chr1.1059_chr1_106235486_106244507_+_2.R fitVsDatCorrelation=0.952886080536324 cont.fitVsDatCorrelation=0.219753595800421 fstatistic=13085.9304093548,58,830 cont.fstatistic=1252.17899701661,58,830 residuals=-0.573093625616236,-0.0861040826979063,-0.00390024233458137,0.0768073855385866,0.670265313253879 cont.residuals=-0.762528371790804,-0.341849499664299,-0.0942017186584186,0.237739929635236,1.79473537698150 predictedValues: Include Exclude Both chr1.1059_chr1_106235486_106244507_+_2.R.tl.Lung 70.9470951363114 76.8688140091988 52.4092620145858 chr1.1059_chr1_106235486_106244507_+_2.R.tl.cerebhem 72.5607477769288 76.4820708661115 54.6284045756495 chr1.1059_chr1_106235486_106244507_+_2.R.tl.cortex 73.378280960919 86.3689011849588 60.8227568306239 chr1.1059_chr1_106235486_106244507_+_2.R.tl.heart 72.5007684365412 80.1018279400508 57.7072216918082 chr1.1059_chr1_106235486_106244507_+_2.R.tl.kidney 67.9997617046635 81.4447353554282 52.9604540068284 chr1.1059_chr1_106235486_106244507_+_2.R.tl.liver 69.9091378474056 81.5038600832837 55.3526535946563 chr1.1059_chr1_106235486_106244507_+_2.R.tl.stomach 74.2852138231974 81.0034557060213 57.5815751158233 chr1.1059_chr1_106235486_106244507_+_2.R.tl.testicle 73.494471560073 76.7968952851319 54.6433359320915 diffExp=-5.92171887288741,-3.92132308918266,-12.9906202240398,-7.60105950350959,-13.4449736507647,-11.5947222358781,-6.71824188282393,-3.30242372505886 diffExpScore=0.984961294097028 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 76.6765231199471 70.5038123709762 76.9659670684326 cerebhem 62.5631837880733 63.6107427438136 70.2692903082841 cortex 71.1722629227224 63.2615766980244 67.4568131662552 heart 69.194804678116 64.8295991648538 71.9573736508729 kidney 70.0207497212383 74.8369796107438 65.2326769296744 liver 74.2137844971567 64.0351155386188 75.2721576237418 stomach 77.8592085967506 69.6061819843207 72.826757107068 testicle 72.3230914090067 75.6558842159513 78.0045714924726 cont.diffExp=6.17271074897094,-1.04755895574034,7.91068622469791,4.36520551326218,-4.81622988950548,10.1786689585378,8.25302661242984,-3.33279280694458 cont.diffExpScore=1.60637760666604 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=-0.0242016745226024 cont.tran.correlation=0.327353461849103 tran.covariance=-4.55872549343163e-05 cont.tran.covariance=0.00175425678403438 tran.mean=75.977877354764 cont.tran.mean=70.0227188162696 weightedLogRatios: wLogRatio Lung -0.344874638790916 cerebhem -0.226883889330289 cortex -0.713470431088489 heart -0.432051316545958 kidney -0.777560816768622 liver -0.663523398070846 stomach -0.376726585018379 testicle -0.189845670119767 cont.weightedLogRatios: wLogRatio Lung 0.360694984268282 cerebhem -0.0688206618160772 cortex 0.49559456234453 heart 0.273969799907746 kidney -0.284844317578741 liver 0.62447308184476 stomach 0.481684065285689 testicle -0.193887869149854 varWeightedLogRatios=0.0506510591150649 cont.varWeightedLogRatios=0.119956140706433 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.4868592573825 0.0690803762294204 64.9512857671961 0 *** df.mm.trans1 -0.460039730581529 0.0598062196643136 -7.69217203768583 4.09723760152601e-14 *** df.mm.trans2 -0.153813373447686 0.0529847722568685 -2.90297319203342 0.00379432297943953 ** df.mm.exp2 -0.0240249041779018 0.0684811134499558 -0.350825256301631 0.725808471706336 df.mm.exp3 0.00134027085818991 0.0684811134499557 0.0195713940774247 0.984389987399515 df.mm.exp4 -0.0334378728849114 0.0684811134499557 -0.488278756001053 0.625481375700411 df.mm.exp5 0.00493202967008339 0.0684811134499557 0.0720202902905133 0.942603110947973 df.mm.exp6 -0.0108292332253417 0.0684811134499557 -0.158134596238062 0.874389204103024 df.mm.exp7 0.00424971886567434 0.0684811134499557 0.062056801526452 0.950532538324598 df.mm.exp8 -0.00740424981408988 0.0684811134499557 -0.108121048871390 0.913925802397952 df.mm.trans1:exp2 0.0465145552052846 0.0634836912452735 0.732700860533968 0.463947761601485 df.mm.trans2:exp2 0.0189809950628067 0.0476608378741979 0.398251392745289 0.690547305041444 df.mm.trans1:exp3 0.0323532608981909 0.0634836912452735 0.509631060569428 0.610445432206106 df.mm.trans2:exp3 0.115187145453049 0.0476608378741979 2.41680907408906 0.0158719359511805 * df.mm.trans1:exp4 0.0551005734519461 0.0634836912452735 0.867948482060713 0.385673411901457 df.mm.trans2:exp4 0.074636292707643 0.0476608378741979 1.56598784319838 0.117732620351219 df.mm.trans1:exp5 -0.0473622892054289 0.0634836912452735 -0.746054431876708 0.455845776874146 df.mm.trans2:exp5 0.052892412052801 0.0476608378741979 1.10976672698059 0.267420981024528 df.mm.trans1:exp6 -0.00390885901041453 0.0634836912452735 -0.0615726485612248 0.950917982166418 df.mm.trans2:exp6 0.0693793606197217 0.0476608378741979 1.45568906704600 0.145856716710982 df.mm.trans1:exp7 0.0417277462742421 0.0634836912452735 0.657298677120461 0.511171112321942 df.mm.trans2:exp7 0.0481418432181018 0.0476608378741979 1.01009225530557 0.312745461237773 df.mm.trans1:exp8 0.0426799759720652 0.0634836912452735 0.672298272751157 0.501580932870304 df.mm.trans2:exp8 0.0064682084597978 0.0476608378741979 0.13571327631442 0.892080858571515 df.mm.trans1:probe2 0.44463149275097 0.0425861547261120 10.4407522963876 4.62792847070895e-24 *** df.mm.trans1:probe3 -0.117227018836322 0.042586154726112 -2.7527025999472 0.00603958688061134 ** df.mm.trans1:probe4 0.520602961611039 0.042586154726112 12.2246999044464 1.02016513825103e-31 *** df.mm.trans1:probe5 0.0718437117883207 0.042586154726112 1.68702040018347 0.091975179583764 . df.mm.trans1:probe6 0.0579199214397566 0.042586154726112 1.36006459874722 0.174178771873192 df.mm.trans1:probe7 -0.103223799407298 0.0425861547261120 -2.42388165992374 0.0155683591704534 * df.mm.trans1:probe8 0.115350223194509 0.042586154726112 2.7086320410089 0.00689524712825956 ** df.mm.trans1:probe9 -0.0401085501214114 0.0425861547261120 -0.94182135906294 0.346558143955983 df.mm.trans1:probe10 0.455312116224521 0.042586154726112 10.6915526690026 4.38594732938882e-25 *** df.mm.trans1:probe11 1.22144047971867 0.042586154726112 28.6816334457578 2.93147302266002e-126 *** df.mm.trans1:probe12 1.03426311645637 0.0425861547261120 24.2863701385608 7.44560974208691e-99 *** df.mm.trans1:probe13 1.51434591837233 0.042586154726112 35.5595833460821 5.27165126022212e-169 *** df.mm.trans1:probe14 0.817617613340832 0.042586154726112 19.1991415660617 2.90861356834117e-68 *** df.mm.trans1:probe15 1.03196210243612 0.0425861547261120 24.2323381642008 1.60527810432777e-98 *** df.mm.trans1:probe16 0.913988036507962 0.042586154726112 21.4620935462751 1.26163679502229e-81 *** df.mm.trans1:probe17 -0.165161162294378 0.042586154726112 -3.87828305599773 0.000113516044499183 *** df.mm.trans1:probe18 -0.132210903489709 0.042586154726112 -3.104551334583 0.00197036340201994 ** df.mm.trans1:probe19 -0.143928800253676 0.042586154726112 -3.37970876167003 