chr3.14774_chr3_95969237_95971978_-_0.R fitVsDatCorrelation=0.875972798263761 cont.fitVsDatCorrelation=0.250345755182632 fstatistic=8442.26146053633,36,324 cont.fstatistic=2088.84738862772,36,324 residuals=-0.415093645691385,-0.0852376763842126,-0.00371891374309350,0.0722936235491317,0.521175186361705 cont.residuals=-0.738726664275122,-0.207604146662157,0.00664155697976109,0.205385201671759,0.90604735885927 predictedValues: Include Exclude Both chr3.14774_chr3_95969237_95971978_-_0.R.tl.Lung 86.5116119013878 120.174831314524 80.2608244720846 chr3.14774_chr3_95969237_95971978_-_0.R.tl.cerebhem 66.1191415724856 71.7513194952923 62.6275886786643 chr3.14774_chr3_95969237_95971978_-_0.R.tl.cortex 86.4531489336884 103.286324763509 62.3396161215264 chr3.14774_chr3_95969237_95971978_-_0.R.tl.heart 92.8833416885303 119.157361477828 69.425395775003 chr3.14774_chr3_95969237_95971978_-_0.R.tl.kidney 94.190383291826 98.7802921194191 63.2212781377729 chr3.14774_chr3_95969237_95971978_-_0.R.tl.liver 89.6932228876135 101.856616151285 60.354387900149 chr3.14774_chr3_95969237_95971978_-_0.R.tl.stomach 101.724165974005 137.022256371772 64.0251995468149 chr3.14774_chr3_95969237_95971978_-_0.R.tl.testicle 82.8805365955255 100.471438280445 66.0850937977238 diffExp=-33.6632194131366,-5.63217792280672,-16.8331758298208,-26.2740197892977,-4.58990882759306,-12.1633932636712,-35.2980903977679,-17.5909016849199 diffExpScore=0.993465969241057 diffExp1.5=0,0,0,0,0,0,0,0 diffExp1.5Score=0 diffExp1.4=0,0,0,0,0,0,0,0 diffExp1.4Score=0 diffExp1.3=-1,0,0,0,0,0,-1,0 diffExp1.3Score=0.666666666666667 diffExp1.2=-1,0,0,-1,0,0,-1,-1 diffExp1.2Score=0.8 cont.predictedValues: Include Exclude Both Lung 88.152202967019 87.9799001220581 85.4680436869966 cerebhem 88.5162088014634 80.2311027024068 84.0539101912239 cortex 79.8578686074201 87.51351317023 83.9980333871396 heart 99.168981930999 80.8447974149199 80.45420786778 kidney 88.8820725653285 80.9985436578924 93.7871027169416 liver 83.6779305141464 76.3850072737846 89.3526060051416 stomach 76.2102677611701 78.7696358735596 70.4359305157209 testicle 79.2202913880277 82.7126517613506 81.6823098418393 cont.diffExp=0.172302844960925,8.28510609905659,-7.65564456280988,18.3241845160792,7.88352890743606,7.29292324036176,-2.55936811238951,-3.49236037332290 cont.diffExpScore=1.90304747842733 cont.diffExp1.5=0,0,0,0,0,0,0,0 cont.diffExp1.5Score=0 cont.diffExp1.4=0,0,0,0,0,0,0,0 cont.diffExp1.4Score=0 cont.diffExp1.3=0,0,0,0,0,0,0,0 cont.diffExp1.3Score=0 cont.diffExp1.2=0,0,0,1,0,0,0,0 cont.diffExp1.2Score=0.5 tran.correlation=0.851346020224834 cont.tran.correlation=-0.0194217205616156 tran.covariance=0.0214426969796776 cont.tran.covariance=-2.76412069627992e-05 tran.mean=97.059749551196 cont.tran.mean=83.695061031986 weightedLogRatios: wLogRatio Lung -1.5199668037152 cerebhem -0.345984506264021 cortex -0.80919839953593 heart -1.15978647500025 kidney -0.217398274016694 liver -0.579896785740155 stomach -1.42123900046990 testicle -0.868754304049324 cont.weightedLogRatios: wLogRatio Lung 0.00876146143359487 cerebhem 0.435753593079345 cortex -0.405179214662786 heart 0.918236015623275 kidney 0.412464923234055 liver 0.399533002617263 stomach -0.143686939069784 testicle -0.189549096632958 varWeightedLogRatios=0.228351231615381 cont.varWeightedLogRatios=0.189390347777337 