chr17.10431_chr17_56298484_56303714_-_1.R fitVsDatCorrelation=0.878784552719893 cont.fitVsDatCorrelation=0.312038814672272 fstatistic=6574.80257845081,43,485 cont.fstatistic=1650.41641682374,43,485 residuals=-0.68613428298676,-0.0835427186738551,-0.00226372708058873,0.0818006742392652,1.49716171730489 cont.residuals=-0.764255597966946,-0.256337431769037,-0.0452183552645781,0.223842590144705,1.65544264812527 predictedValues: Include Exclude Both chr17.10431_chr17_56298484_56303714_-_1.R.tl.Lung 66.4756191695762 53.5292932569833 89.8175176620899 chr17.10431_chr17_56298484_56303714_-_1.R.tl.cerebhem 77.8119090761118 57.0209306225684 98.5809029181022 chr17.10431_chr17_56298484_56303714_-_1.R.tl.cortex 57.5569448446008 47.9893071904364 76.750392317491 chr17.10431_chr17_56298484_56303714_-_1.R.tl.heart 57.8850745593938 48.1179953005183 85.4114509147519 chr17.10431_chr17_56298484_56303714_-_1.R.tl.kidney 65.8498996215518 53.974571213191 79.0551018188854 chr17.10431_chr17_56298484_56303714_-_1.R.tl.liver 65.0927073184359 47.7773577764174 77.9557706143381 chr17.10431_chr17_56298484_56303714_-_1.R.tl.stomach 62.029324845858 47.7457412907962 97.8350763227806 chr17.10431_chr17_56298484_56303714_-_1.R.tl.testicle 66.5951643466195 54.8333409080696 112.679898794640 diffExp=12.9463259125929,20.7909784535435,9.56763765416436,9.76707925887552,11.8753284083608,17.3153495420185,14.2835835550618,11.7618234385499 diffExpScore=0.990851547661448 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=0,1,0,0,0,1,0,0 diffExp1.3Score=0.666666666666667 diffExp1.2=1,1,0,1,1,1,1,1 diffExp1.2Score=0.875 cont.predictedValues: Include Exclude Both Lung 78.5265007077369 67.900789156349 68.9367049720267 cerebhem 59.9325726198052 73.134687503698 72.6194995761348 cortex 70.5162833723786 65.9146583528645 64.2399434676648 heart 56.4650943519139 74.3675505218838 67.8722912836294 kidney 71.6414624581213 83.4496146355084 67.6596073460628 liver 66.164213921495 67.921318102539 65.9847769864408 stomach 56.267828578464 69.0146209819127 75.7188751999686 testicle 58.7017595319367 64.0024593438789 60.186085294197 cont.diffExp=10.6257115513880,-13.2021148838928,4.60162501951403,-17.9024561699699,-11.8081521773871,-1.757104181044,-12.7467924034486,-5.30069981194215 cont.diffExpScore=1.60743830550141 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,-1,0,0,0,0 cont.diffExp1.3Score=0.5 cont.diffExp1.2=0,-1,0,-1,0,0,-1,0 cont.diffExp1.2Score=0.75 tran.correlation=0.828355412937945 cont.tran.correlation=0.0855583286889516 tran.covariance=0.00585740197113005 cont.tran.covariance=0.000797307819401264 tran.mean=58.1428238338205 cont.tran.mean=67.7450883837804 weightedLogRatios: wLogRatio Lung 0.885601452045157 cerebhem 1.30532406712954 cortex 0.72025561448265 heart 0.732940754232251 kidney 0.8129487507812 liver 1.24359353387931 stomach 1.04601856009382 testicle 0.797052282346182 cont.weightedLogRatios: wLogRatio Lung 0.623824528073973 cerebhem -0.834705998295488 cortex 0.284919294147924 heart -1.14876954415665 kidney -0.66336386135839 liver -0.110220337586358 stomach -0.843780604114411 testicle -0.35580932831792 varWeightedLogRatios=0.0524995174584412 cont.varWeightedLogRatios=0.373755925216533 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.52190505301618 0.0919420172313262 38.3057187461426 8.99250778133835e-149 *** df.mm.trans1 0.72766326680227 0.0736043929514718 9.88613909610023 4.052567787963e-21 *** df.mm.trans2 0.449863655956711 0.0736043929514718 6.11191313340919 2.02457851653766e-09 *** df.mm.exp2 0.127551073778488 0.098561296595543 1.29412942183490 0.196236598285071 df.mm.exp3 -0.0960897385064134 0.098561296595543 -0.974923644731746 0.330084136340672 df.mm.exp4 -0.194648638431918 0.0985612965955429 -1.97489932818842 0.048846264197916 * df.mm.exp5 0.126461572813876 0.098561296595543 1.28307537727334 0.200078448109804 df.mm.exp6 0.00693847580608946 0.098561296595543 0.070397570301477 0.943906242185535 df.mm.exp7 -0.269070298923641 0.098561296595543 -2.72997929428425 0.00656424361997057 ** df.mm.exp8 -0.200904920169041 0.098561296595543 -2.03837537764419 0.0420543012446938 * df.mm.trans1:exp2 0.0299081672410994 0.0773178422501045 0.386821028247965 0.699058371893927 df.mm.trans2:exp2 -0.0643617110137805 0.0773178422501046 -0.832430253363589 0.405575828658097 df.mm.trans1:exp3 -0.047970710043016 0.0773178422501046 -0.620435188657261 0.535262732313758 df.mm.trans2:exp3 -0.0131610838395239 0.0773178422501046 -0.170220526808689 0.864907691311437 df.mm.trans1:exp4 0.0562729587414573 0.0773178422501045 0.727813362398654 0.467079054181625 df.mm.trans2:exp4 0.0880758266773967 0.0773178422501045 1.13913973947297 0.255207189264947 df.mm.trans1:exp5 -0.135918920383784 0.0773178422501046 -1.75792438625122 0.0793911472746355 . df.mm.trans2:exp5 -0.118177582190579 0.0773178422501046 -1.52846456589286 0.127049136252523 df.mm.trans1:exp6 -0.0279612070328905 0.0773178422501045 -0.361639774457787 0.717778734074468 df.mm.trans2:exp6 -0.120615676791184 0.0773178422501045 -1.55999796788200 0.119412616006651 df.mm.trans1:exp7 0.199842302125076 0.0773178422501046 2.58468545305021 0.0100377916412526 * df.mm.trans2:exp7 0.154731132673926 0.0773178422501046 2.00123449091360 0.0459237960997472 * df.mm.trans1:exp8 0.202701636263198 0.0773178422501046 2.62166700937549 0.00902502442413999 ** df.mm.trans2:exp8 0.224974298275737 0.0773178422501046 2.90973327408698 0.00378359125149685 ** df.mm.trans1:probe2 -0.35445073050982 0.0529359078725103 -6.69584682222645 5.94754333412565e-11 *** df.mm.trans1:probe3 -0.0719413813028907 0.0529359078725103 -1.35902800564322 0.174769340831172 df.mm.trans1:probe4 -0.306520740239051 0.0529359078725103 -5.79041245457183 1.26296839844878e-08 *** df.mm.trans1:probe5 -0.0934670325794467 0.0529359078725103 -1.76566410846397 0.0780813661326857 . df.mm.trans1:probe6 -0.0173492099355458 0.0529359078725103 -0.327739914791473 0.743249747626567 df.mm.trans2:probe2 -0.0978381115517383 0.0529359078725103 -1.84823715099719 0.065176599971925 . df.mm.trans2:probe3 0.156276731226102 0.0529359078725103 2.95218760774775 0.00330827296204401 ** df.mm.trans2:probe4 -0.0722854975503914 0.0529359078725103 -1.36552862613563 0.172719929862815 df.mm.trans2:probe5 -0.0163306791442787 0.0529359078725103 -0.308499085037119 0.757835057151547 df.mm.trans2:probe6 0.165542878601236 0.0529359078725103 3.12723225603169 0.00187064011972274 ** df.mm.trans3:probe2 -0.0848881712465699 0.0529359078725103 -1.60360282194484 0.109452612960768 df.mm.trans3:probe3 -0.27225578074468 0.0529359078725103 -5.14312102477538 3.92850237021174e-07 *** df.mm.trans3:probe4 -0.0605408697325381 0.0529359078725103 -1.14366357668491 0.253327348296884 df.mm.trans3:probe5 0.135636483384305 0.0529359078725103 2.56227745656065 0.0106997496367939 * df.mm.trans3:probe6 -0.767459124194308 0.0529359078725103 -14.4978929244520 7.92489457361857e-40 *** df.mm.trans3:probe7 -0.333513016924332 0.0529359078725103 -6.30031731443159 6.67254966317451e-10 *** df.mm.trans3:probe8 -0.442295203500712 0.0529359078725103 -8.35529645710293 6.92092695536345e-16 *** df.mm.trans3:probe9 -0.138768676349793 0.0529359078725103 -2.62144698989578 0.00903076874797253 ** df.mm.trans3:probe10 -0.0524350937255338 0.0529359078725103 -0.99053923570778 0.322404534786236 cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.41008770662041 0.183042468118838 24.0932486976587 6.34102654485537e-85 *** df.mm.trans1 -0.0804378352227043 0.146535068034550 -0.548932322491832 