4.461905 3.586496 5.996829 7.150868 6.435182
## 2 9.312439 4.024782 3.707234 5.949738 7.033763 5.791504
## 3 9.487913 4.629158 3.867655 5.770057 7.988645 6.158845
## 4 9.607828 4.284841 3.497784 6.253180 7.281958 6.077392
## 5 9.565859 4.000239 3.419611 5.850207 7.412394 5.808549
## 6 9.216493 4.259931 3.250954 5.861952 7.112491 6.835928
## X221589_s_at X232001_at X229543_at X1558688_at X1553575_at X228933_at
## 1 4.928034 7.540812 3.674867 12.66457 7.684980 4.529713
## 2 4.409970 7.031421 3.910437 12.84299 7.846577 4.647128
## 3 4.565205 6.795965 3.818881 12.85119 8.113368 4.666491
## 4 4.468378 7.091787 3.842904 13.01665 7.748494 4.141614
## 5 4.778443 7.460011 3.859012 12.96792 7.972109 4.950441
## 6 4.739315 8.635567 4.206995 12.68896 7.420898 4.057129
## X229143_at X229204_at X209525_at X222968_at X222487_s_at X230535_s_at
## 1 4.431424 7.233202 4.414093 5.854871 4.016027 5.747304
## 2 4.752348 7.226608 4.571096 5.856773 4.658349 6.216707
## 3 4.570108 7.337305 4.820210 5.626828 4.522799 5.958789
## 4 4.571084 7.076331 4.989856 5.295281 4.876407 5.187970
## 5 4.553459 7.062324 4.485938 5.218874 4.748948 5.883956
## 6 4.763791 7.513756 4.452845 5.628330 4.667896 5.564926
## X239133_at X213868_s_at X225207_at X214163_at X1555247_a_at X217383_at
## 1 6.283434 6.469001 5.671674 3.982233 5.471623 5.902244
## 2 5.189231 6.512403 4.235332 3.642057 5.209230 5.630416
## 3 5.250812 5.643612 4.749232 3.778250 5.269728 6.110575
## 4 4.742697 6.055142 4.185974 3.916288 5.365681 5.926130
## 5 5.534771 5.703193 4.366120 3.926810 5.829262 6.197176
## 6 6.071250 6.216260 6.423705 4.066175 6.107308 5.715122
## X218984_at X221986_s_at X229589_x_at X219433_at X225934_at X229399_at
## 1 5.003615 5.471623 3.315730 5.135255 5.411667 3.566725
## 2 5.166288 5.575538 3.208656 4.473169 5.442546 4.108395
## 3 5.059983 5.021833 3.110129 5.396558 5.530359 3.313351
## 4 4.918855 5.456309 3.126045 5.422009 5.491511 3.494731
## 5 5.189759 5.122689 3.054360 5.325385 5.454852 3.709179
## 6 5.351528 4.688930 3.175341 5.250816 5.546061 3.950181
## X236026_at X224037_at X1569105_at X231500_s_at X206500_s_at X230683_at
## 1 3.943030 4.269368 11.02509 4.653984 4.459405 5.745805
## 2 4.285987 4.225592 11.30419 4.472087 4.165064 5.699399
## 3 4.119918 3.853526 11.28893 4.681078 5.243388 5.903290
## 4 3.971612 3.952088 11.24753 4.857263 4.586914 5.501948
## 5 4.100416 4.182187 11.30427 4.889379 4.701917 5.497803
## 6 4.091758 4.267014 11.46244 4.591109 4.566398 5.385485
## X233191_at X1557066_at X241631_at X221645_s_at X222811_at X239146_at
## 1 3.105728 3.749654 4.988598 5.190971 4.999002 4.639511
## 2 3.444203 3.980398 4.666378 5.377097 4.390143 4.718888
## 3 3.957398 3.508027 4.252023 5.492359 4.911000 4.176924
## 4 3.367998 3.753431 4.414389 5.433937 4.616394 4.263457
## 5 3.638837 3.901699 4.788590 5.645062 5.166918 5.023305
## 6 3.421783 3.859470 4.557869 5.920183 5.887931 4.443397
## X228309_at X228751_at X225726_s_at X226164_x_at X224308_s_at
## 1 7.130985 5.119632 4.158693 4.011572 5.868936
## 2 7.139190 4.640113 4.448604 3.873639 5.179838
## 3 6.805583 4.890507 4.407949 3.666343 5.331649
## 4 6.970606 5.181196 4.471325 3.712516 5.200402
## 5 6.415380 4.621739 4.792548 4.245601 5.482401
## 6 6.736817 5.107175 4.428999 4.004126 6.014322
## X231193_s_at X1558956_s_at X1552480_s_at X240990_at X1567457_at
## 1 5.102576 4.180232 3.544502 3.532775 3.703568
## 2 5.090342 3.902729 3.319698 4.247139 3.473065
## 3 4.468310 4.014124 4.052189 3.833826 3.720188
## 4 4.647335 4.253171 3.368472 3.809759 3.578942
## 5 4.882127 4.166486 3.622599 3.556270 3.295865
## 6 4.777244 4.533236 3.264542 3.637385 3.003025
## X235511_at X214000_s_at X213409_s_at X236223_s_at X214041_x_at
## 1 4.784690 6.642865 3.794178 5.619063 6.997955
## 2 4.264278 6.885210 3.995146 5.503582 6.671450
## 3 4.427687 7.028726 3.949111 4.553921 7.003932
## 4 4.757267 6.969082 3.881897 4.822216 7.661702
## 5 4.554300 6.513179 4.104659 4.958077 7.631244
## 6 4.840748 6.581652 4.269027 4.890505 8.608225
## X200908_s_at X214001_x_at X213350_at X1568012_at X214370_at X234947_s_at
## 1 7.093931 6.906669 8.151063 3.309930 7.389717 4.380850
## 2 6.894127 7.172774 8.393525 3.046721 6.471288 4.526231
## 3 7.283743 6.769505 9.214383 3.122195 6.723308 4.225798
## 4 6.965357 6.804283 9.270904 3.203644 6.280854 4.791969
## 5 7.318156 6.422467 8.934968 3.299530 6.300866 4.721365
## 6 6.802244 6.999898 8.548142 3.107502 7.730309 5.600476
## X237444_at X224974_at X219972_s_at X224873_s_at X217257_at X232371_at
## 1 5.225935 5.074933 3.964905 4.318180 5.674073 5.311657
## 2 5.102268 4.586307 4.040519 4.490818 6.051279 5.620517
## 3 5.916015 4.754940 4.279580 4.977229 5.769328 5.938452
## 4 4.694507 5.294686 4.036626 4.613426 5.460694 5.164133
## 5 4.936176 5.700040 4.362699 5.061126 5.303131 5.584022
## 6 5.203728 5.005953 4.025907 5.156115 5.971139 6.047424
## X223292_s_at X215450_at X217644_s_at X217040_x_at X209340_at X226765_at
## 1 4.092823 4.925997 5.524501 9.902985 5.170040 4.767978
## 2 4.133857 5.163422 5.505681 10.239003 4.546465 4.777852
## 3 4.161325 4.362163 5.603364 10.121330 4.922424 5.040624
## 4 4.182489 4.252617 4.970299 10.008823 4.511258 5.158012
## 5 4.263401 4.609961 5.571713 9.953121 5.040723 5.067520
## 6 4.482454 5.015460 4.697785 10.031675 5.485036 5.651220
## X209358_at X215220_s_at X203983_at X216609_at X1556204_a_at X226637_at
## 1 5.807728 4.004729 6.914480 4.808611 4.703417 4.104400
## 2 5.073714 4.091239 6.592368 4.564736 5.529354 3.888190
## 3 5.254844 3.900279 6.487212 4.761628 5.192986 4.302920
## 4 5.418408 3.811185 6.329218 4.746984 4.431342 4.788744
## 5 5.555653 3.668922 6.581507 4.927281 4.952733 4.460003
## 6 6.082813 3.819827 7.047616 5.419881 4.390389 4.048388
## X229123_at X219303_at X218195_at X209972_s_at X222837_s_at X227528_s_at
## 1 5.450149 5.444812 5.773410 7.277927 4.686180 7.038982
## 2 4.332459 4.797340 5.317996 7.168363 3.888168 7.034889
## 3 4.582920 5.342538 5.208523 7.400291 3.924453 6.980482
## 4 5.354922 4.985053 5.455839 7.123847 4.217482 6.773939
## 5 5.530185 5.441722 5.907724 7.020055 4.405668 6.443791
## 6 5.307830 5.784360 6.416285 7.184089 3.881897 6.832813
## X224953_at X231697_s_at X210596_at X235114_x_at X226344_at X213251_at
## 1 5.498466 5.870447 6.661090 4.740427 4.575531 6.729302
## 2 5.183888 5.414526 6.617307 4.382102 4.568090 6.093483
## 3 5.513171 5.207409 6.865316 4.654218 4.720611 6.523201
## 4 5.231153 5.333926 6.867683 4.516168 4.612608 6.474805
## 5 5.616109 5.860009 6.683817 4.404444 4.770977 7.021233
## 6 5.439149 5.914224 7.562811 4.700437 5.061396 7.809693
## X229787_s_at X60815_at X205063_at X226014_at X201936_s_at X227900_at
## 1 5.339125 5.047291 3.342044 5.950003 5.504916 5.719857
## 2 4.971185 4.892072 3.284853 6.235902 5.445150 4.711413
## 3 4.863580 5.056145 3.237821 6.034105 5.424747 4.991681
## 4 5.441976 4.884251 3.024584 6.035580 5.143927 4.473259
## 5 5.681649 4.761621 3.046040 6.410414 5.969373 5.037386
## 6 7.118462 4.750965 3.594316 5.887825 5.702080 5.579822
## X217654_at X213226_at X214149_s_at X219138_at X239960_x_at X209258_s_at
## 1 6.402773 4.428273 7.007658 6.574781 4.688636 4.331016
## 2 6.286866 4.161561 6.377492 6.982489 