chr17.10644_chr17_23431144_23432181_-_1.R fitVsDatCorrelation=0.840907796836527 cont.fitVsDatCorrelation=0.299908510518881 fstatistic=6740.43546609312,36,324 cont.fstatistic=2163.10490902794,36,324 residuals=-0.470767308070402,-0.0903831373524577,0.00729848568490988,0.0941957886494893,1.02065187251585 cont.residuals=-0.868541447487776,-0.189858669633934,-0.0325956509954801,0.19704469233879,0.995210560128464 predictedValues: Include Exclude Both chr17.10644_chr17_23431144_23432181_-_1.R.tl.Lung 84.6127166050896 101.565732525967 61.7526125977701 chr17.10644_chr17_23431144_23432181_-_1.R.tl.cerebhem 90.768609450343 60.3715727346121 73.1936888234683 chr17.10644_chr17_23431144_23432181_-_1.R.tl.cortex 66.8888545198749 65.0340963388328 59.4544499937489 chr17.10644_chr17_23431144_23432181_-_1.R.tl.heart 69.8297128942578 77.9501719621966 60.5349377047122 chr17.10644_chr17_23431144_23432181_-_1.R.tl.kidney 87.802242161631 108.034129692297 63.7276787908895 chr17.10644_chr17_23431144_23432181_-_1.R.tl.liver 77.6954394205859 99.627430547032 62.8748183905125 chr17.10644_chr17_23431144_23432181_-_1.R.tl.stomach 73.0933758549476 67.1764263083118 62.739833238354 chr17.10644_chr17_23431144_23432181_-_1.R.tl.testicle 78.3662428797634 83.6836415681702 68.2992065201534 diffExp=-16.9530159208776,30.3970367157309,1.85475818104206,-8.12045906793875,-20.2318875306664,-21.9319911264461,5.91694954663578,-5.31739868840674 diffExpScore=3.12901916257511 diffExp1.5=0,1,0,0,0,0,0,0 diffExp1.5Score=0.5 diffExp1.4=0,1,0,0,0,0,0,0 diffExp1.4Score=0.5 diffExp1.3=0,1,0,0,0,0,0,0 diffExp1.3Score=0.5 diffExp1.2=-1,1,0,0,-1,-1,0,0 diffExp1.2Score=1.33333333333333 cont.predictedValues: Include Exclude Both Lung 67.8803708215588 70.1155131600467 85.227563728641 cerebhem 69.0074931222043 66.1540895002314 83.4255306530319 cortex 70.0407746047833 69.6679699028582 64.5899254870809 heart 76.9243113632292 74.8153771491595 72.9096046634792 kidney 69.1826876405487 86.5081699946097 72.6049169551197 liver 69.8863280518848 74.0404703907867 76.5954628251064 stomach 68.2647030069313 73.3145613570667 74.4347162757066 testicle 73.5476189224877 78.8871530062733 83.7857426309349 cont.diffExp=-2.23514233848795,2.85340362197287,0.372804701925062,2.10893421406971,-17.3254823540610,-4.15414233890182,-5.04985835013537,-5.33953408378555 cont.diffExpScore=1.32484395099501 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,-1,0,0,0 cont.diffExp1.2Score=0.5 tran.correlation=0.357102590117838 cont.tran.correlation=0.212445430725352 tran.covariance=0.00819798918035316 cont.tran.covariance=0.000835377808027705 tran.mean=80.7812747164946 cont.tran.mean=72.3898494996663 weightedLogRatios: wLogRatio Lung -0.827165568864662 cerebhem 1.7553200294874 cortex 0.117796669431491 heart -0.473160971918542 kidney -0.949453860577148 liver -1.11319473815662 stomach 0.358725602149580 testicle -0.288481571042919 cont.weightedLogRatios: wLogRatio Lung -0.137167837881567 cerebhem 0.177912444442464 cortex 0.0226626479065055 heart 0.120337680758229 kidney -0.971837298729284 liver -0.246888994131951 stomach -0.303954940949779 testicle -0.303677970603155 varWeightedLogRatios=0.871966620549976 cont.varWeightedLogRatios=0.131174389795947 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.02926365020999 0.093426423098755 53.8312768850616 