chr1.770_chr1_24414946_24418145_-_0.R fitVsDatCorrelation=0.880982093145964 cont.fitVsDatCorrelation=0.295783434152288 fstatistic=9104.12172726801,38,370 cont.fstatistic=2226.20546528176,38,370 residuals=-0.551481502203377,-0.0797238306039565,-0.00614611632839727,0.0716238137765373,0.562462131895488 cont.residuals=-0.613246726816548,-0.203037008244360,-0.0545397909439095,0.181556916529459,0.853564439860549 predictedValues: Include Exclude Both chr1.770_chr1_24414946_24418145_-_0.R.tl.Lung 58.1113783973473 54.467205345565 84.3631397110862 chr1.770_chr1_24414946_24418145_-_0.R.tl.cerebhem 59.3723076671939 66.7775732860742 72.7359043173272 chr1.770_chr1_24414946_24418145_-_0.R.tl.cortex 62.665700182408 53.0288785182885 83.7438996948246 chr1.770_chr1_24414946_24418145_-_0.R.tl.heart 64.584754026575 56.110070615512 85.5290434119113 chr1.770_chr1_24414946_24418145_-_0.R.tl.kidney 57.7790889851486 57.4596888176059 83.9856656785212 chr1.770_chr1_24414946_24418145_-_0.R.tl.liver 61.5965057368132 62.0756540484315 88.6325161901335 chr1.770_chr1_24414946_24418145_-_0.R.tl.stomach 67.4633706957273 56.6903487651014 95.3475690821784 chr1.770_chr1_24414946_24418145_-_0.R.tl.testicle 57.0064560390569 61.657173353941 77.3847304718077 diffExp=3.64417305178232,-7.40526561888027,9.63682166411952,8.47468341106295,0.319400167542646,-0.479148311618317,10.7730219306259,-4.65071731488404 diffExpScore=2.12937162877843 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=0,0,0,0,0,0,0,0 diffExp1.2Score=0 cont.predictedValues: Include Exclude Both Lung 60.9704201627315 61.2861693786649 66.7255857808279 cerebhem 59.96568634143 60.7579826592147 59.1942897029303 cortex 59.4764624576648 67.0181765511872 60.2161623010405 heart 60.4267124841498 63.2040017959742 66.2924450175866 kidney 58.2205340775078 60.9270218856137 56.8031672900816 liver 57.0098192452215 67.1633540274677 54.7735161367571 stomach 62.4919463689332 64.7697883154379 53.8704553295645 testicle 65.8718054212226 63.0594984112878 61.1089760980562 cont.diffExp=-0.315749215933351,-0.792296317784732,-7.54171409352249,-2.77728931182443,-2.70648780810588,-10.1535347822462,-2.27784194650469,2.81230700993481 cont.diffExpScore=1.18683341595659 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=-0.323848693373911 cont.tran.correlation=-0.201823027640404 tran.covariance=-0.00147435429007638 cont.tran.covariance=-0.000356082621495977 tran.mean=59.8028846550494 cont.tran.mean=62.0387112239818 weightedLogRatios: wLogRatio Lung 0.260992404629386 cerebhem -0.486918346510241 cortex 0.676981567479891 heart 0.576387580054245 kidney 0.0224716956706876 liver -0.0319594528495747 stomach 0.717600287962177 testicle -0.320160639468967 cont.weightedLogRatios: wLogRatio Lung -0.0212449966559814 cerebhem -0.0538208850060101 cortex -0.494875987749363 heart -0.185312996398359 kidney -0.185705926000659 liver -0.676133825982804 stomach -0.148681736703875 testicle 0.181765526891309 varWeightedLogRatios=0.209184954086737 cont.varWeightedLogRatios=0.0736776438385033 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.89698506565247 0.0750561798939607 51.9209087267447 5.65627276918906e-172 *** df.mm.trans1 0.258365450297559 0.0618117522717089 4.17987584564582 3.64382739578927e-05 *** df.mm.trans2 0.244798821702463 0.0618117522717089 3.96039284934665 8.9761745174403e-05 *** df.mm.exp2 0.373530382367125 0.0844949502243613 