chr6.19543_chr6_121553259_121553475_+_1.R fitVsDatCorrelation=0.671179373901578 cont.fitVsDatCorrelation=0.366492906057305 fstatistic=5744.80130541607,36,324 cont.fstatistic=3643.39815993828,36,324 residuals=-0.563139357166304,-0.0848837131920009,-0.00280452860343116,0.0728472868844359,0.92248292706156 cont.residuals=-0.414062873080825,-0.114988836114441,-0.0216485751773260,0.080277059741683,1.15574750580952 predictedValues: Include Exclude Both chr6.19543_chr6_121553259_121553475_+_1.R.tl.Lung 52.326596834972 52.2762843728415 52.418909738211 chr6.19543_chr6_121553259_121553475_+_1.R.tl.cerebhem 68.3829802632765 68.0107161185358 60.5029172135067 chr6.19543_chr6_121553259_121553475_+_1.R.tl.cortex 49.4709040916698 46.8515806994144 49.6259707656571 chr6.19543_chr6_121553259_121553475_+_1.R.tl.heart 52.3177385208235 49.4873131555715 55.1111063075038 chr6.19543_chr6_121553259_121553475_+_1.R.tl.kidney 49.1378930038513 49.6879429256005 51.4375378867313 chr6.19543_chr6_121553259_121553475_+_1.R.tl.liver 50.8861591910356 48.1570100859493 55.9411935980026 chr6.19543_chr6_121553259_121553475_+_1.R.tl.stomach 53.1261857921806 49.0516629050217 51.7834136735977 chr6.19543_chr6_121553259_121553475_+_1.R.tl.testicle 58.1413878526143 51.1581855890353 59.9228205148311 diffExp=0.0503124621304423,0.372264144740782,2.61932339225536,2.83042536525202,-0.550049921749185,2.72914910508635,4.07452288715891,6.98320226357895 diffExpScore=1.00497782576585 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=0,0,0,0,0,0,0,0 diffExp1.3Score=0 diffExp1.2=0,0,0,0,0,0,0,0 diffExp1.2Score=0 cont.predictedValues: Include Exclude Both Lung 52.0280229323888 53.1276149815518 55.2891371897542 cerebhem 49.8254407836061 52.07157878669 54.5331949050915 cortex 48.0127951053725 54.6152941713859 47.6279012866162 heart 54.9124420173843 51.2527411926399 60.7856811091689 kidney 52.3124195974155 58.1170039362039 60.297166141626 liver 55.107827122955 50.5618487533139 55.515231287706 stomach 51.6927089437977 49.0552425658471 53.1001824099682 testicle 50.6951182999346 50.4068614780121 56.7221624489912 cont.diffExp=-1.09959204916301,-2.24613800308387,-6.60249906601345,3.65970082474441,-5.80458433878844,4.54597836964107,2.63746637795057,0.288256821922417 cont.diffExpScore=4.78246752479309 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=0.931015738396516 cont.tran.correlation=-0.242232683207437 tran.covariance=0.0117732517751826 cont.tran.covariance=-0.00062197118921454 tran.mean=53.0294088376496 cont.tran.mean=52.1121850417812 weightedLogRatios: wLogRatio Lung 0.00380654190672462 cerebhem 0.0230487195311189 cortex 0.210755466635288 heart 0.218556872866572 kidney -0.0434162758449467 liver 0.215096408819536 stomach 0.313818925770524 testicle 0.51168028714001 cont.weightedLogRatios: wLogRatio Lung -0.0828677591847692 cerebhem -0.173312991300878 cortex -0.50712541855588 heart 0.273900800855259 kidney -0.4219339513013 liver 0.341471619823535 stomach 0.205243695286581 testicle 0.0223700538985012 varWeightedLogRatios=0.0338791443801869 cont.varWeightedLogRatios=0.0988166566664622 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.00315815774050 0.0936293625425896 42.7553712748986 2.94213015251114e-135 *** df.mm.trans1 0.0756321143765217 