chr5.18464_chr5_119635527_119636371_-_1.R fitVsDatCorrelation=0.915010971302951 cont.fitVsDatCorrelation=0.308743696549077 fstatistic=5680.01020658359,36,324 cont.fstatistic=1014.47476181447,36,324 residuals=-0.77995865859305,-0.100910229338721,-0.00801937779995043,0.101870014276674,1.4363467201475 cont.residuals=-1.10912993110305,-0.325768459893964,-0.0610979276066885,0.322164964458912,1.58966861600378 predictedValues: Include Exclude Both chr5.18464_chr5_119635527_119636371_-_1.R.tl.Lung 256.123901306488 145.690846823922 295.659320651813 chr5.18464_chr5_119635527_119636371_-_1.R.tl.cerebhem 133.687561996522 191.466512830903 85.6025411993692 chr5.18464_chr5_119635527_119636371_-_1.R.tl.cortex 125.363431792900 105.272068139302 110.402033782562 chr5.18464_chr5_119635527_119636371_-_1.R.tl.heart 164.585693180513 113.056560406473 204.305771213094 chr5.18464_chr5_119635527_119636371_-_1.R.tl.kidney 210.226127538154 142.803187804525 218.264979973692 chr5.18464_chr5_119635527_119636371_-_1.R.tl.liver 256.870053899338 136.986881187432 334.364381863085 chr5.18464_chr5_119635527_119636371_-_1.R.tl.stomach 148.287895931982 117.646649693721 133.226994026375 chr5.18464_chr5_119635527_119636371_-_1.R.tl.testicle 328.861546428041 131.485871921998 471.942364969234 diffExp=110.433054482565,-57.7789508343816,20.0913636535983,51.5291327740404,67.4229397336293,119.883172711907,30.6412462382615,197.375674506043 diffExpScore=1.21190973585426 diffExp1.5=1,0,0,0,0,1,0,1 diffExp1.5Score=0.75 diffExp1.4=1,-1,0,1,1,1,0,1 diffExp1.4Score=1.2 diffExp1.3=1,-1,0,1,1,1,0,1 diffExp1.3Score=1.2 diffExp1.2=1,-1,0,1,1,1,1,1 diffExp1.2Score=1.16666666666667 cont.predictedValues: Include Exclude Both Lung 160.014950868885 157.968233447459 178.275807432647 cerebhem 191.571486343555 124.269105730050 223.101023096112 cortex 153.616805415747 175.848112678536 153.632627230702 heart 140.21151654873 187.496616913348 165.528479238880 kidney 139.547507969628 163.608170230036 150.440866159558 liver 167.988051098199 172.993229732334 151.88069361937 stomach 187.576751656011 204.528630319905 168.872182280931 testicle 155.627344380662 157.518874039669 143.044871500526 cont.diffExp=2.04671742142583,67.3023806135043,-22.2313072627887,-47.2851003646182,-24.0606622604083,-5.00517863413509,-16.9518786638941,-1.89152965900692 cont.diffExpScore=3.80578344140183 cont.diffExp1.5=0,1,0,0,0,0,0,0 cont.diffExp1.5Score=0.5 cont.diffExp1.4=0,1,0,0,0,0,0,0 cont.diffExp1.4Score=0.5 cont.diffExp1.3=0,1,0,-1,0,0,0,0 cont.diffExp1.3Score=2 cont.diffExp1.2=0,1,0,-1,0,0,0,0 cont.diffExp1.2Score=2 tran.correlation=0.0348517509833706 cont.tran.correlation=-0.195917643263934 tran.covariance=0.00851581609597839 cont.tran.covariance=-0.00458279109163511 tran.mean=169.275924430138 cont.tran.mean=165.024086710797 weightedLogRatios: wLogRatio Lung 2.96957390732122 cerebhem -1.82301715691258 cortex 0.828608504839193 heart 1.84604230399198 kidney 1.99345545978508 liver 3.29068134348252 stomach 1.13036532074141 testicle 4.89287341983693 cont.weightedLogRatios: wLogRatio Lung 0.0652525522869942 cerebhem 2.18087506520024 cortex -0.689588796971224 heart -1.47874965117481 kidney -0.798199965006873 liver -0.150866472578490 stomach -0.456604083291503 testicle -0.0610511634782868 varWeightedLogRatios=3.94962229783735 cont.varWeightedLogRatios=1.15052341486684 