chr12.5648_chr12_26279544_26296347_-_2.R fitVsDatCorrelation=0.886099647111438 cont.fitVsDatCorrelation=0.251410107428896 fstatistic=6529.67947181724,46,554 cont.fstatistic=1488.1187739539,46,554 residuals=-0.58864928923013,-0.0926729682294897,-0.000846435255647731,0.0740368903807996,1.21170159607089 cont.residuals=-0.583954184023688,-0.251581279689300,-0.133824575952297,0.151267183416716,1.77044296382692 predictedValues: Include Exclude Both chr12.5648_chr12_26279544_26296347_-_2.R.tl.Lung 85.0307767287703 48.3510881039713 55.0976833984231 chr12.5648_chr12_26279544_26296347_-_2.R.tl.cerebhem 108.969190149065 64.1101729943795 51.1228042142544 chr12.5648_chr12_26279544_26296347_-_2.R.tl.cortex 75.3269344748314 45.7198761842857 49.2682521243234 chr12.5648_chr12_26279544_26296347_-_2.R.tl.heart 74.682518001505 48.0053528958706 55.592031788101 chr12.5648_chr12_26279544_26296347_-_2.R.tl.kidney 85.9795136513988 44.4723231435762 50.9145894783485 chr12.5648_chr12_26279544_26296347_-_2.R.tl.liver 83.6040654217268 50.6792014625788 50.7478098486851 chr12.5648_chr12_26279544_26296347_-_2.R.tl.stomach 79.6841612864772 49.6218805148764 52.1726811420821 chr12.5648_chr12_26279544_26296347_-_2.R.tl.testicle 79.6113172135602 53.331000415563 51.5254636984104 diffExp=36.679688624799,44.8590171546853,29.6070582905457,26.6771651056343,41.5071905078226,32.9248639591481,30.0622807716009,26.2803167979972 diffExpScore=0.996290767908586 diffExp1.5=1,1,1,1,1,1,1,0 diffExp1.5Score=0.875 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 65.5681648153585 58.7335192654448 71.163371920132 cerebhem 63.3290210641216 55.863823989126 64.7617224825357 cortex 56.2537479432196 54.7953998449731 59.6160732474766 heart 66.4644555742915 54.1392904633725 65.5736457835157 kidney 69.1674375640593 57.1689972128157 63.9761620319864 liver 62.7835346681314 58.2902272420198 60.9638206236188 stomach 70.4452258510498 55.4437722834526 59.9473129115643 testicle 67.5841620673985 58.7327908061721 57.3931103568639 cont.diffExp=6.83464554991375,7.46519707499562,1.45834809824646,12.3251651109191,11.9984403512436,4.49330742611159,15.0014535675971,8.85137126122631 cont.diffExpScore=0.985596574426665 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=0,0,0,1,1,0,1,0 cont.diffExp1.2Score=0.75 tran.correlation=0.815988733531526 cont.tran.correlation=0.216169439195132 tran.covariance=0.0104527320147563 cont.tran.covariance=0.00053358628535043 tran.mean=67.3237107901522 cont.tran.mean=60.9227231659379 weightedLogRatios: wLogRatio Lung 2.34884605888473 cerebhem 2.34773737956149 cortex 2.03326107152347 heart 1.80851535385668 kidney 2.7190357945301 liver 2.09030949438495 stomach 1.96145798977277 testicle 1.67340161609846 cont.weightedLogRatios: wLogRatio Lung 0.454414533915056 cerebhem 0.512447042308466 cortex 0.105505377554033 heart 0.83973189301486 kidney 0.788988533658898 liver 0.304649819874518 stomach 0.990216746577545 testicle 0.581601709066444 varWeightedLogRatios=0.113289801133405 cont.varWeightedLogRatios=0.0857468251274044 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.47142366130917 0.0906750314205213 49.3126232355207 8.65750252826809e-205 *** df.mm.trans1 0.148178647139143 0.0771877126734735 1.91971807437775 0.0554067629057636 . df.mm.trans2 -0.627094126919112 0.0715809399873732 -8.76062995302564 2.36547991036324e-17 *** df.mm.exp2 0.605043250589234 0.0948049712008621 6.38197810647858 3.69682654633926e-10 *** df.mm.exp3 -0.0653033280918154 0.094804971200862 -0.688817551069744 0.491226448404508 df.mm.exp4 -0.145875643959869 0.0948049712008621 -1.53869192840958 0.124450461049307 df.mm.exp5 0.00643226085167258 0.0948049712008621 0.0678472950331332 0.945931673799022 df.mm.exp6 0.112344961113258 0.0948049712008621 1.18501128886200 0.236521063922741 df.mm.exp7 0.0155493798290886 0.0948049712008621 0.164014393255226 0.869779632083206 df.mm.exp8 