chr11.4105_chr11_118675138_118676777_-_2.R fitVsDatCorrelation=0.950081217541808 cont.fitVsDatCorrelation=0.231077266657358 fstatistic=9311.13949256124,58,830 cont.fstatistic=944.689332709131,58,830 residuals=-0.62934780762814,-0.0991288073944994,-0.0108081834523378,0.0942795333123603,1.00812901836483 cont.residuals=-1.04312704694997,-0.393544528462612,-0.137579593261035,0.302575564342235,2.07812018125645 predictedValues: Include Exclude Both chr11.4105_chr11_118675138_118676777_-_2.R.tl.Lung 77.227797333122 174.899824881179 63.1593378978262 chr11.4105_chr11_118675138_118676777_-_2.R.tl.cerebhem 67.4482416876835 155.447263761850 61.624615685747 chr11.4105_chr11_118675138_118676777_-_2.R.tl.cortex 71.7309258617832 187.038604581911 59.0419087446306 chr11.4105_chr11_118675138_118676777_-_2.R.tl.heart 75.269914450117 222.00775074776 59.8963126563216 chr11.4105_chr11_118675138_118676777_-_2.R.tl.kidney 76.334771531021 216.884094027836 64.2489380201234 chr11.4105_chr11_118675138_118676777_-_2.R.tl.liver 77.9070428842882 270.264088770365 60.674554571237 chr11.4105_chr11_118675138_118676777_-_2.R.tl.stomach 87.2675139716966 248.647706207765 62.6546216281714 chr11.4105_chr11_118675138_118676777_-_2.R.tl.testicle 74.3212295146325 288.780836262618 62.1547700039002 diffExp=-97.6720275480571,-87.999022074166,-115.307678720128,-146.737836297643,-140.549322496815,-192.357045886076,-161.380192236069,-214.459606747986 diffExpScore=0.999136041297618 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 85.046696298171 78.2311627146958 94.0784793090767 cerebhem 91.0281260897562 66.4703296580233 85.36652121106 cortex 91.2903441229837 71.9405329813779 87.0861149681773 heart 91.2597421804502 77.7075393551337 94.1355343640994 kidney 83.4500171525983 71.748482034782 79.2840298259425 liver 80.7851743623142 74.6299439193337 87.6644020031075 stomach 90.900353934433 78.0208455236584 86.9387257991894 testicle 84.4363726298158 79.0728017216087 93.8527192646973 cont.diffExp=6.8155335834752,24.5577964317328,19.3498111416059,13.5522028253165,11.7015351178164,6.15523044298044,12.8795084107747,5.36357090820717 cont.diffExpScore=0.990135653395801 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=0,1,0,0,0,0,0,0 cont.diffExp1.3Score=0.5 cont.diffExp1.2=0,1,1,0,0,0,0,0 cont.diffExp1.2Score=0.666666666666667 tran.correlation=0.502330093732383 cont.tran.correlation=-0.200131692190966 tran.covariance=0.0089285418166128 cont.tran.covariance=-0.000611701947287033 tran.mean=148.217350404727 cont.tran.mean=81.001154042446 weightedLogRatios: wLogRatio Lung -3.88739101386221 cerebhem -3.86482612991981 cortex -4.55439739548159 heart -5.2587816711582 kidney -5.072103786326 liver -6.19137649757902 stomach -5.22744901702778 testicle -6.7687564225502 cont.weightedLogRatios: wLogRatio Lung 0.367662392304955 cerebhem 1.36894167463674 cortex 1.04689803259009 heart 0.712691060821614 kidney 0.65700772921507 liver 0.344916437857801 stomach 0.677365081440783 testicle 0.288977837422031 varWeightedLogRatios=1.04453747625244 cont.varWeightedLogRatios=0.139074058372672 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.30918291101479 0.085336216734536 62.2148850063345 0 *** df.mm.trans1 -1.00239700826204 0.0738796862715053 -13.567965145091 5.08380806092522e-38 *** df.mm.trans2 -0.165013009749287 0.0654530310304898 -2.5210904239472 0.0118854715625733 * df.mm.exp2 -0.228706483449466 0.0845959367705199 -2.70351617560391 0.00700133449507963 ** df.mm.exp3 0.0606773696790667 0.0845959367705198 