Description

Gene expression data from Khan et al. (2001). This data set contains 83 samples with 2308 genes: 29 cases of Ewing sarcoma (EWS), coded 1, 11 cases of Burkitt lymphoma (BL), coded 2, 18 cases of neuroblastoma (NB), coded 3, 25 cases of rhabdomyosarcoma (RMS), coded 4. A total of 63 training samples and 25 test samples are provided in Khan et al. (2001). Five of the test set are non-SRBCT and are not considered here. The training sample indexes correspond to 1:65 and the test sample indexes (without non-SRBCT sample) correspond to 66:83.

Standard PCA method

library(plsgenomics)
# For any news related to the 'plsgenomics' package (update, corrected bugs), please check http://thoth.inrialpes.fr/people/gdurif/
# C++ based sparse PLS routines will soon be available on the CRAN in the new 'fastPLS' package.
library(MultiGroupO)
data(SRBCT)
 mydata<-SRBCT$X
 mydata<-mydata[,1:5]
 groups<-as.factor(SRBCT$Y)
 pca(datos=mydata,grupos=groups,Plot=TRUE,center=TRUE,scale=TRUE)

# $loadings
#             PC1        PC2         PC3         PC4          PC5
# [1,] -0.3853353  0.2400701 -0.76059996  0.43733190 -0.155279059
# [2,] -0.4444842  0.4247842 -0.09015326 -0.78347750 -0.005253247
# [3,]  0.3227085 -0.5951899 -0.58350325 -0.43798941 -0.096422977
# [4,]  0.5333248  0.4529326 -0.01106092 -0.05094667 -0.712529858
# [5,] -0.5151450 -0.4500286  0.26974376  0.02176068 -0.677395474
# 
# $variates
#                PC1         PC2          PC3          PC4         PC5
#  [1,] -1.406957352 -0.76339469 -0.927097361  1.294672092 -0.66757421
#  [2,]  0.088045884 -0.34531694 -0.237709302  0.573122797  0.93974973
#  [3,] -0.880526378  0.04633629 -1.234055994  1.299176865  0.30316222
#  [4,] -0.360263552 -0.05657513  0.926182168  0.440867103  0.64971761
#  [5,] -1.241068087  0.34542842 -0.217748557  1.136540110 -0.07622766
#  [6,] -0.716001881 -0.60774253 -0.097190304  0.838568962 -0.04303317
#  [7,] -0.484461042 -0.56604567 -0.064787547  0.584880009 -0.05550315
#  [8,] -1.432068303 -0.10887173 -0.136115186  1.185861782 -0.59292563
#  [9,] -0.908936383 -0.42755182 -0.167476767  1.065744335 -0.23379500
# [10,] -0.819979264  0.02532283  0.141456253  0.627801171  0.27583850
# [11,] -1.524067959  0.05883388 -0.940986082  1.679469800 -0.65009741
# [12,] -1.088510226 -0.32377897  0.288871205  1.112663884 -0.39911816
# [13,] -0.900809093 -0.03748096  0.066382703  0.971939803 -0.77925813
# [14,]  1.492600655 -0.04866498 -0.324359688 -0.474728460 -0.80215002
# [15,] -0.577860919 -0.75740550  0.881399320  0.187496005  0.17851454
# [16,] -0.518524903 -1.87522358  0.487529916 -0.049135993 -0.47188755
# [17,] -0.551422940 -1.37482851 -1.319253917  0.437765315 -0.47667414
# [18,]  2.170173453 -0.36346605 -1.059977142 -0.879361668 -0.56656661
# [19,]  1.952169488 -0.13857031 -0.794521610 -0.626246924 -0.39616949
# [20,]  1.833377285  0.93482522 -0.437675503  