chr1.1544_chr1_78222830_78224901_-_1.R fitVsDatCorrelation=0.928221559191068 cont.fitVsDatCorrelation=0.283032274344772 fstatistic=9831.07583672675,36,324 cont.fstatistic=1471.51295750177,36,324 residuals=-0.407397809913933,-0.0932265257004352,0.00274028663670358,0.0761769019386982,0.653065663257746 cont.residuals=-0.94540833165883,-0.255228696618881,-0.0430105691923982,0.253197022728499,1.12924631534336 predictedValues: Include Exclude Both chr1.1544_chr1_78222830_78224901_-_1.R.tl.Lung 191.842917754237 100.109491517582 64.441657395611 chr1.1544_chr1_78222830_78224901_-_1.R.tl.cerebhem 84.6196733343381 85.8683058484906 70.5861065421271 chr1.1544_chr1_78222830_78224901_-_1.R.tl.cortex 140.53925909364 83.5011645303145 121.259763248055 chr1.1544_chr1_78222830_78224901_-_1.R.tl.heart 107.999997806034 80.4852802440502 70.3558141671529 chr1.1544_chr1_78222830_78224901_-_1.R.tl.kidney 198.174800932897 102.439247461289 59.8345493529916 chr1.1544_chr1_78222830_78224901_-_1.R.tl.liver 156.674472009324 104.191284590434 55.5393235402756 chr1.1544_chr1_78222830_78224901_-_1.R.tl.stomach 105.247840338769 78.2193225186608 59.5988809343521 chr1.1544_chr1_78222830_78224901_-_1.R.tl.testicle 131.692286278615 89.5200697086175 61.2690299237354 diffExp=91.7334262366546,-1.24863251415252,57.0380945633254,27.5147175619835,95.7355534716076,52.4831874188901,27.0285178201083,42.1722165699976 diffExpScore=1.00380540877295 diffExp1.5=1,0,1,0,1,1,0,0 diffExp1.5Score=0.8 diffExp1.4=1,0,1,0,1,1,0,1 diffExp1.4Score=0.833333333333333 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 81.9057117496069 83.8523825349957 91.7062516707791 cerebhem 93.1147778448058 99.7315990683584 95.4053694598459 cortex 100.772572330858 86.5661969206067 112.987213536507 heart 93.7971637612123 104.679002494633 97.3383743497066 kidney 98.308467219927 107.421058407242 101.404019850893 liver 91.416491241904 87.7169254215097 106.187492479444 stomach 100.071602242070 94.1373316957548 103.957155303728 testicle 87.8399741519115 88.4328729690414 107.893659048202 cont.diffExp=-1.94667078538878,-6.61682122355266,14.2063754102515,-10.8818387334207,-9.11259118731506,3.69956582039423,5.93427054631502,-0.592898817129907 cont.diffExpScore=8.3971345359809 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=0.822334307019091 cont.tran.correlation=0.43492787676557 tran.covariance=0.0268359102578497 cont.tran.covariance=0.00301912886711822 tran.mean=115.070338372956 cont.tran.mean=93.7352581284023 weightedLogRatios: wLogRatio Lung 3.20748968596314 cerebhem -0.065117595012417 cortex 2.43922464155093 heart 1.33357822808122 kidney 3.27248110660979 liver 1.97859877154749 stomach 1.33795547580947 testicle 1.80938600612346 cont.weightedLogRatios: wLogRatio Lung -0.103759037359269 cerebhem -0.313602501379295 cortex 0.689411022435555 heart -0.504476842810047 kidney -0.410647032095567 liver 0.185683542443008 stomach 0.279695099001393 testicle -0.0301297998554986 varWeightedLogRatios=1.19931248018947 cont.varWeightedLogRatios=0.159392070465110 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 6.06272523836982 0.0825387333819886 73.4530927475174 4.75294008777564e-204 *** df.mm.trans1 -0.701274907256523 0.0699094449633734 -10.0311897430159 8.43767954215615e-21 *** df.mm.trans2 -1.36615233968204 0.0699094449633734 -19.5417420406898 9.82952932580183e-57 *** df.mm.exp2 -1.06303287851063 0.0973573784671033 -10.9188732815955 7.64872641780705e-24 *** df.mm.exp3 -1.12476872077932 0.0973573784671034 -11.5529889823335 4.36467852189322e-26 *** df.mm.exp4 -0.880541030737965 0.0973573784671033 -9.0444201004806 1.41402486145665e-17 *** df.mm.exp5 0.129655022185643 0.0973573784671033 1.33174315318538 0.183880709540330 df.mm.exp6 -0.0138737160301026 0.0973573784671033 -0.142502974592629 0.886771304660537 df.mm.exp7 -0.76898326125617 0.0973573784671033 -7.89856170496627 4.42819668931668e-14 *** df.mm.exp8 -0.437524739166064 0.0973573784671033 -4.49400698801583 9.74082621390114e-06 *** df.mm.trans1:exp2 0.244522762936862 0.0843139629983675 2.90014553036247 0.00398475199940982 ** df.mm.trans2:exp2 0.909583171559468 0.0843139629983675 10.7880490871610 2.18561478578745e-23 *** df.mm.trans1:exp3 0.813578694200858 0.0843139629983676 9.64939453998397 1.56673655729058e-19 *** df.mm.trans2:exp3 0.943364796828229 0.0843139629983676 11.1887137465771 8.61832577592257e-25 *** df.mm.trans1:exp4 0.305995337073060 0.0843139629983676 3.6292367976937 0.000330194989174765 *** df.mm.trans2:exp4 0.662350842149976 0.0843139629983675 7.8557669286972 5.9021065904692e-14 *** df.mm.trans1:exp5 -0.0971824484391405 0.0843139629983675 -1.15262579272928 0.249913698804033 df.mm.trans2:exp5 -0.106649609204038 0.0843139629983676 -1.26491040643058 0.206812469997619 df.mm.trans1:exp6 -0.188632958313452 0.0843139629983675 -2.23726831956772 0.0259484523792167 * df.mm.trans2:exp6 0.0538376985031149 0.0843139629983676 0.638538346301636 0.523574393019847 df.mm.trans1:exp7 0.168624313786904 0.0843139629983676 1.99995715763199 0.0463393168947452 * df.mm.trans2:exp7 0.522235467135464 0.0843139629983675 6.19393809238424 1.77811251024391e-09 *** df.mm.trans1:exp8 0.0613158753276062 0.0843139629983675 0.72723275181352 0.467608524842048 df.mm.trans2:exp8 0.325723079681178 0.0843139629983676 3.8632163416098 0.000135155340074879 *** df.mm.trans1:probe2 -0.228258892887534 0.0421569814991838 -5.41449802073597 1.19918041672094e-07 *** df.mm.trans1:probe3 -0.307026620962646 0.0421569814991838 -7.28293653967115 2.49885849526152e-12 *** df.mm.trans1:probe4 -0.270773297139503 0.0421569814991838 -6.4229763970351 4.76187585507538e-10 *** df.mm.trans1:probe5 -0.0289280321194402 0.0421569814991838 -0.686197898680206 0.493079071877528 df.mm.trans1:probe6 -0.107974032638933 0.0421569814991838 -2.56123728025983 0.0108824467406512 * df.mm.trans2:probe2 -0.136650538610965 0.0421569814991838 -3.24146876155283 0.00131279839445516 ** df.mm.trans2:probe3 -0.0247950854173775 0.0421569814991838 -0.588160834471927 0.556834084532575 df.mm.trans2:probe4 -0.140248122644540 0.0421569814991838 -3.32680656102609 0.000979419917781284 *** df.mm.trans2:probe5 -0.292724666606792 0.0421569814991838 -6.94368183387276 2.09576601082654e-11 *** df.mm.trans2:probe6 -0.218357155276981 0.0421569814991838 -5.17962025533562 3.91461045578018e-07 *** df.mm.trans3:probe2 0.212785745461784 0.0421569814991838 5.04746160409762 7.48039228160773e-07 *** df.mm.trans3:probe3 