0.0992035911648286 0.0948049712008621 1.04639651178889 0.295834326512678 df.mm.trans1:exp2 -0.356991337616098 0.0841512971279245 -4.24225591048715 2.59352544062853e-05 *** df.mm.trans2:exp2 -0.322928920576183 0.0719367712107526 -4.48906609430802 8.70666443972239e-06 *** df.mm.trans1:exp3 -0.0558721756287287 0.0841512971279245 -0.663949071917375 0.506999123591682 df.mm.trans2:exp3 0.00934773250274424 0.0719367712107526 0.129943731771868 0.896658110918842 df.mm.trans1:exp4 0.0161084091610102 0.0841512971279245 0.191421994797331 0.848265124105077 df.mm.trans2:exp4 0.138699440932208 0.0719367712107526 1.92807431578853 0.0543566358583219 . df.mm.trans1:exp5 0.00466352355121961 0.0841512971279245 0.0554183204583317 0.955825180402737 df.mm.trans2:exp5 -0.090053943383278 0.0719367712107526 -1.25184855905539 0.211153329975344 df.mm.trans1:exp6 -0.129266082875961 0.0841512971279245 -1.53611515553294 0.125081035498254 df.mm.trans2:exp6 -0.0653180886267945 0.0719367712107527 -0.907993054559434 0.364276689301787 df.mm.trans1:exp7 -0.080491813053013 0.0841512971279245 -0.956513040204853 0.339230304258854 df.mm.trans2:exp7 0.0103937696594590 0.0719367712107527 0.144484795251770 0.885170207246774 df.mm.trans1:exp8 -0.165060602488275 0.0841512971279245 -1.96147425080513 0.050324120707728 . df.mm.trans2:exp8 -0.00117453414580314 0.0719367712107527 -0.0163273125278603 0.986979146401818 df.mm.trans1:probe2 0.0690046112501529 0.0534772160281937 1.29035533962301 0.197465603861992 df.mm.trans1:probe3 0.195908664020845 0.0534772160281937 3.66340431628976 0.000272781173041016 *** df.mm.trans1:probe4 -0.0693637432337817 0.0534772160281937 -1.29707094694706 0.195146688960157 df.mm.trans1:probe5 0.249251346722063 0.0534772160281937 4.6608886033008 3.94865676979395e-06 *** df.mm.trans1:probe6 0.109073937527790 0.0534772160281937 2.03963380349278 0.0418606968943769 * df.mm.trans1:probe7 -0.564502233505943 0.0534772160281937 -10.5559390602595 7.37016969120383e-24 *** df.mm.trans1:probe8 -0.725350369263214 0.0534772160281937 -13.563727193293 2.15787944942303e-36 *** df.mm.trans1:probe9 -0.695686975193577 0.0534772160281937 -13.0090350033705 5.95204173153189e-34 *** df.mm.trans1:probe10 -0.565990569862233 0.0534772160281936 -10.5837702838502 5.75742731221872e-24 *** df.mm.trans1:probe11 -0.644140499073392 0.0534772160281937 -12.045138975331 7.6885492129773e-30 *** df.mm.trans1:probe12 -0.713395897674515 0.0534772160281937 -13.3401839261492 2.10765017308485e-35 *** df.mm.trans2:probe2 0.0553952692720465 0.0534772160281937 1.03586673702015 0.300716250384929 df.mm.trans2:probe3 0.215356612933044 0.0534772160281937 4.02707225483664 6.43510917636211e-05 *** df.mm.trans2:probe4 0.123880792333785 0.0534772160281936 2.31651535989595 0.0208940684766126 * df.mm.trans2:probe5 0.0153173686023356 0.0534772160281937 0.286427935857024 0.77465746122978 df.mm.trans2:probe6 0.0341194527512034 0.0534772160281937 0.638018492458833 0.523725266802826 df.mm.trans3:probe2 -0.0343046387746834 0.0534772160281937 -0.641481388197127 0.521475270533324 df.mm.trans3:probe3 -0.0605456987334258 0.0534772160281937 -1.13217746229545 0.258049627302776 df.mm.trans3:probe4 -0.0505594785666723 0.0534772160281937 -0.945439615630269 0.34484664371107 df.mm.trans3:probe5 0.0745290761249414 0.0534772160281937 1.39366035968755 0.163978995923975 df.mm.trans3:probe6 0.109181945630102 0.0534772160281937 2.04165350665488 0.0416590753331743 * df.mm.trans3:probe7 0.0778952254399271 0.0534772160281937 1.45660584498004 0.145791726023540 cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.99254431444376 0.189349721946697 21.0855567855954 6.68943491886348e-73 *** df.mm.trans1 0.230465000415853 0.161185187404479 1.42981501046696 0.153333805823879 df.mm.trans2 0.0447672987657885 0.149476993511411 0.299492903316729 0.764676311880577 df.mm.exp2 0.00942335164090455 0.197973958815581 0.0475989453223122 