0.360279974 -0.56005070
# [21,] -0.627418265 -0.08257983 -0.107542124  1.053404948  0.50020463
# [22,]  1.303226056  0.48427243  0.963791616  0.114709287  0.33960050
# [23,]  1.668390645 -0.16402883 -0.653246516 -0.418946513  0.05828289
# [24,]  1.420350584 -0.04896606  0.943322155 -0.189215953 -1.01084450
# [25,]  2.448473656  0.01865666  0.096387573 -0.795912291 -0.27998976
# [26,]  1.546650140  1.11039240  1.560664681  0.237205320 -0.08875148
# [27,]  2.254334640  0.78312464  0.575067759 -0.058717349  0.25429497
# [28,]  0.144053906 -1.25446073  1.228416338 -0.065155598  0.25627010
# [29,]  0.653143083 -1.76817435  0.255474385 -0.519088609  0.34702191
# [30,]  0.158854109 -1.51271367  0.880842788 -0.195772040 -0.38136790
# [31,] -0.957664712 -1.49170169  2.117309105  0.115562394 -0.73055932
# [32,] -0.454875842 -1.28350621  0.063380143 -0.181635289 -0.13557867
# [33,]  0.194554792 -2.78635216 -1.050611723 -0.901938860 -0.58474689
# [34,]  0.179874054 -0.77790456  0.469617645 -0.037254749  0.52770105
# [35,]  2.027813857  1.31692912  0.646603765  0.244849520 -0.47821756
# [36,]  1.839619673  0.83228000 -0.807293918 -0.202372283 -1.31058544
# [37,]  2.944525656 -0.75405018 -2.091416534 -1.236019328 -0.78046893
# [38,]  1.832093240  0.12646137  0.008656911 -0.209146880  0.42537578
# [39,]  1.467912121  1.27267276  1.052350386  0.335231526 -0.04415075
# [40,]  1.609884035  0.52734889 -0.301885221 -0.004804155 -0.01102314
# [41,]  2.154352287  0.84072252 -0.431900352  0.120989114 -0.19977327
# [42,]  2.114788884  0.03539266 -0.529790434 -0.522584163 -0.50657167
# [43,]  1.791845475  1.17170288  0.798824267 -0.103042493 -0.76610338
# [44,]  0.123345370  0.45888908 -1.160562767  1.095947276  0.69094313
# [45,] -1.227068054  0.50281223  0.396797664  0.760822472  0.09383407
# [46,]  1.060634828  1.91753828  0.635871901  0.427058953 -0.73999561
# [47,]  1.533765584  1.33407877  0.054949585  0.312893277 -0.35209633
# [48,]  0.705472675  1.58903546  0.730509154  0.253324413 -0.54962418
# [49,]  1.431586487  0.97127574  0.217738914 -0.507092334 -0.39478771
# [50,]  0.920931574  1.29571425  0.363347370  0.611447195 -0.08789009
# [51,] -2.750163443 -0.73357625  1.481307108 -1.141750055 -1.39983574
# [52,]  1.545537774  1.31411015 -0.134906440  0.651180753  0.34520243
# [53,] -1.931913227  0.57485780 -0.687983543 -1.011038043 -0.01022203
# [54,] -2.913941922  0.60504728  1.210786202 -1.871773426 -0.60430085
# [55,] -2.766247852  1.79666894 -1.106263656 -0.716365775  0.17687473
# [56,] -2.900015201 -0.26012630  0.470163067 -0.649590826 -1.20465386
# [57,] -0.630994153  1.41107214 -1.033131603  0.924989309  0.90592588
# [58,] -2.022015736 -0.05100951  0.652137885  0.194476816 -1.21999600
# [59,] -3.200460796  2.15034007 -0.168377495 -2.582287572 -0.02281737
# [60,] -1.125464254  0.17073326  0.146614969 -0.052343255 -0.22819766
# [61,] -0.900007504 -0.42936289  0.383740555 -0.335086903  0.16185827
# [62,] -0.791287142  1.28106371  0.526667310 -0.562702221  1.15559439
# [63,] -0.804417620  0.48087987 -0.666337694 -0.607512136  0.76336964
# [64,]  0.479559625 -0.46601546  0.245249549 -0.164611613  1.08598697
# [65,]  0.108707453  0.31636780  1.187789251 -0.209241941  1.35511092
# [66,]  0.120246080 -1.02517069 -0.423671590 -0.614532712  0.66346894
# [67,]  0.311030597 -1.69231060 -3.104502149 -0.161586214  0.18989591
# [68,] -1.731462359  1.42043190 -0.818941954 -1.559787805  0.69923977
# [69,]  0.477959894 -1.18021521  0.831420495 -0.345997003  0.71105359
# [70,] -1.292298171  0.59545754 -2.020673719  1.724009270  0.20448036
# [71,] -1.550747523 -0.14650834  1.151744149  0.132062561 -0.39955053
# [72,] -0.648033683 -0.31142109 -0.015664892  0.733469975  0.03887057
# [73,] -0.805240565  0.03056610  0.153571981  0.627994083  0.29276549
# [74,] -0.578896592 -0.25292265 -1.336412897  0.904381965  0.04311459
# [75,] -2.425497244  2.11280577 -2.248059334 -1.830980132  0.41696121
# [76,]  1.230864908 -1.40113560  0.030806752 -0.734906843  1.03695419
# [77,] -0.622907887  0.14731038  1.301687792  0.196703885  0.67678092
# [78,]  0.451238661 -1.80509900 -0.498131086 -0.903007385  0.29399373
# [79,]  0.341532552 -0.72289691  0.275633756 -0.454880668  0.92334120
# [80,]  0.539381619 -1.27864896 -0.268077804 -0.983079469  0.53645510
# [81,]  0.003776952 -0.54462973  0.297802525 -0.489986807  0.62746189
# [82,]  0.483080781  0.03481055  1.427725977  0.236977664  1.44961741
# [83,] -0.089263044 -0.42216518  0.997745409  0.354678755  0.69884192
# 
# $prop_expl_var
# [1] 0.41242666 0.20418620 0.17296671 0.13076232 0.07965812
# 
# attr(,"class")
# [1] "pca"

Multigroup PCA method

library(plsgenomics)
data(SRBCT)
mydata<-SRBCT$X
mydata<-mydata[,1:5]
groups<-as.factor(SRBCT$Y)
mat.to.diag1<-new.cov(x=mydata,cls=groups,A=diag(ncol(mydata)))
mgpca(mat.to.diag=mat.to.diag1,mat.x=as.matrix(mydata),cls=groups,Plot=TRUE,ncomp=2,center = TRUE,scale = TRUE)

# $variates
#              [,1]         [,2]        [,3]         [,4]         [,5]
#  [1,] -1.72403001  0.508402635 -0.45492278  0.828527233  1.191417771
#  [2,] -0.20672447  0.134090675 -0.58738092  0.721960626 -0.684209083
#  [3,] -1.81731150  0.346363923 -0.23726780  0.754159429 -0.180261753
#  [4,]  0.15430112 -0.976150762 -0.57607111  0.537723073 -0.098069321
#  [5,] -1.47808450 -0.606372349 -0.11903926  0.528329253  0.398492094
#  [6,] -0.66302434  0.008941405 -0.53321498  0.748848978  0.558328904
#  [7,] -0.40779846  0.085523590 -0.43749633  0.572500626  0.460107575
#  [8,] -1.43343854 -0.422371202 -0.18924938  0.631522349  1.082242907
#  [9,] -0.97354219 -0.097064020 -0.35750545  0.805146753  0.702999438
# [10,] -0.69729481 -0.553189472 -0.43842657  0.392986080  0.156024794
# [11,] -2.21297908  0.003891979  0.05806129  0.855311928  