4.329101 4.428452
## 3 6.059232 4.470406 6.979317 7.037529 4.263549 4.893194
## 4 5.866205 4.138679 6.572291 6.720248 4.842912 4.521847
## 5 6.119746 3.974682 6.617851 7.179845 4.791787 4.565631
## 6 4.433250 4.477392 7.173105 6.631789 4.988799 4.734211
## X230003_at X228416_at X213742_at X231418_at X204349_at X202984_s_at
## 1 4.132738 3.840435 6.695251 6.678568 3.761450 5.462649
## 2 4.080552 4.161009 5.763147 6.438065 3.701099 4.797340
## 3 4.112578 3.976249 6.324392 6.815774 3.857658 5.761351
## 4 4.626805 3.850902 5.836396 6.681495 3.767085 4.848443
## 5 4.330908 4.337283 5.723090 7.118228 3.724819 5.253440
## 6 4.920167 3.980809 7.118356 6.707697 3.905906 4.176638
## X226404_at X209700_x_at X209795_at X203493_s_at X204075_s_at
## 1 4.832097 3.688356 4.375334 4.133633 3.765316
## 2 4.512958 3.488145 3.886413 3.757325 4.625129
## 3 4.532338 3.537927 3.311929 4.165247 4.312303
## 4 4.890847 3.397508 3.886521 3.725670 4.279556
## 5 4.732864 3.482392 3.907270 3.837644 4.441698
## 6 4.526019 3.273521 4.750248 4.147595 4.860246
## X203603_s_at X204291_at X236314_at X238653_at X1555884_at X1565823_at
## 1 5.250133 4.368319 5.980720 5.817085 3.314521 4.182549
## 2 4.796279 4.000721 4.795442 5.198891 3.297596 4.412359
## 3 5.535063 3.762056 5.896094 5.335023 3.029826 4.332953
## 4 5.404347 3.807233 5.764666 5.503318 2.959694 4.343529
## 5 6.013989 4.215987 5.750989 5.512610 2.938874 4.460150
## 6 5.613981 4.327696 5.577496 5.906395 3.106248 4.622254
## title geo_accession status submission_date
## 1 Blood_alcohol_T1_S13 GSM514737 Public on Jul 25 2013 Feb 23 2010
## 2 Blood_alcohol_T2_S13 GSM514738 Public on Jul 25 2013 Feb 23 2010
## 3 Blood_alcohol_T3_S13 GSM514739 Public on Jul 25 2013 Feb 23 2010
## 4 Blood_alcohol_T4_S13 GSM514740 Public on Jul 25 2013 Feb 23 2010
## 5 Blood_alcohol_T5_S13 GSM514741 Public on Jul 25 2013 Feb 23 2010
## 6 Blood_alcohol_T1_S15 GSM514742 Public on Jul 25 2013 Feb 23 2010
## last_update_date type channel_count source_name_ch1
## 1 Apr 29 2015 RNA 1 whole blood, BAC 0%
## 2 Apr 29 2015 RNA 1 whole blood, BAC 0.04%rising
## 3 Apr 29 2015 RNA 1 whole blood, BAC 0.08%
## 4 Apr 29 2015 RNA 1 whole blood, BAC 0.04%declining
## 5 Apr 29 2015 RNA 1 whole blood, BAC 0.02%declining
## 6 Apr 29 2015 RNA 1 whole blood, BAC 0%
## organism_ch1 characteristics_ch1 characteristics_ch1.1
## 1 Homo sapiens gender: male tissue: whole blood
## 2 Homo sapiens gender: male tissue: whole blood
## 3 Homo sapiens gender: male tissue: whole blood
## 4 Homo sapiens gender: male tissue: whole blood
## 5 Homo sapiens gender: male tissue: whole blood
## 6 Homo sapiens gender: male tissue: whole blood
## characteristics_ch1.2
## 1 intervention: BAC 0%
## 2 intervention: BAC 0.04%rising
## 3 intervention: BAC 0.08%
## 4 intervention: BAC 0.04%declining
## 5 intervention: BAC 0.02%declining
## 6 intervention: BAC 0%
## treatment_protocol_ch1 molecule_ch1
## 1 Blood was pulled directly into Paxgene tubes total RNA
## 2 Blood was pulled directly into Paxgene tubes total RNA
## 3 Blood was pulled directly into Paxgene tubes total RNA
## 4 Blood was pulled directly into Paxgene tubes total RNA
## 5 Blood was pulled directly into Paxgene tubes total RNA
## 6 Blood was pulled directly into Paxgene tubes total RNA
## extract_protocol_ch1
## 1 Total RNA was extracted using the protocol provided with the Paxgene tubeswith the optional on-column DNase treatment
## 2 Total RNA was extracted using the protocol provided with the Paxgene tubeswith the optional on-column DNase treatment
## 3 Total RNA was extracted using the protocol provided with the Paxgene tubeswith the optional on-column DNase treatment
## 4 Total RNA was extracted using the protocol provided with the Paxgene tubeswith the optional on-column DNase treatment
## 5 Total RNA was extracted using the protocol provided with the Paxgene tubeswith the optional on-column DNase treatment
## 6 Total RNA was extracted using the protocol provided with the Paxgene tubeswith the optional on-column DNase treatment
## label_ch1
## 1 biotin
## 2 biotin
## 3 biotin
## 4 biotin
## 5 biotin
## 6 biotin
## label_protocol_ch1
## 1 For the OJcontrol samples 50 ng total RNA was both reverse transcribed and amplified using the Ovation RNA amplification System V2 (Nugen Technologies). Microarray template material was fragmented and biotin labeled using the FL-Ovation cDNA Biotin Module V2 (Nugen Technologies, Inc.). For the alcohol experimental samples 50 ng total RNA was reverse transcribed and amplified using the 3' IVT one-cycle kit (Affymetrix), fragmented and biotin labeled using the GeneChip IVT labeling kit (Affymetrix).
## 2 For the OJcontrol samples 50 ng total RNA was both reverse transcribed and amplified using the Ovation RNA amplification System V2 (Nugen Technologies). Microarray template material was fragmented and biotin labeled using the FL-Ovation cDNA Biotin Module V2 (Nugen Technologies, Inc.). For the alcohol experimental samples 50 ng total RNA was reverse transcribed and amplified using the 3' IVT one-cycle kit (Affymetrix), fragmented and biotin labeled using the GeneChip IVT labeling kit (Affymetrix).
## 3 For the OJcontrol samples 50 ng total RNA was both reverse transcribed and amplified using the Ovation RNA amplification System V2 (Nugen Technologies). Microarray template material was fragmented and biotin labeled using the FL-Ovation cDNA Biotin Module V2 (Nugen Technologies, Inc.). For the alcohol experimental samples 50 ng total RNA was reverse transcribed and amplified using the 3' IVT one-cycle kit (Affymetrix), fragmented and biotin labeled using the GeneChip IVT labeling kit (Affymetrix).
## 4 For the OJcontrol samples 50 ng total RNA was both reverse transcribed and amplified using the Ovation RNA amplification System V2 (Nugen Technologies). Microarray template material was fragmented and biotin labeled using the FL-Ovation cDNA Biotin Module V2 (Nugen Technologies, Inc.). For the alcohol experimental samples 50 ng total RNA was reverse transcribed and amplified using the 3' IVT one-cycle kit (Affymetrix), fragmented and biotin labeled using the GeneChip IVT labeling kit (Affymetrix).
## 5 For the OJcontrol samples 50 ng total RNA was both reverse transcribed and amplified using the Ovation RNA amplification System V2 (Nugen Technologies). Microarray template material was fragmented and biotin labeled using the FL-Ovation cDNA Biotin Module V2 (Nugen Technologies, Inc.). For the alcohol experimental samples 50 ng total RNA was reverse transcribed and amplified using the 3' IVT one-cycle kit (Affymetrix), fragmented and biotin labeled using the GeneChip IVT labeling kit (Affymetrix).
## 6 For the OJcontrol samples 50 ng total RNA was both reverse transcribed and amplified using the Ovation RNA amplification System V2 (Nugen Technologies). Microarray template material was fragmented and biotin labeled using the FL-Ovation cDNA Biotin Module V2 (Nugen Technologies, Inc.). For the alcohol experimental samples 50 ng total RNA was reverse transcribed and amplified using the 3' IVT one-cycle kit (Affymetrix), fragmented and biotin labeled using the GeneChip IVT labeling kit (Affymetrix).
