chr4.17228_chr4_102912021_102926147_+_1.R fitVsDatCorrelation=0.924358318850055 cont.fitVsDatCorrelation=0.299525886364594 fstatistic=5513.72487711205,37,347 cont.fstatistic=873.80980815591,37,347 residuals=-0.539751249888367,-0.113582818146481,0.00228718979547615,0.115899075255724,0.701951604359984 cont.residuals=-0.960746377686417,-0.395634326770419,-0.0258430964691833,0.372234531127771,1.17094456397554 predictedValues: Include Exclude Both chr4.17228_chr4_102912021_102926147_+_1.R.tl.Lung 70.9677926097692 198.376632045383 149.258026622237 chr4.17228_chr4_102912021_102926147_+_1.R.tl.cerebhem 62.4193627603659 155.602574141341 128.400062433722 chr4.17228_chr4_102912021_102926147_+_1.R.tl.cortex 61.3093507479254 132.664798314074 148.653846414019 chr4.17228_chr4_102912021_102926147_+_1.R.tl.heart 58.6229322276705 128.798255410730 123.620514256021 chr4.17228_chr4_102912021_102926147_+_1.R.tl.kidney 68.6932095971422 200.016913337191 77.6140605108305 chr4.17228_chr4_102912021_102926147_+_1.R.tl.liver 65.1148842181317 170.898456572434 93.6117578837496 chr4.17228_chr4_102912021_102926147_+_1.R.tl.stomach 53.6826913657057 135.11046966573 97.6843881640482 chr4.17228_chr4_102912021_102926147_+_1.R.tl.testicle 57.1653463700112 143.069530569467 95.3032584731656 diffExp=-127.408839435614,-93.1832113809751,-71.3554475661484,-70.17532318306,-131.323703740049,-105.783572354303,-81.4277783000243,-85.904184199456 diffExpScore=0.998697173750625 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 106.904569856628 76.5786574683301 109.925542923819 cerebhem 108.000338489719 116.013654641057 113.699193960225 cortex 119.719840623917 85.934475601664 106.621259580683 heart 109.094698496255 106.384536499446 77.0017911408551 kidney 104.718992076936 94.0249481480723 110.160775787343 liver 107.200622451494 105.823741207915 107.272326497543 stomach 92.5440800973511 90.3688699023429 96.6918114618343 testicle 101.806172882694 87.602009833705 108.208244365028 cont.diffExp=30.3259123882974,-8.01331615133772,33.7853650222534,2.71016199680902,10.6940439288639,1.37688124357955,2.17521019500819,14.2041630489894 cont.diffExpScore=1.17025720625779 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=1,0,1,0,0,0,0,0 cont.diffExp1.3Score=0.666666666666667 cont.diffExp1.2=1,0,1,0,0,0,0,0 cont.diffExp1.2Score=0.666666666666667 tran.correlation=0.900389656586606 cont.tran.correlation=0.0623203890703054 tran.covariance=0.0146683422944550 cont.tran.covariance=0.000622190298955582 tran.mean=110.157074997067 cont.tran.mean=100.795013017345 weightedLogRatios: wLogRatio Lung -4.90964971892541 cerebhem -4.19318122346320 cortex -3.47497006586337 heart -3.51424999094526 kidney -5.09156044994654 liver -4.49517049977669 stomach -4.10236749724914 testicle -4.13247888421377 cont.weightedLogRatios: wLogRatio Lung 1.50299230433556 cerebhem -0.337678294551468 cortex 1.53164098917347 heart 0.11772128858153 kidney 0.495235697676315 liver 0.0603470832564134 stomach 0.107409135195124 testicle 0.683403984572392 varWeightedLogRatios=0.340481746416063 cont.varWeightedLogRatios=0.470851084957231 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.99840019782233 0.109205088892586 45.7707625945781 4.35492349109618e-149 *** df.mm.trans1 -0.707306902930485 0.090982825461552 -7.77407053850381 8.72561130312729e-14 *** df.mm.trans2 