0.907041155
# [12,] -0.87144680 -0.534017411 -0.31190400  0.816298889  0.980932230
# [13,] -0.91423762 -0.355644661  0.16752769  0.561411297  1.031318093
# [14,]  0.96093811  1.015725867  1.10350709 -0.170498169 -0.048449470
# [15,]  0.30569733 -0.546982439 -0.88563856  0.437763728  0.618740572
# [16,]  0.54883989  0.483592318 -1.18173020  0.491095936  1.440611306
# [17,] -0.87820586  1.507868599 -0.65540354  0.460818420  0.816509430
# [18,]  1.22007262  1.986726277  1.08498489 -0.333758241 -0.579086640
# [19,]  1.06667904  1.528796821  1.04530951 -0.181661666 -0.640211428
# [20,]  0.47367378  0.564183541  1.90389483  0.325173793 -0.772635287
# [21,] -0.85902411 -0.343907328 -0.44013035  0.842752338 -0.108462792
# [22,]  1.19611234 -0.577209204  0.68906952  0.452637496 -0.739422910
# [23,]  0.89460669  1.222659484  0.65501500  0.014134844 -0.831633999
# [24,]  1.54114764  0.033502437  1.14627075  0.234381074  0.471306537
# [25,]  1.92292858  0.962156698  1.21765255 -0.108986029 -0.773677567
# [26,]  1.45772199 -1.195033714  1.42043752  0.447899251 -0.594642670
# [27,]  1.54993208 -0.053937157  1.38657624  0.366678809 -1.277450493
# [28,]  1.22030517 -0.275434527 -0.95695728  0.631096484  0.542485653
# [29,]  1.31424340  0.946530346 -1.08777376  0.396487395  0.211119292
# [30,]  1.15668535  0.253675542 -0.73656557  0.479263681  1.048186368
# [31,]  1.03951884 -1.069551242 -1.10482446  0.614338815  2.085611784
# [32,]  0.21426169  0.486112129 -0.97433203  0.160691516  0.807671026
# [33,]  0.72343166  2.497528693 -1.37148960 -0.018601970  1.191001611
# [34,]  0.64275356  0.015014971 -0.74010357  0.415622711 -0.063514599
# [35,]  1.16097600 -0.371169323  2.08180607  0.317773073 -0.795325645
# [36,]  0.51808311  1.110711933  2.20065384 -0.280720289 -0.251853955
# [37,]  1.37039724  3.326166798  1.36030902 -0.503039443 -0.839558330
# [38,]  1.21285912  0.542062574  0.69030436  0.286314342 -1.128700551
# [39,]  1.02143196 -0.945234047  1.51347908  0.385470403 -0.787550471
# [40,]  0.68444444  0.541939618  1.14422497  0.172811355 -0.927267727
# [41,]  0.80652999  0.692789313  1.74826320  0.270994745 -1.152746174
# [42,]  1.22935683  1.305377471  1.29589149 -0.081221023 -0.618636785
# [43,]  1.28453301 -0.395649111  1.96554481 -0.009589968 -0.386301095
# [44,] -1.18144527  0.403947280  0.24019641  0.743458556 -1.040091711
# [45,] -1.00602893 -1.118573267 -0.23301164  0.260914921  0.343436792
# [46,]  0.28395182 -0.992695195  2.16397324 -0.005298199 -0.432810089
# [47,]  0.46935352 -0.144991439  1.83478624  0.170768426 -0.848633519
# [48,]  0.28512312 -1.034731261  1.63624869 -0.098046757 -0.289382285
# [49,]  0.94131884  0.004590750  1.41692477 -0.433965021 -0.609198631
# [50,]  0.15321531 -0.667605970  1.38997787  0.371708166 -0.707973121
# [51,] -0.19492872 -1.316953907 -1.32152134 -1.387317961  2.848772114
# [52,]  0.23694663 -0.161122531  1.50247360  0.532658807 -1.433079495
# [53,] -1.39507175 -0.319061711 -0.72975302 -1.686183076  0.366872700
# [54,] -0.57031958 -1.883675330 -1.15879566 -2.481965252  1.677916021
# [55,] -2.66066014 -0.995918063 -0.40790041 -2.100146394 -0.021622735
# [56,] -1.22417886 -0.955328800 -1.04545755 -1.286698344  2.326397479
# [57,] -1.80685882 -0.456212673  0.28835290  0.119021588 -1.250105471
# [58,] -0.96557946 -1.001002342 -0.32917174 -0.365433006  1.966316405
# [59,] -1.74349451 -1.730272482 -0.71601292 -3.858099787  0.364373439
# [60,] -0.65919189 -0.552171573 -0.33658933 -0.393761962  0.603623490
# [61,] -0.07921936 -0.375778563 -0.89395612 -0.296846327  0.495321740
# [62,] -0.35593996 -1.450371229 -0.41937155 -0.919862587 -0.971792465
# [63,] -0.80009867 -0.079109525 -0.60752386 -0.917662497 -0.645397074
# [64,]  0.65861820  0.052884698 -0.73225661  0.302951778 -0.805732969
# [65,]  0.75414486 -1.224286246 -0.67008136  0.077666665 -0.938192185
# [66,]  0.39115249  0.848365921 -1.04216384 -0.145732763 -0.287584175
# [67,] -1.03557839  3.286493565 -0.79169134  0.062329865 -0.395773429
# [68,] -1.38045341 -0.622164954 -0.61764540 -2.347540749 -0.650349592
# [69,]  1.29123898  0.064751175 -1.03452503  0.434522127 -0.085921121
# [70,] -2.87786572  0.469185378  0.09727047  0.702921070 -0.340501221
# [71,] -0.31853305 -1.296295622 -0.68321191 -0.094224200  1.293203755
# [72,] -0.62033377 -0.176675365 -0.39133568  0.593410628  0.367909362
# [73,] -0.68251182 -0.562687220 -0.43868244  0.398949336  0.137757269
# [74,] -1.43583245  0.785653466 -0.18979208  0.538263476 -0.015535958
# [75,] -2.75926509 -0.057114082 -0.31062410 -3.254925376 -0.786936068
# [76,]  1.52524315  1.045968122 -1.00271429  0.272498913 -0.770981786
# [77,]  0.24362116 -1.424996156 -0.67080577  0.246711853 -0.004253116
# [78,]  0.91146554  1.523635441 -1.19439611 -0.103377739  0.149948492
# [79,]  0.78416949  0.180753104 -0.92150442  0.085719017 -0.520155909
# [80,]  0.97368533  1.085472571 -1.00083079 -0.268960435 -0.227277194
# [81,]  0.54206248  0.010775882 -0.81428063 -0.123671481 -0.216384428
# [82,]  1.03815982 -1.209389165 -0.64751266  0.711474928 -0.982172157
# [83,]  0.51459855 -0.744710351 -0.71844086  0.672919867 -0.086490946
# 
# $loadings
#             [,1]        [,2]        [,3]        [,4]         [,5]
# [1,] -0.93921916  0.27678629  0.19056337  0.07027279  0.002015891
# [2,] -0.14846641 -0.19210171 -0.09662235 -0.96495034 -0.024282003
# [3,]  0.22168438  0.93454616 -0.19067352 -0.20161311  0.021800808
# [4,]  0.21207162  0.10600135  0.94579078 -0.15249441  0.161290425
# [5,] -0.04131301 -0.04328361 -0.15320947  0.00549353  0.986365269
# 
# $prop_expl_var
# [1] 26.52 20.79
# 
# attr(,"class")
# [1] "mgpca"

MDR method

library(plsgenomics)
data(SRBCT)
mydata<-SRBCT$X
mydata<-mydata[,1:5]
groups<-as.factor(SRBCT$Y)
mydata<-split(as.data.frame(mydata),groups)
