chr9.24803_chr9_100216379_100221718_-_1.R fitVsDatCorrelation=0.933953910138586 cont.fitVsDatCorrelation=0.315803714972578 fstatistic=4398.61195075956,42,462 cont.fstatistic=614.636076478373,42,462 residuals=-0.96996940012925,-0.113880593180791,0.00541276795213259,0.102095732217204,0.830312397235833 cont.residuals=-1.02122056432286,-0.363068816093005,-0.136352404047122,0.123095511494569,2.31236598636997 predictedValues: Include Exclude Both chr9.24803_chr9_100216379_100221718_-_1.R.tl.Lung 60.5930055727036 115.825374637589 242.816757047461 chr9.24803_chr9_100216379_100221718_-_1.R.tl.cerebhem 47.3889080688782 43.6130745499786 59.6034110606777 chr9.24803_chr9_100216379_100221718_-_1.R.tl.cortex 50.9123853370047 42.32140770313 59.9882887180901 chr9.24803_chr9_100216379_100221718_-_1.R.tl.heart 54.3590750626041 44.259999619509 56.4990637799772 chr9.24803_chr9_100216379_100221718_-_1.R.tl.kidney 56.8155308044204 42.0796271212735 63.6112740820504 chr9.24803_chr9_100216379_100221718_-_1.R.tl.liver 56.1715995337814 44.4372453950758 59.0545509609728 chr9.24803_chr9_100216379_100221718_-_1.R.tl.stomach 59.3210583069916 189.567744208239 273.360414215938 chr9.24803_chr9_100216379_100221718_-_1.R.tl.testicle 54.3298710440726 41.1595718124626 58.3192557998207 diffExp=-55.2323690648851,3.77583351889952,8.59097763387476,10.0990754430952,14.7359036831469,11.7343541387055,-130.246685901247,13.1702992316101 diffExpScore=1.99067540670041 diffExp1.5=-1,0,0,0,0,0,-1,0 diffExp1.5Score=0.666666666666667 diffExp1.4=-1,0,0,0,0,0,-1,0 diffExp1.4Score=0.666666666666667 diffExp1.3=-1,0,0,0,1,0,-1,1 diffExp1.3Score=4 diffExp1.2=-1,0,1,1,1,1,-1,1 diffExp1.2Score=1.75 cont.predictedValues: Include Exclude Both Lung 59.3846235308098 67.0557950862 57.3114655886737 cerebhem 79.9958686604834 102.773758108177 78.25599754754 cortex 66.3322936496203 92.3556520564989 63.2620302317132 heart 55.9555511249157 91.8925448813945 81.3329983620151 kidney 75.4211744699904 79.6061722023117 62.6771201383908 liver 57.9621017952771 116.404289271544 76.6088320586916 stomach 61.5246145900402 84.520129202148 72.1764941635164 testicle 54.064836126408 89.177736132611 65.3243616397331 cont.diffExp=-7.6711715553902,-22.7778894476935,-26.0233584068786,-35.9369937564788,-4.18499773232122,-58.4421874762665,-22.9955146121079,-35.112900006203 cont.diffExpScore=0.995330267158586 cont.diffExp1.5=0,0,0,-1,0,-1,0,-1 cont.diffExp1.5Score=0.75 cont.diffExp1.4=0,0,0,-1,0,-1,0,-1 cont.diffExp1.4Score=0.75 cont.diffExp1.3=0,0,-1,-1,0,-1,-1,-1 cont.diffExp1.3Score=0.833333333333333 cont.diffExp1.2=0,-1,-1,-1,0,-1,-1,-1 cont.diffExp1.2Score=0.857142857142857 tran.correlation=0.633715732713351 cont.tran.correlation=0.0459307130698439 tran.covariance=0.0307025717746788 cont.tran.covariance=0.00107664652141709 tran.mean=62.6972174236071 cont.tran.mean=77.1516963055268 weightedLogRatios: wLogRatio Lung -2.86900503549646 cerebhem 0.316919564346887 cortex 0.709257437115224 heart 0.800097696600632 kidney 1.16786291873555 liver 0.91653487994767 stomach -5.4183836883339 testicle 1.07056743568650 cont.weightedLogRatios: wLogRatio Lung -0.503548124057599 cerebhem -1.12931491447708 cortex -1.44308297532962 heart -2.11947003661676 kidney -0.234920364036471 liver -3.07390965866565 stomach -1.35855692788800 testicle -2.12210108762915 varWeightedLogRatios=5.83106275325635 cont.varWeightedLogRatios=0.857415995241829 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.22372991353708 0.113253347397959 28.4647649504723 1.10522806184226e-103 *** df.mm.trans1 0.83507237710633 0.0909879497254162 9.17783486303861 1.47366657762112e-18 *** df.mm.trans2 1.46822989426465 0.0909879497254162 16.1365312516161 8.82407646812626e-47 *** df.mm.exp2 0.182076309754108 0.122168625982729 