chr15.8439_chr15_99506305_99507439_-_0.R fitVsDatCorrelation=0.756750618166685 cont.fitVsDatCorrelation=0.283940302380774 fstatistic=6517.70269403296,36,324 cont.fstatistic=3024.62313843621,36,324 residuals=-0.522157488102695,-0.094011503022938,-0.0217898400914722,0.0874074600444053,0.701228129997553 cont.residuals=-0.471496519586701,-0.152748627489725,-0.0310906924522562,0.101405712758159,0.957652365484925 predictedValues: Include Exclude Both chr15.8439_chr15_99506305_99507439_-_0.R.tl.Lung 55.3489351342328 53.584965050531 70.1800764710435 chr15.8439_chr15_99506305_99507439_-_0.R.tl.cerebhem 57.0835442605065 68.8849092419658 68.1531498691149 chr15.8439_chr15_99506305_99507439_-_0.R.tl.cortex 58.5206267345928 54.7533517104821 65.7913730619029 chr15.8439_chr15_99506305_99507439_-_0.R.tl.heart 78.6784181228044 52.3933482106522 93.494021092236 chr15.8439_chr15_99506305_99507439_-_0.R.tl.kidney 55.3990701530942 54.5811283133744 71.6195340066183 chr15.8439_chr15_99506305_99507439_-_0.R.tl.liver 47.1369025499798 53.8332574694675 59.0629031134242 chr15.8439_chr15_99506305_99507439_-_0.R.tl.stomach 63.245097928549 54.7159723997656 79.1283321060145 chr15.8439_chr15_99506305_99507439_-_0.R.tl.testicle 51.9061734615093 57.477157982123 67.1362637601597 diffExp=1.76397008370181,-11.8013649814592,3.76727502411072,26.2850699121523,0.817941839719786,-6.6963549194877,8.5291255287834,-5.57098452061374 diffExpScore=3.6050427053374 diffExp1.5=0,0,0,1,0,0,0,0 diffExp1.5Score=0.5 diffExp1.4=0,0,0,1,0,0,0,0 diffExp1.4Score=0.5 diffExp1.3=0,0,0,1,0,0,0,0 diffExp1.3Score=0.5 diffExp1.2=0,-1,0,1,0,0,0,0 diffExp1.2Score=2 cont.predictedValues: Include Exclude Both Lung 60.3168556782872 60.9216495836177 77.8194630771265 cerebhem 58.1562657999319 64.7416309584031 61.267311432403 cortex 61.6135953727617 60.5627203874781 55.0449233545302 heart 62.8496598283808 64.0948094780104 58.9126866981624 kidney 60.341577496657 64.0653956134688 57.8901227548955 liver 62.6922877176502 60.8268669704745 60.9338606616102 stomach 54.7990596269117 61.7353647626793 59.9036854562039 testicle 55.9977294681402 59.8746830486893 64.0048526584525 cont.diffExp=-0.604793905330482,-6.58536515847123,1.05087498528362,-1.24514964962961,-3.72381811681178,1.86542074717572,-6.93630513576763,-3.87695358054912 cont.diffExpScore=1.22951039379033 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=0,0,0,0,0,0,0,0 cont.diffExp1.2Score=0 tran.correlation=-0.200213523974834 cont.tran.correlation=0.150334883346266 tran.covariance=-0.00246218115752187 cont.tran.covariance=0.000242683904739125 tran.mean=57.3464286702269 cont.tran.mean=60.8493844869714 weightedLogRatios: wLogRatio Lung 0.12947340555282 cerebhem -0.777707663445717 cortex 0.268565516132320 heart 1.69225464276762 kidney 0.0596044757076386 liver -0.520644311209984 stomach 0.590252585858673 testicle -0.407841608631103 cont.weightedLogRatios: wLogRatio Lung -0.0409516384423846 cerebhem -0.441609169735587 cortex 0.0707436597031294 heart -0.0814250073252299 kidney -0.247314530669522 liver 0.124546940709861 stomach -0.484275791452701 testicle -0.271705521156362 varWeightedLogRatios=0.601881210619718 cont.varWeightedLogRatios=0.0511512585136781 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.42229879681096 0.0908219469613964 37.6814075376031 