## taxid_ch1
## 1 9606
## 2 9606
## 3 9606
## 4 9606
## 5 9606
## 6 9606
## hyb_protocol
## 1 Arrays were hybridized for 18 hours at 45 deg C at 60 rpm in a GeneChip Hybridization Oven model 640 (Affymetric, Inc.). Fluidics protocol FS450_0004 was used with the GeneChip Fluidics Station model 450 to wash the arrays.
## 2 Arrays were hybridized for 18 hours at 45 deg C at 60 rpm in a GeneChip Hybridization Oven model 640 (Affymetric, Inc.). Fluidics protocol FS450_0004 was used with the GeneChip Fluidics Station model 450 to wash the arrays.
## 3 Arrays were hybridized for 18 hours at 45 deg C at 60 rpm in a GeneChip Hybridization Oven model 640 (Affymetric, Inc.). Fluidics protocol FS450_0004 was used with the GeneChip Fluidics Station model 450 to wash the arrays.
## 4 Arrays were hybridized for 18 hours at 45 deg C at 60 rpm in a GeneChip Hybridization Oven model 640 (Affymetric, Inc.). Fluidics protocol FS450_0004 was used with the GeneChip Fluidics Station model 450 to wash the arrays.
## 5 Arrays were hybridized for 18 hours at 45 deg C at 60 rpm in a GeneChip Hybridization Oven model 640 (Affymetric, Inc.). Fluidics protocol FS450_0004 was used with the GeneChip Fluidics Station model 450 to wash the arrays.
## 6 Arrays were hybridized for 18 hours at 45 deg C at 60 rpm in a GeneChip Hybridization Oven model 640 (Affymetric, Inc.). Fluidics protocol FS450_0004 was used with the GeneChip Fluidics Station model 450 to wash the arrays.
## scan_protocol
## 1 Scanning done on a GeneChip Laser Scanner model 3000 with system running GCOS version 1.4.
## 2 Scanning done on a GeneChip Laser Scanner model 3000 with system running GCOS version 1.4.
## 3 Scanning done on a GeneChip Laser Scanner model 3000 with system running GCOS version 1.4.
## 4 Scanning done on a GeneChip Laser Scanner model 3000 with system running GCOS version 1.4.
## 5 Scanning done on a GeneChip Laser Scanner model 3000 with system running GCOS version 1.4.
## 6 Scanning done on a GeneChip Laser Scanner model 3000 with system running GCOS version 1.4.
## description
## 1 CHT_S13_T1_12.09.04.CEL
## 2 CHT_S13_T2_12.09.04.CEL
## 3 CHT_S13_T3_12.09.04.CEL
## 4 CHT_S13_T4_12.09.04.CEL
## 5 CHT_S13_T5_12.09.04.CEL
## 6 CHT_S15_T1_01.06.05.CEL
## data_processing
## 1 GCOS report derived with TGT Value set at 500. The ethanol data was imported as CEL files into S+ArrayAnalyzerâ„¢ (version 2.1.1). Tools available in ArrayAnalyzer were used to assess data quality at the chip level. Background subtraction and summarization was done with RMA [Irizarry, 2003] and GCRMA, and the summarized data was quantile normalized [Bolstad, 2003]. RMA summarized data was filtered for log2 (RMA expression) >6 in at least six chips; GCRMA summarized data was filtered for log2 (GCRMA expression) >5. Each list was further filtered for a fold change in at least one pairwise comparison greater than 1.25. The Local Pooled Error (LPE T-test) [Jain, 2003] was used for differential expression testing across all possible pairwise timepoint comparisons. The False Discovery Rate (FDR) was controlled by implementation of the Benjamini and Hochberg correction [Benjamini, 1995]. Statistically significant genes (p<0.05) from the ten pairwise timepoint comparisons from both the RMA and GCRMA summarized data were combined into one list. A second list of significant genes was generated using the application, EDGE (Storey, 2007). RMA summarized data filtered for expression as above was used for input. The resulting list, ranked by Q-value, was filtered for a fold change in at least one pairwise comparison greater than 1.25.
## 2 GCOS report derived with TGT Value set at 500. The ethanol data was imported as CEL files into S+ArrayAnalyzerâ„¢ (version 2.1.1). Tools available in ArrayAnalyzer were used to assess data quality at the chip level. Background subtraction and summarization was done with RMA [Irizarry, 2003] and GCRMA, and the summarized data was quantile normalized [Bolstad, 2003]. RMA summarized data was filtered for log2 (RMA expression) >6 in at least six chips; GCRMA summarized data was filtered for log2 (GCRMA expression) >5. Each list was further filtered for a fold change in at least one pairwise comparison greater than 1.25. The Local Pooled Error (LPE T-test) [Jain, 2003] was used for differential expression testing across all possible pairwise timepoint comparisons. The False Discovery Rate (FDR) was controlled by implementation of the Benjamini and Hochberg correction [Benjamini, 1995]. Statistically significant genes (p<0.05) from the ten pairwise timepoint comparisons from both the RMA and GCRMA summarized data were combined into one list. A second list of significant genes was generated using the application, EDGE (Storey, 2007). RMA summarized data filtered for expression as above was used for input. The resulting list, ranked by Q-value, was filtered for a fold change in at least one pairwise comparison greater than 1.25.
## 3 GCOS report derived with TGT Value set at 500. The ethanol data was imported as CEL files into S+ArrayAnalyzerâ„¢ (version 2.1.1). Tools available in ArrayAnalyzer were used to assess data quality at the chip level. Background subtraction and summarization was done with RMA [Irizarry, 2003] and GCRMA, and the summarized data was quantile normalized [Bolstad, 2003]. RMA summarized data was filtered for log2 (RMA expression) >6 in at least six chips; GCRMA summarized data was filtered for log2 (GCRMA expression) >5. Each list was further filtered for a fold change in at least one pairwise comparison greater than 1.25. The Local Pooled Error (LPE T-test) [Jain, 2003] was used for differential expression testing across all possible pairwise timepoint comparisons. The False Discovery Rate (FDR) was controlled by implementation of the Benjamini and Hochberg correction [Benjamini, 1995]. Statistically significant genes (p<0.05) from the ten pairwise timepoint comparisons from both the RMA and GCRMA summarized data were combined into one list. A second list of significant genes was generated using the application, EDGE (Storey, 2007). RMA summarized data filtered for expression as above was used for input. The resulting list, ranked by Q-value, was filtered for a fold change in at least one pairwise comparison greater than 1.25.
## 4 GCOS report derived with TGT Value set at 500. The ethanol data was imported as CEL files into S+ArrayAnalyzerâ„¢ (version 2.1.1). Tools available in ArrayAnalyzer were used to assess data quality at the chip level. Background subtraction and summarization was done with RMA [Irizarry, 2003] and GCRMA, and the summarized data was quantile normalized [Bolstad, 2003]. RMA summarized data was filtered for log2 (RMA expression) >6 in at least six chips; GCRMA summarized data was filtered for log2 (GCRMA expression) >5. Each list was further filtered for a fold change in at least one pairwise comparison greater than 1.25. The Local Pooled Error (LPE T-test) [Jain, 2003] was used for differential expression testing across all possible pairwise timepoint comparisons. The False Discovery Rate (FDR) was controlled by implementation of the Benjamini and Hochberg correction [Benjamini, 1995]. Statistically significant genes (p<0.05) from the ten pairwise timepoint comparisons from both the RMA and GCRMA summarized data were combined into one list. A second list of significant genes was generated using the application, EDGE (Storey, 2007). RMA summarized data filtered for expression as above was used for input. The resulting list, ranked by Q-value, was filtered for a fold change in at least one pairwise comparison greater than 1.25.
## 5 GCOS report derived with TGT Value set at 500. The ethanol data was imported as CEL files into S+ArrayAnalyzerâ„¢ (version 2.1.1). Tools available in ArrayAnalyzer were used to assess data quality at the chip level. Background subtraction and summarization was done with RMA [Irizarry, 2003] and GCRMA, and the summarized data was quantile normalized [Bolstad, 2003]. RMA summarized data was filtered for log2 (RMA expression) >6 in at least six chips; GCRMA summarized data was filtered for log2 (GCRMA expression) >5. Each list was further filtered for a fold change in at least one pairwise comparison greater than 1.25. The Local Pooled Error (LPE T-test) [Jain, 2003] was used for differential expression testing across all possible pairwise timepoint comparisons. The False Discovery Rate (FDR) was controlled by implementation of the Benjamini and Hochberg correction [Benjamini, 1995]. Statistically significant genes (p<0.05) from the ten pairwise timepoint comparisons from both the RMA and GCRMA summarized data were combined into one list. A second list of significant genes was generated using the application, EDGE (Storey, 2007). RMA summarized data filtered for expression as above was used for input. The resulting list, ranked by Q-value, was filtered for a fold change in at least one pairwise comparison greater than 1.25.
