chr13.6690_chr13_34347694_34348730_-_1.R fitVsDatCorrelation=0.895844610677173 cont.fitVsDatCorrelation=0.253117539886869 fstatistic=7486.91587663273,50,646 cont.fstatistic=1569.39219463977,50,646 residuals=-0.667577307560958,-0.113090516944369,-0.0022548095079328,0.097124005653887,0.704944024580482 cont.residuals=-0.763420250010754,-0.292412884740224,-0.0678220017976745,0.208032587002515,1.43042778657652 predictedValues: Include Exclude Both chr13.6690_chr13_34347694_34348730_-_1.R.tl.Lung 127.148459530272 73.4503688612652 60.7109794720762 chr13.6690_chr13_34347694_34348730_-_1.R.tl.cerebhem 82.0020717064636 69.4345147558573 56.2854054340151 chr13.6690_chr13_34347694_34348730_-_1.R.tl.cortex 120.615707420272 73.5378886840107 64.4512472696749 chr13.6690_chr13_34347694_34348730_-_1.R.tl.heart 278.872692565694 116.440748485248 97.9745125205 chr13.6690_chr13_34347694_34348730_-_1.R.tl.kidney 185.107061067760 94.8191567900392 99.7572422973293 chr13.6690_chr13_34347694_34348730_-_1.R.tl.liver 204.136624861759 97.9878523212095 87.113518538103 chr13.6690_chr13_34347694_34348730_-_1.R.tl.stomach 127.221504275101 75.8498403755462 62.1315256351212 chr13.6690_chr13_34347694_34348730_-_1.R.tl.testicle 119.743511639458 80.0720603563557 59.156738577166 diffExp=53.6980906690065,12.5675569506064,47.0778187362612,162.431944080445,90.2879042777206,106.148772540550,51.3716638995547,39.6714512831025 diffExpScore=0.998227752272942 diffExp1.5=1,0,1,1,1,1,1,0 diffExp1.5Score=0.857142857142857 diffExp1.4=1,0,1,1,1,1,1,1 diffExp1.4Score=0.875 diffExp1.3=1,0,1,1,1,1,1,1 diffExp1.3Score=0.875 diffExp1.2=1,0,1,1,1,1,1,1 diffExp1.2Score=0.875 cont.predictedValues: Include Exclude Both Lung 68.1148615106417 78.165353408993 78.0306294917892 cerebhem 86.9422886259491 99.5918081411136 82.8322158760663 cortex 71.0823772194996 90.0697966969776 85.7888818775157 heart 71.5422932651207 82.3984118005778 76.7257088235963 kidney 90.584897058374 88.5321464222822 73.3840773589929 liver 85.5231914838645 85.4439844224282 78.2088087471563 stomach 75.4997935629827 86.5633813438406 81.7805848538155 testicle 67.8107798315805 82.1367254018176 82.553017786961 cont.diffExp=-10.0504918983513,-12.6495195151645,-18.9874194774780,-10.8561185354571,2.0527506360919,0.0792070614362643,-11.0635877808580,-14.3259455702372 cont.diffExpScore=1.04249827579551 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,-1,0,0,0,0,-1 cont.diffExp1.2Score=0.666666666666667 tran.correlation=0.983297166544118 cont.tran.correlation=0.63509390379867 tran.covariance=0.0670085599588559 cont.tran.covariance=0.00555506568571879 tran.mean=120.402503981019 cont.tran.mean=81.8751306372527 weightedLogRatios: wLogRatio Lung 2.50830594006181 cerebhem 0.719270045195667 cortex 2.24900729363709 heart 4.53635871809458 kidney 3.26885572022493 liver 3.63436584051803 stomach 2.37245477833422 testicle 1.84477265990017 cont.weightedLogRatios: wLogRatio Lung -0.590438834202763 cerebhem -0.615763742762916 cortex -1.03746875493331 heart -0.613274832079373 kidney 0.103029415702757 liver 0.00412171189208159 stomach -0.600661468869807 testicle -0.826561477753266 varWeightedLogRatios=1.36339515195837 