1.49036881023650 0.136809674703081 df.mm.exp3 0.217293855995663 0.122168625982729 1.77863878101062 0.0759564911350613 . df.mm.exp4 0.387512772395424 0.122168625982729 3.17194999352949 0.00161503449696561 ** df.mm.exp5 0.262626645150575 0.122168625982729 2.14970613803664 0.0320970201419364 * df.mm.exp6 0.380071591560975 0.122168625982729 3.11104089534989 0.00197971746661826 ** df.mm.exp7 0.352963624553145 0.122168625982729 2.88915113609482 0.00404445216404954 ** df.mm.exp8 0.282642307935444 0.122168625982729 2.31354249638038 0.0211309471167331 * df.mm.trans1:exp2 -0.427867582244241 0.0965827791796625 -4.4300607818328 1.17755057954356e-05 *** df.mm.trans2:exp2 -1.15880299516465 0.0965827791796626 -11.9980291000847 4.65039797583619e-29 *** df.mm.trans1:exp3 -0.391367102003253 0.0965827791796626 -4.05214164810101 5.95346167426528e-05 *** df.mm.trans2:exp3 -1.22408447150388 0.0965827791796626 -12.673941275047 8.43892563445975e-32 *** df.mm.trans1:exp4 -0.496080665115516 0.0965827791796625 -5.13632626156585 4.13886168013858e-07 *** df.mm.trans2:exp4 -1.34951511218076 0.0965827791796626 -13.9726266280908 2.94920424514792e-37 *** df.mm.trans1:exp5 -0.326996393964821 0.0965827791796626 -3.38565939748477 0.000770668698094333 *** df.mm.trans2:exp5 -1.27514660375837 0.0965827791796626 -13.2026290254741 5.40778370241298e-34 *** df.mm.trans1:exp6 -0.455839775587403 0.0965827791796626 -4.71967963087346 3.135843927088e-06 *** df.mm.trans2:exp6 -1.33807727933148 0.0965827791796626 -13.8542014497470 9.47450324851178e-37 *** df.mm.trans1:exp7 -0.374178733620299 0.0965827791796625 -3.87417650225465 0.000122444680391928 *** df.mm.trans2:exp7 0.139699159499301 0.0965827791796625 1.44641892359955 0.148737814151302 df.mm.trans1:exp8 -0.391747587763987 0.0965827791796625 -4.05608112638031 5.85739301560242e-05 *** df.mm.trans2:exp8 -1.31726946583662 0.0965827791796625 -13.6387612473467 7.83664297341933e-36 *** df.mm.trans1:probe2 0.201496841031711 0.064789697910473 3.11001359058875 0.00198647237185258 ** df.mm.trans1:probe3 0.0467766742619683 0.064789697910473 0.721977039105888 0.470673845443511 df.mm.trans1:probe4 0.120084511752976 0.064789697910473 1.85345071247145 0.064455082845119 . df.mm.trans1:probe5 0.323982252620552 0.064789697910473 5.00052111785169 8.13437558643609e-07 *** df.mm.trans1:probe6 -0.0116826369949213 0.0647896979104731 -0.180316275143997 0.856983345056902 df.mm.trans2:probe2 0.181410264618302 0.064789697910473 2.79998627048665 0.0053246210310106 ** df.mm.trans2:probe3 0.0521254659246778 0.064789697910473 0.804533245342573 0.421502881789245 df.mm.trans2:probe4 0.488034811938826 0.0647896979104731 7.53259897296012 2.63935585286851e-13 *** df.mm.trans2:probe5 0.153893363956823 0.064789697910473 2.37527521998134 0.0179430468139096 * df.mm.trans2:probe6 0.0263939637081965 0.0647896979104731 0.407379021039238 0.683918322116002 df.mm.trans3:probe2 -0.285598825654660 0.064789697910473 -4.4080900955782 1.29815983127131e-05 *** df.mm.trans3:probe3 0.0711033327711322 0.064789697910473 1.09744812932117 0.27301719724101 df.mm.trans3:probe4 0.13719073100922 0.064789697910473 2.11747755328002 0.0347529744709906 * df.mm.trans3:probe5 -0.322558052058972 0.064789697910473 -4.97853921937845 9.06166789420993e-07 *** df.mm.trans3:probe6 0.221804944813489 0.064789697910473 3.42346008650914 0.000673353148912654 *** df.mm.trans3:probe7 -0.123003843874024 0.064789697910473 -1.89850929763543 0.0582518778519954 . df.mm.trans3:probe8 -0.083021143993891 0.064789697910473 -1.28139421345366 0.200697997607292 df.mm.trans3:probe9 0.0715568466657971 0.0647896979104731 1.10444791338084 0.269973760035681 cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.21156431195764 0.300670169037325 14.0072569401949 