## 6 GCOS report derived with TGT Value set at 500. The ethanol data was imported as CEL files into S+ArrayAnalyzerâ„¢ (version 2.1.1). Tools available in ArrayAnalyzer were used to assess data quality at the chip level. Background subtraction and summarization was done with RMA [Irizarry, 2003] and GCRMA, and the summarized data was quantile normalized [Bolstad, 2003]. RMA summarized data was filtered for log2 (RMA expression) >6 in at least six chips; GCRMA summarized data was filtered for log2 (GCRMA expression) >5. Each list was further filtered for a fold change in at least one pairwise comparison greater than 1.25. The Local Pooled Error (LPE T-test) [Jain, 2003] was used for differential expression testing across all possible pairwise timepoint comparisons. The False Discovery Rate (FDR) was controlled by implementation of the Benjamini and Hochberg correction [Benjamini, 1995]. Statistically significant genes (p<0.05) from the ten pairwise timepoint comparisons from both the RMA and GCRMA summarized data were combined into one list. A second list of significant genes was generated using the application, EDGE (Storey, 2007). RMA summarized data filtered for expression as above was used for input. The resulting list, ranked by Q-value, was filtered for a fold change in at least one pairwise comparison greater than 1.25.
## platform_id contact_name contact_email contact_phone
## 1 GPL570 Dennis,M,Burian dennis.burian@faa.gov 405-954-6087
## 2 GPL570 Dennis,M,Burian dennis.burian@faa.gov 405-954-6087
## 3 GPL570 Dennis,M,Burian dennis.burian@faa.gov 405-954-6087
## 4 GPL570 Dennis,M,Burian dennis.burian@faa.gov 405-954-6087
## 5 GPL570 Dennis,M,Burian dennis.burian@faa.gov 405-954-6087
## 6 GPL570 Dennis,M,Burian dennis.burian@faa.gov 405-954-6087
## contact_laboratory contact_department
## 1 Bioaeronautical Sciences Research Lab Aviation Medicine
## 2 Bioaeronautical Sciences Research Lab Aviation Medicine
## 3 Bioaeronautical Sciences Research Lab Aviation Medicine
## 4 Bioaeronautical Sciences Research Lab Aviation Medicine
## 5 Bioaeronautical Sciences Research Lab Aviation Medicine
## 6 Bioaeronautical Sciences Research Lab Aviation Medicine
## contact_institute contact_address
## 1 Federal Aviation Administration 6500 S. MacArthur Blvd., AAM610
## 2 Federal Aviation Administration 6500 S. MacArthur Blvd., AAM610
## 3 Federal Aviation Administration 6500 S. MacArthur Blvd., AAM610
## 4 Federal Aviation Administration 6500 S. MacArthur Blvd., AAM610
## 5 Federal Aviation Administration 6500 S. MacArthur Blvd., AAM610
## 6 Federal Aviation Administration 6500 S. MacArthur Blvd., AAM610
## contact_city contact_state contact_zip.postal_code contact_country
## 1 Oklahoma City OK 73169 USA
## 2 Oklahoma City OK 73169 USA
## 3 Oklahoma City OK 73169 USA
## 4 Oklahoma City OK 73169 USA
## 5 Oklahoma City OK 73169 USA
## 6 Oklahoma City OK 73169 USA
## supplementary_file
## 1 ftp://ftp.ncbi.nlm.nih.gov/geo/samples/GSM514nnn/GSM514737/suppl/GSM514737.CEL.gz
## 2 ftp://ftp.ncbi.nlm.nih.gov/geo/samples/GSM514nnn/GSM514738/suppl/GSM514738.CEL.gz
## 3 ftp://ftp.ncbi.nlm.nih.gov/geo/samples/GSM514nnn/GSM514739/suppl/GSM514739.CEL.gz
## 4 ftp://ftp.ncbi.nlm.nih.gov/geo/samples/GSM514nnn/GSM514740/suppl/GSM514740.CEL.gz
## 5 ftp://ftp.ncbi.nlm.nih.gov/geo/samples/GSM514nnn/GSM514741/suppl/GSM514741.CEL.gz
## 6 ftp://ftp.ncbi.nlm.nih.gov/geo/samples/GSM514nnn/GSM514742/suppl/GSM514742.CEL.gz
## data_row_count gender.ch1 intervention.ch1 tissue.ch1
## 1 54675 male BAC 0% whole blood
## 2 54675 male BAC 0.04%rising whole blood
## 3 54675 male BAC 0.08% whole blood
## 4 54675 male BAC 0.04%declining whole blood
## 5 54675 male BAC 0.02%declining whole blood
## 6 54675 male BAC 0% whole blood
class(dataku)
## [1] "data.frame"
summary(dataku)
## sample X216671_x_at X1562738_a_at X1565866_a_at
## GSM514737: 1 Min. : 4.025 Min. :3.094 Min. : 4.569
## GSM514738: 1 1st Qu.: 5.817 1st Qu.:3.514 1st Qu.: 5.103
## GSM514739: 1 Median :10.975 Median :3.884 Median : 5.620
## GSM514740: 1 Mean : 8.700 Mean :5.656 Mean : 7.533
## GSM514741: 1 3rd Qu.:11.361 3rd Qu.:8.148 3rd Qu.:10.312
## GSM514742: 1 Max. :11.620 Max. :8.529 Max. :10.522
## (Other) :48
## X221057_at X213964_x_at X230156_x_at X1553113_s_at
## Min. :3.796 Min. : 3.798 Min. : 3.190 Min. :3.349
## 1st Qu.:4.291 1st Qu.: 4.388 1st Qu.: 3.923 1st Qu.:3.719
## Median :4.688 Median : 4.617 Median : 4.164 Median :4.163
## Mean :6.435 Mean : 7.171 Mean : 6.635 Mean :6.243
## 3rd Qu.:8.910 3rd Qu.:10.475 3rd Qu.: 9.877 3rd Qu.:9.132
## Max. :9.383 Max. :10.738 Max. :10.440 Max. :9.522
##
## X226746_s_at X235547_at X214384_s_at X212768_s_at
## Min. : 5.674 Min. : 3.687 Min. : 4.256 Min. : 3.370
## 1st Qu.: 6.192 1st Qu.: 4.384 1st Qu.: 4.844 1st Qu.: 4.705
## Median : 6.670 Median : 4.873 Median : 5.366 Median : 5.811
## Mean : 8.312 Mean : 6.801 Mean : 7.195 Mean : 6.724
## 3rd Qu.:10.691 3rd Qu.: 9.562 3rd Qu.: 9.900 3rd Qu.: 9.641
## Max. :11.006 Max. :10.034 Max. :10.292 Max. :10.435
##
## X213684_s_at X242497_at X230790_x_at X217494_s_at
## Min. :3.767 Min. : 6.463 Min. : 5.159 Min. :4.025
## 1st Qu.:4.205 1st Qu.: 7.030 1st Qu.: 5.572 1st Qu.:4.510
## Median :4.736 Median : 7.334 Median : 6.589 Median :4.913
## Mean :6.498 Mean : 9.142 Mean : 8.584 Mean :6.580
## 3rd Qu.:9.048 3rd Qu.:11.652 3rd Qu.:11.926 3rd Qu.:8.970
## Max. :9.701 Max. :11.936 Max. :12.120 Max. :9.225
##
## X238992_at X213817_at X208325_s_at X226836_at
## Min. :3.448 Min. : 4.535 Min. : 6.141 Min. : 5.529
## 1st Qu.:3.901 1st Qu.: 5.439 1st Qu.: 7.244 1st Qu.: 6.266
## Median :4.213 Median : 6.566 Median : 7.786 Median : 6.676
## Mean :6.417 Mean : 7.659 Mean : 9.364 Mean : 8.494
## 3rd Qu.:9.379 3rd Qu.:10.052 3rd Qu.:11.801 3rd Qu.:11.093
## Max. :9.857 Max. :10.565 Max. :12.307 Max. :11.420
##
## X224673_at X228985_at X225830_at X214683_s_at
## Min. : 7.102 Min. : 4.601 Min. :4.116 Min. : 5.651
## 1st Qu.: 7.511 1st Qu.: 5.078 1st Qu.:4.528 1st Qu.: 6.753
## Median : 7.857 Median : 5.540 Median :5.037 Median : 7.657
## Mean : 9.670 Mean : 7.545 Mean :6.748 Mean : 8.770
## 3rd Qu.:12.107 3rd Qu.:10.353 3rd Qu.:9.272 3rd Qu.:11.145
## Max. :12.528 Max. :10.798 Max. :9.634 Max. :11.564
##
## X230559_x_at X225537_at X203634_s_at X228324_at
## Min. :3.290 Min. : 