chr8.23596_chr8_24287309_24287822_+_0.R fitVsDatCorrelation=0.956000301986614 cont.fitVsDatCorrelation=0.307366463023404 fstatistic=5400.36847085779,43,485 cont.fstatistic=503.057329849161,43,485 residuals=-0.872344266423418,-0.111971106699238,-0.00353864590598382,0.117251756182458,1.03323083959658 cont.residuals=-1.14012575314509,-0.51327590194388,-0.221839863327172,0.410788247014293,2.07855119671626 predictedValues: Include Exclude Both chr8.23596_chr8_24287309_24287822_+_0.R.tl.Lung 63.2026892499893 305.385332852530 77.6247230313315 chr8.23596_chr8_24287309_24287822_+_0.R.tl.cerebhem 71.6197680076985 239.225333741383 82.3456448409706 chr8.23596_chr8_24287309_24287822_+_0.R.tl.cortex 60.7530469513718 337.950214577409 80.9970857434743 chr8.23596_chr8_24287309_24287822_+_0.R.tl.heart 59.8164703439923 305.579350336988 79.9517196584064 chr8.23596_chr8_24287309_24287822_+_0.R.tl.kidney 67.5158571504752 391.641871411562 71.8039233159278 chr8.23596_chr8_24287309_24287822_+_0.R.tl.liver 65.5271358341724 442.502579038563 62.7141087577934 chr8.23596_chr8_24287309_24287822_+_0.R.tl.stomach 57.2186154692325 432.128282915358 76.0924645338727 chr8.23596_chr8_24287309_24287822_+_0.R.tl.testicle 61.2676612757283 395.872265621655 68.1660464047097 diffExp=-242.182643602541,-167.605565733684,-277.197167626038,-245.762879992995,-324.126014261087,-376.975443204391,-374.909667446125,-334.604604345926 diffExpScore=0.99957344507684 diffExp1.5=-1,-1,-1,-1,-1,-1,-1,-1 diffExp1.5Score=0.888888888888889 diffExp1.4=-1,-1,-1,-1,-1,-1,-1,-1 diffExp1.4Score=0.888888888888889 diffExp1.3=-1,-1,-1,-1,-1,-1,-1,-1 diffExp1.3Score=0.888888888888889 diffExp1.2=-1,-1,-1,-1,-1,-1,-1,-1 diffExp1.2Score=0.888888888888889 cont.predictedValues: Include Exclude Both Lung 131.399680336503 120.032841121149 83.3607637559843 cerebhem 83.6479757140321 109.350715355113 82.1212792707829 cortex 97.1500938588679 93.2924124227149 105.309011979298 heart 164.150223397670 80.5942316049551 137.772666580336 kidney 70.1700832162587 118.161114573001 106.963894333294 liver 119.875450346590 113.244592432890 105.541530698158 stomach 111.340026321806 98.7297869366165 100.215303841525 testicle 144.719249839365 156.843446068069 146.085995153711 cont.diffExp=11.3668392153539,-25.7027396410812,3.857681436153,83.5559917927151,-47.9910313567419,6.63085791370008,12.6102393851891,-12.1241962287035 cont.diffExpScore=6.13907274985941 cont.diffExp1.5=0,0,0,1,-1,0,0,0 cont.diffExp1.5Score=2 cont.diffExp1.4=0,0,0,1,-1,0,0,0 cont.diffExp1.4Score=2 cont.diffExp1.3=0,-1,0,1,-1,0,0,0 cont.diffExp1.3Score=1.5 cont.diffExp1.2=0,-1,0,1,-1,0,0,0 cont.diffExp1.2Score=1.5 tran.correlation=-0.409508219567479 cont.tran.correlation=0.0235575070928659 tran.covariance=-0.00680284788671584 cont.tran.covariance=-0.00285331561610397 tran.mean=209.825404673632 cont.tran.mean=113.2938702216 weightedLogRatios: wLogRatio Lung -7.77211050340916 cerebhem -5.8786821979907 cortex -8.52010009035784 heart -8.00255038794621 kidney -8.95052772091101 liver -9.81244691906656 stomach -10.2260803660452 testicle -9.41907819927294 cont.weightedLogRatios: wLogRatio Lung 0.437281994605534 cerebhem -1.22197811332694 cortex 0.184601574268581 heart 3.37545349072787 kidney -2.35105700800756 liver 0.270745879849798 stomach 0.559238917571844 testicle -0.403471007098527 varWeightedLogRatios=1.90803738445664 cont.varWeightedLogRatios=2.72829050612809 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.46277860586442 0.112886851249773 48.3916288335255 9.00991760188143e-188 *** df.mm.trans1 -1.36100441350904 0.0903718279047247 -15.0600518442970 2.51252120893930e-42 *** df.mm.trans2 0.346793453362608 0.0903718279047247 3.83740664987122 0.000140782085500539 *** df.mm.exp2 -0.178183762216683 0.121014034310038 -1.4724222957494 0.141555492135898 df.mm.exp3 