0.717261041078886 0.473414841944822 df.mm.exp4 0.26586572643321 0.0845959367705198 3.14277182312449 0.0017330134015873 ** df.mm.exp5 0.186414307217418 0.0845959367705198 2.20358464406035 0.0278275091573222 * df.mm.exp6 0.484079399567939 0.0845959367705199 5.72225355079503 1.46775755979298e-08 *** df.mm.exp7 0.482065750967486 0.0845959367705198 5.69845041464778 1.67918690327372e-08 *** df.mm.exp8 0.479124985725428 0.0845959367705198 5.66368792658603 2.04207302014698e-08 *** df.mm.trans1:exp2 0.0933075360788714 0.0784225322864962 1.18980519193128 0.234463194143712 df.mm.trans2:exp2 0.110799636979734 0.0588762802488903 1.88190620248674 0.0601984410128313 . df.mm.trans1:exp3 -0.134514853332418 0.0784225322864962 -1.71525771242636 0.0866712194102237 . df.mm.trans2:exp3 0.00642428671094544 0.0588762802488903 0.109115023635797 0.913137632860148 df.mm.trans1:exp4 -0.291544675264165 0.0784225322864962 -3.71761363429432 0.000214614077360586 *** df.mm.trans2:exp4 -0.0273668126651227 0.0588762802488903 -0.464818982269835 0.642183004528939 df.mm.trans1:exp5 -0.198045212794341 0.0784225322864962 -2.52536110503081 0.0117431011308927 * df.mm.trans2:exp5 0.0287353939484671 0.0588762802488903 0.488064018769404 0.625633400012226 df.mm.trans1:exp6 -0.475322502783551 0.0784225322864962 -6.06104507116762 2.05067673290954e-09 *** df.mm.trans2:exp6 -0.0488931928201244 0.0588762802488903 -0.830439569440122 0.406529102670783 df.mm.trans1:exp7 -0.359846938132509 0.0784225322864962 -4.58856565378305 5.15230987018474e-06 *** df.mm.trans2:exp7 -0.130242071606076 0.0588762802488903 -2.21213145693815 0.0272291951525201 * df.mm.trans1:exp8 -0.517487809136952 0.0784225322864962 -6.59871332956256 7.38654556922425e-11 *** df.mm.trans2:exp8 0.0223296818872459 0.0588762802488903 0.379264481262244 0.704588479357012 df.mm.trans1:probe2 0.0195061582960872 0.0526074339480833 0.37078710806038 0.710890715865578 df.mm.trans1:probe3 -0.354239829671681 0.0526074339480832 -6.73364585737578 3.08792212933165e-11 *** df.mm.trans1:probe4 -0.341203550412197 0.0526074339480832 -6.48584287058976 1.51433052925364e-10 *** df.mm.trans1:probe5 -0.397068125726838 0.0526074339480832 -7.54775695995158 1.16570113495237e-13 *** df.mm.trans1:probe6 -0.426266758443316 0.0526074339480832 -8.10278560372259 1.91561631215827e-15 *** df.mm.trans1:probe7 -0.199607113371856 0.0526074339480833 -3.79427579700698 0.000158831122239442 *** df.mm.trans1:probe8 -0.43864614760774 0.0526074339480833 -8.33810195039407 3.12113431966609e-16 *** df.mm.trans1:probe9 -0.0462656084700358 0.0526074339480833 -0.879450013009454 0.37941186739189 df.mm.trans1:probe10 -0.0604038787798264 0.0526074339480832 -1.14820043949373 0.25121664061039 df.mm.trans1:probe11 0.0822651474999579 0.0526074339480832 1.56375518298693 0.118256244978801 df.mm.trans1:probe12 0.0527982213303015 0.0526074339480833 1.00362662399399 0.315851114663796 df.mm.trans1:probe13 -0.0790115271076281 0.0526074339480833 -1.50190802283955 0.133501197949593 df.mm.trans1:probe14 0.0129328497925905 0.0526074339480832 0.245836924974398 0.80586924933838 df.mm.trans1:probe15 0.0048803920559099 0.0526074339480832 0.0927700077659408 0.926108665596691 df.mm.trans1:probe16 0.278400236741272 0.0526074339480833 5.2920322442645 1.54920547257998e-07 *** df.mm.trans1:probe17 0.432309721827042 0.0526074339480832 8.21765460474038 7.94267307661328e-16 *** df.mm.trans1:probe18 0.325910806130939 0.0526074339480833 6.195147371236 9.15807472317834e-10 *** df.mm.trans1:probe19 0.509786868029056 