0.583304514301834 df.mm.trans2 -0.198643706767959 0.146535068034550 -1.35560524475358 0.175855704807406 df.mm.exp2 -0.248005607806886 0.196220439067049 -1.26391322425969 0.206868303358757 df.mm.exp3 -0.0667157355256312 0.196220439067048 -0.340004006936477 0.734000709864227 df.mm.exp4 -0.223280573004936 0.196220439067048 -1.13790680556291 0.255721206859687 df.mm.exp5 0.133132614239934 0.196220439067048 0.67848494719983 0.497787862206919 df.mm.exp6 -0.127229422543513 0.196220439067048 -0.648400457915798 0.517032837410964 df.mm.exp7 -0.410881196616571 0.196220439067048 -2.09397756202234 0.0367805200939802 * df.mm.exp8 -0.214345021984858 0.196220439067049 -1.09236847600579 0.275213484820164 df.mm.trans1:exp2 -0.0222104080177486 0.153927976579788 -0.144290911316150 0.885330691453522 df.mm.trans2:exp2 0.322260726438228 0.153927976579788 2.09358125532940 0.0368160108950831 * df.mm.trans1:exp3 -0.0408767679563288 0.153927976579788 -0.265557755416478 0.790692663318255 df.mm.trans2:exp3 0.0370289287459155 0.153927976579788 0.24056009549844 0.809997731928225 df.mm.trans1:exp4 -0.106532935292060 0.153927976579788 -0.692095989690597 0.489208250137755 df.mm.trans2:exp4 0.314252613974774 0.153927976579788 2.04155619372987 0.0417361708165794 * df.mm.trans1:exp5 -0.224894779719225 0.153927976579788 -1.46103901783345 0.144652266603491 df.mm.trans2:exp5 0.0730627611192196 0.153927976579788 0.474655502804896 0.635246187415977 df.mm.trans1:exp6 -0.0440669923327128 0.153927976579788 -0.286283191086259 0.774783475367321 df.mm.trans2:exp6 0.127531714221366 0.153927976579788 0.828515498319826 0.407786149303446 df.mm.trans1:exp7 0.0775679835365614 0.153927976579788 0.503923882195347 0.614543689648358 df.mm.trans2:exp7 0.427151920225947 0.153927976579788 2.77501159774249 0.0057331123476813 ** df.mm.trans1:exp8 -0.0766214330916607 0.153927976579788 -0.49777457479891 0.618868552241235 df.mm.trans2:exp8 0.155218875025127 0.153927976579788 1.00838637961741 0.313771823263751 df.mm.trans1:probe2 0.165830027213079 0.105387281254846 1.57352979637145 0.116248272322660 df.mm.trans1:probe3 0.0935338575905393 0.105387281254846 0.88752510243012 0.375236165368062 df.mm.trans1:probe4 0.0437142287283002 0.105387281254846 0.414796057055414 0.678474619436863 df.mm.trans1:probe5 0.0248725088052728 0.105387281254846 0.236010536652202 0.813524125944358 df.mm.trans1:probe6 0.212629938527217 0.105387281254846 2.01760531247635 0.0441826295142377 * df.mm.trans2:probe2 -0.102239625134803 0.105387281254846 -0.970132485793691 0.332464007732567 df.mm.trans2:probe3 0.117805155830669 0.105387281254846 1.11783086562214 0.26419263248561 df.mm.trans2:probe4 0.0576999846266706 0.105387281254846 0.547504252312394 0.584284205643227 df.mm.trans2:probe5 0.023768202696631 0.105387281254846 0.225531984634417 0.821660447850428 df.mm.trans2:probe6 0.00862479360883157 0.105387281254846 0.0818390369894371 0.934808475348885 df.mm.trans3:probe2 0.0245757860326005 0.105387281254846 0.233194990324987 0.815708380894987 df.mm.trans3:probe3 0.104518929085393 0.105387281254846 0.991760370330145 0.321808961176836 df.mm.trans3:probe4 0.228624917237882 0.105387281254846 2.16937864337751 0.0305389395813705 * df.mm.trans3:probe5 0.108981660547343 0.105387281254846 1.03410638598603 0.301601780985048 df.mm.trans3:probe6 0.157431732690522 0.105387281254846 1.49383996641704 0.135867726550071 df.mm.trans3:probe7 0.00889662246505916 0.105387281254846 0.0844183696469545 0.932758636205527 df.mm.trans3:probe8 0.0890302893881945 0.105387281254846 0.844791594660294 0.398643738759214 df.mm.trans3:probe9 0.0927175905543181 0.105387281254846 0.879779698748557 0.379414367577688 df.mm.trans3:probe10 0.207048469266125 0.105387281254846 1.96464380521823 0.0500259602822616 .