chr4.16371_chr4_143224046_143224872_-_1.R fitVsDatCorrelation=0.853274147820898 cont.fitVsDatCorrelation=0.30944718872908 fstatistic=12312.5661050315,37,347 cont.fstatistic=3696.06917502815,37,347 residuals=-0.331935088351907,-0.0723595816409289,0.0042181785205358,0.0726521609032278,0.337582413506801 cont.residuals=-0.490073026528993,-0.137408359705724,-0.0221274361402132,0.110503834125959,0.760151623264057 predictedValues: Include Exclude Both chr4.16371_chr4_143224046_143224872_-_1.R.tl.Lung 72.6866439808265 81.5816863266418 57.7881071194596 chr4.16371_chr4_143224046_143224872_-_1.R.tl.cerebhem 63.7590456555453 68.0043604458384 64.2463713856235 chr4.16371_chr4_143224046_143224872_-_1.R.tl.cortex 66.8092407030785 68.3201844365332 59.933460603972 chr4.16371_chr4_143224046_143224872_-_1.R.tl.heart 70.6505685554452 75.9592799776717 61.6245193563224 chr4.16371_chr4_143224046_143224872_-_1.R.tl.kidney 66.9956316374874 85.3680622101832 54.7516145081386 chr4.16371_chr4_143224046_143224872_-_1.R.tl.liver 68.0610570460026 78.3147019208002 60.0118270177493 chr4.16371_chr4_143224046_143224872_-_1.R.tl.stomach 68.1518518693278 81.2385785463572 57.6104452983267 chr4.16371_chr4_143224046_143224872_-_1.R.tl.testicle 63.8313850114446 73.9098084339005 55.1651101215441 diffExp=-8.89504234581533,-4.24531479029304,-1.51094373345464,-5.30871142222647,-18.3724305726958,-10.2536448747976,-13.0867266770294,-10.0784234224558 diffExpScore=0.98625452941136 diffExp1.5=0,0,0,0,0,0,0,0 diffExp1.5Score=0 diffExp1.4=0,0,0,0,0,0,0,0 diffExp1.4Score=0 diffExp1.3=0,0,0,0,0,0,0,0 diffExp1.3Score=0 diffExp1.2=0,0,0,0,-1,0,0,0 diffExp1.2Score=0.5 cont.predictedValues: Include Exclude Both Lung 69.6189075849281 67.2474258157678 86.439397216598 cerebhem 72.012147589323 74.7024071793504 66.2676908613107 cortex 69.5706834407127 72.3987104824986 77.430023515712 heart 68.5165184985096 67.6862856477627 68.426455769794 kidney 68.056313646049 75.5456157011234 74.3477374790204 liver 64.8150853260585 74.2366639898536 73.3098220989231 stomach 67.0232227945019 68.4678559114241 63.5237047041231 testicle 66.2566713737066 70.2096556451997 70.1877583160522 cont.diffExp=2.37148176916035,-2.69025959002740,-2.82802704178594,0.830232850746896,-7.4893020550744,-9.4215786637951,-1.44463311692219,-3.95298427149316 cont.diffExpScore=1.21086495430769 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=0.528304067795872 cont.tran.correlation=0.0473325658578733 tran.covariance=0.00202847577396906 cont.tran.covariance=5.26284483123962e-05 tran.mean=72.1026304223178 cont.tran.mean=69.7727606641731 weightedLogRatios: wLogRatio Lung -0.501488712190025 cerebhem -0.269919215044937 cortex -0.094219397383102 heart -0.311103624514002 kidney -1.04833435446569 liver -0.602096367333483 stomach -0.756983191047243 testicle -0.620053652167126 cont.weightedLogRatios: wLogRatio Lung 0.146452250413315 cerebhem -0.15753620683224 cortex -0.169830940900434 heart 0.0514591316860721 kidney -0.446057684305085 liver -0.575370188938006 stomach -0.0899007262707312 testicle -0.244693189292746 varWeightedLogRatios=0.0913734950347837 cont.varWeightedLogRatios=0.0571287532512259 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.45744773778376 0.0669797726890199 66.5491619160791 1.20378221242182e-199 *** df.mm.trans1 -0.123950480280663 0.0558033424066309 -2.22120172260388 0.0269822598528035 * df.mm.trans2 -0.175164151158359 0.0558033424066309 -3.13895447125663 0.00184089288005791 ** df.mm.exp2 -0.419021814446878 0.0768852830973027 -5.44996126133244 9.5738261542815e-08 *** df.mm.exp3 -0.298167765662773 0.0768852830973026 -3.87808633396622 0.000125937416393653 *** df.mm.exp4 -0.164095732003645 0.0768852830973026 -2.13429313638570 0.0335192800848231 * df.mm.exp5 0.0178131501862557 0.0768852830973026 0.231684783727884 0.816919414811746 df.mm.exp6 -0.144380573038219 0.0768852830973026 -1.87787008412907 0.0612374192836169 . df.mm.exp7 -0.0655547851374463 0.0768852830973026 -0.85263112128342 0.394452010227356 df.mm.exp8 -0.182219610735802 0.0768852830973026 -2.37001937685776 0.0183334545624866 * df.mm.trans1:exp2 0.287975227550094 0.0649799241356918 4.43175690615983 1.25524129411283e-05 *** df.mm.trans2:exp2 0.236988837260797 0.0649799241356918 3.64710855565042 0.000305876699565080 *** df.mm.trans1:exp3 0.213851517011028 0.0649799241356918 3.29103980737899 0.00110069182822430 ** df.mm.trans2:exp3 0.120768210227587 0.0649799241356918 1.85854649468962 0.0639379977123387 . df.mm.trans1:exp4 0.135684235090201 0.0649799241356918 2.08809469840045 0.0375180104042414 * df.mm.trans2:exp4 0.0926883344260466 0.0649799241356918 1.42641493751968 0.154647677811215 df.mm.trans1:exp5 -0.0993433858668696 0.0649799241356918 -1.52883197677208 0.127217139283558 df.mm.trans2:exp5 0.0275540973474569 0.0649799241356918 0.424040158771471 0.671799275773066 df.mm.trans1:exp6 0.078628119575109 0.0649799241356918 1.21003710947580 0.227088301684930 df.mm.trans2:exp6 0.103511117894594 0.0649799241356918 1.59297074090824 0.112077221997059 df.mm.trans1:exp7 0.00113546283635630 0.0649799241356918 0.0174740560482221 0.986068472730874 df.mm.trans2:exp7 0.061340220219194 0.0649799241356918 0.943987255065158 0.345832957662454 df.mm.trans1:exp8 0.0523069547031486 0.0649799241356918 0.804971002950397 0.421387614902148 df.mm.trans2:exp8 0.0834603511360499 0.0649799241356918 1.28440210182097 0.199858117940371 df.mm.trans1:probe2 -0.178898571534678 0.0355909702340928 -5.02651572457866 8.01824706784707e-07 *** df.mm.trans1:probe3 -0.0173157972140115 0.0355909702340928 -0.486522202123747 0.626904101579379 df.mm.trans1:probe4 -0.104887027937643 0.0355909702340928 -2.94701232497368 0.00342564415644340 ** df.mm.trans1:probe5 -0.106754075402182 0.0355909702340928 -2.99947078430364 0.00289989131671749 ** df.mm.trans1:probe6 -0.06554056788729 0.0355909702340928 -1.84149427386243 0.0664024927445005 . df.mm.trans2:probe2 0.0554257225578625 0.0355909702340928 1.55729731989070 0.120311456746038 df.mm.trans2:probe3 0.224660242988628 0.0355909702340928 6.3122820623031 8.40086286856612e-10 *** df.mm.trans2:probe4 0.539349421101329 0.0355909702340928 15.1541084031669 3.62075240420703e-40 *** df.mm.trans2:probe5 0.207663332797344 0.0355909702340928 5.83471963342046 1.23607563054698e-08 *** df.mm.trans2:probe6 0.166113459399074 0.0355909702340928 4.66729224594031 4.36627371579887e-06 *** df.mm.trans3:probe2 -0.187552602480560 0.0355909702340928 -5.26966815591057 2.40595292756119e-07 *** df.mm.trans3:probe3 -0.109021432533311 0.0355909702340928 -3.06317675006451 0.00236122435875987 ** df.mm.trans3:probe4 -0.109626409052647 0.0355909702340928 -3.08017478398595 0.00223393963067219 ** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.02026700379615 