0.0192674064093643 0.121014034310038 0.159216296847035 0.873564744085644 df.mm.exp4 -0.0839676623190399 0.121014034310038 -0.693867143573734 0.48809772100254 df.mm.exp5 0.392735957997508 0.121014034310038 3.24537530077973 0.00125402008949205 ** df.mm.exp6 0.620288949706406 0.121014034310038 5.12576043962988 4.28786676310549e-07 *** df.mm.exp7 0.267617301610496 0.121014034310038 2.21145673835533 0.0274697956193270 * df.mm.exp8 0.358361920235849 0.121014034310038 2.96132528990584 0.00321338715396766 ** df.mm.trans1:exp2 0.303208035899181 0.094931218825457 3.19397601390399 0.00149457597913313 ** df.mm.trans2:exp2 -0.0659846766329738 0.0949312188254571 -0.69507878914201 0.487338794947093 df.mm.trans1:exp3 -0.0587970215397252 0.0949312188254571 -0.619364443722468 0.535967131501093 df.mm.trans2:exp3 0.0820568184670324 0.0949312188254571 0.86438180697863 0.387805482792804 df.mm.trans1:exp4 0.028901857494624 0.094931218825457 0.304450504820376 0.760915283686924 df.mm.trans2:exp4 0.0846027808334729 0.094931218825457 0.891200828138799 0.373263337885032 df.mm.trans1:exp5 -0.326720318632208 0.0949312188254571 -3.44165304811818 0.000628162477005573 *** df.mm.trans2:exp5 -0.14396249473374 0.0949312188254571 -1.51649264082907 0.130046315557315 df.mm.trans1:exp6 -0.58417145698538 0.094931218825457 -6.15362853456514 1.58716568064411e-09 *** df.mm.trans2:exp6 -0.249417022547766 0.094931218825457 -2.62734457256206 0.00887792055222164 ** df.mm.trans1:exp7 -0.367084862575673 0.0949312188254571 -3.86685083281827 0.000125277430412919 *** df.mm.trans2:exp7 0.0795308281371954 0.0949312188254571 0.837773170103533 0.402570763904603 df.mm.trans1:exp8 -0.3894566166877 0.0949312188254571 -4.102513604126 4.79325666427406e-05 *** df.mm.trans2:exp8 -0.098844688185114 0.0949312188254571 -1.04122426118696 0.29829023261115 df.mm.trans1:probe2 0.100126679854584 0.0649949624527024 1.54052985148576 0.124083415535567 df.mm.trans1:probe3 0.189398269286425 0.0649949624527024 2.91404536811991 0.0037326182953972 ** df.mm.trans1:probe4 0.00977720830557232 0.0649949624527024 0.150430247770161 0.88048771937479 df.mm.trans1:probe5 0.164588494002101 0.0649949624527024 2.53232693413546 0.0116452255571122 * df.mm.trans1:probe6 0.24927189760779 0.0649949624527024 3.8352495055165 0.000141986537754653 *** df.mm.trans2:probe2 -0.472816624856478 0.0649949624527024 -7.27466571275508 1.40524608984634e-12 *** df.mm.trans2:probe3 -0.00650330201742642 0.0649949624527024 -0.10005855487891 0.920339184418289 df.mm.trans2:probe4 -0.91483125588748 0.0649949624527024 -14.0754178687804 5.65883319319195e-38 *** df.mm.trans2:probe5 -0.0105444756295297 0.0649949624527024 -0.162235275344655 0.871188149384334 df.mm.trans2:probe6 -0.00326743951199160 0.0649949624527024 -0.0502721963162816 0.959926176574088 df.mm.trans3:probe2 -0.190757166465503 0.0649949624527024 -2.93495309893162 0.00349423475466899 ** df.mm.trans3:probe3 0.301245683395202 0.0649949624527024 4.63490818406768 4.59612917728885e-06 *** df.mm.trans3:probe4 0.374063284890159 0.0649949624527024 5.75526580482864 1.53525000629989e-08 *** df.mm.trans3:probe5 -0.153359604564871 0.0649949624527024 -2.35956139949265 0.0186918474478746 * df.mm.trans3:probe6 0.165308952076554 0.0649949624527024 2.54341176359400 0.0112869643220844 * df.mm.trans3:probe7 -0.415725551030283 0.0649949624527024 -6.39627342400285 3.75201785727487e-10 *** df.mm.trans3:probe8 -0.395172758870612 0.0649949624527024 -6.08005211416475 2.43602862331799e-09 *** df.mm.trans3:probe9 -0.242892981409654 0.0649949624527024 -3.73710472694573 0.000208321535947298 *** df.mm.trans3:probe10 -0.409526593071851 0.0649949624527024 -6.30089744831945 6.64950499297767e-10 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.30173870234597 0.366171450913664 14.4788423267766 9.61718319598842e-40 *** df.mm.trans1 -0.399695983051023 0.293139395591561 -1.36350142308382 0.173357090369196 df.mm.trans2 -0.49781350742797 0.293139395591561 -1.69821427933073 0.090108725391119 . df.mm.exp2 -0.529850967985351 0.392533621353103 -1.34982314676358 0.177702370725106 df.mm.exp3 -0.78773439189235 0.392533621353103 -2.00679470251987 0.0453260319829479 * df.mm.exp4 -0.67822721405899 0.392533621353103 -1.72781942020934 0.0846571593411938 . df.mm.exp5 -0.892351529813209 0.392533621353103 -2.27331235153102 0.0234438027793038 * df.mm.exp6 -0.385932541618974 0.392533621353103 -0.983183402962084 0.326007381591495 df.mm.exp7 -0.545176711735566 0.392533621353103 -1.38886628324037 0.165510835094380 df.mm.exp8 -0.196982964160968 0.392533621353103 -0.501824438584261 0.61601874647444 df.mm.trans1:exp2 0.0782245223553228 0.307928706926264 0.254034523562801 0.799576548039193 df.mm.trans2:exp2 0.436645875622449 0.307928706926264 1.41800964249497 0.156830123731892 df.mm.trans1:exp3 0.485747860542087 0.307928706926264 1.57746858157789 0.115339735316503 df.mm.trans2:exp3 0.535707790574072 0.307928706926264 1.73971370166001 0.0825436737389806 . df.mm.trans1:exp4 0.90076554564539 0.307928706926264 2.92524056830169 0.00360319024678026 ** df.mm.trans2:exp4 0.279888911484538 0.307928706926264 0.908940625505109 0.363832913695521 df.mm.trans1:exp5 0.265029911703864 0.307928706926264 0.860685950164847 0.389836307010807 df.mm.trans2:exp5 0.876635219386412 0.307928706926264 2.84687721432978 0.00460223935501311 ** df.mm.trans1:exp6 0.294142158320668 0.307928706926264 0.955228115159472 0.339938214630284 df.mm.trans2:exp6 0.327717174555969 0.307928706926264 1.06426314658102 0.287739076937326 df.mm.trans1:exp7 0.379521857603713 0.307928706926264 1.23249911121340 0.218359821014761 df.mm.trans2:exp7 0.349798023966465 0.307928706926264 1.13597081434251 0.256529788746379 df.mm.trans1:exp8 0.293534948406944 0.307928706926264 0.953256197958944 0.340935118827004 df.mm.trans2:exp8 0.464465731864406 0.307928706926264 1.5083547633499 0.132114868694195 df.mm.trans1:probe2 -0.0162922962719000 0.21082437360864 -0.0772789976463722 0.938433467956934 df.mm.trans1:probe3 -0.121724418854976 0.21082437360864 -0.577373558718294 0.563955052036149 df.mm.trans1:probe4 -0.0743179017231454 0.21082437360864 -0.352510957111174 0.72460823666526 df.mm.trans1:probe5 0.0306834572636290 0.21082437360864 0.145540369637657 0.884344710714547 df.mm.trans1:probe6 -0.199133576389745 0.21082437360864 -0.944547221847333 0.345360382557102 df.mm.trans2:probe2 -0.0145743236442972 0.21082437360864 -0.0691301645764733 0.944914502805672 df.mm.trans2:probe3 0.0865775123423956 0.21082437360864 0.410661779093494 0.681501922306177 df.mm.trans2:probe4 -0.174303980370647 0.21082437360864 -0.826773381972491 0.408772081301406 df.mm.trans2:probe5 -0.091787591549638 0.21082437360864 -0.435374667447257 0.663484178608921 df.mm.trans2:probe6 -0.0644686338789341 0.21082437360864 -0.305793076841339 0.759893408709947 df.mm.trans3:probe2 0.102376012561695 0.21082437360864 0.485598561538901 0.627471109344988 df.mm.trans3:probe3 -0.0259720568222814 0.21082437360864 -0.123192856583528 0.90200541573316 df.mm.trans3:probe4 0.0559442628037825 0.21082437360864 0.2653595589836 0.790845236990176 df.mm.trans3:probe5 -0.0192435426577533 0.21082437360864 -0.0912775991142072 0.92730970332264 df.mm.trans3:probe6 0.00498899415195023 0.21082437360864 0.0236642190205742 0.98113017993729 df.mm.trans3:probe7 -0.0655609148939456 0.21082437360864 -0.310974076534663 0.755953937068519 df.mm.trans3:probe8 0.169090308673756 0.21082437360864 0.80204345341798 0.422920623332607 df.mm.trans3:probe9 0.00289312291364661 0.21082437360864 0.0137229052984984 0.989056692420835 df.mm.trans3:probe10 -0.0350309043704502 0.21082437360864 -0.166161548453023 0.868099063439739