chr3.15403_chr3_138783734_138784127_+_0.R fitVsDatCorrelation=0.964148817772741 cont.fitVsDatCorrelation=0.304321303468107 fstatistic=4521.96803746094,49,623 cont.fstatistic=339.195584097707,49,623 residuals=-1.10858629088357,-0.123151706395413,0.0155099493868687,0.135922386106562,1.12206974622368 cont.residuals=-1.67180152807289,-0.72972203707036,-0.232952434119111,0.647751054845957,2.56372028562653 predictedValues: Include Exclude Both chr3.15403_chr3_138783734_138784127_+_0.R.tl.Lung 106.669275800597 43.0608123326708 130.88333271875 chr3.15403_chr3_138783734_138784127_+_0.R.tl.cerebhem 62.5660548674196 50.3428539960131 65.2652571610123 chr3.15403_chr3_138783734_138784127_+_0.R.tl.cortex 66.5323450684062 45.3134494793861 75.8494674470837 chr3.15403_chr3_138783734_138784127_+_0.R.tl.heart 82.4863887042581 44.1996718622596 101.893617313633 chr3.15403_chr3_138783734_138784127_+_0.R.tl.kidney 209.913240538939 42.0309611587237 290.575608826202 chr3.15403_chr3_138783734_138784127_+_0.R.tl.liver 453.313470047699 44.1670479976496 583.855279643739 chr3.15403_chr3_138783734_138784127_+_0.R.tl.stomach 101.714401995680 43.9500321798668 135.000679528607 chr3.15403_chr3_138783734_138784127_+_0.R.tl.testicle 547.932346470215 47.1615566973829 662.74843085003 diffExp=63.6084634679261,12.2232008714065,21.2188955890201,38.2867168419986,167.882279380215,409.146422050050,57.7643698158134,500.770789772832 diffExpScore=0.999213775371144 diffExp1.5=1,0,0,1,1,1,1,1 diffExp1.5Score=0.857142857142857 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=1,1,1,1,1,1,1,1 diffExp1.2Score=0.888888888888889 cont.predictedValues: Include Exclude Both Lung 93.7818784388356 126.340646634497 135.958596615407 cerebhem 66.9336933460788 199.519970058085 140.144940216871 cortex 62.9629803431844 156.100362503998 93.5253740753985 heart 168.147163778255 134.454810212114 111.626688151647 kidney 105.466624768282 153.279073012566 109.408134093017 liver 156.359641044422 156.847214666218 153.141658002879 stomach 77.5434204586661 237.864678793789 144.121024306833 testicle 157.115187117791 151.128452132491 153.650550188564 cont.diffExp=-32.5587681956619,-132.586276712006,-93.1373821608132,33.6923535661412,-47.8124482442839,-0.487573621796685,-160.321258335123,5.98673498529953 cont.diffExpScore=1.18298382128851 cont.diffExp1.5=0,-1,-1,0,0,0,-1,0 cont.diffExp1.5Score=0.75 cont.diffExp1.4=0,-1,-1,0,-1,0,-1,0 cont.diffExp1.4Score=0.8 cont.diffExp1.3=-1,-1,-1,0,-1,0,-1,0 cont.diffExp1.3Score=0.833333333333333 cont.diffExp1.2=-1,-1,-1,1,-1,0,-1,0 cont.diffExp1.2Score=1.2 tran.correlation=0.0322120567302738 cont.tran.correlation=-0.499760583682623 tran.covariance=-0.00741038179282861 cont.tran.covariance=-0.0417857975426181 tran.mean=124.459619324823 cont.tran.mean=137.740362331830 weightedLogRatios: wLogRatio Lung 3.82457429089233 cerebhem 0.87545099313749 cortex 1.53850590084327 heart 2.55847665869661 kidney 7.30572835214035 liver 11.5319067211832 stomach 3.52647634742268 testicle 12.4587395353222 cont.weightedLogRatios: wLogRatio Lung -1.39766071351714 cerebhem -5.18779704423135 cortex -4.17342325555421 