mdr(group=groups,data.x=mydata,c=2)

# $variates
#             V1           V2
# 1   3.12202176 -0.821840479
# 2   1.59601843 -0.815421086
# 3   3.19351655 -0.675033314
# 4   0.96173934 -0.248191188
# 5   2.62641826 -0.186473588
# 6   1.99336399 -0.697375665
# 7   1.76629017 -0.763485594
# 8   2.62973615 -0.321697736
# 9   2.28264534 -0.590075377
# 10  1.86028044 -0.336384244
# 11  3.51718635 -0.441444760
# 12  2.08399635 -0.366983036
# 13  2.19519126 -0.428479665
# 14  0.81774008 -1.400475271
# 15  0.87611500 -0.529004301
# 16  0.87157853 -1.176914092
# 17  2.51859002 -1.489369550
# 18  0.79927593 -1.964447242
# 19  0.84147391 -1.694077685
# 20  1.31135152 -1.071361224
# 21  2.11366050 -0.458186627
# 22  0.22782228 -0.590485766
# 23  0.90382926 -1.515588029
# 24  3.05356781 -2.408330961
# 25  4.24802863 -0.554183285
# 26  1.90789878 -0.579941444
# 27  1.84484902 -0.333574180
# 28  2.92707061 -0.969156826
# 29  0.68099806 -0.452015376
# 30  0.07902264 -0.986420975
# 31 -0.06985239 -1.514802041
# 32 -0.08656825 -0.270430892
# 33  0.10102938 -0.906384146
# 34  0.10277898 -0.847239929
# 35  0.27888174 -1.526406320
# 36  0.29923080 -1.126845238
# 37  0.04741245 -0.406547431
# 38  0.09384939 -1.022781851
# 39  0.10817210 -1.583933587
# 40  0.09437601 -0.259207594
# 41  1.17583097 -1.078191735
# 42  1.13121560 -2.295174559
# 43  0.71875988 -0.880029695
# 44  0.45768545 -0.653024251
# 45  1.37024418 -1.340190390
# 46  1.00538890 -2.715296664
# 47  0.47357144 -1.200251812
# 48  0.38764563 -0.327760965
# 49  1.00568606 -1.097142484
# 50  1.01066255 -1.189705730
# 51  0.67397690 -1.597442927
# 52  0.28474238 -0.644696642
# 53  0.70601123 -0.878932571
# 54  1.06511637 -1.264522535
# 55  0.73125839 -1.745627267
# 56  0.57328484 -0.964640487
# 57  0.57087070 -1.483461202
# 58  0.74497419 -0.816276902
# 59  2.67267029 -0.780445452
# 60  2.01664477  0.043711589
# 61  1.09467821 -0.139665161
# 62  1.11523969 -0.659996537
# 63  1.01141553 -0.125191926
# 64  0.59592249 -0.788236205
# 65  1.25092103 -0.345112431
# 66  0.89036181  0.074664639
# 67  1.33282685 -0.638146291
# 68  2.30740446 -0.197582836
# 69  1.00584282  0.571725222
# 70  3.31532714  0.439825462
# 71  1.98670759  0.050155344
# 72  2.98186403 -0.138733308
# 73  1.91933878 -0.015127747
# 74  2.04687561  0.827889538
# 75  1.74805569 -0.286574117
# 76  1.19721947 -0.500400564
# 77  1.18396499  0.241875198
# 78  1.91516519 -0.467418666
# 79  0.28362805 -0.154640916
# 80  2.16479920  0.047981812
# 81  1.23465926  0.028026774
# 82  3.52898464  0.040489155
# 83  0.72383697  0.008385486
# 
# $loadings
#             [,1]         [,2]
# [1,]  0.98614287 -0.002436152
# [2,] -0.06903002  0.560697342
# [3,] -0.02923694 -0.819796115
# [4,] -0.14390561 -0.109894629
# [5,]  0.03454657  0.038341319
# 
# $prop_expl_dim
# [1] 66.78 25.87  7.36  0.00  0.00
# 
# attr(,"class")
# [1] "mdr"