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.98124866687794 0.0863844232401985 57.6637370492964 1.99739648346025e-172 *** df.mm.trans1 -0.330528389886541 0.0731667041006623 -4.51746998787594 8.77896117948883e-06 *** df.mm.trans2 -0.123764175225720 0.0731667041006623 -1.69153683696680 0.0916958467961003 . df.mm.exp2 -0.536485979466905 0.101893506750779 -5.26516356708668 2.55633686620609e-07 *** df.mm.exp3 0.100565884162068 0.101893506750780 0.98697048878729 0.324393572381235 df.mm.exp4 0.207591946909477 0.101893506750779 2.03734225594202 0.0424280182669468 * df.mm.exp5 0.127630657295515 0.101893506750779 1.25258872096420 0.211258750615345 df.mm.exp6 0.155783041621015 0.101893506750779 1.52888095216944 0.127269633086221 df.mm.exp7 0.519186894768728 0.101893506750779 5.09538744248545 5.92376671907735e-07 *** df.mm.exp8 -0.0276140871832469 0.101893506750779 -0.271009292582186 0.786556458287568 df.mm.trans1:exp2 0.267665622900409 0.0882423653268562 3.03330063636617 0.00261442966329172 ** df.mm.trans2:exp2 0.0207446140020733 0.0882423653268562 0.235086785414622 0.81428988279492 df.mm.trans1:exp3 -0.101241894346380 0.0882423653268562 -1.14731618958051 0.252097456249999 df.mm.trans2:exp3 -0.252008510616444 0.0882423653268563 -2.85586758336526 0.00456893827230419 ** df.mm.trans1:exp4 -0.136526278171146 0.0882423653268562 -1.54717382818834 0.122797510364117 df.mm.trans2:exp4 -0.216094572106854 0.0882423653268562 -2.44887556341474 0.0148597694885204 * df.mm.trans1:exp5 -0.042591215684501 0.0882423653268562 -0.482661763731513 0.629661855353112 df.mm.trans2:exp5 -0.323680155028243 0.0882423653268563 -3.66808112893742 0.000285578566059085 *** df.mm.trans1:exp6 -0.119666475065696 0.0882423653268562 -1.35611137147608 0.176008058418641 df.mm.trans2:exp6 -0.321164551414412 0.0882423653268562 -3.63957323928018 0.000317722013400756 *** df.mm.trans1:exp7 -0.357200646307492 0.0882423653268562 -4.04794958730305 6.46793618439105e-05 *** df.mm.trans2:exp7 -0.387991136980374 0.0882423653268562 -4.39688051814145 1.49106636197478e-05 *** df.mm.trans1:exp8 -0.0152643065224507 0.0882423653268562 -0.172981611110610 0.862773893475833 df.mm.trans2:exp8 -0.151460032037249 0.0882423653268563 -1.71640947606322 0.0870429148796502 . df.mm.trans1:probe2 -0.0908278676750474 0.0441211826634281 -2.05860002366469 0.040331763614493 * df.mm.trans1:probe3 -0.356598387834751 0.0441211826634281 -8.08224907648122 1.27551950258532e-14 *** df.mm.trans1:probe4 -0.457160685995626 0.0441211826634281 -10.3614785098352 6.43565607862468e-22 *** df.mm.trans1:probe5 -0.394424705933595 0.0441211826634281 -8.93957691348405 3.03425212112040e-17 *** df.mm.trans1:probe6 -0.41496302641861 0.0441211826634281 -9.4050748726319 9.84285718344904e-19 *** df.mm.trans2:probe2 -0.0338092944846297 0.0441211826634281 -0.766282598146538 0.44406609215691 df.mm.trans2:probe3 -0.0258130196379555 0.0441211826634281 -0.585048225811767 0.558922500920382 df.mm.trans2:probe4 -0.0193056318072565 0.0441211826634281 -0.437559254803449 0.66199734020221 df.mm.trans2:probe5 -0.208820354807072 0.0441211826634281 -4.73288208070095 3.31232780452372e-06 *** df.mm.trans2:probe6 -0.329083633109285 0.0441211826634281 -7.4586312796656 8.08314970418896e-13 *** df.mm.trans3:probe2 -0.103751225607358 0.0441211826634281 -2.35150599653706 0.0192960772486632 * df.mm.trans3:probe3 -0.321272167785506 0.0441211826634281 -7.28158558750075 2.5204596550997e-12 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.47854701915269 0.173384097071316 25.8302064307004 1.15301147919965e-80 *** df.mm.trans1 -0.00660827162793737 0.146854519024839 -0.0449987625291916 0.964136016129783 df.mm.trans2 -0.0364444835957008 0.146854519024839 -0.248167259936595 0.80416220886903 df.mm.exp2 -0.0713921738004648 0.204512723506763 -0.349084265156265 0.727252804183977 df.mm.exp3 -0.086782488978549 0.204512723506763 -0.424337847985674 0.671601056257262 df.mm.exp4 0.0936376100808519 0.204512723506763 0.457857137078102 0.647361983144565 df.mm.exp5 -0.167316442444992 0.204512723506763 -0.81812241104627 0.413888556299319 df.mm.exp6 -0.237859433637306 0.204512723506763 -1.16305445235264 0.245663278597886 df.mm.exp7 -0.0627104497258732 0.204512723506763 -0.306633487885655 0.759319323650865 df.mm.exp8 -0.123263140378853 0.204512723506763 -0.602716243103459 0.54711908954703 df.mm.trans1:exp2 0.0755129596941655 0.177113213954000 0.426354183340481 0.670132903328813 df.mm.trans2:exp2 -0.0208049529484095 0.177113213954000 -0.117466972022839 0.906562799392513 df.mm.trans1:exp3 -0.0120339985049699 0.177113213954000 -0.0679452325228282 0.945871142108759 df.mm.trans2:exp3 0.0814673259639607 0.177113213954000 0.459973167135455 0.645843994245493 df.mm.trans1:exp4 0.0241227735182964 0.177113213954000 0.136199739024338 0.891747966852756 df.mm.trans2:exp4 -0.178214755423031 0.177113213954000 -1.00621942002203 0.315060903349587 df.mm.trans1:exp5 0.175562006547069 0.177113213954000 0.991241718377185 0.322307250010977 df.mm.trans2:exp5 0.0846392367382961 0.177113213954000 0.477882111948343 0.633056362706426 df.mm.trans1:exp6 0.185769803049374 0.177113213954000 1.04887602060918 0.295016936475912 df.mm.trans2:exp6 0.0965374899949796 0.177113213954000 0.54506091239501 0.586086616018385 df.mm.trans1:exp7 -0.0828582487864768 0.177113213954000 -0.467826464986384 0.640223212331153 df.mm.trans2:exp7 -0.0478703399086944 0.177113213954000 -0.270281018790204 0.787116147024416 df.mm.trans1:exp8 0.0164307111295439 0.177113213954000 0.0927695385495707 0.926143986899153 df.mm.trans2:exp8 0.0615273338355458 0.177113213954000 0.3473898556859 0.72852400367296 df.mm.trans1:probe2 -0.0243370454924495 0.0885566069769998 -0.274819082654899 0.783630392325016 df.mm.trans1:probe3 0.0385305745306104 0.0885566069769999 0.435095424789904 0.663782838195045 df.mm.trans1:probe4 0.0157890760640594 0.0885566069769999 0.178293597768038 0.858603832541877 df.mm.trans1:probe5 0.0187245004321221 0.0885566069769998 0.211441032705615 0.832676075303253 df.mm.trans1:probe6 0.0154282635860268 0.0885566069769999 0.174219226692299 0.861801982206802 df.mm.trans2:probe2 0.101284615817782 0.0885566069769998 1.14372737704470 0.253581028170518 df.mm.trans2:probe3 0.0525528051045126 0.0885566069769998 0.593437428312511 0.553302485162396 df.mm.trans2:probe4 0.105262560855614 0.0885566069769998 1.18864717663531 0.235449017293651 df.mm.trans2:probe5 0.00359083718522199 0.0885566069769998 0.0405484955645897 0.967680819498785 df.mm.trans2:probe6 0.0523617871917759 0.0885566069769999 0.591280413502918 0.554744831714136 df.mm.trans3:probe2 -0.00750141523618638 0.0885566069769998 -0.084707572842472 0.932546191437353 df.mm.trans3:probe3 0.0454462675418663 0.0885566069769999 0.513188897962969 0.608168928064976