0.0793030920081367 0.953709527098409 0.340941666900133 df.mm.trans2 -0.151863899801124 0.0793030920081367 -1.91498081544592 0.0563752340012522 . df.mm.exp2 0.387317466608023 0.110439170934524 3.5070660466806 0.000517022623756108 *** df.mm.exp3 -0.110925053477181 0.110439170934524 -1.00439954898742 0.31593558820695 df.mm.exp4 -0.105079644122237 0.110439170934524 -0.951470780096091 0.342074673878774 df.mm.exp5 -0.094755620592492 0.110439170934524 -0.857989242319375 0.391532641632077 df.mm.exp6 -0.175023544485499 0.110439170934524 -1.58479589265719 0.113988229710719 df.mm.exp7 -0.03630606412698 0.110439170934524 -0.328742635604398 0.742562602728441 df.mm.exp8 -0.0500373340203294 0.110439170934524 -0.453075965682458 0.650797303327659 df.mm.trans1:exp2 -0.119698284998339 0.0956431276021896 -1.25150952294453 0.211651461541915 df.mm.trans2:exp2 -0.124194998424957 0.0956431276021896 -1.29852506435720 0.195030431406181 df.mm.trans1:exp3 0.0548049686080027 0.0956431276021896 0.573015228401502 0.567031840016473 df.mm.trans2:exp3 0.00136698661888513 0.0956431276021896 0.0142925754641867 0.988605359687015 df.mm.trans1:exp4 0.104910340850549 0.0956431276021896 1.09689366586698 0.273502449468958 df.mm.trans2:exp4 0.0502531664034956 0.0956431276021896 0.525423704382762 0.599648062420141 df.mm.trans1:exp5 0.031881323855688 0.0956431276021896 0.333336274701227 0.739096068138904 df.mm.trans2:exp5 0.0439751126377215 0.0956431276021896 0.459783297976495 0.645980141421725 df.mm.trans1:exp6 0.147109723977870 0.0956431276021896 1.53811076306232 0.124997529262656 df.mm.trans2:exp6 0.0929474460703806 0.0956431276021896 0.971815209316228 0.331867427552940 df.mm.trans1:exp7 0.0514712264203728 0.0956431276021896 0.538159172653346 0.590836652571783 df.mm.trans2:exp7 -0.0273626627487766 0.0956431276021896 -0.286091258564721 0.774991059236582 df.mm.trans1:exp8 0.155410314244082 0.0956431276021896 1.62489786919645 0.105156651877575 df.mm.trans2:exp8 0.0284170301250322 0.0956431276021896 0.297115232818690 0.766568927882542 df.mm.trans1:probe2 -0.273375474829792 0.0478215638010948 -5.71657330084077 2.46768874704435e-08 *** df.mm.trans1:probe3 -0.177102570482125 0.0478215638010948 -3.70340399612927 0.000249991520635700 *** df.mm.trans1:probe4 -0.255968431033079 0.0478215638010948 -5.35257341432274 1.64463158411495e-07 *** df.mm.trans1:probe5 -0.0942959058757703 0.0478215638010948 -1.97182815409335 0.0494795731791918 * df.mm.trans1:probe6 -0.290826997367826 0.0478215638010948 -6.08150328536868 3.35118008286175e-09 *** df.mm.trans2:probe2 0.14383263490843 0.0478215638010948 3.00769409186776 0.00283844406547616 ** df.mm.trans2:probe3 0.227112595037790 0.0478215638010948 4.74916704904138 3.07250449270745e-06 *** df.mm.trans2:probe4 0.328795948693977 0.0478215638010948 6.87547463026396 3.1864411909671e-11 *** df.mm.trans2:probe5 0.0981077509656472 0.0478215638010948 2.05153790816437 0.0410181619840488 * df.mm.trans2:probe6 0.149388079939340 0.0478215638010948 3.12386438387279 0.00194612627818931 ** df.mm.trans3:probe2 -0.0117162278931316 0.0478215638010948 -0.244998844911536 0.806612423312703 df.mm.trans3:probe3 0.10873930822943 0.0478215638010948 2.2738551311645 0.02362850681635 * cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.85208874880959 