1.8746590896258e-120 *** df.mm.trans1 0.569532688289719 0.0769252403375225 7.40371672276613 1.15248423430067e-12 *** df.mm.trans2 0.521152131536771 0.0769252403375225 6.77478717323634 5.882906979978e-11 *** df.mm.exp2 0.311334150437777 0.107127724174277 2.90619587821444 0.00391044841495371 ** df.mm.exp3 0.141867663523809 0.107127724174277 1.32428523631303 0.186341742460865 df.mm.exp4 0.0423895537836362 0.107127724174277 0.395691723224478 0.692592882226134 df.mm.exp5 -0.00097834733407773 0.107127724174277 -0.00913253167299755 0.992719015779252 df.mm.exp6 0.0164831158616107 0.107127724174277 0.153864146640470 0.877812644743494 df.mm.exp7 0.0342408104498991 0.107127724174277 0.31962604184698 0.749457825375697 df.mm.exp8 0.0502395207964418 0.107127724174277 0.468968431689181 0.63940759538687 df.mm.trans1:exp2 -0.280475687098141 0.0927753305845361 -3.02317098016238 0.00270103136952723 ** df.mm.trans2:exp2 -0.0601655464116849 0.0927753305845361 -0.648508025060202 0.51711577419902 df.mm.trans1:exp3 -0.0861457978811746 0.0927753305845361 -0.928542074044988 0.353817680154664 df.mm.trans2:exp3 -0.120297604184569 0.0927753305845362 -1.29665508521098 0.195672591731716 df.mm.trans1:exp4 0.309321914132023 0.0927753305845362 3.33409659855829 0.000954942376387337 *** df.mm.trans2:exp4 -0.0648784389992226 0.0927753305845361 -0.699307009637717 0.484861906331377 df.mm.trans1:exp5 0.00188373650395241 0.0927753305845361 0.0203042823138848 0.983813137797669 df.mm.trans2:exp5 0.0193980091132221 0.0927753305845362 0.209085852790864 0.834512612558811 df.mm.trans1:exp6 -0.177084348182335 0.0927753305845361 -1.90874392003354 0.0571785059295333 . df.mm.trans2:exp6 -0.0118601970437902 0.0927753305845362 -0.127837831124549 0.898356618526731 df.mm.trans1:exp7 0.0991193908459351 0.0927753305845361 1.06838089631616 0.28614407972817 df.mm.trans2:exp7 -0.0133536695898410 0.0927753305845361 -0.143935564612979 0.885640834337899 df.mm.trans1:exp8 -0.114459208738793 0.0927753305845361 -1.23372461211010 0.218199743736930 df.mm.trans2:exp8 0.019879569656484 0.0927753305845362 0.214276462624619 0.830466263090928 df.mm.trans1:probe2 0.0733928836467201 0.0463876652922681 1.58216377531191 0.114587821378870 df.mm.trans1:probe3 0.0259278346274966 0.0463876652922681 0.558938124265078 0.57659005824253 df.mm.trans1:probe4 0.0157005045090287 0.0463876652922681 0.338462917029921 0.735233592009842 df.mm.trans1:probe5 -0.0475523273677032 0.0463876652922681 -1.02510715010331 0.306077362443353 df.mm.trans1:probe6 0.128964520499350 0.0463876652922681 2.78014682754138 0.00575101539928472 ** df.mm.trans2:probe2 0.153495392827929 0.0463876652922681 3.30897000012445 0.00104179162190281 ** df.mm.trans2:probe3 -0.0427978186509324 0.0463876652922681 -0.922612043121428 0.356895941113856 df.mm.trans2:probe4 0.0704319981490467 0.0463876652922681 1.51833461988841 0.129905203519094 df.mm.trans2:probe5 0.0912316562550076 0.0463876652922681 1.96672231034258 0.0500683941159535 . df.mm.trans2:probe6 0.0679971497484011 0.0463876652922681 1.46584548543198 0.143660181780579 df.mm.trans3:probe2 -0.446392068532439 0.0463876652922681 -9.62307686148723 1.91204595674443e-19 *** df.mm.trans3:probe3 -0.339365401991848 0.0463876652922681 -7.31585433010385 2.02540396390483e-12 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.91996205048373 