chr2.13375_chr2_44138741_44146411_+_1.R fitVsDatCorrelation=0.84677367178467 cont.fitVsDatCorrelation=0.270701795358688 fstatistic=8158.49263796864,36,324 cont.fstatistic=2484.94592607785,36,324 residuals=-0.478179508982942,-0.0799120228476146,-0.00870628064375703,0.0731477850924334,0.705294293891472 cont.residuals=-0.569797909411903,-0.150455732049158,-0.0485075872948527,0.0849057427473735,1.09994302881373 predictedValues: Include Exclude Both chr2.13375_chr2_44138741_44146411_+_1.R.tl.Lung 48.41571061821 49.0014054222957 62.5497388161624 chr2.13375_chr2_44138741_44146411_+_1.R.tl.cerebhem 57.764066064198 64.2679590595341 60.4704340719435 chr2.13375_chr2_44138741_44146411_+_1.R.tl.cortex 47.1974316776958 48.3651928404546 55.433880605975 chr2.13375_chr2_44138741_44146411_+_1.R.tl.heart 47.6789223335167 48.3993111327321 62.9729027894462 chr2.13375_chr2_44138741_44146411_+_1.R.tl.kidney 47.7593165363957 46.9668828816923 63.2836016419469 chr2.13375_chr2_44138741_44146411_+_1.R.tl.liver 78.5577073337438 50.1555374155382 135.264460520432 chr2.13375_chr2_44138741_44146411_+_1.R.tl.stomach 47.5051482033105 49.2703394722529 62.9204531600004 chr2.13375_chr2_44138741_44146411_+_1.R.tl.testicle 52.9338448363923 49.6701602894722 62.3016411328744 diffExp=-0.585694804085698,-6.50389299533606,-1.16776116275885,-0.720388799215407,0.792433654703387,28.4021699182056,-1.76519126894240,3.26368454692014 diffExpScore=1.90185050476066 diffExp1.5=0,0,0,0,0,1,0,0 diffExp1.5Score=0.5 diffExp1.4=0,0,0,0,0,1,0,0 diffExp1.4Score=0.5 diffExp1.3=0,0,0,0,0,1,0,0 diffExp1.3Score=0.5 diffExp1.2=0,0,0,0,0,1,0,0 diffExp1.2Score=0.5 cont.predictedValues: Include Exclude Both Lung 55.2271471149099 56.0043074012322 49.5224416994389 cerebhem 54.2257344872857 51.8487048147847 51.1422961527823 cortex 56.5997772785899 52.0640071080292 57.8000878284094 heart 54.2144381255655 51.8586625431452 58.516818921226 kidney 52.8165953651771 49.0993510738362 52.8513105896634 liver 54.7431609831947 53.2506010100128 53.4530092958844 stomach 56.2313926566331 56.7681099595275 63.280418240455 testicle 51.3129399958243 57.3744653945759 52.9809770952404 cont.diffExp=-0.777160286322378,2.37702967250097,4.53577017056075,2.35577558242039,3.71724429134083,1.49255997318192,-0.536717302894338,-6.06152539875153 cont.diffExpScore=2.69700672747589 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=0.266515028367084 cont.tran.correlation=0.0115239007793044 tran.covariance=0.0057979068159255 cont.tran.covariance=2.90346238898466e-05 tran.mean=52.1193085073397 cont.tran.mean=53.9774622070202 weightedLogRatios: wLogRatio Lung -0.0467257061766312 cerebhem -0.438483125751899 cortex -0.09450228720396 heart -0.0580649455888955 kidney 0.0645466318889308 liver 1.85740406938433 stomach -0.141525052356720 testicle 0.250559270595511 cont.weightedLogRatios: wLogRatio Lung -0.0561536135622968 cerebhem 0.177991113712819 cortex 0.333643545718233 heart 0.176400953948934 kidney 0.28683443709128 liver 0.110264669960433 stomach -0.0383232593156951 testicle -0.445930064177476 varWeightedLogRatios=0.500149933203727 cont.varWeightedLogRatios=0.0621332740524965 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.72024172076721 0.0790396452246045 47.0680468035441 6.57052020922645e-147 *** df.mm.trans1 0.167333574386359 0.0669457538460341 2.49953977322002 0.0129297385000956 * df.mm.trans2 0.209192984956227 0.0669457538460342 3.12481334420912 0.00194004450871191 ** df.mm.exp2 0.481562259462113 0.0932300792456381 5.16530998749145 4.20161696932989e-07 *** df.mm.exp3 0.0822176271252666 0.0932300792456382 0.881878764777658 0.378496136884932 df.mm.exp4 -0.0344407972349138 0.0932300792456381 -0.369417225787944 0.71205807752707 df.mm.exp5 -0.0677206244691958 0.0932300792456381 -0.726381710893635 0.468129224503964 df.mm.exp6 -0.263980702709419 0.0932300792456381 -2.83149713960765 0.00492275318127127 ** df.mm.exp7 -0.0194222044437367 0.0932300792456381 -0.208325516838444 0.8351057063892 df.mm.exp8 0.106748232503313 0.0932300792456381 1.14499776646181 0.253055167741122 df.mm.trans1:exp2 -0.305019732108254 0.080739617023559 -3.77781990245572 0.000188230933393290 *** df.mm.trans2:exp2 -0.210350036095427 0.080739617023559 -2.60528899999673 0.00960313128323033 ** df.mm.trans1:exp3 -0.107702510223715 0.080739617023559 -1.33394873785801 0.183157543978386 df.mm.trans2:exp3 -0.0952862080954647 0.080739617023559 -1.18016670883714 0.23879964560182 df.mm.trans1:exp4 0.0191058570697269 0.080739617023559 0.236635468114148 0.813089136882559 df.mm.trans2:exp4 0.022077398274449 0.080739617023559 0.273439472322578 0.784689633769847 df.mm.trans1:exp5 0.0540704224728299 0.080739617023559 0.669688864848748 0.503533118397369 df.mm.trans2:exp5 0.0253143784928012 0.080739617023559 0.313531069702928 0.754078967830854 df.mm.trans1:exp6 0.747989822094827 0.080739617023559 9.26422306259605 2.80628514547663e-18 *** df.mm.trans2:exp6 0.287260648294462 0.080739617023559 3.55786488571828 0.000429725573233326 *** df.mm.trans1:exp7 0.000435932237540581 0.080739617023559 0.00539923588457671 0.99569537678853 df.mm.trans2:exp7 0.0248954912285379 0.080739617023559 0.308342944223698 0.758019538698612 df.mm.trans1:exp8 -0.0175296698503941 0.080739617023559 -0.217113611590196 0.828256458503983 df.mm.trans2:exp8 -0.0931928560880075 0.080739617023559 -1.15423951120321 0.249252639766274 df.mm.trans1:probe2 -0.0344540415675849 0.0403698085117795 -0.853460614199633 0.394034434572154 df.mm.trans1:probe3 0.107745162651452 0.0403698085117795 2.66895401844705 0.00799187469515566 ** df.mm.trans1:probe4 -0.0420154282812765 0.0403698085117795 -1.04076362584224 0.298761263266942 df.mm.trans1:probe5 0.0109624850059801 0.0403698085117795 0.271551573071776 0.786139779974168 df.mm.trans1:probe6 -0.111996588778555 0.0403698085117795 -2.77426603957944 0.00585351689348742 ** df.mm.trans2:probe2 -0.0189082531147173 0.0403698085117795 -0.468376091236600 0.639830602967822 df.mm.trans2:probe3 -0.0649267267276388 0.0403698085117795 -1.60829910076719 0.108743642539925 df.mm.trans2:probe4 -0.105621168893071 0.0403698085117795 -2.61634059676680 0.00930409502048764 ** df.mm.trans2:probe5 -0.106481892986106 0.0403698085117795 -2.63766158204678 0.00875067262124897 ** df.mm.trans2:probe6 -0.042333491706611 0.0403698085117795 -1.04864237080190 0.295124335320647 df.mm.trans3:probe2 0.0978094421388873 0.0403698085117795 2.42283641524699 0.0159476599361670 * df.mm.trans3:probe3 0.0197719014415855 0.0403698085117795 0.489769512674706 0.624628450751142 cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.12986113545761 0.143036159755957 28.8728468556750 1.33787688673325e-91 *** df.mm.trans1 -0.119881714447434 0.121150133137534 -0.989530191529705 0.323142203052756 df.mm.trans2 -0.0930050507568145 0.121150133137534 -0.767684263716256 0.443233884977998 df.mm.exp2 -0.127583610614244 0.168716249562422 -0.756202268276716 0.450077395410913 df.mm.exp3 -0.202968676551694 0.168716249562422 -1.20301794923790 0.229847705574322 df.mm.exp4 -0.262302265879637 0.168716249562422 -1.55469474078483 0.120995012469411 df.mm.exp5 -0.241268543625577 0.168716249562422 -1.43002552659466 0.153673283435265 df.mm.exp6 -0.135598697688603 0.168716249562422 -0.803708581955136 0.422154547800574 df.mm.exp7 -0.213583319080133 0.168716249562422 -1.26593211758842 0.206446872625239 df.mm.exp8 -0.11684791290124 0.168716249562422 -0.69257059236614 0.489075150100059 df.mm.trans1:exp2 0.109284584462398 0.146112558152292 0.747947923466587 0.455034101938043 df.mm.trans2:exp2 0.0504849598573867 0.146112558152292 0.345521018150723 0.729926934847531 df.mm.trans1:exp3 0.227519098794635 0.146112558152292 1.55714951316842 0.120411212974310 df.mm.trans2:exp3 0.130013938456883 0.146112558152292 0.889820424069023 0.374222527230382 df.mm.trans1:exp4 0.243794896980103 0.146112558152292 1.66854170553907 0.0961742578858304 . df.mm.trans2:exp4 0.185395650243231 0.146112558152292 1.26885500184039 0.205403585398758 df.mm.trans1:exp5 0.196639363161409 0.146112558152292 1.34580740798784 0.179305594935307 df.mm.trans2:exp5 0.109685756263633 0.146112558152292 0.750693558792586 0.453381938076701 df.mm.trans1:exp6 0.126796517082703 0.146112558152292 0.867800267726087 0.386145965346556 df.mm.trans2:exp6 0.0851791831311866 0.146112558152292 0.582969624297487 0.560319271253185 df.mm.trans1:exp7 0.231603880272575 0.146112558152292 1.58510591561319 0.113917770695451 df.mm.trans2:exp7 0.227129437107544 0.146112558152292 1.55448265350887 0.121045555779702 df.mm.trans1:exp8 0.0433362469531866 0.146112558152292 0.296594950503963 0.766965801209884 df.mm.trans2:exp8 0.141018657840673 0.146112558152292 0.965137149222248 0.335195933620141 df.mm.trans1:probe2 -0.0856191047842155 0.0730562790761461 -1.17196093021621 0.24207378714237 df.mm.trans1:probe3 0.0419352567263474 0.0730562790761461 0.574013038395215 0.566357242160051 df.mm.trans1:probe4 0.0475749128115287 0.0730562790761461 0.651209087201685 0.515373118736846 df.mm.trans1:probe5 -0.00105782626979861 0.0730562790761461 -0.0144796078198295 0.98845626003742 df.mm.trans1:probe6 0.0104436239854418 0.0730562790761461 0.142953133084652 0.886416055289677 df.mm.trans2:probe2 -0.0281305057953474 0.0730562790761461 -0.385052539645869 0.700451135792656 df.mm.trans2:probe3 -0.0058968543969405 0.0730562790761461 -0.0807165991960012 0.935717170647964 df.mm.trans2:probe4 -0.0421598438798269 0.0730562790761461 -0.577087204727249 0.564281299727019 df.mm.trans2:probe5 -0.0686720013295257 0.0730562790761461 -0.93998766701421 0.347924137149135 df.mm.trans2:probe6 0.0420118940009095 0.0730562790761461 0.575062055338471 0.565648441769055 df.mm.trans3:probe2 0.0441938938949414 0.0730562790761461 0.6049294386986 0.545649308415598 df.mm.trans3:probe3 -0.087839201154994 0.0730562790761461 -1.20234978109739 0.230106009017227