heart 1.12097157992893 kidney -1.81150180350834 liver -0.0157343959514270 stomach -5.50486519515611 testicle 0.195704267517532 varWeightedLogRatios=20.0692630820983 cont.varWeightedLogRatios=6.57031283638032 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.46732638584712 0.133539549218756 33.4532085212376 3.07373194312019e-141 *** df.mm.trans1 0.202135448855042 0.105534163691159 1.91535557572221 0.0559046865816833 . df.mm.trans2 -0.721942674474657 0.105534163691159 -6.84084327978746 1.88482852510903e-11 *** df.mm.exp2 0.318579526032898 0.139896488377089 2.27725177185414 0.0231092953612715 * df.mm.exp3 0.124501235311404 0.139896488377089 0.889952541023135 0.373834893656233 df.mm.exp4 0.0193811700573748 0.139896488377089 0.138539360653093 0.889858931986828 df.mm.exp5 -0.144803179452944 0.139896488377089 -1.03507372581526 0.301036085482903 df.mm.exp6 -0.0231304675208806 0.139896488377089 -0.165339872281373 0.868730113258055 df.mm.exp7 -0.0580977379677483 0.139896488377089 -0.41529089573104 0.678071951242833 df.mm.exp8 0.105295242531404 0.139896488377089 0.752665372468696 0.451935319379376 df.mm.trans1:exp2 -0.85208981697116 0.106445266899955 -8.00495730610564 5.86859589111145e-15 *** df.mm.trans2:exp2 -0.162336200426732 0.106445266899955 -1.52506734357017 0.127749764496456 df.mm.trans1:exp3 -0.596546181350838 0.106445266899955 -5.60425276505263 3.14307637571293e-08 *** df.mm.trans2:exp3 -0.0735107057805031 0.106445266899955 -0.690596284094 0.490076489062147 df.mm.trans1:exp4 -0.276481043188362 0.106445266899955 -2.59740100467049 0.00961512270826163 ** df.mm.trans2:exp4 0.00672283817565019 0.106445266899955 0.0631576994585282 0.949661186295037 df.mm.trans1:exp5 0.821764317056582 0.106445266899955 7.72006441422083 4.64889357021209e-14 *** df.mm.trans2:exp5 0.120596339713149 0.106445266899955 1.13294224558142 0.257674325421118 df.mm.trans1:exp6 1.46998117309456 0.106445266899955 13.8097373035492 4.88935283530122e-38 *** df.mm.trans2:exp6 0.0484961012585319 0.106445266899955 0.455596595986856 0.648838839100379 df.mm.trans1:exp7 0.0105334760826113 0.106445266899955 0.0989567351314115 0.92120445315603 df.mm.trans2:exp7 0.078537737399021 0.106445266899955 0.737822729805698 0.460899990456902 df.mm.trans1:exp8 1.53112341399195 0.106445266899955 14.3841380512579 1.02335443732001e-40 *** df.mm.trans2:exp8 -0.0143295154489456 0.106445266899955 -0.134618624822591 0.89295689356644 df.mm.trans1:probe2 0.0061115871030417 0.078615039662451 0.0777406858698156 0.938059290100388 df.mm.trans1:probe3 -0.132060372960239 0.078615039662451 -1.67983598974530 0.0934905723953869 . df.mm.trans1:probe4 0.0650376634953798 0.078615039662451 0.82729289172443 0.408387832014642 df.mm.trans1:probe5 0.163488721734548 0.078615039662451 2.07961126059999 0.0379695545857474 * df.mm.trans1:probe6 -0.0966082787639763 0.078615039662451 -1.22887782259963 0.219581586207889 df.mm.trans2:probe2 0.0862768096266416 0.078615039662451 1.09745934107631 0.272864634255853 df.mm.trans2:probe3 0.0435401059555481 0.078615039662451 0.55383939437665 0.579887485943494 df.mm.trans2:probe4 