4.930 Min. :4.076 Min. :3.834
## 1st Qu.:3.784 1st Qu.: 5.610 1st Qu.:4.328 1st Qu.:4.259
## Median :4.424 Median : 6.176 Median :4.852 Median :5.064
## Mean :6.177 Mean : 7.695 Mean :6.421 Mean :6.487
## 3rd Qu.:8.801 3rd Qu.:10.128 3rd Qu.:8.828 3rd Qu.:8.879
## Max. :9.207 Max. :10.459 Max. :9.566 Max. :9.682
##
## X1553749_at X234464_s_at X1554704_at X240050_s_at
## Min. :3.151 Min. : 5.020 Min. : 4.488 Min. :3.353
## 1st Qu.:3.602 1st Qu.: 5.614 1st Qu.: 4.873 1st Qu.:3.725
## Median :3.894 Median : 6.117 Median : 5.223 Median :3.934
## Mean :6.008 Mean : 7.833 Mean : 7.416 Mean :6.302
## 3rd Qu.:8.716 3rd Qu.:10.304 3rd Qu.:10.309 3rd Qu.:9.196
## Max. :9.407 Max. :10.760 Max. :11.236 Max. :9.936
##
## X1559129_a_at X227310_at X217547_x_at X214395_x_at
## Min. : 4.710 Min. :3.343 Min. :3.165 Min. : 5.637
## 1st Qu.: 5.173 1st Qu.:3.809 1st Qu.:3.547 1st Qu.: 6.444
## Median : 5.504 Median :4.060 Median :3.912 Median : 7.142
## Mean : 7.867 Mean :5.900 Mean :5.774 Mean : 9.368
## 3rd Qu.:10.988 3rd Qu.:8.328 3rd Qu.:8.376 3rd Qu.:12.759
## Max. :11.350 Max. :8.603 Max. :9.168 Max. :13.145
##
## X219599_at X201437_s_at X231035_s_at X208939_at
## Min. : 6.329 Min. : 4.309 Min. : 6.384 Min. : 4.880
## 1st Qu.: 7.118 1st Qu.: 4.854 1st Qu.: 6.845 1st Qu.: 5.464
## Median : 8.044 Median : 5.700 Median : 7.419 Median : 6.079
## Mean : 9.278 Mean : 7.567 Mean : 9.166 Mean : 7.661
## 3rd Qu.:11.680 3rd Qu.:10.538 3rd Qu.:11.758 3rd Qu.:10.086
## Max. :12.005 Max. :11.194 Max. :12.019 Max. :10.346
##
## X226099_at X230126_s_at X231548_at X214052_x_at
## Min. : 3.761 Min. : 4.841 Min. : 5.739 Min. : 4.715
## 1st Qu.: 4.309 1st Qu.: 5.482 1st Qu.: 6.337 1st Qu.: 5.415
## Median : 4.920 Median : 6.296 Median : 6.721 Median : 6.250
## Mean : 6.724 Mean : 8.066 Mean : 8.915 Mean : 7.777
## 3rd Qu.: 9.513 3rd Qu.:11.001 3rd Qu.:11.921 3rd Qu.:10.411
## Max. :10.132 Max. :11.367 Max. :12.323 Max. :10.867
##
## X213582_at X216563_at X241621_at X211074_at
## Min. : 5.162 Min. : 3.228 Min. :3.460 Min. : 4.254
## 1st Qu.: 5.674 1st Qu.: 4.117 1st Qu.:3.745 1st Qu.: 6.006
## Median : 6.397 Median : 4.780 Median :4.036 Median : 9.860
## Mean : 8.062 Mean : 6.613 Mean :6.180 Mean : 8.888
## 3rd Qu.:10.726 3rd Qu.: 9.349 3rd Qu.:9.029 3rd Qu.:12.025
## Max. :10.903 Max. :10.106 Max. :9.463 Max. :12.616
##
## X212477_at X227553_at X224321_at X230699_at
## Min. :3.882 Min. : 5.301 Min. : 6.303 Min. : 4.969
## 1st Qu.:4.392 1st Qu.: 5.588 1st Qu.: 7.172 1st Qu.: 5.499
## Median :4.678 Median : 6.011 Median : 8.236 Median : 5.920
## Mean :6.591 Mean : 8.044 Mean :10.035 Mean : 7.776
## 3rd Qu.:9.175 3rd Qu.:10.764 3rd Qu.:13.312 3rd Qu.:10.334
## Max. :9.533 Max. :11.274 Max. :13.514 Max. :10.913
##
## X1554283_at X213552_at X202318_s_at X232125_at
## Min. :3.693 Min. :3.685 Min. : 4.993 Min. :3.178
## 1st Qu.:4.015 1st Qu.:4.203 1st Qu.: 5.813 1st Qu.:3.883
## Median :4.383 Median :4.554 Median : 6.642 Median :4.542
## Mean :6.184 Mean :6.316 Mean : 7.900 Mean :6.133
## 3rd Qu.:8.662 3rd Qu.:8.705 3rd Qu.:10.214 3rd Qu.:8.694
## Max. :9.183 Max. :9.369 Max. :10.571 Max. :9.539
##
## X62987_r_at X231951_at X210007_s_at X1563498_s_at
## Min. : 6.422 Min. :3.160 Min. :4.089 Min. :3.561
## 1st Qu.: 7.166 1st Qu.:4.139 1st Qu.:4.606 1st Qu.:4.228
## Median :11.414 Median :9.188 Median :5.053 Median :4.642
## Mean : 9.543 Mean :6.999 Mean :6.719 Mean :6.370
## 3rd Qu.:11.689 3rd Qu.:9.535 3rd Qu.:9.110 3rd Qu.:8.822
## Max. :11.851 Max. :9.885 Max. :9.399 Max. :9.266
##
## X228193_s_at X242685_at X227244_s_at X220132_s_at
## Min. : 4.211 Min. :3.005 Min. : 4.307 Min. : 3.959
## 1st Qu.: 4.997 1st Qu.:3.419 1st Qu.: 5.112 1st Qu.: 4.929
## Median : 5.583 Median :3.724 Median : 5.463 Median : 5.616
## Mean : 7.247 Mean :5.564 Mean : 7.370 Mean : 7.263
## 3rd Qu.: 9.833 3rd Qu.:8.055 3rd Qu.: 9.938 3rd Qu.: 9.888
## Max. :10.180 Max. :8.562 Max. :10.385 Max. :10.776
##
## X213951_s_at X213826_s_at X1552980_at X213831_at
## Min. : 5.801 Min. : 6.537 Min. : 4.864 Min. : 2.822
## 1st Qu.: 6.425 1st Qu.: 7.093 1st Qu.: 5.343 1st Qu.: 3.631
## Median : 7.087 Median : 7.870 Median : 5.669 Median : 5.173
## Mean : 8.916 Mean : 9.398 Mean : 7.783 Mean : 6.758
## 3rd Qu.:11.712 3rd Qu.:11.974 3rd Qu.:10.651 3rd Qu.: 9.696
## Max. :11.914 Max. :12.190 Max. :10.882 Max. :10.963
##
## X209480_at X209728_at X221919_at X209657_s_at
## Min. : 3.829 Min. : 4.146 Min. : 5.003 Min. :4.111
## 1st Qu.: 4.106 1st Qu.: 5.557 1st Qu.: 5.510 1st Qu.:5.107
## Median : 5.154 Median :10.193 Median : 5.819 Median :5.615
## Mean : 6.497 Mean : 9.003 Mean : 7.846 Mean :7.175
## 3rd Qu.: 8.680 3rd Qu.:10.801 3rd Qu.:10.481 3rd Qu.:9.641
## Max. :10.543 Max. :11.640 Max. :11.377 Max. :9.983
##
## X228520_s_at X206638_at X1558700_s_at X200602_at
## Min. : 5.603 Min. :3.652 Min. :4.013 Min. : 4.525
## 1st Qu.: 6.284 1st Qu.:4.129 1st Qu.:4.492 1st Qu.: 5.205
## Median : 7.987 Median :4.668 Median :5.095 Median : 5.958
## Mean : 9.350 Mean :6.308 Mean :6.814 Mean : 7.354
## 3rd Qu.:12.688 3rd Qu.:8.744 3rd Qu.:9.470 3rd Qu.: 9.795
## Max. :12.931 Max. :9.183 Max. :9.855 Max. :10.600
##
## X207688_s_at X214723_x_at X231735_s_at X1562364_at
## Min. : 4.676 Min. :3.462 Min. : 7.652 Min. : 4.990
## 1st Qu.: 5.629 1st Qu.:4.168 1st Qu.: 8.819 1st Qu.: 5.340
## Median : 6.494 Median :4.608 Median :10.354 Median : 5.798
## Mean : 8.225 Mean :6.646 Mean :11.464 Mean : 7.706
## 3rd Qu.:11.194 3rd Qu.:9.442 3rd Qu.:14.413 3rd Qu.:10.384
## Max. :11.477 Max. :9.728 Max. :14.528 Max. :10.794
##
## X1554597_at X206123_at X1562481_at X232197_x_at
## Min. : 6.068 Min. :3.649 Min. :3.702 Min. :3.100
## 1st Qu.: 6.454 1st Qu.:4.767 1st Qu.:4.124 1st Qu.:3.365
## Median : 6.869 Median :9.116 Median :4.464 Median :3.787
## Mean : 8.753 Mean :7.267 Mean :6.249 Mean :5.526
## 3rd Qu.:11.386 3rd Qu.:9.581 3rd Qu.:8.636 3rd Qu.:7.947
## Max. :11.829 Max. :9.958 Max. :9.216 Max. :8.604
##
## X228938_at X214057_at X1560145_at X221589_s_at
## Min. : 5.684 Min. : 6.963 Min. : 5.792 Min. :3.939
## 1st Qu.: 5.929 1st Qu.: 7.396 1st Qu.: 6.315 1st Qu.:4.578
## Median : 6.368 Median : 8.096 Median : 6.929 Median :4.984
## Mean : 8.038 Mean : 9.824 Mean : 8.613 Mean :6.778
## 3rd Qu.:10.458 3rd Qu.:12.555 3rd Qu.:11.245 3rd Qu.:9.277
## Max. :10.794 Max. :12.713 