1.16246982568459e-163 *** df.mm.trans1 -0.443169845003207 0.0791312044191426 -5.60044357034959 4.56703765184792e-08 *** df.mm.trans2 -0.310134897129258 0.0791312044191426 -3.9192490422177 0.000108400115184917 *** df.mm.exp2 -0.61993182586832 0.110199796625884 -5.62552604314615 4.00173188254648e-08 *** df.mm.exp3 -0.642920913350107 0.110199796625884 -5.83413883723172 1.31034015921862e-08 *** df.mm.exp4 -0.436745760041356 0.110199796625884 -3.96321747783309 9.10065938747551e-05 *** df.mm.exp5 0.0672607583478342 0.110199796625884 0.610352835551747 0.542055974701724 df.mm.exp6 -0.122566131161411 0.110199796625884 -1.11221739888967 0.266869251614347 df.mm.exp7 -0.575590898581568 0.110199796625884 -5.22315753935223 3.15350314719955e-07 *** df.mm.exp8 -0.371115858543162 0.110199796625884 -3.3676637335644 0.000849406563681829 *** df.mm.trans1:exp2 0.69016077100742 0.0954358233698943 7.23167408880065 3.46139843609163e-12 *** df.mm.trans2:exp2 0.0997439699638261 0.0954358233698942 1.04514181825869 0.296736540092403 df.mm.trans1:exp3 0.407868697703056 0.0954358233698943 4.27374840286358 2.53060179939888e-05 *** df.mm.trans2:exp3 0.197126404806159 0.0954358233698943 2.06553889142998 0.0396668992109691 * df.mm.trans1:exp4 0.244720795598133 0.0954358233698943 2.56424460917190 0.0107904979800342 * df.mm.trans2:exp4 0.172109361634851 0.0954358233698942 1.80340416792741 0.072253632361907 . df.mm.trans1:exp5 -0.0302582906814655 0.0954358233698943 -0.317053802367159 0.751406978752506 df.mm.trans2:exp5 -0.00551976544217187 0.0954358233698943 -0.0578374581710069 0.953913754090145 df.mm.trans1:exp6 0.0372781222996046 0.0954358233698942 0.390609322404235 0.696342733481728 df.mm.trans2:exp6 0.103297464967563 0.0954358233698943 1.08237621178368 0.279890278175661 df.mm.trans1:exp7 0.429244073854852 0.0954358233698943 4.4977248448014 9.58194452903556e-06 *** df.mm.trans2:exp7 0.162207085617318 0.0954358233698942 1.69964568743362 0.090157348745372 . df.mm.trans1:exp8 0.294424547864997 0.0954358233698943 3.0850527345885 0.00221046238868835 ** df.mm.trans2:exp8 0.177453175731421 0.0954358233698943 1.85939796467874 0.0638770569845265 . df.mm.trans1:probe2 -0.188780975115637 0.0477179116849471 -3.95618685834462 9.35975566688939e-05 *** df.mm.trans1:probe3 -0.360362126814226 0.0477179116849471 -7.55192576727754 4.40659556087413e-13 *** df.mm.trans1:probe4 -0.450386284411025 0.0477179116849471 -9.4385162407076 7.66541214241928e-19 *** df.mm.trans1:probe5 -0.158447179840254 0.0477179116849471 -3.32049694224646 0.00100107544543889 ** df.mm.trans1:probe6 -0.174106552506454 0.0477179116849471 -3.64866244893482 0.000307121512899479 *** df.mm.trans2:probe2 -0.614267679965429 0.0477179116849471 -12.8728952771670 6.5619296315844e-31 *** df.mm.trans2:probe3 -0.149317532669633 0.0477179116849471 -3.12917157094988 0.00191233767160536 ** df.mm.trans2:probe4 -0.190047027562504 0.0477179116849471 -3.98271887540408 8.41713484932889e-05 *** df.mm.trans2:probe5 0.0699438637491591 0.0477179116849471 1.46577797056495 0.143678570262781 df.mm.trans2:probe6 -0.0021146015883137 0.0477179116849471 -0.044314629740613 0.964680908818284 df.mm.trans3:probe2 -0.297262279774509 0.0477179116849471 -6.2295743731862 1.45191451152995e-09 *** df.mm.trans3:probe3 -0.161205592791960 0.0477179116849471 -3.37830359920830 0.000818291975568124 