0.000759483773396796 *** df.mm.trans1:probe20 -0.161528173518640 0.042586154726112 -3.79297390331413 0.000159652121111002 *** df.mm.trans1:probe21 -0.0225241192239952 0.042586154726112 -0.528907091256688 0.5970113109842 df.mm.trans1:probe22 -0.0248022263001593 0.0425861547261119 -0.582401169104653 0.560454664434644 df.mm.trans2:probe2 -0.00978729249147098 0.042586154726112 -0.229823344098965 0.818285669758046 df.mm.trans2:probe3 -0.00668299449110554 0.042586154726112 -0.156928807827015 0.875339119966683 df.mm.trans2:probe4 0.0557097494455514 0.042586154726112 1.30816575959587 0.191179253806951 df.mm.trans2:probe5 0.0586116993484434 0.042586154726112 1.37630879626014 0.169097239451418 df.mm.trans2:probe6 0.0379643999051318 0.042586154726112 0.891472830766138 0.372933915058488 df.mm.trans3:probe2 0.105032046735849 0.042586154726112 2.46634258038441 0.0138511488640904 * df.mm.trans3:probe3 -0.0624563267965615 0.0425861547261120 -1.46658760806751 0.142867039467581 df.mm.trans3:probe4 -0.142184543584772 0.042586154726112 -3.33875045773012 0.000879061484724976 *** df.mm.trans3:probe5 -0.104780431255634 0.042586154726112 -2.46043419344896 0.014079594261694 * df.mm.trans3:probe6 0.769654611336517 0.042586154726112 18.0728834591069 8.07925870570487e-62 *** df.mm.trans3:probe7 0.0726633225871571 0.042586154726112 1.70626634535292 0.0883325842235588 . df.mm.trans3:probe8 -0.153324807047292 0.0425861547261120 -3.60034400930029 0.000336657449510304 *** df.mm.trans3:probe9 0.290090733244495 0.0425861547261119 6.81185552229781 1.84976265278356e-11 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.98731161526574 0.222174168299050 17.9467831287153 4.15629352737639e-61 *** df.mm.trans1 0.288015512983922 0.192346912948199 1.49737528182471 0.134675813039373 df.mm.trans2 0.2311473311794 0.170407984889794 1.35643486030826 0.175329690964724 df.mm.exp2 -0.215274532752745 0.220246837892250 -0.977423943121772 0.328644107087110 df.mm.exp3 -0.0510052906290283 0.220246837892250 -0.231582396901340 0.816919460843146 df.mm.exp4 -0.119284872807920 0.220246837892250 -0.541596301447363 0.588241987449125 df.mm.exp5 0.134244221123087 0.220246837892250 0.609517132721614 0.542348531020859 df.mm.exp6 -0.106627813704695 0.220246837892250 -0.484128692720937 0.628422252856435 df.mm.exp7 0.0577731114049905 0.220246837892250 0.262310741701792 0.793146970147194 df.mm.exp8 -0.00132777405737430 0.220246837892250 -0.00602857262370266 0.995191372753314 df.mm.trans1:exp2 0.0118559450222111 0.204174283245514 0.05806776854436 0.95370862461986 df.mm.trans2:exp2 0.112390115360987 0.153285311880309 0.733208641991382 0.463638214388592 df.mm.trans1:exp3 -0.0234871069713078 0.204174283245514 -0.115034599842651 0.908445520122963 df.mm.trans2:exp3 -0.0573833522528477 0.153285311880309 -0.374356496059158 0.708234723244955 df.mm.trans1:exp4 0.0166150812815554 0.204174283245514 0.0813769541268635 0.935161794772134 df.mm.trans2:exp4 0.0353803645703644 0.153285311880309 0.230813795114242 0.817516344851736 df.mm.trans1:exp5 -0.225048172835435 0.204174283245514 -1.10223564524441 0.270678745637818 df.mm.trans2:exp5 -0.0745988630255382 0.153285311880309 -0.48666674001869 0.626622999864625 df.mm.trans1:exp6 0.0739821470925679 0.204174283245514 0.362348019136212 0.717184218896131 df.mm.trans2:exp6 0.0103926423450745 0.153285311880309 0.067799335876287 0.945961701280542 df.mm.trans1:exp7 -0.0424665081394475 0.204174283245514 -0.207991464274581 