chr1.1056_chr1_182387526_182389790_-_0.R fitVsDatCorrelation=0.911939596531549 cont.fitVsDatCorrelation=0.268726498113117 fstatistic=6812.21279256453,47,577 cont.fstatistic=1226.16963037367,47,577 residuals=-0.985101619345646,-0.100653919279179,-0.00549815864108659,0.0948879808913346,1.51907292484244 cont.residuals=-0.894217116834058,-0.349196255980645,-0.0291758949413229,0.276386159830261,1.42867604559285 predictedValues: Include Exclude Both chr1.1056_chr1_182387526_182389790_-_0.R.tl.Lung 154.341300420118 52.0411462310287 108.381279118478 chr1.1056_chr1_182387526_182389790_-_0.R.tl.cerebhem 75.3794721434093 66.5574187743128 82.5372299638391 chr1.1056_chr1_182387526_182389790_-_0.R.tl.cortex 92.6230284150215 54.1363603751369 78.8300484614469 chr1.1056_chr1_182387526_182389790_-_0.R.tl.heart 101.995697055883 54.003140239751 85.3538136053058 chr1.1056_chr1_182387526_182389790_-_0.R.tl.kidney 80.838921604217 50.9275585744523 79.5169162623711 chr1.1056_chr1_182387526_182389790_-_0.R.tl.liver 233.184222035753 51.5899560141258 155.170120036137 chr1.1056_chr1_182387526_182389790_-_0.R.tl.stomach 100.444739563752 52.720618152877 90.4741290009098 chr1.1056_chr1_182387526_182389790_-_0.R.tl.testicle 107.583391959145 53.4027948723401 92.1588830235662 diffExp=102.300154189089,8.82205336909655,38.4866680398846,47.9925568161317,29.9113630297647,181.594266021627,47.7241214108749,54.1805970868044 diffExpScore=0.99804691993596 diffExp1.5=1,0,1,1,1,1,1,1 diffExp1.5Score=0.875 diffExp1.4=1,0,1,1,1,1,1,1 diffExp1.4Score=0.875 diffExp1.3=1,0,1,1,1,1,1,1 diffExp1.3Score=0.875 diffExp1.2=1,0,1,1,1,1,1,1 diffExp1.2Score=0.875 cont.predictedValues: Include Exclude Both Lung 74.4321326710244 96.7607039277983 91.9934380031293 cerebhem 90.5482820766682 85.6744955234641 82.124652529903 cortex 71.1156625896704 93.519025371885 92.5054251359392 heart 78.9109363301943 80.625754312827 93.2582809390034 kidney 81.3605595059288 76.6134979006715 79.3528560837881 liver 79.6504425565619 81.603607715783 75.1691466167523 stomach 82.3976710081364 88.0590211685834 88.4141724489259 testicle 87.5303823010718 78.4363994383226 72.5484491279673 cont.diffExp=-22.3285712567739,4.87378655320413,-22.4033627822146,-1.71481798263278,4.74706160525733,-1.9531651592211,-5.66135016044694,9.09398286274924 cont.diffExpScore=2.00228979043805 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,-1,0,0,0,0,0 cont.diffExp1.3Score=0.5 cont.diffExp1.2=-1,0,-1,0,0,0,0,0 cont.diffExp1.2Score=0.666666666666667 tran.correlation=-0.405112500647429 cont.tran.correlation=-0.56897852776817 tran.covariance=-0.0151429008495977 cont.tran.covariance=-0.00379795354360618 tran.mean=86.3606104019577 cont.tran.mean=82.952410899912 weightedLogRatios: wLogRatio Lung 4.88730988286987 cerebhem 0.530279412710858 cortex 2.28776699612958 heart 2.73876282418077 kidney 1.92280746907333 liver 7.08630467287125 stomach 2.76360294179777 testicle 3.03139036766080 cont.weightedLogRatios: wLogRatio Lung -1.16512753850541 cerebhem 0.247771057510388 cortex -1.20531064659383 heart -0.094142550154859 kidney 0.262642619639926 liver -0.106345814487204 stomach -0.295356280043155 testicle 0.484550484816616 varWeightedLogRatios=3.99390279547328 cont.varWeightedLogRatios=0.406447877186789 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.98573705491697 0.0969101707877785 41.1281604656878 1.12670720375841e-173 *** df.mm.trans1 1.07171644765633 0.0768328029734624 13.9486834552488 2.57185139052762e-38 *** df.mm.trans2 -0.0107460425968408 0.0768328029734623 -0.139862691206938 0.888817285929675 df.mm.exp2 -0.198195157112998 0.102110586050488 -1.94098540395216 0.0527466574086091 . df.mm.exp3 -0.152796090162186 0.102110586050488 -1.49637854479297 0.135101801769203 df.mm.exp4 -0.138377999882789 0.102110586050488 -1.35517780511385 0.175891189806595 df.mm.exp5 -0.35865272057871 0.102110586050488 -3.51239508508331 0.000478837228149482 *** df.mm.exp6 0.0450880388472497 0.102110586050488 0.441560866421393 0.658972433854563 df.mm.exp7 -0.235995299736143 