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.07310740765797 0.164688414286876 24.7322036908006 1.32876938840113e-76 *** df.mm.trans1 0.146010917835062 0.139489366542739 1.04675303540307 0.295993748737065 df.mm.trans2 0.207811771449608 0.139489366542739 1.48980367894879 0.137248652135122 df.mm.exp2 -0.0203186542895798 0.194255855668041 -0.104597383794195 0.916760010423062 df.mm.exp3 0.302193716487216 0.194255855668041 1.55564791315031 0.120768063191142 df.mm.exp4 0.346058954497597 0.194255855668041 1.78145957715154 0.0757740319820558 . df.mm.exp5 0.389390793030223 0.194255855668041 2.00452538066932 0.0458455886825589 * df.mm.exp6 0.190377961305958 0.194255855668041 0.980037181639922 0.327798977893757 df.mm.exp7 0.185663559561999 0.194255855668041 0.955768148782477 0.339901952782816 df.mm.exp8 0.215122530121623 0.194255855668041 1.10741850937683 0.268934487249390 df.mm.trans1:exp2 0.0367868457149673 0.168230505842406 0.218669292651525 0.827045344604578 df.mm.trans2:exp2 -0.0378387054251423 0.168230505842406 -0.224921783571099 0.822181910717762 df.mm.trans1:exp3 -0.270863052917526 0.168230505842406 -1.61007096519856 0.108356166922397 df.mm.trans2:exp3 -0.308597116611735 0.168230505842407 -1.83437073476329 0.0675158481298751 . df.mm.trans1:exp4 -0.220983888633512 0.168230505842406 -1.31357798353483 0.189917656969967 df.mm.trans2:exp4 -0.281179583770615 0.168230505842406 -1.67139474712165 0.0956092367152715 . df.mm.trans1:exp5 -0.370387043561005 0.168230505842406 -2.20166397114667 0.0283935485665659 * df.mm.trans2:exp5 -0.179296002733693 0.168230505842407 -1.06577580466680 0.287318554224814 df.mm.trans1:exp6 -0.161254827409744 0.168230505842406 -0.958534996980888 0.338507766565600 df.mm.trans2:exp6 -0.135910190408596 0.168230505842406 -0.807880768877391 0.419751955056656 df.mm.trans1:exp7 -0.180017623275099 0.168230505842406 -1.07006527962137 0.28538643255564 df.mm.trans2:exp7 -0.141048386126991 0.168230505842406 -0.838423360975453 0.402411080531317 df.mm.trans1:exp8 -0.134936360437504 0.168230505842406 -0.80209210429355 0.423087583716926 df.mm.trans2:exp8 -0.0972482117962503 0.168230505842407 -0.57806526414032 0.563621602126031 df.mm.trans1:probe2 0.024511503476873 0.0841152529212032 0.291403789748272 0.770928985907945 df.mm.trans1:probe3 0.00106534442971475 0.0841152529212032 0.0126652942565926 0.989902622431566 df.mm.trans1:probe4 0.0178121789256155 0.0841152529212032 0.21175920308177 0.832428040467523 df.mm.trans1:probe5 0.0405799196596504 0.0841152529212032 0.482432356206127 0.629824601861108 df.mm.trans1:probe6 -0.0963117466815996 0.0841152529212032 -1.14499740935002 0.253055315455380 df.mm.trans2:probe2 -0.0488036702720521 0.0841152529212032 -0.580200006267234 0.562183024465168 df.mm.trans2:probe3 -0.145825080073144 0.0841152529212032 -1.73363421031081 0.083934300113436 . df.mm.trans2:probe4 -0.072947117371206 0.0841152529212032 -0.867228176078134 0.386458814795465 df.mm.trans2:probe5 -0.00594794169811979 0.0841152529212032 -0.0707118089948758 0.943670747462128 df.mm.trans2:probe6 -0.00345217268112787 0.0841152529212032 -0.0410409831895978 0.96728850190692 df.mm.trans3:probe2 0.0660529906749912 0.0841152529212032 0.785267693801833 0.43287046735353 df.mm.trans3:probe3 -0.0108685831336607 0.0841152529212032 -0.129210609921628 0.8972711741653