cont.varWeightedLogRatios=0.150560808980767 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.68061508067107 0.0928536719360245 50.4085081729022 4.54560622327633e-226 *** df.mm.trans1 0.249857182773285 0.0732818976557587 3.40953483419586 0.000691234830388532 *** df.mm.trans2 -0.358651464174141 0.0732818976557587 -4.89413450861909 1.24846787193796e-06 *** df.mm.exp2 -0.419147425028934 0.097037648044579 -4.31943099894978 1.81048357223615e-05 *** df.mm.exp3 -0.111339534588431 0.097037648044579 -1.14738492566599 0.251647320129008 df.mm.exp4 0.767589818714378 0.0970376480445791 7.91022694987153 1.11720153386686e-14 *** df.mm.exp5 0.134325434904118 0.0970376480445791 1.38426103281490 0.166756534274948 df.mm.exp6 0.400580197226470 0.097037648044579 4.12809054319250 4.13748325854456e-05 *** df.mm.exp7 0.0095910390626991 0.097037648044579 0.0988383298232143 0.921297295863718 df.mm.exp8 0.052247790159073 0.097037648044579 0.538428035014517 0.590467045547031 df.mm.trans1:exp2 -0.019463439734323 0.0735824398505756 -0.264512019088353 0.791469773342363 df.mm.trans2:exp2 0.362921575145596 0.0735824398505756 4.93217642528005 1.03543024151252e-06 *** df.mm.trans1:exp3 0.0585936779283631 0.0735824398505756 0.796299742810237 0.426150363652707 df.mm.trans2:exp3 0.112530375742000 0.0735824398505756 1.52931019915236 0.126677056773640 df.mm.trans1:exp4 0.017810183501871 0.0735824398505756 0.242043937902008 0.808822934829644 df.mm.trans2:exp4 -0.306817196325114 0.0735824398505756 -4.16970675270037 3.46619856670036e-05 *** df.mm.trans1:exp5 0.241253554840079 0.0735824398505756 3.27868381817719 0.00109888378736937 ** df.mm.trans2:exp5 0.121036105242406 0.0735824398505756 1.64490475564815 0.100475926858447 df.mm.trans1:exp6 0.0728539257420563 0.0735824398505756 0.990099348295617 0.322496260393584 df.mm.trans2:exp6 -0.112346606689266 0.0735824398505756 -1.52681274115685 0.127297023393897 df.mm.trans1:exp7 -0.00901672010031693 0.0735824398505756 -0.122539020432419 0.902510255878662 df.mm.trans2:exp7 0.0225546377101228 0.0735824398505756 0.306522014707921 0.759305988664679 df.mm.trans1:exp8 -0.112251114308805 0.0735824398505756 -1.52551498070402 0.127620111135211 df.mm.trans2:exp8 0.0340692689892341 0.0735824398505756 0.46300814512836 0.643514461584527 df.mm.trans1:probe2 -0.556290631652657 0.054785465798376 -10.1539819648507 1.41680217947862e-22 *** df.mm.trans1:probe3 -0.564606299485705 0.054785465798376 -10.3057679853192 3.67744542760737e-23 *** df.mm.trans1:probe4 -0.106180432376163 0.054785465798376 -1.93811316247513 0.0530447822947545 . df.mm.trans1:probe5 -0.316492162686862 0.054785465798376 -5.7769366030697 1.18308356909112e-08 *** df.mm.trans1:probe6 -0.414118875328104 0.054785465798376 -7.55891857983217 1.39827265179963e-13 *** df.mm.trans2:probe2 -0.0416331358950948 0.054785465798376 -0.75993030794545 0.447573481532689 df.mm.trans2:probe3 -0.169011574051729 0.054785465798376 -3.08497101537355 0.00212266145893314 ** df.mm.trans2:probe4 -0.273346797801449 0.054785465798376 -4.98940355472075 7.79594154714436e-07 *** df.mm.trans2:probe5 -0.0581889227831741 0.054785465798376 -1.06212335580615 0.288576584028386 