2.09491219424451e-37 *** df.mm.trans1 -0.143701635486289 0.241558972452885 -0.594892559887492 0.552206533398526 df.mm.trans2 0.066328740354759 0.241558972452884 0.274586117341165 0.783756973974096 df.mm.exp2 0.413459904431012 0.324338858578823 1.27477757750859 0.203028723470700 df.mm.exp3 0.331978795009586 0.324338858578823 1.02355541505029 0.306580951980186 df.mm.exp4 -0.0944339322871521 0.324338858578823 -0.291158243267364 0.771060965623445 df.mm.exp5 0.32112355938831 0.324338858578823 0.99008660508765 0.322650039787304 df.mm.exp6 0.237086728736645 0.324338858578823 0.73098465529386 0.465159080994963 df.mm.exp7 0.0362529622712613 0.324338858578823 0.111774957925527 0.911050388598665 df.mm.exp8 0.060390705739311 0.324338858578822 0.186196331836182 0.852372526691447 df.mm.trans1:exp2 -0.115520242574649 0.256412381702080 -0.450525211800688 0.652543127465222 df.mm.trans2:exp2 0.0135451093642732 0.256412381702080 0.0528254886693067 0.957893786083814 df.mm.trans1:exp3 -0.22133726243993 0.256412381702081 -0.8632081686956 0.388470909693912 df.mm.trans2:exp3 -0.0118569229935130 0.256412381702081 -0.0462416163946768 0.963137653811355 df.mm.trans1:exp4 0.0349562481996317 0.256412381702080 0.136328238003134 0.891621185136702 df.mm.trans2:exp4 0.409528800966892 0.256412381702081 1.59714908558010 0.110916193472892 df.mm.trans1:exp5 -0.0820708250249636 0.256412381702081 -0.320073564623411 0.74905726587731 df.mm.trans2:exp5 -0.149556964631289 0.256412381702080 -0.583267327570225 0.559997959486796 df.mm.trans1:exp6 -0.261332678823253 0.256412381702081 -1.01918899972190 0.308646652948304 df.mm.trans2:exp6 0.314457619976381 0.256412381702081 1.22637455293302 0.220682431863463 df.mm.trans1:exp7 -0.000850960036000802 0.256412381702080 -0.00331871663276196 0.997353484589424 df.mm.trans2:exp7 0.195211723815843 0.256412381702080 0.76131941258069 0.446854730270052 df.mm.trans1:exp8 -0.154242040134150 0.256412381702080 -0.601538970584348 0.5477761134655 df.mm.trans2:exp8 0.224715672449495 0.256412381702080 0.87638385852438 0.381276833293287 df.mm.trans1:probe2 0.109858626131362 0.172006654727543 0.638688231599976 0.523342259556523 df.mm.trans1:probe3 0.140738914961129 0.172006654727543 0.818217848513237 0.413654609516315 df.mm.trans1:probe4 -0.0207042261446452 0.172006654727543 -0.120368750717468 0.904243372670205 df.mm.trans1:probe5 0.0524883344474496 0.172006654727543 0.305152928708432 0.760387109239885 df.mm.trans1:probe6 -0.0397918503643145 0.172006654727543 -0.231339016663888 0.817153857802805 df.mm.trans2:probe2 -0.112965807321556 0.172006654727543 -0.656752539606643 0.511667044701575 df.mm.trans2:probe3 -0.157002917965373 0.172006654727543 -0.912772347174968 0.361838345546652 df.mm.trans2:probe4 -0.178586609352211 0.172006654727543 -1.03825407008288 0.299694863462279 df.mm.trans2:probe5 -0.402292787446959 0.172006654727543 -2.33882106529069 0.0197701390095042 * df.mm.trans2:probe6 -0.234672132840725 0.172006654727543 -1.36432007943207 0.173131052620594 df.mm.trans3:probe2 -0.00733596019653159 0.172006654727543 -0.0426492812627029 0.965999536226228 df.mm.trans3:probe3 0.0419939247030374 0.172006654727543 0.244141279124087 0.807229785489349 df.mm.trans3:probe4 -0.212078099743335 0.172006654727543 -1.23296450407262 0.218216002332415 df.mm.trans3:probe5 -0.208504271886761 0.172006654727543 -1.21218723901718 0.22606025632437 df.mm.trans3:probe6 -0.309581739982042 0.172006654727543 -1.79982420140906 0.0725406812207268 . df.mm.trans3:probe7 -0.00483885663805605 0.172006654727543 -0.0281317990034791 0.977569179737146 df.mm.trans3:probe8 -0.0538585464250413 0.172006654727543 -0.313118969207051 0.754331580442534 df.mm.trans3:probe9 -0.0170128901293997 0.172006654727543 -0.098908325124676 0.921253958699893