0.122141418066189 32.9148544977393 9.27551061915929e-109 *** df.mm.trans1 0.243088067542376 0.101760562939270 2.38882392668612 0.0174362002886127 * df.mm.trans2 0.210918319744808 0.101760562939270 2.07269214765138 0.0389388130844167 * df.mm.exp2 0.404673303573531 0.140204678650162 2.88630384855608 0.00414200132635038 ** df.mm.exp3 0.183185772904461 0.140204678650162 1.30655962888047 0.192227610211429 df.mm.exp4 0.224227543199939 0.140204678650162 1.59928716615392 0.110666888557228 df.mm.exp5 0.244347544943883 0.140204678650162 1.74279166213545 0.0822558581713428 . df.mm.exp6 0.192130555072646 0.140204678650162 1.37035765797838 0.171461149751914 df.mm.exp7 0.288019035024524 0.140204678650162 2.05427549064314 0.0406976708345302 * df.mm.exp8 0.201876720406503 0.140204678650162 1.43987149608770 0.150805307010671 df.mm.trans1:exp2 -0.370874673420408 0.118494580694029 -3.12988721718897 0.00189703803930014 ** df.mm.trans2:exp2 -0.29953972724768 0.118494580694029 -2.52787701760925 0.0119186372821455 * df.mm.trans1:exp3 -0.183878700382581 0.118494580694029 -1.55178995786638 0.121624031587849 df.mm.trans2:exp3 -0.109376024603504 0.118494580694029 -0.923046640301045 0.356624272795238 df.mm.trans1:exp4 -0.240188872189407 0.118494580694029 -2.02700301383075 0.0434262698180525 * df.mm.trans2:exp4 -0.217722699085150 0.118494580694029 -1.83740638440963 0.0670048365270397 . df.mm.trans1:exp5 -0.267048231784656 0.118494580694029 -2.2536746425072 0.0248402926619446 * df.mm.trans2:exp5 -0.127989629578098 0.118494580694029 -1.08013065938084 0.280834158810426 df.mm.trans1:exp6 -0.263628371716356 0.118494580694029 -2.22481374398957 0.0267363438356558 * df.mm.trans2:exp6 -0.0932511430027112 0.118494580694029 -0.786965466745691 0.43183923094482 df.mm.trans1:exp7 -0.326016057965651 0.118494580694029 -2.75131618725648 0.00624715289330602 ** df.mm.trans2:exp7 -0.270033396576173 0.118494580694029 -2.27886705868381 0.0232819553212386 * df.mm.trans1:exp8 -0.251376751779874 0.118494580694029 -2.1214198177465 0.0345949495118028 * df.mm.trans2:exp8 -0.158769613946625 0.118494580694029 -1.33988924233246 0.181158119548700 df.mm.trans1:probe2 -0.0440280480742147 0.0649021547882357 -0.678375752205308 0.497985615547412 df.mm.trans1:probe3 -0.0757601406936688 0.0649021547882357 -1.16729777217507 0.243891635194975 df.mm.trans1:probe4 0.0116788828641364 0.0649021547882357 0.179945995664436 0.857300001792203 df.mm.trans1:probe5 -0.050074581203306 0.0649021547882357 -0.771539579335857 0.440912252240581 df.mm.trans1:probe6 -0.0450049147754795 0.0649021547882357 -0.693427127686633 0.488505428168165 df.mm.trans2:probe2 -0.0238200948638223 0.0649021547882357 -0.367015470311318 0.71383119154262 df.mm.trans2:probe3 -0.0077599358942711 0.0649021547882357 -0.119563609553341 0.904898039510034 df.mm.trans2:probe4 -0.103603334525425 0.0649021547882356 -1.59630038268321 0.111332014364723 df.mm.trans2:probe5 -0.0535884845044463 0.0649021547882357 -0.825681129991695 0.409552300560968 df.mm.trans2:probe6 -0.0392939864528234 0.0649021547882357 -0.605434235288994 0.545286270068056 df.mm.trans3:probe2 0.0042279720762056 0.0649021547882356 0.0651437859035764 0.948097031504798 df.mm.trans3:probe3 -0.0537666115899713 0.0649021547882357 -0.828425678090385 0.407998897793749 df.mm.trans3:probe4 -0.00978069208732135 0.0649021547882357 -0.150699034866162 0.88030069801585