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.19888432793204 0.121551555806647 42.7710224968405 2.66004718354448e-135 *** df.mm.trans1 0.20969882117303 0.102952898023651 2.03684233468452 0.0424784099861584 * df.mm.trans2 0.00194468939216626 0.102952898023651 0.0188891175430489 0.984941187621608 df.mm.exp2 0.862563048283266 0.143374393294425 6.01615831435087 4.82423547902314e-09 *** df.mm.exp3 -0.0543038166169552 0.143374393294425 -0.378755336773702 0.705117626102571 df.mm.exp4 -0.326238514620553 0.143374393294425 -2.27543082920399 0.0235327886538786 * df.mm.exp5 0.0860009349850306 0.143374393294425 0.599834691599526 0.549035670345454 df.mm.exp6 -0.181716226602719 0.143374393294425 -1.26742455488239 0.205913683690895 df.mm.exp7 0.0368465111682621 0.143374393294425 0.256995062518565 0.797345708498634 df.mm.exp8 -0.320260989649660 0.143374393294425 -2.23373910982829 0.0261823658786944 * df.mm.trans1:exp2 -1.51271891457155 0.124165866845153 -12.1830496013696 2.29612781504832e-28 *** df.mm.trans2:exp2 -0.589337011831935 0.124165866845153 -4.74636892413351 3.11248526620162e-06 *** df.mm.trans1:exp3 -0.660140527081122 0.124165866845153 -5.31660225031393 1.97330034114452e-07 *** df.mm.trans2:exp3 -0.270634948420899 0.124165866845153 -2.17962436293709 0.0300050037461206 * df.mm.trans1:exp4 -0.115991436495937 0.124165866845153 -0.934165237541408 0.35091433324553 df.mm.trans2:exp4 0.0726398535233235 0.124165866845153 0.58502272298322 0.558939627910292 df.mm.trans1:exp5 -0.283478502670636 0.124165866845153 -2.28306305004225 0.0230739271631281 * df.mm.trans2:exp5 -0.106020450922100 0.124165866845153 -0.853861480742668 0.393812588708409 df.mm.trans1:exp6 0.184625239901854 0.124165866845153 1.48692426181907 0.138007293627051 df.mm.trans2:exp6 0.120114500935322 0.124165866845153 0.967371339541457 0.334079962637234 df.mm.trans1:exp7 -0.583352201028122 0.124165866845153 -4.69816879509743 3.88519157016915e-06 *** df.mm.trans2:exp7 -0.250647762446302 0.124165866845153 -2.01865270073686 0.0443468085796823 * df.mm.trans1:exp8 0.570236503441986 0.124165866845153 4.59253833545998 6.2764751137408e-06 *** df.mm.trans2:exp8 0.217673508485609 0.124165866845153 1.75308652865983 0.0805328648548325 . df.mm.trans1:probe2 0.331350900375814 0.0620829334225766 5.33723009060196 1.7777455982344e-07 *** df.mm.trans1:probe3 0.263042521101808 0.0620829334225766 4.23695380679534 2.95698987604035e-05 *** df.mm.trans1:probe4 0.336705558796429 0.0620829334225766 5.42348017779046 1.14520790808408e-07 *** df.mm.trans1:probe5 0.227332553854966 0.0620829334225766 3.66175599834489 0.000292434340879491 *** df.mm.trans1:probe6 0.0752719757814197 0.0620829334225766 1.21244231919697 0.226226444121331 df.mm.trans2:probe2 -0.301308231811701 0.0620829334225766 -4.853318218081 1.89073424395404e-06 *** df.mm.trans2:probe3 -0.567382452041308 0.0620829334225766 -9.13910507706419 7.06459653456258e-18 *** df.mm.trans2:probe4 -0.326679282166572 0.0620829334225766 -5.26198206426525 2.59742842128763e-07 *** df.mm.trans2:probe5 -0.415875831534307 0.0620829334225766 -6.69871426183403 9.30940408401679e-11 *** df.mm.trans2:probe6 -0.362833355973642 0.0620829334225766 -5.84433331305341 1.23978350348601e-08 *** df.mm.trans3:probe2 0.243077647599244 0.0620829334225766 3.91536988023262 0.000110077408749478 *** df.mm.trans3:probe3 0.592962380116401 