0.102110586050488 -2.31117368790202 0.0211747857854491 * df.mm.exp8 -0.17293040169139 0.102110586050488 -1.69355997629752 0.0908886426822382 . df.mm.trans1:exp2 -0.518436244358808 0.0783152444914111 -6.61986370247067 8.23231291837396e-11 *** df.mm.trans2:exp2 0.444225493076879 0.078315244491411 5.67227359068767 2.23065315371236e-08 *** df.mm.trans1:exp3 -0.357832498794172 0.078315244491411 -4.56912956242402 5.99304480995962e-06 *** df.mm.trans2:exp3 0.192267466555117 0.078315244491411 2.45504521889353 0.0143807144011717 * df.mm.trans1:exp4 -0.275857760127705 0.078315244491411 -3.52240182507454 0.000461487628545864 *** df.mm.trans2:exp4 0.175385517981162 0.078315244491411 2.23948120343794 0.0255047751064544 * df.mm.trans1:exp5 -0.288055113531690 0.078315244491411 -3.67814868487426 0.000256904364381565 *** df.mm.trans2:exp5 0.337022244078233 0.078315244491411 4.30340537486535 1.97571182215867e-05 *** df.mm.trans1:exp6 0.367574368153088 0.078315244491411 4.69352257711972 3.35787105642428e-06 *** df.mm.trans2:exp6 -0.0537957155587992 0.078315244491411 -0.68691243841675 0.492413881668735 df.mm.trans1:exp7 -0.193563365755800 0.078315244491411 -2.47159243405067 0.0137388050682817 * df.mm.trans2:exp7 0.248967235704884 0.078315244491411 3.17903924480743 0.00155680847563442 ** df.mm.trans1:exp8 -0.187969698994445 0.078315244491411 -2.40016742864232 0.0167033864166988 * df.mm.trans2:exp8 0.198758805358179 0.078315244491411 2.53793251427539 0.0114128565618527 * df.mm.trans1:probe2 -0.0623463541973294 0.0567447856447487 -1.09871512402301 0.272350583585551 df.mm.trans1:probe3 -0.148047483848618 0.0567447856447487 -2.60900595828259 0.00931601240310182 ** df.mm.trans1:probe4 -0.0721273271290612 0.0567447856447487 -1.27108290761049 0.204211336310945 df.mm.trans1:probe5 -0.00813950811711288 0.0567447856447487 -0.143440635551438 0.885992271510192 df.mm.trans1:probe6 -0.075081644608137 0.0567447856447488 -1.32314614911379 0.186310862503957 df.mm.trans2:probe2 -0.090089881369741 0.0567447856447488 -1.58763277270531 0.112917205597533 df.mm.trans2:probe3 -0.0433730664425780 0.0567447856447487 -0.76435334013094 0.444969170765473 df.mm.trans2:probe4 -0.136648574067424 0.0567447856447487 -2.40812565445068 0.0163472962754498 * df.mm.trans2:probe5 -0.178923239766877 0.0567447856447487 -3.15312213684316 0.00169927009917138 ** df.mm.trans2:probe6 -0.0100918974942165 0.0567447856447488 -0.177847133962174 0.85890544786205 df.mm.trans3:probe2 0.041990224021516 0.0567447856447487 0.739983833658236 0.459610774942222 df.mm.trans3:probe3 -0.57647120331804 0.0567447856447487 -10.1590163178524 2.03730692849758e-22 *** df.mm.trans3:probe4 -0.534118261316329 0.0567447856447487 -9.41264039061107 1.139984232244e-19 *** df.mm.trans3:probe5 -0.560409034071228 0.0567447856447487 -9.87595649016412 2.33493045959869e-21 *** df.mm.trans3:probe6 -0.965035382423629 0.0567447856447487 -17.0065913803119 7.09189291825982e-53 *** df.mm.trans3:probe7 -0.272638735375742 0.0567447856447487 -4.80464825583445 1.97904779706507e-06 *** df.mm.trans3:probe8 -0.55984047312165 0.0567447856447487 -9.86593687438589 2.54325644374834e-21 *** df.mm.trans3:probe9 -0.426338076156744 0.0567447856447487 -7.51325555841971 2.20924320985287e-13 *** df.mm.trans3:probe10 -0.210580306949529 0.0567447856447487 -3.71100717989965 0.000226422857860718 *** df.mm.trans3:probe11 -0.226783007858147 0.0567447856447488 -3.99654356398355 7.26069415638097e-05 *** df.mm.trans3:probe12 0.116201196883378 0.0567447856447487 2.04778633953888 0.0410331040797701 * df.mm.trans3:probe13 -0.666307523585372 0.0567447856447487 -11.7421806429369 1.06810870338800e-28 *** df.mm.trans3:probe14 -0.214398645153591 0.0567447856447487 -3.77829685525355 0.000174304685052717 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.429299780276 0.227491860912162 19.4701461516736 2.79692669531076e-65 *** df.mm.trans1 -0.140325827895499 0.180361227159603 -0.778026575364359 0.436872251982789 df.mm.trans2 0.147420546973311 0.180361227159603 0.817362740844834 0.414058529073532 