0.084672437613037 0.078615039662451 1.07705138834242 0.281874186275171 df.mm.trans2:probe5 0.130803648830383 0.078615039662451 1.66385019192274 0.0966452455155601 . df.mm.trans2:probe6 0.0337591994106586 0.078615039662451 0.429424185952335 0.667763024224826 df.mm.trans3:probe2 0.781962758251299 0.078615039662451 9.94673235056305 9.82254407896743e-22 *** df.mm.trans3:probe3 1.37181333750013 0.078615039662451 17.4497569853081 8.13937420532763e-56 *** df.mm.trans3:probe4 1.23345342051393 0.078615039662451 15.6897894577171 5.3542466338836e-47 *** df.mm.trans3:probe5 0.849987810719134 0.078615039662451 10.8120254644496 4.33731838801358e-25 *** df.mm.trans3:probe6 0.88276033338594 0.078615039662451 11.2288989126793 8.99702382591457e-27 *** df.mm.trans3:probe7 0.54281430934654 0.078615039662451 6.90471329248474 1.2429992711287e-11 *** df.mm.trans3:probe8 0.580959832132571 0.078615039662451 7.38993244329628 4.74649558594567e-13 *** df.mm.trans3:probe9 1.1608371214797 0.078615039662451 14.7660947124619 1.58027867377647e-42 *** df.mm.trans3:probe10 1.50766423077792 0.078615039662451 19.1778091984863 8.98505511337297e-65 *** df.mm.trans3:probe11 0.861671426886619 0.078615039662451 10.9606435433522 1.10151952230897e-25 *** df.mm.trans3:probe12 1.25767173873949 0.078615039662451 15.9978516087959 1.62867555659238e-48 *** df.mm.trans3:probe13 0.823254903374337 0.078615039662451 10.4719772057502 9.5183267223153e-24 *** df.mm.trans3:probe14 0.851738354498974 0.078615039662451 10.8342927530925 3.53494866285570e-25 *** df.mm.trans3:probe15 0.555004620481108 0.078615039662451 7.05977663897555 4.46484955614077e-12 *** df.mm.trans3:probe16 1.56700062158615 0.078615039662451 19.9325806908496 9.3648359811851e-69 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.50369323475495 0.479366428920925 9.39509519866244 1.06552060361302e-19 *** df.mm.trans1 -0.0304669328168618 0.378835599444138 -0.080422570797374 0.935927003365774 df.mm.trans2 0.412903559118646 0.378835599444138 1.08992808417291 0.276166214309893 df.mm.exp2 0.0893365906771336 0.502185910048616 0.177895454431378 0.858862907205329 df.mm.exp3 0.187210265225317 0.502185910048616 0.372790756330048 0.70943097614842 df.mm.exp4 0.843304522700234 0.502185910048616 1.67926758960361 0.0936013041515876 . df.mm.exp5 0.527966532745643 0.502185910048616 1.05133681009595 0.293511546223393 df.mm.exp6 0.608464514752303 0.502185910048616 1.21163199240974 0.226112634861125 df.mm.exp7 0.384283541089022 0.502185910048616 0.765221670699244 0.444429337118077 df.mm.exp8 0.57282544979299 0.502185910048616 1.14066412125648 0.254448019477411 df.mm.trans1:exp2 -0.426605756597720 0.382106183283412 -1.11645865798854 0.264656267339506 df.mm.trans2:exp2 0.367595937518600 0.382106183283413 0.962025619056654 0.336409970307353 df.mm.trans1:exp3 -0.585634968878629 0.382106183283412 -1.53264980913501 0.125869788081322 df.mm.trans2:exp3 0.0243070808820847 0.382106183283413 0.063613419372635 0.949298450885133 df.mm.trans1:exp4 -0.259436595600552 0.382106183283412 -0.678964662050822 0.497412400400025 df.mm.trans2:exp4 -0.781058167332754 0.382106183283413 -2.04408670024959 0.041364914923708 * df.mm.trans1:exp5 -0.410543626519002 0.382106183283412 -1.07442288159597 0.283049137876570 df.mm.trans2:exp5 -0.334688069881378 0.382106183283413 -0.875903307832986 0.381420184322313 df.mm.trans1:exp6 -0.0972774132617758 0.382106183283412 -0.25458214893535 0.799129857413579 df.mm.trans2:exp6 -0.392174141885218 0.382106183283413 -1.02634858853969 0.305125629665561 df.mm.trans1:exp7 -0.574417141368264 0.382106183283412 -1.50329192904532 0.133270505131551 df.mm.trans2:exp7 0.248436590718619 0.382106183283413 0.65017683980882 0.515817676183579 df.mm.trans1:exp8 -0.0568178812758513 0.382106183283412 -0.148696576400882 0.881841180110596 df.mm.trans2:exp8 -0.39367710189027 0.382106183283413 -1.03028194547241 0.303277480378765 df.mm.trans1:probe2 0.36426241268031 0.282204118876665 1.29077638600841 0.197260019595122 df.mm.trans1:probe3 0.0724519734366483 0.282204118876665 0.256736059434742 0.797467293926437 df.mm.trans1:probe4 0.0702666753407561 0.282204118876665 0.248992380481398 0.803448738362706 df.mm.trans1:probe5 0.480303452826025 0.282204118876665 1.70197180231781 0.089259544401034 . df.mm.trans1:probe6 0.50311300518378 0.282204118876665 1.78279823549869 0.0751059779351042 . df.mm.trans2:probe2 -0.0480966326414069 0.282204118876665 -0.17043207176727 0.864725684185176 df.mm.trans2:probe3 -0.314961463010289 0.282204118876665 -1.11607677543481 0.264819555557416 df.mm.trans2:probe4 -0.451803324263417 0.282204118876665 -1.60098061666093 0.109888132952837 df.mm.trans2:probe5 -0.536597394731208 0.282204118876665 -1.90145132135979 0.0577040071591595 . df.mm.trans2:probe6 -0.356070969915492 0.282204118876665 -1.26174972687451 0.207511045531662 df.mm.trans3:probe2 -0.271601919691013 0.282204118876665 -0.962430742584997 0.336206675132285 df.mm.trans3:probe3 0.00717475226048265 0.282204118876665 0.0254239813686714 0.979724924123438 df.mm.trans3:probe4 0.110058669200573 0.282204118876665 0.389996679136614 0.696672298158886 df.mm.trans3:probe5 -0.104491991812226 0.282204118876665 -0.370270966377687 0.711306451156596 df.mm.trans3:probe6 0.211584046901101 0.282204118876665 0.749755346390152 0.453685091856721 df.mm.trans3:probe7 0.502409449258487 0.282204118876665 1.78030516088272 0.075513300195647 . df.mm.trans3:probe8 0.172265746536333 0.282204118876665 0.610429596924561 0.541799877215997 df.mm.trans3:probe9 -0.169618321792355 0.282204118876665 -0.601048356301579 0.548026392429367 df.mm.trans3:probe10 -0.0746645740087508 0.282204118876665 -0.264576485651446 0.791423241903427 df.mm.trans3:probe11 -0.0155050708109303 0.282204118876665 -0.0549427516247794 0.95620168685019 df.mm.trans3:probe12 0.116096547459509 0.282204118876665 0.411392108384668 0.680926521810914 df.mm.trans3:probe13 -0.083828072033661 0.282204118876665 -0.297047656027648 0.766529137975468 df.mm.trans3:probe14 0.103990265212477 0.282204118876665 0.368493080917523 0.71263078344739 df.mm.trans3:probe15 0.0749962779680033 0.282204118876665 0.265751890038075 0.790518215272754 df.mm.trans3:probe16 -0.159337137805473 0.282204118876665 -0.564616627282857 0.572537780725675