4.42074208429357 1.29442444065453e-05 *** df.mm.exp3 0.0560578685587901 0.0844949502243614 0.663446376498695 0.507457855844033 df.mm.exp4 0.121607981006639 0.0844949502243613 1.43923371377498 0.150929752656940 df.mm.exp5 0.0522347311203727 0.0844949502243614 0.618199442471682 0.536824221818101 df.mm.exp6 0.139630524329207 0.0844949502243614 1.65253099692280 0.0992746238193674 . df.mm.exp7 0.0668302405101724 0.0844949502243614 0.790937687195703 0.429487043339094 df.mm.exp8 0.191134926664892 0.0844949502243614 2.26208697865810 0.0242715712867867 * df.mm.trans1:exp2 -0.352063951883006 0.0700595116434906 -5.02521276018225 7.8451588869824e-07 *** df.mm.trans2:exp2 -0.169761871218932 0.0700595116434906 -2.42310954268128 0.0158674473290260 * df.mm.trans1:exp3 0.0193948965729019 0.0700595116434906 0.276834595587763 0.782061701621956 df.mm.trans2:exp3 -0.0828200094694068 0.0700595116434906 -1.18213797850676 0.237910107602449 df.mm.trans1:exp4 -0.0159910901424713 0.0700595116434906 -0.228250094346141 0.819577909149262 df.mm.trans2:exp4 -0.0918914564996944 0.0700595116434906 -1.31161999768567 0.190461653409145 df.mm.trans1:exp5 -0.057969289454966 0.0700595116434906 -0.827429254002687 0.408527133384781 df.mm.trans2:exp5 0.00125012300664621 0.0700595116434906 0.0178437299564357 0.985773136867853 df.mm.trans1:exp6 -0.08138686674046 0.0700595116434906 -1.16168190201797 0.246113533939220 df.mm.trans2:exp6 -0.0088754403422446 0.0700595116434907 -0.126684302160265 0.899259085596448 df.mm.trans1:exp7 0.0823930674273979 0.0700595116434906 1.17604398738416 0.240333422811463 df.mm.trans2:exp7 -0.0268250438221999 0.0700595116434906 -0.382889392074321 0.702021646430492 df.mm.trans1:exp8 -0.210331887691171 0.0700595116434906 -3.00218889280131 0.00286249050355233 ** df.mm.trans2:exp8 -0.067144131491626 0.0700595116434906 -0.958387090011418 0.338493418235888 df.mm.trans1:probe2 -0.277887201675043 0.040905941882197 -6.79332118730616 4.38957904550746e-11 *** df.mm.trans1:probe3 -0.266300037004077 0.040905941882197 -6.5100575796783 2.44935538159925e-10 *** df.mm.trans1:probe4 -0.261283966479425 0.040905941882197 -6.38743308323969 5.06812878059259e-10 *** df.mm.trans1:probe5 -0.0401885966844400 0.040905941882197 -0.982463545276067 0.326513513198054 df.mm.trans1:probe6 -0.177219524416531 0.040905941882197 -4.33236630822233 1.90276999934925e-05 *** df.mm.trans2:probe2 -0.365211604317687 0.040905941882197 -8.9280820221532 2.05435692759786e-17 *** df.mm.trans2:probe3 -0.364117274078004 0.040905941882197 -8.90132966811048 2.50599014449537e-17 *** df.mm.trans2:probe4 -0.244454795182593 0.040905941882197 -5.97602167153578 5.3794689183326e-09 *** df.mm.trans2:probe5 -0.230921347988292 0.040905941882197 -5.64517860640665 3.28965757406403e-08 *** df.mm.trans2:probe6 -0.38133111781989 0.040905941882197 -9.3221449078979 1.05460589221616e-18 *** df.mm.trans3:probe2 -0.127735605413780 0.040905941882197 -3.12266628113929 0.00193331188483225 ** df.mm.trans3:probe3 0.165241309712233 0.040905941882197 4.03954296390738 6.5146702190128e-05 *** df.mm.trans3:probe4 -0.116926412929240 0.040905941882197 -2.85842123537873 0.00449849792035959 ** df.mm.trans3:probe5 0.254326884994286 0.040905941882197 6.21735799964487 1.36547388615246e-09 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.0029139341528 0.151533028204006 26.4161152297685 3.59048479831896e-87 *** df.mm.trans1 0.0565768506438798 0.124793481543571 0.453363829136592 0.650552543790421 df.mm.trans2 0.153716757781435 0.124793481543571 1.23176912672130 0.218817600219257 df.mm.exp2 0.0944913476676111 0.170589226543816 0.553911578017156 0.579973954653898 df.mm.exp3 0.167249174182585 0.170589226543816 0.9804204964821 0.327519217193563 df.mm.exp4 0.0283683937991429 0.170589226543816 0.166296514580048 0.868014443860208 df.mm.exp5 0.108968258299974 0.170589226543816 0.638775733425261 0.523364046535617 df.mm.exp6 0.22178994479058 0.170589226543816 1.30014039739850 0.194362160761165 df.mm.exp7 0.293940213727505 0.170589226543816 1.72308779213561 0.0857081351245706 . df.mm.exp8 0.193775894843271 0.170589226543816 1.13592105884541 0.256724828596182 df.mm.trans1:exp2 -0.111107674547714 0.141445114430693 -0.785517937433995 0.432652673860847 df.mm.trans2:exp2 -0.103147067885873 0.141445114430693 -0.729237402797778 0.466317815357147 df.mm.trans1:exp3 -0.192057360042539 0.141445114430693 -1.35782250815488 0.175347487395206 df.mm.trans2:exp3 -0.0778394953800574 0.141445114430693 -0.550315899515907 0.582434791575396 df.mm.trans1:exp4 -0.0373259581537803 0.141445114430693 -0.263890048829291 0.792011557210843 df.mm.trans2:exp4 0.0024450293013904 0.141445114430693 0.0172860640060385 0.986217720598566 df.mm.trans1:exp5 -0.155118977786252 0.141445114430693 -1.09667257445119 0.273497794256042 df.mm.trans2:exp5 -0.114845668474762 0.141445114430693 -0.811945106319211 0.417345181017374 df.mm.trans1:exp6 -0.288955255531115 0.141445114430693 -2.04287901136875 0.0417725861963215 * df.mm.trans2:exp6 -0.130216368582749 0.141445114430693 -0.920614113162274 0.357851766536433 df.mm.trans1:exp7 -0.269291354583912 0.141445114430693 -1.9038575893398 0.0577042963912138 . df.mm.trans2:exp7 -0.238655144392401 0.141445114430693 -1.68726325651452 0.0923955303791385 . df.mm.trans1:exp8 -0.116454214910917 0.141445114430693 -0.823317336760882 0.410857894922221 df.mm.trans2:exp8 -0.165251390512434 0.141445114430693 -1.16830751756651 0.243434968301757 df.mm.trans1:probe2 0.083118440748272 0.0825861541808254 1.00644522768648 0.314859176111142 df.mm.trans1:probe3 0.084393441535507 0.0825861541808254 1.02188366043447 0.307503633951816 df.mm.trans1:probe4 0.0699796217540788 0.0825861541808254 0.847352954598852 0.397346184993677 df.mm.trans1:probe5 0.23297236467527 0.0825861541808254 2.82096153993523 0.00504610462961428 ** df.mm.trans1:probe6 0.0894146417099682 0.0825861541808254 1.08268320031214 0.279654132980476 df.mm.trans2:probe2 -0.0211963437396541 0.0825861541808254 -0.25665735315927 0.797585948432766 df.mm.trans2:probe3 -0.0432890727686553 0.0825861541808254 -0.524168647856786 0.600475099017376 df.mm.trans2:probe4 -0.057336756430494 0.0825861541808254 -0.694265969873752 0.487951106692643 df.mm.trans2:probe5 -0.118898771199659 0.0825861541808254 -1.43969376439694 0.150799569873155 df.mm.trans2:probe6 -0.211120515491526 0.0825861541808254 -2.55636695503788 0.0109757705031139 * df.mm.trans3:probe2 0.0330024131166146 0.0825861541808254 0.399611937908558 0.689672938664144 df.mm.trans3:probe3 -0.00390318636754597 0.0825861541808254 -0.04726199453482 0.962329917402143 df.mm.trans3:probe4 -0.0144313187299812 0.0825861541808254 -0.174742593030585 0.861377476441034 df.mm.trans3:probe5 -0.0777632494955586 0.0825861541808254 -0.94160153438424 0.347011041682858