df.mm.exp2 0.187788694141355 0.239699580040225 0.783433555076907 0.43369400816087 df.mm.exp3 -0.0852062468630094 0.239699580040225 -0.355470989347209 0.722366684771458 df.mm.exp4 -0.137646350656208 0.239699580040225 -0.574245272491127 0.566025628608704 df.mm.exp5 0.00334801124808716 0.239699580040225 0.0139675307212692 0.98886071329281 df.mm.exp6 0.0993687517964863 0.239699580040225 0.414555385452952 0.678621489873005 df.mm.exp7 0.0471207266067298 0.239699580040225 0.196582432888795 0.844223538218656 df.mm.exp8 0.189608003457744 0.239699580040225 0.791023511288275 0.429255290795244 df.mm.trans1:exp2 0.0082067785710029 0.183841185732271 0.044640587680687 0.964409235019727 df.mm.trans2:exp2 -0.309474475359334 0.183841185732271 -1.68337945671229 0.0928425674045679 . df.mm.trans1:exp3 0.039626109658842 0.183841185732271 0.215545333332161 0.829418340864964 df.mm.trans2:exp3 0.0511301816686846 0.183841185732271 0.278121474603334 0.781018743631936 df.mm.trans1:exp4 0.196078439577031 0.183841185732271 1.06656426739208 0.286614706024968 df.mm.trans2:exp4 -0.0447764791565559 0.183841185732271 -0.243560652517572 0.80765767374128 df.mm.trans1:exp5 0.08565487804444 0.183841185732271 0.465917784979802 0.641450175507888 df.mm.trans2:exp5 -0.236815697925638 0.183841185732271 -1.28815366906148 0.198208804220115 df.mm.trans1:exp6 -0.0316088985308406 0.183841185732271 -0.171935893499256 0.863548212611944 df.mm.trans2:exp6 -0.269736239303478 0.183841185732271 -1.46722421436237 0.142859906530941 df.mm.trans1:exp7 0.0545487061042233 0.183841185732271 0.296716461477044 0.766789763971975 df.mm.trans2:exp7 -0.141354402549370 0.183841185732271 -0.768894097295618 0.442270785991811 df.mm.trans1:exp8 -0.0275097834059733 0.183841185732271 -0.149638848859667 0.88110184499561 df.mm.trans2:exp8 -0.399560865998232 0.183841185732271 -2.17340235490058 0.0301560351820201 * df.mm.trans1:probe2 0.0194443500103545 0.133205594195626 0.145972473061443 0.883994100056622 df.mm.trans1:probe3 0.0765469154737084 0.133205594195626 0.574652408075981 0.565750376569213 df.mm.trans1:probe4 0.0433619457790273 0.133205594195626 0.325526461864250 0.744900668884824 df.mm.trans1:probe5 0.262110461846431 0.133205594195626 1.96771361915548 0.0495795088777368 * df.mm.trans1:probe6 0.0168120660936637 0.133205594195626 0.126211411729251 0.899608543851042 df.mm.trans2:probe2 0.0641005180001523 0.133205594195626 0.481214909833397 0.630546197850526 df.mm.trans2:probe3 -0.168481880790907 0.133205594195626 -1.26482586417110 0.206444360006488 df.mm.trans2:probe4 -0.075155710313255 0.133205594195626 -0.56420836352324 0.572831576495325 df.mm.trans2:probe5 0.120979399266299 0.133205594195626 0.908215604583604 0.364143488731133 df.mm.trans2:probe6 -0.0310296570896618 0.133205594195626 -0.232945600198229 0.815886257314594 df.mm.trans3:probe2 0.214974498284511 0.133205594195626 1.61385488036485 0.107105620173081 df.mm.trans3:probe3 0.147183803726796 0.133205594195626 1.10493710579934 0.269647371896928 df.mm.trans3:probe4 0.0138270546260954 0.133205594195626 0.103802356872407 0.917362264820758 df.mm.trans3:probe5 0.00496067093531484 0.133205594195626 0.0372407102364604 0.970305959412725 df.mm.trans3:probe6 0.0741434828234975 0.133205594195626 0.556609377190347 0.578010152829417 df.mm.trans3:probe7 -0.0443483129981282 0.133205594195626 -0.332931310174542 0.739307065803858 df.mm.trans3:probe8 0.0800099465537558 0.133205594195626 0.600650048047178 0.548308949716838 df.mm.trans3:probe9 0.0686882723962738 0.133205594195626 0.515656063929252 0.606292163806496 df.mm.trans3:probe10 0.26866056123298 0.133205594195626 2.01688647429044 0.044170036243991 * df.mm.trans3:probe11 -0.0204333845141868 0.133205594195626 -0.153397345190911 0.878138569539972 df.mm.trans3:probe12 0.133338257389715 0.133205594195626 1.00099592809814 0.317248372379878 df.mm.trans3:probe13 0.150603542084336 0.133205594195626 1.13060973898108 0.258689116920564 df.mm.trans3:probe14 0.102910094837474 0.133205594195626 0.77256586300978 0.440095687914549