0.300708181652462 0.090982825461552 3.30510928987952 0.00104850920547935 ** df.mm.exp2 -0.220687218930676 0.125355220510460 -1.76049484043836 0.0792048462088673 . df.mm.exp3 -0.544579443486862 0.125355220510460 -4.34429010031874 1.83707164532056e-05 *** df.mm.exp4 -0.43456030484362 0.125355220510459 -3.46663109102314 0.000593213927522522 *** df.mm.exp5 0.629586655442872 0.125355220510460 5.02242070875971 8.17928823031713e-07 *** df.mm.exp6 0.231349699949061 0.125355220510459 1.84555297343805 0.0658088887541977 . df.mm.exp7 -0.239275410659535 0.125355220510459 -1.90877898571101 0.0571153666766921 . df.mm.exp8 -0.0945024041206135 0.125355220510459 -0.753876892687755 0.45143438796039 df.mm.trans1:exp2 0.0923365979119054 0.105944497966846 0.871556330757268 0.384053067686457 df.mm.trans2:exp2 -0.0221750320216623 0.105944497966846 -0.209308009827954 0.834330623140787 df.mm.trans1:exp3 0.398285666637309 0.105944497966846 3.75938037633579 0.000199813703053460 *** df.mm.trans2:exp3 0.142237671059673 0.105944497966846 1.3425677953015 0.180289581427863 df.mm.trans1:exp4 0.243460110910468 0.105944497966846 2.29799673963866 0.0221562553611395 * df.mm.trans2:exp4 0.00264016758979067 0.105944497966846 0.0249202897786808 0.98013286791803 df.mm.trans1:exp5 -0.662162451388208 0.105944497966846 -6.25008815082989 1.20317392308269e-09 *** df.mm.trans2:exp5 -0.621352131669044 0.105944497966846 -5.86488343985062 1.04801586313711e-08 *** df.mm.trans1:exp6 -0.317422689552348 0.105944497966846 -2.99612245698385 0.0029311011072028 ** df.mm.trans2:exp6 -0.380447546926486 0.105944497966846 -3.59100806769165 0.000376908337580546 *** df.mm.trans1:exp7 -0.0398601096265381 0.105944497966846 -0.376235768647577 0.706971554694787 df.mm.trans2:exp7 -0.144799257586274 0.105944497966846 -1.36674636592820 0.172589677286939 df.mm.trans1:exp8 -0.121775862684280 0.105944497966846 -1.14943073988031 0.251170029599855 df.mm.trans2:exp8 -0.232334261915985 0.105944497966846 -2.19298091335230 0.0289720222518937 * df.mm.trans1:probe2 -0.0291381854873871 0.0580281913800019 -0.502138439858887 0.615888621650607 df.mm.trans1:probe3 -0.0501303421350723 0.0580281913800019 -0.863896339742696 0.388241590017784 df.mm.trans1:probe4 -0.212831049622324 0.0580281913800019 -3.66771813080618 0.000283101976550352 *** df.mm.trans1:probe5 -0.0138744731229937 0.0580281913800019 -0.239098837875813 0.811170097309586 df.mm.trans1:probe6 0.0173025905268389 0.0580281913800019 0.298175595608893 0.765747606515408 df.mm.trans2:probe2 -0.0369866177336209 0.0580281913800019 -0.637390496826126 0.524290838571019 df.mm.trans2:probe3 -0.102423178872457 0.0580281913800019 -1.76505895559851 0.0784334234284894 . df.mm.trans2:probe4 0.0190097748630566 0.0580281913800019 0.327595508510159 0.743415072701739 df.mm.trans2:probe5 0.124236674912232 0.0580281913800019 2.14097099974492 0.0329726983442126 * df.mm.trans2:probe6 -0.093246389071118 0.0580281913800019 -1.60691530881063 0.108982478953224 df.mm.trans3:probe2 0.391557325281537 0.0580281913800019 6.74770858732085 6.31172911692032e-11 *** df.mm.trans3:probe3 0.630436185942876 0.0580281913800019 10.8643087256402 7.31667505247646e-24 *** df.mm.trans3:probe4 0.633506704758813 0.0580281913800019 10.9172229858113 4.74521701174433e-24 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.48519357274046 