0.0526074339480833 9.69039601004205 4.13575814416304e-21 *** df.mm.trans1:probe20 0.80760463226381 0.0526074339480832 15.3515306042262 5.27433348619575e-47 *** df.mm.trans1:probe21 0.532800175657689 0.0526074339480832 10.1278495389738 8.24962562355971e-23 *** df.mm.trans1:probe22 0.52269764503368 0.0526074339480833 9.93581335956274 4.67592997846813e-22 *** df.mm.trans2:probe2 -0.361252680617181 0.0526074339480833 -6.86695117982168 1.28534374460286e-11 *** df.mm.trans2:probe3 -0.102674964244730 0.0526074339480833 -1.95171968178597 0.0513074828186765 . df.mm.trans2:probe4 0.754895507306059 0.0526074339480833 14.3495975882618 7.07318086474682e-42 *** df.mm.trans2:probe5 0.0463429640217033 0.0526074339480833 0.880920443058254 0.37861589159621 df.mm.trans2:probe6 -0.0366586338543728 0.0526074339480833 -0.69683371917646 0.486101974127068 df.mm.trans3:probe2 0.139793554426892 0.0526074339480833 2.65729658216841 0.00802840878788109 ** df.mm.trans3:probe3 -0.0927769244988551 0.0526074339480832 -1.76357061229054 0.0781721817163155 . df.mm.trans3:probe4 -0.123645836735904 0.0526074339480833 -2.35034913236648 0.0189890348225377 * df.mm.trans3:probe5 -0.100390843052471 0.0526074339480832 -1.90830146080768 0.0566970073774078 . df.mm.trans3:probe6 0.144611182638591 0.0526074339480832 2.74887352957196 0.00610993637061962 ** df.mm.trans3:probe7 -0.253995680660209 0.0526074339480832 -4.82813286256976 1.64061319897318e-06 *** df.mm.trans3:probe8 0.388730801056014 0.0526074339480832 7.38927508685638 3.60236600922944e-13 *** df.mm.trans3:probe9 -0.0673359326276523 0.0526074339480832 -1.27996991250522 0.200913347455168 cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.14357924318151 0.266108685496552 15.5710033870172 3.743454671208e-48 *** df.mm.trans1 0.332826526539307 0.230383147401136 1.44466524697572 0.148929332170388 df.mm.trans2 0.117732280832700 0.204105838245342 0.576819760986854 0.5642176217897 df.mm.exp2 0.00223099156737949 0.263800229185012 0.00845712520520525 0.993254303044406 df.mm.exp3 0.0642481907396634 0.263800229185012 0.243548653987727 0.80764058074945 df.mm.exp4 0.0631872139139827 0.263800229185012 0.239526758976647 0.810756286352388 df.mm.exp5 0.0656386127280427 0.263800229185012 0.248819392351658 0.803562044649272 df.mm.exp6 -0.0279198497441856 0.263800229185012 -0.105837094343859 0.915737177885063 df.mm.exp7 0.142797144770021 0.263800229185012 0.541307887454003 0.588440642217194 df.mm.exp8 0.0059012737865224 0.263800229185012 0.0223702375269115 0.982157998120394 df.mm.trans1:exp2 0.0657370712475209 0.244549357572172 0.268809012217995 0.78814345915061 df.mm.trans2:exp2 -0.165143382384388 0.183597189370338 -0.899487530014821 0.368653917115954 df.mm.trans1:exp3 0.00659635753197188 0.244549357572172 0.0269735222265924 0.978487336382934 df.mm.trans2:exp3 -0.148076412165661 0.183597189370338 -0.806528752828419 0.420169067820949 df.mm.trans1:exp4 0.00732206261453945 0.244549357572172 0.0299410421161240 0.976121271402782 df.mm.trans2:exp4 -0.0699029980091186 0.183597189370338 -0.380741111826695 0.703492784815024 df.mm.trans1:exp5 -0.0845912309334216 0.244549357572172 -0.345906575969871 0.729500584079852 df.mm.trans2:exp5 -0.152139982980848 0.183597189370338 -0.828661830296126 0.407534015512138 df.mm.trans1:exp6 -0.023487161035853 0.244549357572172 -0.0960426200625836 0.923509906885694 df.mm.trans2:exp6 -0.0192063989212469 0.183597189370338 -0.104611617351643 0.916709269538351 df.mm.trans1:exp7 -0.0762337237826585 0.244549357572172 -0.311731441617712 0.755322917337602 df.mm.trans2:exp7 -0.145489171841197 0.183597189370338 -0.79243681420268 0.428332454453549 df.mm.trans1:exp8 -0.0131034835462365 0.244549357572172 -0.0535821630296837 0.95728096165442 df.mm.trans2:exp8 0.00479962674326132 0.183597189370338 0.0261421580565697 0.979150235130623 df.mm.trans1:probe2 -0.112299493121974 0.164048696215584 -0.684549744756252 0.493819187756197 df.mm.trans1:probe3 -0.118393965194287 0.164048696215584 -0.721700128836745 0.47068211846416 df.mm.trans1:probe4 -0.0673276329263255 0.164048696215584 -0.410412484094645 0.681609309747497 df.mm.trans1:probe5 0.0921475644137403 0.164048696215584 0.561708605673068 0.574466208742247 df.mm.trans1:probe6 -0.205226123693289 0.164048696215584 -1.25100734371940 0.211284309268052 df.mm.trans1:probe7 -0.184794765635735 0.164048696215584 -1.12646287290749 0.260295226083291 df.mm.trans1:probe8 -0.0864276093730439 0.164048696215584 -0.526841184153427 0.598444650023885 df.mm.trans1:probe9 -0.122424298125734 0.164048696215584 -0.746268034735556 0.455716829330679 df.mm.trans1:probe10 0.0610279852304271 0.164048696215584 0.372011400506515 0.709979317861246 df.mm.trans1:probe11 -0.217897179687632 0.164048696215584 -1.32824694565865 0.184461648353730 df.mm.trans1:probe12 0.267136769640789 0.164048696215584 1.62839922415313 0.103819745602908 df.mm.trans1:probe13 -0.116323581318039 0.164048696215584 -0.709079584303264 0.478474211792977 df.mm.trans1:probe14 -0.165588391510061 0.164048696215584 -1.00938559909342 0.313083907189161 df.mm.trans1:probe15 -0.046841482649124 0.164048696215584 -0.285534013556362 0.775306289568268 df.mm.trans1:probe16 0.0167113462897522 0.164048696215584 0.101868205449137 0.918885890967509 df.mm.trans1:probe17 0.225002241391493 0.164048696215584 1.37155763247156 0.170571840454706 df.mm.trans1:probe18 -0.0375726126279877 0.164048696215584 -0.229033290082427 0.818899463647152 df.mm.trans1:probe19 -0.201160919047147 0.164048696215584 -1.22622686853172 0.220461083718247 df.mm.trans1:probe20 -0.084101206886531 0.164048696215584 -0.512660013926657 0.608325566791078 df.mm.trans1:probe21 0.0668844968721076 0.164048696215584 0.407711237059828 0.683590826440763 df.mm.trans1:probe22 0.00810468616837021 0.164048696215584 0.0494041486176731 0.96060910788438 df.mm.trans2:probe2 0.391643241258108 0.164048696215584 2.38735966998136 0.0171927721702065 * df.mm.trans2:probe3 0.394469334845227 0.164048696215584 2.40458683272214 0.0164088586461324 * df.mm.trans2:probe4 0.267780529729713 0.164048696215584 1.63232342534323 0.102990669068914 df.mm.trans2:probe5 0.197496422169403 0.164048696215584 1.20388900811418 0.228975703614663 df.mm.trans2:probe6 0.223958637170567 0.164048696215584 1.36519608102373 0.172561336457897 df.mm.trans3:probe2 0.132787173804146 0.164048696215584 0.809437544262128 0.418495493249097 df.mm.trans3:probe3 -0.116330090500770 0.164048696215584 -0.709119262660248 0.47844960369364 df.mm.trans3:probe4 -0.0751086738795168 0.164048696215584 -0.457843772076147 0.6471845173853 df.mm.trans3:probe5 -0.0783166656444224 0.164048696215584 -0.477398891006747 0.633203787885039 df.mm.trans3:probe6 -0.0341558173055076 0.164048696215584 -0.208205356662036 0.835119705287287 df.mm.trans3:probe7 0.0073577665401294 0.164048696215584 0.0448511125651388 0.964236772234056 df.mm.trans3:probe8 -0.126928721504796 0.164048696215584 -0.773725877942934 0.439313226443554 df.mm.trans3:probe9 -0.159383544573050 0.164048696215584 -0.971562397323759 0.331551340583547