chr3.15403_chr3_138783913_138788251_+_0.R fitVsDatCorrelation=0.951311518246184 cont.fitVsDatCorrelation=0.315240198647489 fstatistic=4488.00074423233,48,600 cont.fstatistic=462.255874034221,48,600 residuals=-1.10188406910954,-0.134093143032311,0.0124221874832463,0.128419123221435,1.15769748436120 cont.residuals=-1.52027617390873,-0.594510401318744,-0.193075969660078,0.508376687426768,2.43036667943797 predictedValues: Include Exclude Both chr3.15403_chr3_138783913_138788251_+_0.R.tl.Lung 122.931015483857 86.1825643634138 124.539820397063 chr3.15403_chr3_138783913_138788251_+_0.R.tl.cerebhem 89.9049855660946 79.2513422014287 64.9156637661736 chr3.15403_chr3_138783913_138788251_+_0.R.tl.cortex 95.3581206426912 69.310040739417 73.2134283307073 chr3.15403_chr3_138783913_138788251_+_0.R.tl.heart 91.9833873618412 81.5435220586613 98.4397222662175 chr3.15403_chr3_138783913_138788251_+_0.R.tl.kidney 197.976254458253 94.997730829029 275.686838065745 chr3.15403_chr3_138783913_138788251_+_0.R.tl.liver 354.011010822667 101.871280732343 555.723031392812 chr3.15403_chr3_138783913_138788251_+_0.R.tl.stomach 104.981057962246 78.0291165629817 128.548867795285 chr3.15403_chr3_138783913_138788251_+_0.R.tl.testicle 351.498588828569 89.46389117823 620.67575105086 diffExp=36.7484511204428,10.6536433646660,26.0480799032742,10.4398653031799,102.978523629224,252.139730090324,26.9519413992647,262.034697650340 diffExpScore=0.998628248351982 diffExp1.5=0,0,0,0,1,1,0,1 diffExp1.5Score=0.75 diffExp1.4=1,0,0,0,1,1,0,1 diffExp1.4Score=0.8 diffExp1.3=1,0,1,0,1,1,1,1 diffExp1.3Score=0.857142857142857 diffExp1.2=1,0,1,0,1,1,1,1 diffExp1.2Score=0.857142857142857 cont.predictedValues: Include Exclude Both Lung 131.107860869099 180.188763162881 122.965150814304 cerebhem 119.034281783114 186.799899628696 168.478805518113 cortex 104.753402247340 182.131518400461 128.648718643025 heart 105.672297384152 153.803536733161 166.496665137533 kidney 164.380708494275 202.110999532239 99.7464457744917 liver 139.676233941990 169.018191243219 160.441767334809 stomach 193.6249810069 148.360608604568 148.722306167141 testicle 99.2968861469503 262.723687749809 109.760652633782 cont.diffExp=-49.0809022937822,-67.7656178455819,-77.3781161531211,-48.1312393490091,-37.7302910379643,-29.3419573012285,45.2643724023316,-163.426801602858 cont.diffExpScore=1.20889108296983 cont.diffExp1.5=0,-1,-1,0,0,0,0,-1 cont.diffExp1.5Score=0.75 cont.diffExp1.4=0,-1,-1,-1,0,0,0,-1 cont.diffExp1.4Score=0.8 cont.diffExp1.3=-1,-1,-1,-1,0,0,1,-1 cont.diffExp1.3Score=1.2 cont.diffExp1.2=-1,-1,-1,-1,-1,-1,1,-1 cont.diffExp1.2Score=1.14285714285714 tran.correlation=0.784332397489122 cont.tran.correlation=-0.423947794646097 tran.covariance=0.0580245554668883 cont.tran.covariance=-0.0183345553163788 tran.mean=130.580869361983 cont.tran.mean=158.917741058053 weightedLogRatios: wLogRatio Lung 1.64580660621063 cerebhem 0.559469213989568 cortex 1.40321720632792 heart 0.537466435890082 kidney 3.61346126027576 liver 6.53515831145877 stomach 1.33675185572461 testicle 7.08545089110274 cont.weightedLogRatios: wLogRatio Lung -1.60105666944208 cerebhem -2.25526137556888 cortex -2.72586894528785 heart -1.8196192795422 kidney -1.07562267594989 liver -0.960006326558733 stomach 1.36674424069717 testicle -4.94726639920616 varWeightedLogRatios=6.93270976615176 cont.varWeightedLogRatios=3.17858311083388 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.41910337874532 0.133975170881015 40.4485647833813 1.5102955561361e-173 *** df.mm.trans1 -0.590435753170213 0.106038345888155 -5.5681343218328 3.88792927940368e-08 *** df.mm.trans2 -0.888148398134885 0.106038345888155 -8.37572852250703 3.8904587350164e-16 *** df.mm.exp2 0.254823070084074 0.140734414241263 1.81066636371703 0.0706925669075736 . df.mm.exp3 0.0593846988845953 0.140734414241263 0.421962880968057 0.673203258086617 df.mm.exp4 -0.110165253519959 0.140734414241263 -0.78278830457987 0.434060276828613 df.mm.exp5 -0.220731203646294 0.140734414241263 -1.56842379197948 0.117309463859089 df.mm.exp6 -0.270697674387846 0.140734414241263 -1.92346467526972 0.0548945671119656 . df.mm.exp7 -0.288912874985513 0.140734414241263 -2.05289428703789 0.0405159386067681 * df.mm.exp8 -0.518233744320153 0.140734414241263 -3.68235265776384 0.000251943647001769 *** df.mm.trans1:exp2 -0.567693021659315 0.107487684357643 -5.28147038474131 1.79485579058215e-07 *** df.mm.trans2:exp2 -0.338666608818905 0.107487684357643 -3.15074802143901 0.00170962507160568 ** df.mm.trans1:exp3 -0.313368552099869 0.107487684357643 -2.91539029771261 0.0036850438031466 ** df.mm.trans2:exp3 -0.277262802813752 0.107487684357643 -2.57948437972872 0.0101316035740924 * df.mm.trans1:exp4 -0.179850106202652 0.107487684357643 -1.67321593424822 0.0948060367491213 . df.mm.trans2:exp4 0.0548342565778553 0.107487684357643 0.51014455196007 0.61013780335695 df.mm.trans1:exp5 0.697254951857855 0.107487684357643 6.48683573401658 1.83455999503858e-10 *** df.mm.trans2:exp5 0.318116321306904 0.107487684357643 2.95956065299944 0.00320233414586332 ** df.mm.trans1:exp6 1.32840234274410 0.107487684357643 12.358646952744 2.03604280984535e-31 *** df.mm.trans2:exp6 0.437939849489215 0.107487684357643 4.07432583654942 5.23504673360487e-05 *** df.mm.trans1:exp7 0.131069460196738 0.107487684357643 1.21939049092017 0.223175152972976 df.mm.trans2:exp7 0.189527033644561 0.107487684357643 1.76324417794646 0.078368284801804 . df.mm.trans1:exp8 1.56881609253771 0.107487684357643 14.5953101689101 1.64446916983316e-41 *** df.mm.trans2:exp8 0.555600950025899 0.107487684357643 5.16897310930293 3.21044630908233e-07 *** df.mm.trans1:probe2 0.0534028631747032 0.0786729292542697 0.678795917234833 0.497528915083773 df.mm.trans1:probe3 -0.17323526189425 0.0786729292542697 -2.20196786285097 0.0280473241802470 * df.mm.trans1:probe4 -0.0339881487091792 0.0786729292542697 -0.432018345209062 0.66588328850894 df.mm.trans1:probe5 -0.0215883421203433 0.0786729292542697 -0.274406232550082 0.783866904567077 df.mm.trans1:probe6 -0.182520932962759 0.0786729292542697 -2.31999665822604 0.0206756642962244 * df.mm.trans2:probe2 -0.324577441768554 0.0786729292542697 -4.12565598923519 4.21922547944669e-05 *** df.mm.trans2:probe3 -0.403473298691834 0.0786729292542697 -5.12848958995557 3.94739431777433e-07 *** df.mm.trans2:probe4 -0.229304094306299 0.0786729292542697 -2.91465052184839 0.00369366514077599 ** df.mm.trans2:probe5 -0.272194291526075 0.0786729292542697 -3.45982149268075 0.00057888924715888 *** df.mm.trans2:probe6 -0.334679825993254 0.0786729292542697 -4.25406590507865 2.43493710654765e-05 *** df.mm.trans3:probe2 0.781962758251298 0.0786729292542697 9.93941328565517 1.18639649786043e-21 *** df.mm.trans3:probe3 1.37181333750013 0.0786729292542697 17.4369169993207 2.1682160681019e-55 *** df.mm.trans3:probe4 1.23345342051393 0.0786729292542697 15.6782445017070 1.10463002293872e-46 *** df.mm.trans3:probe5 0.849987810719133 0.0786729292542697 10.8040696943161 5.52355581023482e-25 *** df.mm.trans3:probe6 0.882760333385939 0.0786729292542697 11.2206363961976 1.17919995984933e-26 *** df.mm.trans3:probe7 0.54281430934654 0.0786729292542697 6.89963262448475 1.32795293532611e-11 *** df.mm.trans3:probe8 0.58095983213257 0.0786729292542697 7.38449473839873 5.14136852706561e-13 *** df.mm.trans3:probe9 1.1608371214797 0.0786729292542697 14.7552294351198 2.90116665390491e-42 *** df.mm.trans3:probe10 1.50766423077792 0.0786729292542697 19.1636976666417 3.2056664522021e-64 *** df.mm.trans3:probe11 0.861671426886619 0.0786729292542697 10.9525784161628 1.41688544749048e-25 *** df.mm.trans3:probe12 1.25767173873949 0.0786729292542697 15.9860799726259 3.50284082521004e-48 *** df.mm.trans3:probe13 0.823254903374337 0.0786729292542697 10.4642716519883 1.18592946087809e-23 *** df.mm.trans3:probe14 0.851738354498974 0.0786729292542697 10.8263205981077 4.50841634694073e-25 *** df.mm.trans3:probe15 0.555004620481108 0.0786729292542697 7.05458187132376 4.79009976393683e-12 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.06056258215824 0.412495832471171 12.2681544485953 4.98420871505194e-31 *** df.mm.trans1 -0.185242003718843 0.326481208968539 -0.567389481018169 0.570661818148251 df.mm.trans2 0.248067769125306 0.326481208968538 0.759822502217 0.447659126727676 df.mm.exp2 -0.375484783259057 0.433306850650329 -0.866556304603792 0.386531556655669 df.mm.exp3 -0.258871832974743 0.433306850650329 -0.597433049087995 0.550443689728054 df.mm.exp4 -0.677080803171057 0.433306850650329 -1.56258965708679 0.118676400350722 df.mm.exp5 0.550246409161147 0.433306850650329 1.26987701287277 0.204620708358909 df.mm.exp6 -0.266721924045536 0.433306850650329 -0.615549751048767 0.538425135613135 df.mm.exp7 0.00536385844429987 0.43330685065033 0.0123788913935921 0.990127440764151 df.mm.exp8 0.212790618564216 0.433306850650330 0.491085285738844 0.623545698894048 df.mm.trans1:exp2 0.278875967259155 0.33094357370801 0.842669232505497 0.399749237004014 df.mm.trans2:exp2 0.411517786090796 0.33094357370801 1.2434681280558 0.21418101176887 df.mm.trans1:exp3 0.0344605211029815 0.33094357370801 0.104128086600605 0.917102498536704 df.mm.trans2:exp3 0.269595902011941 0.33094357370801 0.814628001357732 0.415608486889793 df.mm.trans1:exp4 0.461403224672912 0.33094357370801 1.39420511932951 