0.273091279543148 16.4237890724438 2.97712546959318e-45 *** df.mm.trans1 0.180597581578524 0.227522512675076 0.793756975761052 0.427879378730327 df.mm.trans2 -0.126838338450465 0.227522512675076 -0.55747599197624 0.577561689572903 df.mm.exp2 0.391834219622046 0.313478226278328 1.2499567331166 0.212157691971861 df.mm.exp3 0.259004794212151 0.313478226278328 0.826228977007761 0.409241939535881 df.mm.exp4 0.704996121419432 0.313478226278328 2.24894765352375 0.0251425908022871 * df.mm.exp5 0.182448026032108 0.313478226278328 0.582011797751202 0.560936664651468 df.mm.exp6 0.350654511045268 0.313478226278328 1.11859287711400 0.264087627572841 df.mm.exp7 0.149604475437022 0.313478226278328 0.477240404263971 0.633491379797905 df.mm.exp8 0.101365394787272 0.313478226278328 0.323357050952791 0.746619633341271 df.mm.trans1:exp2 -0.381636424348645 0.264937456703878 -1.44047742096053 0.150634026897057 df.mm.trans2:exp2 0.0235552621845977 0.264937456703878 0.0889087654031705 0.929205708256339 df.mm.trans1:exp3 -0.145787008478760 0.264937456703878 -0.55026952508911 0.582488559555041 df.mm.trans2:exp3 -0.143738114764428 0.264937456703878 -0.542536025493311 0.587797562802816 df.mm.trans1:exp4 -0.6847163888393 0.264937456703878 -2.58444539084034 0.0101614296923547 * df.mm.trans2:exp4 -0.376254303520731 0.264937456703878 -1.42016273652567 0.156458140569375 df.mm.trans1:exp5 -0.203104095420520 0.264937456703878 -0.766611478600893 0.443833769460118 df.mm.trans2:exp5 0.0227937120594951 0.264937456703878 0.0860343129396452 0.931488760921401 df.mm.trans1:exp6 -0.347889021984891 0.264937456703878 -1.31309866982579 0.190017369481603 df.mm.trans2:exp6 -0.0271980345391498 0.264937456703878 -0.102658321241263 0.918293453151323 df.mm.trans1:exp7 -0.293855968845515 0.264937456703878 -1.10915222219393 0.268132622378025 df.mm.trans2:exp7 0.0159769583733474 0.264937456703878 0.060304641601527 0.951947721297635 df.mm.trans1:exp8 -0.150231221164629 0.264937456703878 -0.567044098005907 0.571050844086338 df.mm.trans2:exp8 0.033120131403955 0.264937456703878 0.125011132121547 0.900587127823925 df.mm.trans1:probe2 -0.061637701337243 0.145112221364762 -0.424758857369477 0.671275723607775 df.mm.trans1:probe3 -0.138672290139458 0.145112221364762 -0.955621027886297 0.339928998660772 df.mm.trans1:probe4 0.131690305042099 0.145112221364762 0.907506644192808 0.364768726646885 df.mm.trans1:probe5 0.117643481265982 0.145112221364762 0.810706914686854 0.418089669970358 df.mm.trans1:probe6 0.0124303220785235 0.145112221364762 0.0856600633745242 0.931786053150969 df.mm.trans2:probe2 -0.0216161482494607 0.145112221364762 -0.148961597074068 0.881670468250138 df.mm.trans2:probe3 0.00639794974207543 0.145112221364762 0.044089668546891 0.964858288213311 df.mm.trans2:probe4 -0.0054473545787828 0.145112221364762 -0.0375389097317312 0.970076902938382 df.mm.trans2:probe5 -0.183789391463384 0.145112221364762 -1.26653282359589 0.206171888541373 df.mm.trans2:probe6 0.00408674960022588 0.145112221364762 0.0281626837615090 0.977548589185122 df.mm.trans3:probe2 0.145535073487232 0.145112221364762 1.00291396629789 0.316601219313711 df.mm.trans3:probe3 0.269589532561179 0.145112221364762 1.85780032877812 0.0640442285103758 . df.mm.trans3:probe4 0.228277146850659 0.145112221364762 1.57310765904995 0.116605193628967