chr11.4929_chr11_86364773_86366322_-_1.R fitVsDatCorrelation=0.936508252603841 cont.fitVsDatCorrelation=0.346263352422948 fstatistic=7166.88658883872,40,416 cont.fstatistic=992.283952856288,40,416 residuals=-0.535951298683597,-0.107411560967583,0.00255104592004279,0.0834484728878335,1.09876598785441 cont.residuals=-0.85612030755727,-0.330994839127862,-0.101422979863602,0.361096615663354,1.52032304833036 predictedValues: Include Exclude Both chr11.4929_chr11_86364773_86366322_-_1.R.tl.Lung 69.0569301305576 158.720601715178 62.6194898834692 chr11.4929_chr11_86364773_86366322_-_1.R.tl.cerebhem 79.3213910900362 129.104620899497 82.9075330670185 chr11.4929_chr11_86364773_86366322_-_1.R.tl.cortex 61.0139904902001 127.719030895782 61.2153992347582 chr11.4929_chr11_86364773_86366322_-_1.R.tl.heart 60.9988558591196 133.659657426272 56.8705295180145 chr11.4929_chr11_86364773_86366322_-_1.R.tl.kidney 69.5902683513533 175.025600727777 64.1984491579423 chr11.4929_chr11_86364773_86366322_-_1.R.tl.liver 69.1196374687603 198.968334882039 62.4708565142996 chr11.4929_chr11_86364773_86366322_-_1.R.tl.stomach 67.2110939858716 143.517817455200 65.025286171345 chr11.4929_chr11_86364773_86366322_-_1.R.tl.testicle 68.1075536505211 174.299511759026 65.245261129127 diffExp=-89.6636715846201,-49.7832298094611,-66.7050404055817,-72.6608015671522,-105.435332376424,-129.848697413279,-76.3067234693286,-106.191958108505 diffExpScore=0.998566504421419 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 101.680863187544 93.690213650942 95.5936078667174 cerebhem 83.4744138271266 109.302926618278 83.8906720435007 cortex 71.3817742958247 97.8562601953217 79.3437121756654 heart 90.7494149353154 92.865141584533 79.5478870230206 kidney 84.7990795911177 74.4463537750289 67.0783726007782 liver 112.280734850820 76.1639719527755 101.066957040442 stomach 91.391515651661 81.6127454318372 84.9459165355879 testicle 86.2620284155391 76.3379876224847 113.836364990721 cont.diffExp=7.99064953660235,-25.8285127911513,-26.4744858994971,-2.11572664921769,10.3527258160888,36.1167628980442,9.77877021982381,9.92404079305435 cont.diffExpScore=6.19843263725486 cont.diffExp1.5=0,0,0,0,0,0,0,0 cont.diffExp1.5Score=0 cont.diffExp1.4=0,0,0,0,0,1,0,0 cont.diffExp1.4Score=0.5 cont.diffExp1.3=0,-1,-1,0,0,1,0,0 cont.diffExp1.3Score=1.5 cont.diffExp1.2=0,-1,-1,0,0,1,0,0 cont.diffExp1.2Score=1.5 tran.correlation=0.136675338621595 cont.tran.correlation=-0.377997944040506 tran.covariance=0.00243744580864421 cont.tran.covariance=-0.00720334108943868 tran.mean=111.589681049199 cont.tran.mean=89.0184640991343 weightedLogRatios: wLogRatio Lung -3.87066012904055 cerebhem -2.24904299493328 cortex -3.30985427730072 heart -3.53240002809723 kidney -4.33833026841355 liver -5.03753014571554 stomach -3.4799067714858 testicle -4.40800759361727 cont.weightedLogRatios: wLogRatio Lung 0.374926826292003 cerebhem -1.22911834154038 cortex -1.39614089893179 heart -0.104160747056997 kidney 0.569674503627366 liver 1.75696978262217 stomach 0.504563791816332 testicle 0.537308164997295 varWeightedLogRatios=0.71599002146234 cont.varWeightedLogRatios=1.06251244049825 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.93461644267913 0.0946428116489997 52.1393686081524 1.55205856587496e-184 *** df.mm.trans1 -0.667351573716968 0.0811083834592943 -8.2278988343035 2.47095522837006e-15 *** df.mm.trans2 0.083781224845938 0.0778346388686499 1.07640025140122 0.282372129133896 df.mm.exp2 -0.348595099454907 0.106295750925794 -3.27948291835545 0.00112745383834625 ** df.mm.exp3 -0.318462912785201 0.106295750925794 -2.9960079308111 0.0028990349868291 ** df.mm.exp4 -0.199625569357858 0.106295750925794 -1.87802021829845 0.0610776789099065 . df.mm.exp5 0.0805778304349526 0.106295750925794 0.758053165184415 0.448848371800402 df.mm.exp6 0.229284314471172 0.106295750925794 2.15704120319199 0.0315746065316618 * df.mm.exp7 -0.165478802049376 0.106295750925794 -1.55677720518573 0.120283804202212 df.mm.exp8 0.0387097574570369 0.106295750925794 0.364170318379522 0.715915855567494 df.mm.trans1:exp2 0.487171701882159 0.0944462531571814 5.15818982327851 3.86648215744165e-07 *** df.mm.trans2:exp2 0.142072755269005 0.0879246766880967 1.61584620632718 0.106885658767635 df.mm.trans1:exp3 0.19463486419323 0.0944462531571814 2.06080027197384 0.0399432176884912 * df.mm.trans2:exp3 0.101150258300519 0.0879246766880967 1.15041945117795 0.250632017541619 df.mm.trans1:exp4 0.0755494381809629 0.0944462531571814 0.799919908471439 0.424213740271814 df.mm.trans2:exp4 0.0277768338363199 0.0879246766880967 0.315916246526048 0.752224518360345 df.mm.trans1:exp5 -0.0728843341751163 0.0944462531571814 -0.771701700583285 0.440729259822951 df.mm.trans2:exp5 0.0172089880846287 0.0879246766880967 0.195724212278604 0.844921598504737 df.mm.trans1:exp6 -0.228376673709832 0.0944462531571814 -2.41805964848344 0.0160322255533238 * df.mm.trans2:exp6 -0.00328405818120668 0.0879246766880968 -0.0373508132746 0.970223207309938 df.mm.trans1:exp7 0.138385886261821 0.0944462531571814 1.46523426431235 0.143612378658606 df.mm.trans2:exp7 0.0647925584146571 0.0879246766880968 0.736909828448977 0.461592573173012 df.mm.trans1:exp8 -0.0525528692408795 0.0944462531571814 -0.556431488641681 0.578215102477663 df.mm.trans2:exp8 0.0549199593343562 0.0879246766880967 0.624625092784576 0.532559571747812 df.mm.trans1:probe2 0.358041550072725 0.0517303433260318 6.92130627891177 1.7014981417446e-11 *** df.mm.trans1:probe3 -0.0985584607317555 0.0517303433260318 -1.90523500125620 0.057438755628082 . df.mm.trans1:probe4 0.0928885786937337 0.0517303433260318 1.79563043122102 0.0732789157706662 . df.mm.trans1:probe5 0.0277072851827482 0.0517303433260318 0.535609922557876 0.592514396647055 df.mm.trans1:probe6 -0.314121315191070 0.0517303433260318 -6.07228359594121 2.84534538177434e-09 *** df.mm.trans1:probe7 -0.300816905919937 0.0517303433260318 -5.81509587176004 1.20898291945185e-08 *** df.mm.trans1:probe8 0.134360886728223 0.0517303433260318 2.59733220561499 0.00972825572006543 ** df.mm.trans1:probe9 -0.287505181183494 0.0517303433260318 -5.55776673221528 4.88926510092122e-08 *** df.mm.trans2:probe2 0.272988186955626 0.0517303433260318 5.27713851104971 2.11671074703793e-07 *** df.mm.trans2:probe3 0.0686508174022917 0.0517303433260318 1.32708992417890 0.185206846958402 df.mm.trans2:probe4 -0.0512542994390611 0.0517303433260318 -0.99079758887409 0.322360365963192 df.mm.trans2:probe5 -0.0500734646642029 0.0517303433260318 -0.967970855105555 0.333621339463416 df.mm.trans2:probe6 0.247166430270888 0.0517303433260318 4.77797776661011 2.45916337652507e-06 *** df.mm.trans3:probe2 -0.12959801871041 0.0517303433260318 -2.50526113645941 0.0126173633567701 * df.mm.trans3:probe3 -0.382293543863109 0.0517303433260318 -7.39012191459265 8.11658974979994e-13 *** df.mm.trans3:probe4 -0.343986534093540 0.0517303433260318 -6.64960856581902 9.26104685376373e-11 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.64074013519721 0.253212852431413 18.3274272638046 1.97968927745376e-55 *** df.mm.trans1 