0.133216159328627 29.4255747218599 1.55796503248489e-93 *** df.mm.trans1 0.185270157411023 0.112832695356686 1.64198999966586 0.101562283410552 df.mm.trans2 0.242289550246287 0.112832695356686 2.14733459552980 0.0325082660622834 * df.mm.exp2 0.263482988485101 0.157133208982842 1.67681287864408 0.0945435727672155 . df.mm.exp3 0.36160380630343 0.157133208982842 2.30125642214126 0.0220114714254712 * df.mm.exp4 0.370243813996479 0.157133208982842 2.35624166522881 0.0190560142184652 * df.mm.exp5 0.346570333876695 0.157133208982842 2.20558299623689 0.0281149878111432 * df.mm.exp6 0.281672362461061 0.157133208982842 1.79257054752708 0.073974398116754 . df.mm.exp7 0.178983310661469 0.157133208982842 1.13905463918205 0.255521818807598 df.mm.exp8 0.103797371060399 0.157133208982842 0.66056928215431 0.509357946307876 df.mm.trans1:exp2 -0.299960957953566 0.136081350757311 -2.2042767527236 0.0282075703657239 * df.mm.trans2:exp2 -0.202667153393542 0.136081350757311 -1.48930880143144 0.137378807313873 df.mm.trans1:exp3 -0.340332851003921 0.136081350757311 -2.50095144639530 0.0128793093381306 * df.mm.trans2:exp3 -0.367512883176846 0.136081350757311 -2.70068514996058 0.00728339652353 ** df.mm.trans1:exp4 -0.329109886402807 0.136081350757311 -2.41847898019286 0.0161364251034545 * df.mm.trans2:exp4 -0.319469034257298 0.136081350757311 -2.34763273938281 0.0194943922550492 * df.mm.trans1:exp5 -0.346160552014537 0.136081350757311 -2.54377657252892 0.0114302598676062 * df.mm.trans2:exp5 -0.296254571272154 0.136081350757311 -2.17704020149314 0.0301990244534134 * df.mm.trans1:exp6 -0.243045520287628 0.136081350757311 -1.78603106843846 0.0750292925284026 . df.mm.trans2:exp6 -0.283229385658953 0.136081350757311 -2.08132403215242 0.0381891410239351 * df.mm.trans1:exp7 -0.274921871939262 0.136081350757311 -2.02027588945352 0.0441772938952225 * df.mm.trans2:exp7 -0.165714976662732 0.136081350757311 -1.21776404878778 0.224199758508133 df.mm.trans1:exp8 -0.178097821350685 0.136081350757311 -1.30875994660214 0.191543211053281 df.mm.trans2:exp8 -0.121132214420112 0.136081350757311 -0.890145591192296 0.374048187843118 df.mm.trans1:probe2 -0.00495645383698434 0.0680406753786553 -0.0728454532439754 0.941974049018214 df.mm.trans1:probe3 -0.0392561971923811 0.0680406753786553 -0.576951903753383 0.564372589149082 df.mm.trans1:probe4 -0.0408585534471705 0.0680406753786553 -0.600501879497629 0.548591613653665 df.mm.trans1:probe5 0.0595784515140932 0.0680406753786553 0.875629925519277 0.381879928736775 df.mm.trans1:probe6 -0.0250927631652406 0.0680406753786553 -0.368790624513882 0.712524659025007 df.mm.trans2:probe2 -0.117939936351414 0.0680406753786553 -1.73337398100567 0.0839805838656929 . df.mm.trans2:probe3 -0.0806504347543985 0.0680406753786553 -1.18532678145195 0.236756900184177 df.mm.trans2:probe4 -0.0842522163919188 0.0680406753786553 -1.23826249406027 0.216515189488395 df.mm.trans2:probe5 -0.108545753697611 0.0680406753786553 -1.59530682336028 0.111618565364679 df.mm.trans2:probe6 -0.0825786156344186 0.0680406753786553 -1.21366543137407 0.225759485285743 df.mm.trans3:probe2 0.0171514860146809 0.0680406753786553 0.252076951312294 0.80114141147517 df.mm.trans3:probe3 0.00345794351417161 0.0680406753786553 0.0508217106154179 0.959498907305748