0.962053026380958 df.mm.exp3 -0.045568937623966 0.197973958815581 -0.230176422679989 0.818039647943383 df.mm.exp4 0.0139309769941059 0.197973958815581 0.0703677245100858 0.943926372726167 df.mm.exp5 0.132908765884062 0.197973958815581 0.671344689368312 0.502280793191852 df.mm.exp6 0.103724089607892 0.197973958815581 0.523927946020994 0.600538188753675 df.mm.exp7 0.185616176936985 0.197973958815581 0.937578750495624 0.348869486504852 df.mm.exp8 0.245324957312656 0.197973958815581 1.23917791400627 0.215804334455675 df.mm.trans1:exp2 -0.0441699446366402 0.175726707374707 -0.251355899717937 0.801632166269529 df.mm.trans2:exp2 -0.05951692733409 0.150220048596713 -0.396198296366364 0.692111296625421 df.mm.trans1:exp3 -0.107648679118259 0.175726707374707 -0.61259145366399 0.540397875462495 df.mm.trans2:exp3 -0.0238354069093192 0.150220048596713 -0.158669945403285 0.873986740710801 df.mm.trans1:exp4 -0.000353960580738114 0.175726707374707 -0.00201426741572841 0.99839357329929 df.mm.trans2:exp4 -0.0953813890124785 0.150220048596713 -0.634944469153673 0.52572677015305 df.mm.trans1:exp5 -0.0794688551478063 0.175726707374708 -0.452229808064135 0.651280453378803 df.mm.trans2:exp5 -0.159907611734959 0.150220048596713 -1.06448914927630 0.287570901525174 df.mm.trans1:exp6 -0.147121523032655 0.175726707374707 -0.837217775434346 0.402831177521158 df.mm.trans2:exp6 -0.111300229613469 0.150220048596713 -0.740914615946305 0.459059131999389 df.mm.trans1:exp7 -0.113870993083460 0.175726707374707 -0.648000493406216 0.517253093214705 df.mm.trans2:exp7 -0.243257372268239 0.150220048596713 -1.61934025811227 0.105943160908604 df.mm.trans1:exp8 -0.215041576366239 0.175726707374707 -1.22372734104497 0.221575303125336 df.mm.trans2:exp8 -0.245337360175608 0.150220048596713 -1.63318653180743 0.102997935154177 df.mm.trans1:probe2 -0.0249237397765884 0.111672373604827 -0.223186263281065 0.823472810633586 df.mm.trans1:probe3 -0.194822211948915 0.111672373604827 -1.74458736444815 0.0816112643891894 . df.mm.trans1:probe4 -0.0348933520573318 0.111672373604827 -0.312461810660605 0.754807157548202 df.mm.trans1:probe5 -0.154031997700678 0.111672373604827 -1.37932053137644 0.168352480555819 df.mm.trans1:probe6 0.0224899258973083 0.111672373604827 0.201392028944356 0.840465969023874 df.mm.trans1:probe7 -0.0931805606231415 0.111672373604827 -0.834410137576888 0.404409556341442 df.mm.trans1:probe8 -0.126744277755606 0.111672373604827 -1.13496537831383 0.256880631205433 df.mm.trans1:probe9 -0.148715741245696 0.111672373604827 -1.33171469760241 0.183501602685026 df.mm.trans1:probe10 -0.0906772376818272 0.111672373604827 -0.811993465838784 0.417144133082445 df.mm.trans1:probe11 0.0762573462004874 0.111672373604827 0.682866708558893 0.494976520773155 df.mm.trans1:probe12 0.010780292825486 0.111672373604827 0.0965350021450605 0.923130586942068 df.mm.trans2:probe2 0.175787248755254 0.111672373604827 1.57413371884893 0.116027412592967 df.mm.trans2:probe3 -0.0343866190479993 0.111672373604827 -0.307924135020919 0.758255794336232 df.mm.trans2:probe4 0.111349195771107 0.111672373604827 0.997106018048261 0.319148360443358 df.mm.trans2:probe5 0.0875147028632706 0.111672373604827 0.78367370584382 0.433566503244309 df.mm.trans2:probe6 0.123822176810230 0.111672373604827 1.10879864744702 0.267998161419203 df.mm.trans3:probe2 -0.0334421627628801 0.111672373604827 -0.299466749773057 0.764696253733514 df.mm.trans3:probe3 0.0470084994678252 0.111672373604827 0.420950123565684 0.673954755069142 df.mm.trans3:probe4 0.0422256750098465 0.111672373604827 0.378121048624521 0.705485510103002 df.mm.trans3:probe5 -0.0946160446358704 0.111672373604827 -0.847264561338029 0.397213541593455 df.mm.trans3:probe6 -0.00865211979787307 0.111672373604827 -0.077477710185423 0.938271495989236 df.mm.trans3:probe7 0.027887584413554 0.111672373604827 0.249726799147650 0.802891200559047