0.0620829334225766 9.55113341826674 3.29093032855767e-19 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.02719936435111 0.286576325349125 17.5422703121992 6.65534765063054e-49 *** df.mm.trans1 0.0152234863015770 0.242727153954271 0.0627185135802525 0.950029328165757 df.mm.trans2 0.0459068713698759 0.242727153954271 0.189129525156154 0.850109719362567 df.mm.exp2 -0.284243611280246 0.338026991977258 -0.840890278073916 0.401029551920195 df.mm.exp3 0.215188254826139 0.338026991977258 0.636600803880822 0.524834391260189 df.mm.exp4 0.113440275617259 0.338026991977258 0.335595317266531 0.7373932556337 df.mm.exp5 0.0679799928792046 0.338026991977258 0.201108179206524 0.840740177502914 df.mm.exp6 0.299720628014795 0.338026991977258 0.886676612011384 0.375910695020278 df.mm.exp7 0.471424578723573 0.338026991977258 1.39463590160661 0.164081103829868 df.mm.exp8 0.189521868464921 0.338026991977258 0.560670813168883 0.575409469477419 df.mm.trans1:exp2 0.464237393277362 0.292739962217144 1.58583539384694 0.113752117849055 df.mm.trans2:exp2 0.0442990742040665 0.292739962217144 0.151325681224236 0.879812987199784 df.mm.trans1:exp3 -0.255994283637503 0.292739962217144 -0.874476725687404 0.382506426446723 df.mm.trans2:exp3 -0.107961587211095 0.292739962217144 -0.368796888519828 0.712519994169041 df.mm.trans1:exp4 -0.245555414475026 0.292739962217144 -0.838817538320516 0.402190140174363 df.mm.trans2:exp4 0.0579265678187455 0.292739962217144 0.197877212868456 0.843265222884628 df.mm.trans1:exp5 -0.204842144471586 0.292739962217144 -0.699740967786424 0.484591169233856 df.mm.trans2:exp5 -0.0328995883590077 0.292739962217144 -0.112385026321087 0.910587723030504 df.mm.trans1:exp6 -0.251095029355320 0.292739962217144 -0.857740868221699 0.391669601745554 df.mm.trans2:exp6 -0.208862127460841 0.292739962217144 -0.713473233647253 0.476066563193872 df.mm.trans1:exp7 -0.312503728704204 0.292739962217144 -1.06751304583554 0.286534977274045 df.mm.trans2:exp7 -0.213110570158563 0.292739962217144 -0.7279859180978 0.467147977760161 df.mm.trans1:exp8 -0.217324790864845 0.292739962217144 -0.742381700191794 0.458393962321009 df.mm.trans2:exp8 -0.192370540889265 0.292739962217144 -0.657137957634125 0.511558733014 df.mm.trans1:probe2 0.0918310167223815 0.146369981108572 0.627389687604486 0.530845708917518 df.mm.trans1:probe3 0.115636660960209 0.146369981108572 0.790029896051116 0.430088128973189 df.mm.trans1:probe4 -0.174650648388704 0.146369981108572 -1.19321357470938 0.233658744087398 df.mm.trans1:probe5 0.155876905435851 0.146369981108572 1.06495132577920 0.287690940624073 df.mm.trans1:probe6 0.106905693585649 0.146369981108572 0.730379909705327 0.465685776206312 df.mm.trans2:probe2 -0.103317454610898 0.146369981108572 -0.705865053943411 0.480779275288955 df.mm.trans2:probe3 -0.0188420255168552 0.146369981108572 -0.128728755542292 0.89765215037862 df.mm.trans2:probe4 0.0732246115636055 0.146369981108572 0.500270690813918 0.61722410658992 df.mm.trans2:probe5 -0.123735703541155 0.146369981108572 -0.845362570958944 0.39853227605555 df.mm.trans2:probe6 0.0762600787622747 0.146369981108572 0.521009008709973 0.602716391646225 df.mm.trans3:probe2 0.109523469340671 0.146369981108572 0.748264558833482 0.454843395572624 df.mm.trans3:probe3 0.175482857727569 0.146369981108572 1.19889923055604 0.231443239205415