0.163771728392725 df.mm.trans2:exp4 0.518751869999205 0.33094357370801 1.56749340737130 0.117526618559037 df.mm.trans1:exp5 -0.324081628184622 0.33094357370801 -0.979265512103756 0.327843482436412 df.mm.trans2:exp5 -0.435434345689628 0.33094357370801 -1.31573591476899 0.188765199234415 df.mm.trans1:exp6 0.330028703896703 0.33094357370801 0.997235571608005 0.319052179345520 df.mm.trans2:exp6 0.202723288024961 0.33094357370801 0.612561488212559 0.540398415191321 df.mm.trans1:exp7 0.384538992365777 0.33094357370801 1.16194730133982 0.245718865563782 df.mm.trans2:exp7 -0.199722989259900 0.33094357370801 -0.603495596007902 0.546407116711868 df.mm.trans1:exp8 -0.49069675587628 0.33094357370801 -1.48272030297594 0.138673773860361 df.mm.trans2:exp8 0.164307258764606 0.33094357370801 0.49648118839006 0.619736794304448 df.mm.trans1:probe2 -0.211840429414518 0.242225893292621 -0.874557325539939 0.382164741843873 df.mm.trans1:probe3 0.0288279651656612 0.242225893292621 0.119012731355007 0.905305104160653 df.mm.trans1:probe4 -0.122875966668462 0.242225893292621 -0.507278412717097 0.61214587773233 df.mm.trans1:probe5 -0.0702391525247169 0.242225893292621 -0.289973757842083 0.77193649699005 df.mm.trans1:probe6 0.390822782744806 0.242225893292621 1.61346409928468 0.107169496581684 df.mm.trans2:probe2 -0.297199379740678 0.242225893292621 -1.22695132093763 0.220322108905943 df.mm.trans2:probe3 -0.236725708694948 0.242225893292621 -0.977293160021382 0.328817903133379 df.mm.trans2:probe4 -0.70114983689758 0.242225893292621 -2.8946114198062 0.00393430842564219 ** df.mm.trans2:probe5 -0.543481312973603 0.242225893292621 -2.24369618617548 0.0252158996487692 * df.mm.trans2:probe6 -0.628576440139453 0.242225893292621 -2.59500101989551 0.00969036366083046 ** df.mm.trans3:probe2 -0.214356684438679 0.242225893292621 -0.884945376916105 0.376540586251883 df.mm.trans3:probe3 -0.342531132304815 0.242225893292621 -1.41409792177346 0.157851819129793 df.mm.trans3:probe4 -0.390280663728889 0.242225893292621 -1.61122602717543 0.107656358348253 df.mm.trans3:probe5 -0.329260085833687 0.242225893292621 -1.35931002816418 0.17455903097916 df.mm.trans3:probe6 -0.54169114766549 0.242225893292621 -2.23630570746249 0.0256985124952953 * df.mm.trans3:probe7 -0.444132093068301 0.242225893292621 -1.83354507245749 0.0672167437229436 . df.mm.trans3:probe8 -0.118780860759893 0.242225893292621 -0.490372268403194 0.624049768240257 df.mm.trans3:probe9 -0.433026751315985 0.242225893292621 -1.78769802612666 0.0743293132385511 . df.mm.trans3:probe10 -0.178578428586858 0.242225893292621 -0.737239219801848 0.461265079450947 df.mm.trans3:probe11 -0.534122191762627 0.242225893292621 -2.20505819795813 0.0278285950712704 * df.mm.trans3:probe12 -0.236055858169472 0.242225893292621 -0.974527763983944 0.330187285370052 df.mm.trans3:probe13 -0.120042336642930 0.242225893292621 -0.495580117431594 0.620372142368902 df.mm.trans3:probe14 -0.319425073404164 0.242225893292621 -1.31870738120587 0.187770067800929 df.mm.trans3:probe15 -0.470027078065979 0.242225893292621 -1.94044935360466 0.0527932017462323 .