chr4.16979_chr4_141045589_141050458_-_2.R fitVsDatCorrelation=0.82886699346227 cont.fitVsDatCorrelation=0.193677394893617 fstatistic=6109.9619200105,47,577 cont.fstatistic=1978.53582965135,47,577 residuals=-0.760713326960879,-0.102699686919951,-0.00649854617541786,0.0939702060217102,0.881427938839537 cont.residuals=-0.56723636552851,-0.211140299321054,-0.0704835774193155,0.113141370761133,1.68385316546026 predictedValues: Include Exclude Both chr4.16979_chr4_141045589_141050458_-_2.R.tl.Lung 107.805529127659 51.1531781641217 106.325016020600 chr4.16979_chr4_141045589_141050458_-_2.R.tl.cerebhem 55.832602070028 53.602098301889 64.3167774026121 chr4.16979_chr4_141045589_141050458_-_2.R.tl.cortex 63.5278951371358 48.9403016004741 57.7209823596341 chr4.16979_chr4_141045589_141050458_-_2.R.tl.heart 61.3437265097566 46.1793874275352 63.5078255112456 chr4.16979_chr4_141045589_141050458_-_2.R.tl.kidney 61.1024402878677 47.6197461513799 57.4503605435966 chr4.16979_chr4_141045589_141050458_-_2.R.tl.liver 56.2736396886572 52.1799433713683 59.0446312546396 chr4.16979_chr4_141045589_141050458_-_2.R.tl.stomach 60.6130703600887 50.3917538638927 65.9258893063964 chr4.16979_chr4_141045589_141050458_-_2.R.tl.testicle 55.8295496806229 52.4225741095286 58.6597538625409 diffExp=56.6523509635369,2.23050376813895,14.5875935366617,15.1643390822214,13.4826941364878,4.0936963172889,10.2213164961960,3.40697557109426 diffExpScore=0.991724558200542 diffExp1.5=1,0,0,0,0,0,0,0 diffExp1.5Score=0.5 diffExp1.4=1,0,0,0,0,0,0,0 diffExp1.4Score=0.5 diffExp1.3=1,0,0,1,0,0,0,0 diffExp1.3Score=0.666666666666667 diffExp1.2=1,0,1,1,1,0,1,0 diffExp1.2Score=0.833333333333333 cont.predictedValues: Include Exclude Both Lung 64.5107973187689 54.1317748177278 53.886281360044 cerebhem 63.6759658747017 56.437223995162 57.743030311984 cortex 60.4502995434949 62.7771538782188 63.7346722896785 heart 60.3795487069217 56.2548705101631 60.3503180007615 kidney 59.4354536095638 58.1672211111095 54.7267963563614 liver 58.1420840412689 62.7461466095697 55.3567332967316 stomach 60.0220971804476 56.4745258218884 55.5491625319142 testicle 63.3900565975398 57.7361293994642 64.1415024081172 cont.diffExp=10.3790225010411,7.23874187953967,-2.32685433472395,4.12467819675861,1.26823249845428,-4.6040625683008,3.54757135855913,5.65392719807556 cont.diffExpScore=1.48939188633471 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=-0.00813441170687749 cont.tran.correlation=-0.646627649058014 tran.covariance=-0.000577238367686837 cont.tran.covariance=-0.00129166659571997 tran.mean=57.8010897407503 cont.tran.mean=59.6707093135007 weightedLogRatios: wLogRatio Lung 3.21131711623223 cerebhem 0.163159444483665 cortex 1.04900044198121 heart 1.12860026947049 kidney 0.994200509826187 liver 0.301542763126332 stomach 0.740979434532068 testicle 0.251285955797904 cont.weightedLogRatios: wLogRatio Lung 0.715524810264286 cerebhem 0.493992557856722 cortex -0.155637774557645 heart 0.287649775466751 kidney 0.0878740984735888 liver -0.312526162534724 stomach 0.247606843418898 testicle 0.383280334178676 varWeightedLogRatios=0.960215504594846 cont.varWeightedLogRatios=0.113534606946996 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.2084447280051 0.102572990477363 41.0287806606737 3.19037328591075e-173 *** df.mm.trans1 0.537687051299324 0.0914997462201514 5.87637751481443 7.09331915579902e-09 *** df.mm.trans2 -0.239596000012555 0.0849886908932874 -2.81915155409787 0.00498038215510866 ** df.mm.exp2 -0.108527321668898 0.116663735475404 -0.930257557986203 0.35262677521653 df.mm.exp3 0.037806589814028 0.116663735475404 0.324064626080815 0.746006542546457 df.mm.exp4 -0.150789667819422 0.116663735475404 -1.29251534082082 0.196696086527330 df.mm.exp5 -0.0237749457171432 0.116663735475404 -0.203790369134508 0.838589172168034 df.mm.exp6 -0.0420221921084203 0.116663735475404 -0.360199267897433 0.7188299323195 df.mm.exp7 -0.112846102225073 0.116663735475404 -0.967276607124104 0.333811025404993 df.mm.exp8 -0.0387662525941026 0.116663735475404 -0.332290513724169 0.739790580470382 df.mm.trans1:exp2 -0.549443660841747 0.110352846045448 -4.9789713680376 8.45437189375827e-07 *** df.mm.trans2:exp2 0.155290911739402 0.0977301231195631 1.58897693753459 0.112613361242999 df.mm.trans1:exp3 -0.566656434646976 0.110352846045448 -5.13495079604565 3.86469890208884e-07 *** df.mm.trans2:exp3 -0.0820299938239774 0.0977301231195631 -0.83935219976774 0.401619315870395 df.mm.trans1:exp4 -0.413046371400636 0.110352846045448 -3.74296075001569 0.000200071463894517 *** df.mm.trans2:exp4 0.0484985821078433 0.0977301231195632 0.496250087074075 0.619906959969218 df.mm.trans1:exp5 -0.544002197426543 0.110352846045448 -4.92966168903791 1.07819919216888e-06 *** df.mm.trans2:exp5 -0.0478021686160703 0.0977301231195631 -0.48912420336961 0.624939638863167 df.mm.trans1:exp6 -0.608080541728998 0.110352846045448 -5.51032948872533 5.40376146698769e-08 *** df.mm.trans2:exp6 0.0618957618976061 0.097730123119563 0.633333509893186 0.526766818375231 df.mm.trans1:exp7 -0.46297229321473 0.110352846045448 -4.19538154026456 3.15326401448744e-05 *** df.mm.trans2:exp7 0.097849025441229 0.0977301231195631 1.00121663943389 0.317141771568028 df.mm.trans1:exp8 -0.61925940178804 0.110352846045448 -5.61163054673735 3.11475501403065e-08 *** df.mm.trans2:exp8 0.0632789301055073 0.0977301231195631 0.64748644620136 0.517574688402191 df.mm.trans1:probe2 0.0347756387518168 0.0551764230227239 0.630262652899677 0.528772272690108 df.mm.trans1:probe3 0.529062825664984 0.0551764230227239 9.58856694003332 2.64500731900296e-20 *** df.mm.trans1:probe4 0.0171159294567418 0.055176423022724 0.31020367974366 0.756518081861843 df.mm.trans1:probe5 0.236838208879661 0.055176423022724 4.29238062028997 2.07322487806802e-05 *** df.mm.trans1:probe6 -0.231414047225658 0.055176423022724 -4.19407483392593 3.17095048328823e-05 *** df.mm.trans1:probe7 -0.263254264876523 0.055176423022724 -4.77113684531714 2.32369466065316e-06 *** df.mm.trans1:probe8 -0.252916279730124 0.055176423022724 -4.58377447965343 5.60179742972526e-06 *** df.mm.trans1:probe9 -0.266628673009324 0.055176423022724 -4.83229354863245 1.73231107891925e-06 *** df.mm.trans1:probe10 -0.27795419313595 0.055176423022724 -5.03755368523032 6.31600272581843e-07 *** df.mm.trans1:probe11 -0.283313811353640 0.0551764230227239 -5.13468970681481 3.86983237260434e-07 *** df.mm.trans1:probe12 -0.000686365720933198 0.055176423022724 -0.0124394747490341 0.990079290894385 df.mm.trans1:probe13 -0.129709099723696 0.055176423022724 -2.35080660575399 0.0190683657992792 * df.mm.trans1:probe14 -0.239744937137722 0.055176423022724 -4.34506124180947 1.64534402088653e-05 *** df.mm.trans1:probe15 -0.173975954941919 0.055176423022724 -3.15308505718591 0.00169948226482278 ** df.mm.trans1:probe16 0.0129920075217402 0.0551764230227239 0.235463025872292 0.813932918956248 df.mm.trans1:probe17 -0.0272436141348206 0.0551764230227239 -0.493754626384544 0.621667373230483 df.mm.trans2:probe2 -0.083414388057686 0.055176423022724 -1.51177592689059 0.131138346128190 df.mm.trans2:probe3 -0.0373725042796028 0.055176423022724 -0.677327420521827 0.49846971196267 df.mm.trans2:probe4 -0.108260996140526 0.055176423022724 -1.96208797543726 0.050232489529319 . df.mm.trans2:probe5 -0.0697121969851532 0.055176423022724 -1.26344175947112 0.206940713625941 df.mm.trans2:probe6 -0.00745684450012526 0.055176423022724 -0.135145485908976 0.892543978280633 df.mm.trans3:probe2 0.291535076929873 0.055176423022724 5.28368931798653 1.79748401159679e-07 *** df.mm.trans3:probe3 0.188359360640862 0.055176423022724 3.41376534255017 0.00068567134167435 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.15070986085961 0.179875895341975 23.0754090367050 5.78945658031081e-84 *** df.mm.trans1 0.0702956795163702 0.160457433270852 0.438095500366823 0.661481015291515 df.mm.trans2 -0.173505629654470 0.149039399136425 -1.16415948171966 0.244840516963665 df.mm.exp2 -0.0404445577119006 0.204585961420408 -0.197689799588889 0.843357394275145 df.mm.exp3 -0.084694005761696 0.204585961420408 -0.41397760224445 0.679044345066776 df.mm.exp4 -0.141001175702908 0.204585961420408 -0.689202595935512 0.490972832750167 df.mm.exp5 -0.0255186057820758 0.204585961420408 -0.124732926956005 0.90077843168566 df.mm.exp6 0.0168105729075816 0.204585961420408 0.082168750929284 0.934541017787568 df.mm.exp7 -0.0601440263236113 0.204585961420408 -0.293979244255280 0.768879482568595 df.mm.exp8 -0.127279500859017 0.204585961420408 -0.622132134459937 0.534100740408121 df.mm.trans1:exp2 0.0274191372009085 0.193518945811966 0.141687094696922 0.88737662422253 df.mm.trans2:exp2 0.082152150093868 0.171383259045104 0.479347577771569 0.63187300329475 df.mm.trans1:exp3 0.0196829279547441 0.193518945811966 0.101710599301575 0.919021723244774 df.mm.trans2:exp3 0.232863872967364 0.171383259045104 1.35873173532124 0.174762520181540 df.mm.trans1:exp4 0.0748190156562039 0.193518945811966 0.386623724836236 0.699177328601329 df.mm.trans2:exp4 0.179472451554250 0.171383259045104 1.04719943216284 0.295446068760829 df.mm.trans1:exp5 -0.0564230938696549 0.193518945811966 -0.291563669039820 0.770725044759748 df.mm.trans2:exp5 0.097419242375064 0.171383259045104 0.568429162322241 0.569964744728004 df.mm.trans1:exp6 -0.120753443279066 0.193518945811966 -0.623987707107482 0.532882270636029 df.mm.trans2:exp6 0.130865246274183 0.171383259045104 0.763582435083363 0.445428220746421 df.mm.trans1:exp7 -0.0119758029971155 0.193518945811966 -0.061884395591695 0.950676324050403 df.mm.trans2:exp7 0.102512344062221 0.171383259045104 0.598146777190424 0.549976705473031 df.mm.trans1:exp8 0.109753903918343 0.193518945811966 0.567148107684435 0.570834131446821 df.mm.trans2:exp8 0.191741289521061 0.171383259045104 1.11878657570982 0.263696742604466 df.mm.trans1:probe2 -0.107912333512279 0.0967594729059828 -1.11526375941644 0.265201688814883 df.mm.trans1:probe3 -0.0950641293147865 0.0967594729059828 -0.98247878434762 0.326275802901033 df.mm.trans1:probe4 -0.0458041966061143 0.0967594729059829 -0.473382039302967 0.636119683444408 df.mm.trans1:probe5 -0.0318502420381528 0.0967594729059829 -0.329169238748338 0.742147218067189 df.mm.trans1:probe6 -0.094678971040227 0.0967594729059829 -0.978498210012188 0.328238049884733 df.mm.trans1:probe7 -0.0731844674753652 0.0967594729059829 -0.756354548835497 0.449745343880596 df.mm.trans1:probe8 -0.113646778891871 0.0967594729059829 -1.17452870999305 0.240667821798907 df.mm.trans1:probe9 -0.0703139961283437 0.0967594729059829 -0.726688498982057 0.467711500591002 df.mm.trans1:probe10 -0.0505532094504028 0.0967594729059829 -0.522462637839328 0.601548785611385 df.mm.trans1:probe11 -0.116955873543005 0.0967594729059828 -1.20872789020509 0.227262498251672 df.mm.trans1:probe12 -0.050872849667962 0.0967594729059829 -0.525766089253018 0.599252737077921 df.mm.trans1:probe13 -0.102566597538737 0.0967594729059829 -1.06001608378331 0.289580796246198 df.mm.trans1:probe14 0.0102638031496437 0.0967594729059829 0.106075434697920 0.91555936863083 df.mm.trans1:probe15 0.029891177831961 0.0967594729059829 0.308922495485326 0.757491994623824 df.mm.trans1:probe16 -0.129749162824346 0.0967594729059828 -1.34094532480988 0.180465837081919 df.mm.trans1:probe17 -0.040460778812618 0.0967594729059828 -0.418158321841336 0.675986945094384 df.mm.trans2:probe2 0.062112219097028 0.0967594729059829 0.641923909169904 0.5211775243955 df.mm.trans2:probe3 -0.0229587718368120 0.0967594729059829 -0.237276735262087 0.812526330895413 df.mm.trans2:probe4 0.049652137330086 0.0967594729059829 0.513150142708311 0.608042709221816 df.mm.trans2:probe5 -0.00815936299339128 0.0967594729059829 -0.0843262447421494 0.932826295051064 df.mm.trans2:probe6 0.0473078325457892 0.0967594729059829 0.488921974510509 0.625082721334523 df.mm.trans3:probe2 -0.0751502047204216 0.0967594729059829 -0.776670257323972 0.437671605890093 df.mm.trans3:probe3 -0.106721751552016 0.0967594729059829 -1.10295920747432 0.270504684320517