Max. :11.575 Max. :9.862
##
## X232001_at X229543_at X1558688_at X1553575_at
## Min. : 6.626 Min. :3.675 Min. : 3.132 Min. : 7.148
## 1st Qu.: 7.174 1st Qu.:4.111 1st Qu.: 3.819 1st Qu.: 7.880
## Median : 8.468 Median :4.650 Median :12.651 Median : 8.979
## Mean : 9.511 Mean :6.373 Mean : 8.693 Mean :10.231
## 3rd Qu.:12.045 3rd Qu.:8.883 3rd Qu.:12.856 3rd Qu.:12.780
## Max. :12.315 Max. :9.954 Max. :13.090 Max. :13.133
##
## X228933_at X229143_at X229204_at X209525_at
## Min. :3.944 Min. :4.115 Min. : 6.601 Min. : 4.091
## 1st Qu.:4.423 1st Qu.:4.564 1st Qu.: 7.305 1st Qu.: 4.616
## Median :4.680 Median :4.831 Median : 8.237 Median : 5.443
## Mean :6.122 Mean :6.673 Mean : 9.519 Mean : 7.171
## 3rd Qu.:8.845 3rd Qu.:9.109 3rd Qu.:11.919 3rd Qu.: 9.899
## Max. :9.453 Max. :9.974 Max. :12.207 Max. :10.354
##
## X222968_at X222487_s_at X230535_s_at X239133_at
## Min. : 5.215 Min. : 3.883 Min. : 5.175 Min. : 4.743
## 1st Qu.: 5.627 1st Qu.: 4.529 1st Qu.: 5.792 1st Qu.: 5.542
## Median : 6.195 Median : 4.951 Median : 6.296 Median : 6.259
## Mean : 7.912 Mean : 6.743 Mean : 7.935 Mean : 7.856
## 3rd Qu.:10.448 3rd Qu.: 9.116 3rd Qu.:10.400 3rd Qu.:10.455
## Max. :10.898 Max. :11.162 Max. :11.378 Max. :10.809
##
## X213868_s_at X225207_at X214163_at X1555247_a_at
## Min. : 5.444 Min. : 4.038 Min. :3.642 Min. : 5.108
## 1st Qu.: 6.098 1st Qu.: 4.640 1st Qu.:4.047 1st Qu.: 5.594
## Median : 6.532 Median : 6.015 Median :4.507 Median : 6.101
## Mean : 8.428 Mean : 7.100 Mean :6.161 Mean : 8.158
## 3rd Qu.:11.078 3rd Qu.: 9.664 3rd Qu.:8.575 3rd Qu.:11.013
## Max. :11.505 Max. :10.462 Max. :9.075 Max. :11.355
##
## X217383_at X218984_at X221986_s_at X229589_x_at
## Min. : 5.228 Min. : 3.878 Min. : 3.803 Min. :3.001
## 1st Qu.: 5.731 1st Qu.: 4.853 1st Qu.: 4.720 1st Qu.:3.216
## Median : 6.322 Median : 5.364 Median : 5.524 Median :3.441
## Mean : 7.984 Mean : 7.043 Mean : 6.975 Mean :5.515
## 3rd Qu.:10.501 3rd Qu.: 9.549 3rd Qu.: 9.467 3rd Qu.:8.167
## Max. :10.850 Max. :10.087 Max. :10.093 Max. :8.863
##
## X219433_at X225934_at X229399_at X236026_at
## Min. : 4.473 Min. : 5.125 Min. :3.180 Min. :3.678
## 1st Qu.: 5.199 1st Qu.: 5.465 1st Qu.:3.575 1st Qu.:4.101
## Median : 5.525 Median : 5.826 Median :4.096 Median :4.352
## Mean : 7.291 Mean : 7.656 Mean :6.377 Mean :6.353
## 3rd Qu.: 9.736 3rd Qu.:10.061 3rd Qu.:9.544 3rd Qu.:8.921
## Max. :10.464 Max. :10.582 Max. :9.874 Max. :9.514
##
## X224037_at X1569105_at X231500_s_at X206500_s_at
## Min. :3.647 Min. : 6.068 Min. : 4.370 Min. : 4.152
## 1st Qu.:3.924 1st Qu.: 6.582 1st Qu.: 4.665 1st Qu.: 4.572
## Median :4.431 Median :10.826 Median : 4.899 Median : 5.244
## Mean :6.266 Mean : 9.072 Mean : 7.717 Mean : 6.988
## 3rd Qu.:8.762 3rd Qu.:11.247 3rd Qu.:11.290 3rd Qu.: 9.678
## Max. :9.397 Max. :11.799 Max. :11.630 Max. :10.177
##
## X230683_at X233191_at X1557066_at X241631_at
## Min. : 5.226 Min. :3.106 Min. : 3.427 Min. : 4.141
## 1st Qu.: 5.711 1st Qu.:3.935 1st Qu.: 3.865 1st Qu.: 4.949
## Median : 6.087 Median :4.388 Median : 4.167 Median : 6.486
## Mean : 7.881 Mean :6.478 Mean : 6.625 Mean : 7.745
## 3rd Qu.:10.429 3rd Qu.:9.459 3rd Qu.: 9.727 3rd Qu.:10.707
## Max. :10.920 Max. :9.748 Max. :10.364 Max. :11.433
##
## X221645_s_at X222811_at X239146_at X228309_at
## Min. : 5.093 Min. : 4.218 Min. : 4.175 Min. : 6.275
## 1st Qu.: 5.656 1st Qu.: 5.026 1st Qu.: 4.739 1st Qu.: 6.819
## Median : 6.305 Median : 6.185 Median : 5.269 Median : 7.214
## Mean : 7.810 Mean : 7.186 Mean : 6.934 Mean : 9.065
## 3rd Qu.:10.162 3rd Qu.: 9.500 3rd Qu.: 9.321 3rd Qu.:11.653
## Max. :10.806 Max. :10.002 Max. :10.239 Max. :12.037
##
## X228751_at X225726_s_at X226164_x_at X224308_s_at
## Min. : 4.229 Min. : 4.159 Min. :3.238 Min. : 4.979
## 1st Qu.: 4.805 1st Qu.: 4.496 1st Qu.:3.971 1st Qu.: 5.345
## Median : 5.255 Median : 5.050 Median :4.375 Median : 5.904
## Mean : 7.607 Mean : 6.990 Mean :6.091 Mean : 7.485
## 3rd Qu.:10.766 3rd Qu.: 9.798 3rd Qu.:8.492 3rd Qu.: 9.870
## Max. :11.448 Max. :10.380 Max. :9.118 Max. :10.582
##
## X231193_s_at X1558956_s_at X1552480_s_at X240990_at
## Min. : 4.253 Min. :3.608 Min. :3.057 Min. :3.311
## 1st Qu.: 4.871 1st Qu.:4.070 1st Qu.:3.504 1st Qu.:3.683
## Median : 5.271 Median :4.489 Median :4.004 Median :4.055
## Mean : 7.124 Mean :6.266 Mean :5.819 Mean :5.840
## 3rd Qu.: 9.734 3rd Qu.:8.705 3rd Qu.:8.496 3rd Qu.:8.264
## Max. :10.101 Max. :9.470 Max. :9.016 Max. :8.873
##
## X1567457_at X235511_at X214000_s_at X213409_s_at
## Min. :3.003 Min. :4.264 Min. : 6.209 Min. :3.779
## 1st Qu.:3.482 1st Qu.:4.694 1st Qu.: 6.520 1st Qu.:3.935
## Median :4.013 Median :5.049 Median : 7.006 Median :4.405
## Mean :6.039 Mean :6.822 Mean : 8.914 Mean :6.330
## 3rd Qu.:8.989 3rd Qu.:9.237 3rd Qu.:11.563 3rd Qu.:8.982
## Max. :9.165 Max. :9.804 Max. :11.854 Max. :9.511
##
## X236223_s_at X214041_x_at X200908_s_at X214001_x_at
## Min. : 4.308 Min. : 6.671 Min. : 6.063 Min. : 6.388
## 1st Qu.: 5.249 1st Qu.: 7.397 1st Qu.: 6.994 1st Qu.: 6.904
## Median : 6.504 Median : 9.113 Median : 7.550 Median : 7.809
## Mean : 7.615 Mean : 9.948 Mean : 9.868 Mean : 9.941
## 3rd Qu.:10.143 3rd Qu.:12.590 3rd Qu.:13.159 3rd Qu.:13.331
## Max. :10.722 Max. :12.913 Max. :13.427 Max. :13.920
##
## X213350_at X1568012_at X214370_at X234947_s_at
## Min. : 7.596 Min. :2.709 Min. : 5.927 Min. : 4.081
## 1st Qu.: 8.845 1st Qu.:3.178 1st Qu.: 6.755 1st Qu.: 4.818
## Median :11.210 Median :3.355 Median : 8.074 Median : 5.680
## Mean :11.279 Mean :5.368 Mean : 9.901 Mean : 7.395
## 3rd Qu.:13.834 3rd Qu.:7.923 3rd Qu.:13.204 3rd Qu.:10.300
## Max. :14.020 Max. :8.462 Max. :13.577 Max. :10.760
##
## X237444_at X224974_at X219972_s_at X224873_s_at
## Min. : 4.052 Min. : 4.555 Min. :3.799 Min. : 4.258
## 1st Qu.: 5.029 1st Qu.: 5.118 1st Qu.:4.072 1st Qu.: 4.921
## Median : 5.956 Median : 6.215 Median :4.447 Median : 5.363
## Mean : 7.738 Mean : 8.114 Mean :6.236 Mean : 7.429
## 3rd Qu.:10.749 3rd Qu.:11.420 3rd Qu.:8.589 3rd Qu.:10.360
## Max. :11.468 Max. :11.778 Max. :9.043 Max. :10.530
##
## X217257_at X232371_at X223292_s_at X215450_at
## Min. : 5.232 Min. : 5.123 Min. :3.544 Min. : 4.253
## 1st Qu.: 5.784 1st Qu.: 5.685 1st Qu.:4.096 1st Qu.: 4.724
## Median : 6.352 Median : 6.318 Median :4.538 Median : 5.120
## Mean : 8.021 Mean : 7.818 Mean :6.416 Mean : 7.434
## 3rd Qu.:10.557 3rd Qu.:10.212 3rd Qu.:9.054 3rd Qu.:10.444
## Max. :10.889 Max. :10.655 Max. :9.452 Max. :11.432
##
## X217644_s_at X217040_x_at X209340_at X226765_at
## Min. : 4.385 Min. : 5.114 Min. :4.375 Min. : 4.478
## 1st Qu.: 5.090 1st Qu.: 5.525 1st Qu.:4.974 1st Qu.: 5.142
## Median : 5.613 Median : 9.678 Median :5.526 Median : 6.061
## Mean : 7.624 Mean : 7.911 Mean :7.143 Mean : 8.152
## 3rd Qu.:10.522 3rd Qu.:10.007 3rd Qu.:9.616 3rd Qu.:11.388
## Max. :10.863 Max. :10.301 Max. :9.918 Max. :11.830
##
## X209358_at X215220_s_at X203983_at X216609_at
## Min. : 4.906 Min. :3.554 Min. : 6.043 Min. : 4.565
## 1st Qu.: 5.334 1st Qu.:3.760 1st Qu.: 6.525 1st Qu.: 5.278
## Median : 6.164 Median :4.003 Median : 7.371 Median : 6.116
## Mean : 7.495 Mean :6.048 Mean : 8.985 Mean : 7.746
## 3rd Qu.: 9.917 3rd Qu.:8.591 3rd Qu.:11.642 3rd Qu.:10.454
## Max. :10.421 Max. :9.200 Max. :11.931 Max. :11.029
##
## X1556204_a_at X226637_at X229123_at X219303_at
## Min. :4.156 Min. : 3.805 Min. : 4.332 Min. : 4.329
## 1st Qu.:4.677 1st Qu.: 4.425 1st Qu.: 5.115 1st Qu.: 5.121
## Median :5.187 Median : 5.075 Median : 5.967 Median : 5.612
## Mean :6.881 Mean : 7.147 Mean : 7.272 Mean : 7.268
## 3rd Qu.:9.395 3rd Qu.:10.143 3rd Qu.: 9.707 3rd Qu.: 9.708
## Max. :9.753 Max. :10.786 Max. :10.095 Max. :10.384
##
## X218195_at X209972_s_at X222837_s_at X227528_s_at
## Min. : 4.851 Min. : 6.783 Min. :3.367 Min. : 6.166
## 1st Qu.: 5.393 1st Qu.: 7.212 1st Qu.:3.984 1st Qu.: 6.839
## Median : 6.481 Median : 7.715 Median :4.652 Median : 7.214
## Mean : 7.674 Mean : 9.517 Mean :6.315 Mean : 8.948
## 3rd Qu.:10.133 3rd Qu.:12.109 3rd Qu.:8.866 3rd Qu.:11.466
## Max. :10.700 Max. :12.629 Max. :9.249 Max. :11.909
##
## X224953_at X231697_s_at X210596_at X235114_x_at
## Min. : 4.776 Min. : 4.992 Min. : 6.467 Min. :4.074
## 1st Qu.: 5.503 1st Qu.: 5.591 1st Qu.: 6.880 1st Qu.:4.599
## Median : 6.118 Median : 6.155 Median : 7.547 Median :5.070
## Mean : 7.723 Mean : 8.095 Mean : 9.180 Mean :6.682
## 3rd Qu.:10.233 3rd Qu.:10.909 3rd Qu.:11.674 3rd Qu.:9.070
## Max. :10.586 Max. :11.383 Max. :12.164 Max. :9.751
##
## X226344_at X213251_at X229787_s_at X60815_at
## Min. : 4.128 Min. : 5.900 Min. : 4.864 Min. :4.545
## 1st Qu.: 4.620 1st Qu.: 6.665 1st Qu.: 6.084 1st Qu.:4.916
## Median : 5.052 Median : 7.792 Median : 7.132 Median :5.460
## Mean : 6.743 Mean : 8.796 Mean : 8.572 Mean :7.028
## 3rd Qu.: 9.234 3rd Qu.:11.219 3rd Qu.:11.517 3rd Qu.:9.405
## Max. :10.262 Max. :11.541 Max. :11.780 Max. :9.849
##
## X205063_at X226014_at X201936_s_at X227900_at
## Min. :2.927 Min. : 5.371 Min. : 5.144 Min. : 4.250
## 1st Qu.:3.301 1st Qu.: 6.060 1st Qu.: 5.559 1st Qu.: 4.999
## Median :3.719 Median : 6.411 Median : 5.910 Median : 5.564
## Mean :5.532 Mean : 8.942 Mean : 7.869 Mean : 7.192
## 3rd Qu.:8.146 3rd Qu.:12.196 3rd Qu.:10.499 3rd Qu.: 9.648
## Max. :8.485 Max. :12.487 Max. :10.810 Max. :10.224
##
## X217654_at X213226_at X214149_s_at X219138_at
## Min. : 4.433 Min. :3.908 Min. : 6.009 Min. : 6.130
## 1st Qu.: 5.892 1st Qu.:4.200 1st Qu.: 6.769 1st Qu.: 6.635
## Median : 6.384 Median :4.674 Median : 8.071 Median : 7.164
## Mean : 8.155 Mean :6.405 Mean : 9.779 Mean : 9.377
## 3rd Qu.:10.899 3rd Qu.:8.788 3rd Qu.:13.049 3rd Qu.:12.481
## Max. :11.563 Max. :9.792 Max. :13.237 Max. :12.752
##
## X239960_x_at X209258_s_at X230003_at X228416_at
## Min. :4.201 Min. : 3.874 Min. : 3.794 Min. : 3.712
## 1st Qu.:4.712 1st Qu.: 4.527 1st Qu.: 4.424 1st Qu.: 4.072
## Median :5.004 Median : 5.028 Median : 5.014 Median : 4.353
## Mean :6.783 Mean : 7.251 Mean : 6.714 Mean : 6.735
## 3rd Qu.:9.218 3rd Qu.:10.345 3rd Qu.: 9.304 3rd Qu.: 9.737
## Max. :9.705 Max. :10.677 Max. :10.360 Max. :10.233
##
## X213742_at X231418_at X204349_at X202984_s_at
## Min. : 5.723 Min. : 5.785 Min. :3.487 Min. : 3.564
## 1st Qu.: 6.357 1st Qu.: 6.377 1st Qu.:3.762 1st Qu.: 4.556
## Median : 7.405 Median : 6.905 Median :4.139 Median : 5.417
## Mean : 8.605 Mean : 8.713 Mean :6.073 Mean : 7.041
## 3rd Qu.:10.967 3rd Qu.:11.342 3rd Qu.:8.602 3rd Qu.: 9.879
## Max. :11.477 Max. :12.072 Max. :9.628 Max. :10.330
##
## X226404_at X209700_x_at X209795_at X203493_s_at
## Min. :4.029 Min. :3.020 Min. : 3.262 Min. :3.690
## 1st Qu.:4.695 1st Qu.:3.477 1st Qu.: 3.980 1st Qu.:4.131
## Median :4.998 Median :3.688 Median : 5.061 Median :4.674
## Mean :6.920 Mean :5.563 Mean : 6.435 Mean :6.349
## 3rd Qu.:9.476 3rd Qu.:7.977 3rd Qu.: 9.072 3rd Qu.:8.924
## Max. :9.986 Max. :9.004 Max. :10.062 Max. :9.471
##
## X204075_s_at X203603_s_at X204291_at X236314_at
## Min. :3.736 Min. : 4.775 Min. :3.366 Min. : 4.795
## 1st Qu.:4.422 1st Qu.: 5.437 1st Qu.:4.026 1st Qu.: 5.601
## Median :4.761 Median : 6.229 Median :4.640 Median : 5.987
## Mean :6.698 Mean : 7.764 Mean :6.468 Mean : 7.801
## 3rd Qu.:9.434 3rd Qu.:10.383 3rd Qu.:9.234 3rd Qu.:10.390
## Max. :9.714 Max. :10.890 Max. :9.699 Max. :10.769
##
## X238653_at X1555884_at X1565823_at
## Min. : 5.004 Min. :2.732 Min. : 4.104
## 1st Qu.: 5.690 1st Qu.:3.083 1st Qu.: 4.374
## Median : 6.211 Median :3.368 Median : 4.944
## Mean : 7.750 Mean :5.212 Mean : 7.090
## 3rd Qu.:10.065 3rd Qu.:7.686 3rd Qu.:10.142
## Max. :10.531 Max. :8.253 Max. :10.805
##
## title geo_accession status
## Blood_alcohol_T1_S13: 1 GSM514737: 1 Public on Jul 25 2013:54
## Blood_alcohol_T1_S15: 1 GSM514738: 1
## Blood_alcohol_T1_S17: 1 GSM514739: 1
## Blood_alcohol_T1_S18: 1 GSM514740: 1
## Blood_alcohol_T1_S19: 1 GSM514741: 1
## Blood_alcohol_T1_S8 : 1 GSM514742: 1
## (Other) :48 (Other) :48
## submission_date last_update_date type channel_count
## Feb 23 2010:54 Apr 29 2015:54 RNA:54 Min. :1
## 1st Qu.:1
## Median :1
## Mean :1
## 3rd Qu.:1
## Max. :1
##
## source_name_ch1 organism_ch1
## whole blood, BAC 0% : 6 Homo sapiens:54
## whole blood, BAC 0.02%declining: 6
## whole blood, BAC 0.04%rising : 6
## whole blood, BAC 0.08% : 6
## whole blood, BAC 0.04%declining: 5
## whole blood, OJ time 1 : 5
## (Other) :20
## characteristics_ch1 characteristics_ch1.1
## gender: male:54 tissue: whole blood:54
##
##
##
##
##
##
## characteristics_ch1.2
## intervention: BAC 0% : 6
## intervention: BAC 0.02%declining: 6
## intervention: BAC 0.04%rising : 6
## intervention: BAC 0.08% : 6
## intervention: BAC 0.04%declining: 5
## intervention: OJ time 1 : 5
## (Other) :20
## treatment_protocol_ch1 molecule_ch1
## Blood was pulled directly into Paxgene tubes:54 total RNA:54
##
##
##
##
##
##
## extract_protocol_ch1
## Total RNA was extracted using the protocol provided with the Paxgene tubeswith the optional on-column DNase treatment:54
##
##
##
##
##
##
## label_ch1
## biotin:54
##
##
##
##
##
##
## label_protocol_ch1
## For the OJcontrol samples 50 ng total RNA was both reverse transcribed and amplified using the Ovation RNA amplification System V2 (Nugen Technologies). Microarray template material was fragmented and biotin labeled using the FL-Ovation cDNA Biotin Module V2 (Nugen Technologies, Inc.). For the alcohol experimental samples 50 ng total RNA was reverse transcribed and amplified using the 3' IVT one-cycle kit (Affymetrix), fragmented and biotin labeled using the GeneChip IVT labeling kit (Affymetrix).:54
##
##
##
##
##
##
## taxid_ch1
## Min. :9606
## 1st Qu.:9606
## Median :9606
## Mean :9606
## 3rd Qu.:9606
## Max. :9606
##
## hyb_protocol
## Arrays were hybridized for 18 hours at 45 deg C at 60 rpm in a GeneChip Hybridization Oven model 640 (Affymetric, Inc.). Fluidics protocol FS450_0004 was used with the GeneChip Fluidics Station model 450 to wash the arrays.:54
##
##
##
##
##
##
## scan_protocol
## Scanning done on a GeneChip Laser Scanner model 3000 with system running GCOS version 1.4.:54
##
##
##
##
##
##
## description
## 08CHT051T1.CEL: 1
## 08CHT051T2.CEL: 1
## 08CHT051T3.CEL: 1
## 08CHT051T4.CEL: 1
## 08CHT051T5.CEL: 1
## 08CHT052T1.CEL: 1
## (Other) :48
## data_processing
## GCOS report derived with TGT Value set at 500. The ethanol data was imported as CEL files into S+ArrayAnalyzerâ„¢ (version 2.1.1). Tools available in ArrayAnalyzer were used to assess data quality at the chip level. Background subtraction and summarization was done with RMA [Irizarry, 2003] and GCRMA, and the summarized data was quantile normalized [Bolstad, 2003]. RMA summarized data was filtered for log2 (RMA expression) >6 in at least six chips; GCRMA summarized data was filtered for log2 (GCRMA expression) >5. Each list was further filtered for a fold change in at least one pairwise comparison greater than 1.25. The Local Pooled Error (LPE T-test) [Jain, 2003] was used for differential expression testing across all possible pairwise timepoint comparisons. The False Discovery Rate (FDR) was controlled by implementation of the Benjamini and Hochberg correction [Benjamini, 1995]. Statistically significant genes (p<0.05) from the ten pairwise timepoint comparisons from both the RMA and GCRMA summarized data were combined into one list. A second list of significant genes was generated using the application, EDGE (Storey, 2007). RMA summarized data filtered for expression as above was used for input. The resulting list, ranked by Q-value, was filtered for a fold change in at least one pairwise comparison greater than 1.25.:54
##
##
##
##
##
##
## platform_id contact_name contact_email
## GPL570:54 Dennis,M,Burian:54 dennis.burian@faa.gov:54
##
##
##
##
##
##
## contact_phone contact_laboratory
## 405-954-6087:54 Bioaeronautical Sciences Research Lab:54
##
##
##
##
##
##
## contact_department contact_institute
## Aviation Medicine:54 Federal Aviation Administration:54
##
##
##
##
##
##
## contact_address contact_city contact_state
## 6500 S. MacArthur Blvd., AAM610:54 Oklahoma City:54 OK:54
##
##
##
##
##
##
## contact_zip.postal_code contact_country
## Min. :73169 USA:54
## 1st Qu.:73169
## Median :73169
## Mean :73169
## 3rd Qu.:73169
## Max. :73169
##
## supplementary_file
## ftp://ftp.ncbi.nlm.nih.gov/geo/samples/GSM514nnn/GSM514737/suppl/GSM514737.CEL.gz: 1
## ftp://ftp.ncbi.nlm.nih.gov/geo/samples/GSM514nnn/GSM514738/suppl/GSM514738.CEL.gz: 1
## ftp://ftp.ncbi.nlm.nih.gov/geo/samples/GSM514nnn/GSM514739/suppl/GSM514739.CEL.gz: 1
## ftp://ftp.ncbi.nlm.nih.gov/geo/samples/GSM514nnn/GSM514740/suppl/GSM514740.CEL.gz: 1
## ftp://ftp.ncbi.nlm.nih.gov/geo/samples/GSM514nnn/GSM514741/suppl/GSM514741.CEL.gz: 1
## ftp://ftp.ncbi.nlm.nih.gov/geo/samples/GSM514nnn/GSM514742/suppl/GSM514742.CEL.gz: 1
## (Other) :48
## data_row_count gender.ch1 intervention.ch1 tissue.ch1
## Min. :54675 male:54 BAC 0% : 6 whole blood:54
## 1st Qu.:54675 BAC 0.02%declining: 6
## Median :54675 BAC 0.04%rising : 6
## Mean :54675 BAC 0.08% : 6
## 3rd Qu.:54675 BAC 0.04%declining: 5
## Max. :54675 OJ time 1 : 5
## (Other) :20
baru <- dataku[,2:202]
View(sampel)
rownames(baru)<-(sampel)
dim(baru)
## [1] 54 201
View(baru)
dataku<-baru
dim(dataku)
## [1] 54 201
library(biclust)
## Warning: package 'biclust' was built under R version 3.5.3
## Loading required package: MASS
## Loading required package: grid
## Loading required package: colorspace
## Warning: package 'colorspace' was built under R version 3.5.3
## Loading required package: lattice
## Warning: package 'lattice' was built under R version 3.5.3
set.seed(994)
spectral <- biclust(x=as.matrix(dataku), method=BCSpectral(), normalization="bistochastization",
minr=3, minc=3, withinVar=0.95)
spectral
##
## An object of class Biclust
##
## call:
## biclust(x = as.matrix(dataku), method = BCSpectral(), normalization = "bistochastization",
## minr = 3, minc = 3, withinVar = 0.95)
##
## Number of Clusters found: 15
##
## First 5 Cluster sizes:
## BC 1 BC 2 BC 3 BC 4 BC 5
## Number of Rows: 13 13 13 13 13
## Number of Columns: 24 37 43 35 51
constantVariance(x=as.matrix(dataku), spectral,1,"row")
## [1] 0.7691421
constantVariance(x=as.matrix(dataku), spectral,1,"col")
## [1] 1.09421
library(ComplexHeatmap)
## ========================================
## ComplexHeatmap version 1.20.0
## Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/
## Github page: https://github.com/jokergoo/ComplexHeatmap
## Documentation: http://bioconductor.org/packages/ComplexHeatmap/
##
## If you use it in published research, please cite:
## Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional
## genomic data. Bioinformatics 2016.
## ========================================
Heatmap(dataku,
name = "BAC Intervention", #title of legend
column_title = "Gen", row_title = "Samples",
row_names_gp = gpar(fontsize = 7) # Text size for row names
)
hc = hclust(dist(dataku))
plot(hc)