0.0331282023477504 0.217002060420569 0.152663077408321 0.878737996500792 df.mm.trans2 -0.0922167555088765 0.208243294789183 -0.442831811714432 0.658117565753993 df.mm.exp2 0.087422004709776 0.284389800179228 0.307402039927876 0.758691207906696 df.mm.exp3 -0.123973860089670 0.284389800179228 -0.435929347717602 0.663114113850037 df.mm.exp4 0.0611642816249912 0.284389800179228 0.215071994798844 0.829816585037827 df.mm.exp5 -0.0572251067445466 0.284389800179228 -0.201220672149571 0.840624377077516 df.mm.exp6 -0.163619302006060 0.284389800179229 -0.575334635429766 0.565376056157078 df.mm.exp7 -0.126603588516442 0.284389800179229 -0.445176263131284 0.65642393329739 df.mm.exp8 -0.543928732045827 0.284389800179228 -1.91261687902672 0.0564835077996923 . df.mm.trans1:exp2 -0.284720957142669 0.252686968473448 -1.12677341005256 0.260487832824718 df.mm.trans2:exp2 0.0667074257644327 0.2352387655797 0.283573269057271 0.776878496893527 df.mm.trans1:exp3 -0.229822681214019 0.252686968473448 -0.909515368372343 0.363604791088194 df.mm.trans2:exp3 0.167479788990745 0.2352387655797 0.711956588354067 0.476890730213759 df.mm.trans1:exp4 -0.174901371595691 0.252686968473448 -0.692166171656256 0.489219135728772 df.mm.trans2:exp4 -0.0700096717226811 0.2352387655797 -0.29761111673136 0.766148555086195 df.mm.trans1:exp5 -0.124329320495937 0.252686968473448 -0.492029016165909 0.622958369312952 df.mm.trans2:exp5 -0.172689851174625 0.2352387655797 -0.734104562864308 0.463298564341334 df.mm.trans1:exp6 0.262782482183236 0.252686968473448 1.03995264880804 0.29896593833706 df.mm.trans2:exp6 -0.043485896492796 0.2352387655797 -0.184858547381141 0.853430072489467 df.mm.trans1:exp7 0.0199171199985242 0.252686968473448 0.0788213184037509 0.937212647211025 df.mm.trans2:exp7 -0.0114047080562359 0.2352387655797 -0.0484814143116729 0.961355843237573 df.mm.trans1:exp8 0.37947912202287 0.252686968473448 1.50177559339688 0.133913722650294 df.mm.trans2:exp8 0.339105677930155 0.2352387655797 1.44153824772246 0.150185014043716 df.mm.trans1:probe2 -0.0865781192595958 0.138402352620504 -0.625553811913811 0.531950663321786 df.mm.trans1:probe3 -0.0561814991242682 0.138402352620504 -0.40592878705116 0.685003638422373 df.mm.trans1:probe4 -0.0288244641408364 0.138402352620504 -0.208265709325566 0.835123431995957 df.mm.trans1:probe5 -0.0128853640050093 0.138402352620504 -0.0931007584845083 0.925868335117784 df.mm.trans1:probe6 -0.21319939814992 0.138402352620504 -1.54043189377356 0.124215399258910 df.mm.trans1:probe7 -0.216136648894165 0.138402352620504 -1.56165444301953 0.119129802309804 df.mm.trans1:probe8 0.0372350537016393 0.138402352620504 0.26903483211544 0.788036257688554 df.mm.trans1:probe9 -0.0477802174540527 0.138402352620504 -0.345226916662789 0.730098273743348 df.mm.trans2:probe2 0.108481961942918 0.138402352620504 0.783815880936454 0.433594198970454 df.mm.trans2:probe3 0.0254188800578395 0.138402352620504 0.183659306193569 0.854370219382156 df.mm.trans2:probe4 0.108412697213344 0.138402352620504 0.783315421744377 0.433887627791099 df.mm.trans2:probe5 -0.108539856737731 0.138402352620504 -0.784234188817182 0.433349025414099 df.mm.trans2:probe6 -0.219070075726336 0.138402352620504 -1.58284936331264 0.114215724153315 df.mm.trans3:probe2 -0.0401141279997373 0.138402352620504 -0.289837038462267 0.77208531879169 df.mm.trans3:probe3 0.135715934560432 0.138402352620504 0.980589794832183 0.327364994091663 df.mm.trans3:probe4 -0.181784316692826 0.138402352620504 -1.31344816942002 0.189755921353122