0.117516930453768 32.7790109385562 6.54585116728541e-105 *** df.mm.trans1 0.0830187408867974 0.0995356124960238 0.834060682452864 0.404861284914321 df.mm.trans2 0.119864219243334 0.0995356124960238 1.20423450700243 0.229377935394795 df.mm.exp2 -0.0495674673413481 0.13861540885938 -0.357589879431315 0.720883076604444 df.mm.exp3 0.0964598755053642 0.13861540885938 0.695881333100702 0.487001998904501 df.mm.exp4 -0.0767480666328786 0.13861540885938 -0.553676299513978 0.580182283151031 df.mm.exp5 0.00850412226513889 0.13861540885938 0.06135048285841 0.95111791369679 df.mm.exp6 0.00392878296735204 0.13861540885938 0.0283430464165614 0.977405997985634 df.mm.exp7 -0.0458194258805259 0.13861540885938 -0.330550739326592 0.741197508411056 df.mm.exp8 -0.104110950403485 0.13861540885938 -0.751077757229007 0.453151021328805 df.mm.trans1:exp2 0.0063107040648855 0.120044465428190 0.0525697210810651 0.958107139365268 df.mm.trans2:exp2 0.0294899053076757 0.120044465428190 0.245658183428011 0.80610238237381 df.mm.trans1:exp3 -0.176774811395806 0.120044465428190 -1.47257777162207 0.141835652716720 df.mm.trans2:exp3 -0.0688427681650991 0.120044465428190 -0.573477235452231 0.566719438905149 df.mm.trans1:exp4 0.130705544053451 0.120044465428190 1.08880941397201 0.277047142375174 df.mm.trans2:exp4 0.0408203206913795 0.120044465428190 0.340043337656397 0.734044233281693 df.mm.trans1:exp5 -0.00305278695513008 0.120044465428190 -0.0254304681539546 0.979727264191466 df.mm.trans2:exp5 0.0812573162749404 0.120044465428190 0.676893482636635 0.498956516032617 df.mm.trans1:exp6 0.0535805001795864 0.120044465428190 0.446338779455336 0.655650701370335 df.mm.trans2:exp6 -0.0534283174802478 0.120044465428190 -0.445071060041569 0.656565596410469 df.mm.trans1:exp7 0.0393536952460859 0.120044465428190 0.327825986027046 0.743254972144755 df.mm.trans2:exp7 -0.0339303609585021 0.120044465428190 -0.282648274016424 0.777626953412905 df.mm.trans1:exp8 0.078158094395946 0.120044465428190 0.651076200116032 0.515458782351869 df.mm.trans2:exp8 0.0515414074359769 0.120044465428190 0.429352634060492 0.66795198372278 df.mm.trans1:probe2 0.0455305420347641 0.0600222327140948 0.75856128597616 0.448666481268448 df.mm.trans1:probe3 0.0285817116931638 0.0600222327140948 0.476185413316891 0.634263231961299 df.mm.trans1:probe4 -0.0418680849396392 0.0600222327140948 -0.697542944446441 0.485963315448446 df.mm.trans1:probe5 0.0819835535080846 0.0600222327140948 1.36588643575787 0.172921973887465 df.mm.trans1:probe6 0.0358471541799759 0.0600222327140948 0.597231268465594 0.550770118998567 df.mm.trans2:probe2 -0.0223786886030861 0.0600222327140948 -0.372839989303347 0.709511325598091 df.mm.trans2:probe3 -0.0724080199072236 0.0600222327140948 -1.20635332331148 0.22856140021772 df.mm.trans2:probe4 0.148233689475468 0.0600222327140948 2.46964637556141 0.0140396277177075 * df.mm.trans2:probe5 -0.0271678317086645 0.0600222327140948 -0.452629475449099 0.651118493322577 df.mm.trans2:probe6 -0.0195842187949981 0.0600222327140948 -0.326282744067254 0.744421094284078 df.mm.trans3:probe2 -0.050539003157825 0.0600222327140948 -0.842004718460883 0.400406379932220 df.mm.trans3:probe3 -0.076646758508609 0.0600222327140948 -1.27697279895772 0.202526241850598