df.mm.trans2:probe6 -0.0409544843818632 0.054785465798376 -0.747542870815149 0.455007953880814 df.mm.trans3:probe2 -0.145543001095899 0.054785465798376 -2.65659877076766 0.00808830034509762 ** df.mm.trans3:probe3 -0.555145282551612 0.054785465798376 -10.1330758890448 1.70415268587954e-22 *** df.mm.trans3:probe4 -0.215158784731155 0.054785465798376 -3.92729680391862 9.51468600440245e-05 *** df.mm.trans3:probe5 -0.303338576841252 0.054785465798376 -5.53684398627936 4.48307449825885e-08 *** df.mm.trans3:probe6 -0.859918913554359 0.054785465798376 -15.6961139423195 2.84309801340546e-47 *** df.mm.trans3:probe7 -0.321945256142431 0.054785465798376 -5.87647200677766 6.7150909943071e-09 *** df.mm.trans3:probe8 -0.306877230739964 0.054785465798376 -5.60143509355835 3.14764086259439e-08 *** df.mm.trans3:probe9 -0.414726929877845 0.054785465798376 -7.57001740943743 1.29280182254870e-13 *** df.mm.trans3:probe10 -0.606284939251498 0.054785465798376 -11.0665288761581 3.46699854954200e-26 *** df.mm.trans3:probe11 -0.68345893732447 0.054785465798376 -12.4751871206091 3.72665431015069e-32 *** df.mm.trans3:probe12 -0.38916856435244 0.054785465798376 -7.10350014700388 3.22205209218032e-12 *** df.mm.trans3:probe13 -0.598897595039004 0.054785465798376 -10.9316875618635 1.22142770965694e-25 *** df.mm.trans3:probe14 -0.729259390926569 0.054785465798376 -13.3111835465710 6.71060327784075e-36 *** df.mm.trans3:probe15 -0.544272294881862 0.054785465798376 -9.93461106792297 9.70507546372077e-22 *** df.mm.trans3:probe16 -0.593145667917951 0.054785465798376 -10.8266975423897 3.23283496141806e-25 *** df.mm.trans3:probe17 -0.649694657616286 0.054785465798376 -11.8588871728740 1.73033612003577e-29 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.30573337173954 0.202152387543415 21.2994435735508 1.16358103574094e-76 *** df.mm.trans1 -0.0882602807431013 0.159542538985756 -0.553208450261539 0.580312074928383 df.mm.trans2 0.0601985068262707 0.159542538985756 0.377319473595974 0.706060125607076 df.mm.exp2 0.426586913710660 0.211261351595495 2.01923783261337 0.043875020532563 * df.mm.exp3 0.0896144363995857 0.211261351595495 0.424187555948102 0.67157025455575 df.mm.exp4 0.118697629543146 0.211261351595495 0.561852078701161 0.57441168279557 df.mm.exp5 0.471025757129217 0.211261351595495 2.22958791833868 0.0261177809254707 * df.mm.exp6 0.314345824852283 0.211261351595495 1.48794761785944 0.137252663623230 df.mm.exp7 0.158046450459232 0.211261351595495 0.74810867802193 0.454666865492343 df.mm.exp8 -0.0112547912149045 0.211261351595495 -0.0532742554655914 0.957529862284832 df.mm.trans1:exp2 -0.182537784342673 0.160196851529062 -1.13945925029343 0.254933982825046 df.mm.trans2:exp2 -0.184333498421067 0.160196851529062 -1.15066867208452 0.250294314787882 df.mm.trans1:exp3 -0.0469704094374918 0.160196851529062 -0.293204323238342 0.769460142160032 df.mm.trans2:exp3 0.0521439538873601 0.160196851529062 0.325499242898044 0.744908654117296 df.mm.trans1:exp4 -0.0696042605674519 0.160196851529062 -0.434492063377566 0.664076247709768 df.mm.trans2:exp4 -0.0659579654175635 0.160196851529062 -0.411730722470521 0.68067337585647 df.mm.trans1:exp5 -0.185933677157269 0.160196851529062 -1.16065749971083 0.246209941078996 df.mm.trans2:exp5 -0.346486532999001 0.160196851529062 -2.16287979252915 0.0309165936917427 * df.mm.trans1:exp6 -0.0867536603108383 0.160196851529062 -0.541544103287821 0.588319322604729 df.mm.trans2:exp6 -0.225311314909364 0.160196851529062 -1.40646531288718 0.160066851640130 df.mm.trans1:exp7 -0.0551119485193179 0.160196851529062 -0.344026414959346 0.730938371431016 df.mm.trans2:exp7 -0.0559960708791728 0.160196851529062 -0.349545389592218 0.726793818545153 df.mm.trans1:exp8 0.00678054804284609 0.160196851529062 0.0423263502255285 0.966251618296775 df.mm.trans2:exp8 0.0608135345492134 0.160196851529062 0.379617539101141 0.704354099031405 df.mm.trans1:probe2 0.0418292503335629 0.119273826041585 0.350699325424331 0.725928261265586 df.mm.trans1:probe3 0.0650231157661068 0.119273826041585 0.545158296032495 0.585832813417217 df.mm.trans1:probe4 0.00760678307379302 0.119273826041585 0.0637757949605884 0.949168480544313 df.mm.trans1:probe5 -0.0216458278826515 0.119273826041585 -0.181480116812088 0.856047664633231 df.mm.trans1:probe6 -0.00719975314644944 0.119273826041585 -0.0603632279217674 0.951885014219645 df.mm.trans2:probe2 0.152517805534315 0.119273826041585 1.27871982140607 0.201454917048999 df.mm.trans2:probe3 -0.0630940813258272 0.119273826041585 -0.528985137978463 0.596997466654393 df.mm.trans2:probe4 -0.169531799764356 0.119273826041585 -1.42136632478988 0.155692844235912 df.mm.trans2:probe5 -0.078091187383551 0.119273826041585 -0.65472191154767 0.512879854516048 df.mm.trans2:probe6 -0.00522448227129756 0.119273826041585 -0.0438024204025787 0.965075433325498 df.mm.trans3:probe2 0.0990646367905723 0.119273826041585 0.83056476075508 0.406526397356291 df.mm.trans3:probe3 0.0861137991711921 0.119273826041585 0.721984043181178 0.470565539065824 df.mm.trans3:probe4 0.117150456490388 0.119273826041585 0.982197522946423 0.326370248532054 df.mm.trans3:probe5 0.0496691610301351 0.119273826041585 0.416429678484681 0.677233935663825 df.mm.trans3:probe6 -0.0157860343652225 0.119273826041585 -0.132351203018495 0.894747721813319 df.mm.trans3:probe7 0.0918663115762913 0.119273826041585 0.770213504715291 0.441454821193142 df.mm.trans3:probe8 -0.0601049845884023 0.119273826041585 -0.50392434436912 0.614486350327185 df.mm.trans3:probe9 0.123835076666495 0.119273826041585 1.03824184044637 0.299545927916285 df.mm.trans3:probe10 0.207633775254158 0.119273826041585 1.74081592034924 0.0821919609878922 . df.mm.trans3:probe11 0.132186489512891 0.119273826041585 1.10826066287841 0.268161702501224 df.mm.trans3:probe12 -0.0399828878661179 0.119273826041585 -0.335219294903626 0.737568494190326 df.mm.trans3:probe13 0.114296348059822 0.119273826041585 0.95826848063021 0.338285887022048 df.mm.trans3:probe14 0.145032516570814 0.119273826041585 1.21596264146208 0.224443294647061 df.mm.trans3:probe15 0.044899075686996 0.119273826041585 0.376436953329071 0.706715680908787 df.mm.trans3:probe16 0.08084931426341 0.119273826041585 0.677846237909913 0.498111894692455 df.mm.trans3:probe17 0.173584184575307 0.119273826041585 1.45534179908664 0.146060419401717