0.83528665664044 df.mm.trans2:exp7 -0.0705865109354369 0.153285311880309 -0.460491028589572 0.645284429612884 df.mm.trans1:exp8 -0.0571243389451784 0.204174283245514 -0.279782243077537 0.779714284298307 df.mm.trans2:exp8 0.0718562088277906 0.153285311880309 0.468774261188826 0.639354094289608 df.mm.trans1:probe2 0.239521375123779 0.136964272978280 1.74878725608804 0.080697455863374 . df.mm.trans1:probe3 0.112560945225634 0.136964272978280 0.821827055903 0.411411341060514 df.mm.trans1:probe4 0.0993057657987664 0.136964272978280 0.725048683422097 0.468626517890098 df.mm.trans1:probe5 0.064072369105258 0.136964272978280 0.467803520670086 0.640047906799727 df.mm.trans1:probe6 0.0419377487157815 0.136964272978280 0.306194803972216 0.759533115924684 df.mm.trans1:probe7 0.0427726873535327 0.136964272978280 0.312290836314049 0.754897941859817 df.mm.trans1:probe8 0.148945878839255 0.136964272978280 1.08747979017035 0.277140515864722 df.mm.trans1:probe9 0.180417320562130 0.136964272978280 1.31725826479393 0.188115594132666 df.mm.trans1:probe10 0.108880904562367 0.136964272978280 0.794958438392427 0.426864936185424 df.mm.trans1:probe11 0.135961207797775 0.136964272978280 0.992676446501756 0.321156958258048 df.mm.trans1:probe12 0.0978772938726989 0.136964272978280 0.714619161218931 0.47504533643897 df.mm.trans1:probe13 0.140483272591064 0.136964272978280 1.02569282876669 0.305335225872006 df.mm.trans1:probe14 0.0231355815906272 0.136964272978280 0.168916908676587 0.865903154870901 df.mm.trans1:probe15 0.0316337671801184 0.136964272978280 0.230963641044808 0.817399968538299 df.mm.trans1:probe16 0.0401275906779777 0.136964272978280 0.292978525022663 0.76961179704873 df.mm.trans1:probe17 0.0599249465104939 0.136964272978280 0.437522466314971 0.661846308302364 df.mm.trans1:probe18 0.148660208216676 0.136964272978280 1.08539405922486 0.278062306596391 df.mm.trans1:probe19 0.0858909806367377 0.136964272978280 0.627105001684334 0.530762868302914 df.mm.trans1:probe20 0.27569976268379 0.136964272978280 2.01293196166209 0.0444442590397001 * df.mm.trans1:probe21 -0.122267267156194 0.136964272978280 -0.892694602011898 0.372279482106834 df.mm.trans1:probe22 0.0367794915701094 0.136964272978280 0.268533470593036 0.788355443429232 df.mm.trans2:probe2 0.0799334433327755 0.136964272978280 0.583607984729358 0.559642639730878 df.mm.trans2:probe3 0.090573991147113 0.136964272978280 0.66129647664743 0.508605724620091 df.mm.trans2:probe4 0.196755150681682 0.136964272978280 1.43654360661546 0.151224528736923 df.mm.trans2:probe5 0.132867231891793 0.136964272978280 0.970086789807322 0.332285834866624 df.mm.trans2:probe6 0.0579877543728313 0.136964272978280 0.423378689288025 0.672128673121174 df.mm.trans3:probe2 -0.188997448458394 0.136964272978280 -1.37990327220856 0.167988016205289 df.mm.trans3:probe3 -0.0408840183756446 0.136964272978280 -0.298501335323615 0.765395270523775 df.mm.trans3:probe4 -0.200658921394904 0.136964272978280 -1.46504571616808 0.143287125369987 df.mm.trans3:probe5 -0.218154852984271 0.136964272978280 -1.59278655842511 0.111588816151759 df.mm.trans3:probe6 -0.125572202225596 0.136964272978280 -0.916824508282608 0.359500919384773 df.mm.trans3:probe7 -0.19998100926594 0.136964272978280 -1.46009616170236 0.144642039693822 df.mm.trans3:probe8 -0.194594303034807 0.136964272978280 -1.42076688178140 0.155760098828651 df.mm.trans3:probe9 -0.299157336899021 0.136964272978280 -2.18419979454396 0.0292267598502880 *