0.298601114123172 0.0421569814991838 7.08307624275598 8.82173427141406e-12 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.13698434603556 0.212789853922289 19.4416428686792 2.41859566167731e-56 *** df.mm.trans1 0.202759134633289 0.180230783439557 1.12499724388807 0.261422906934083 df.mm.trans2 0.302600202247025 0.180230783439557 1.67895958987775 0.0941240015722335 . df.mm.exp2 0.262144531424907 0.250993218497736 1.04442874191547 0.297065676747735 df.mm.exp3 0.0304648856467977 0.250993218497737 0.121377325766562 0.90346741660101 df.mm.exp4 0.297803784584584 0.250993218497736 1.18650131811139 0.236293669049319 df.mm.exp5 0.329717584618071 0.250993218497736 1.31365136712267 0.189892977316401 df.mm.exp6 0.00829835705505085 0.250993218497736 0.0330620767553753 0.973645442515613 df.mm.exp7 0.190625718847287 0.250993218497736 0.759485535060409 0.448114381986873 df.mm.exp8 -0.0394217323091427 0.250993218497737 -0.157062937975347 0.875293074484216 df.mm.trans1:exp2 -0.133880357819318 0.217366503396658 -0.615919912807395 0.538379819319519 df.mm.trans2:exp2 -0.0887198652814844 0.217366503396658 -0.408157944739007 0.683427318141932 df.mm.trans1:exp3 0.176832604112591 0.217366503396658 0.813522789157172 0.416515819981017 df.mm.trans2:exp3 0.00138661581385732 0.217366503396658 0.00637916050628545 0.994914126741189 df.mm.trans1:exp4 -0.162237895076550 0.217366503396658 -0.746379467587483 0.455979434264706 df.mm.trans2:exp4 -0.0759631381773275 0.217366503396658 -0.349470304717132 0.726963290421803 df.mm.trans1:exp5 -0.147176153614082 0.217366503396658 -0.67708755173519 0.498833545053679 df.mm.trans2:exp5 -0.0820192493252128 0.217366503396658 -0.37733159453525 0.706174232835477 df.mm.trans1:exp6 0.101558805512425 0.217366503396658 0.467223808293483 0.640653818756088 df.mm.trans2:exp6 0.0367586138488555 0.217366503396658 0.169108916389831 0.865816499164786 df.mm.trans1:exp7 0.0096915043800419 0.217366503396658 0.0445860067149191 0.964464762628645 df.mm.trans2:exp7 -0.0749289293940242 0.217366503396658 -0.344712401511521 0.730534243017086 df.mm.trans1:exp8 0.109369686847310 0.217366503396658 0.503157961959432 0.615195091434909 df.mm.trans2:exp8 0.0926075968761518 0.217366503396658 0.426043550542644 0.670359001889768 df.mm.trans1:probe2 0.077564027960799 0.108683251698329 0.713670475889815 0.475944725234534 df.mm.trans1:probe3 0.0568226906105034 0.108683251698329 0.522828400168092 0.601451006565559 df.mm.trans1:probe4 0.173227621155047 0.108683251698329 1.59387595096872 0.111938837195517 df.mm.trans1:probe5 0.129924216023422 0.108683251698329 1.1954391683463 0.232789714398591 df.mm.trans1:probe6 0.154888678867938 0.108683251698329 1.42513843161282 0.155079773372258 df.mm.trans2:probe2 0.0627727211534731 0.108683251698329 0.577574926886717 0.563952286183802 df.mm.trans2:probe3 -0.0575323400074909 0.108683251698329 -0.529357919536515 0.596919682310068 df.mm.trans2:probe4 -0.121001426023241 0.108683251698329 -1.11334013412760 0.266387660825035 df.mm.trans2:probe5 0.0257100188844141 0.108683251698329 0.236559161440781 0.813148289706658 df.mm.trans2:probe6 -0.00468878949624993 0.108683251698329 -0.0431417851691128 0.965615085226963 df.mm.trans3:probe2 -0.168069524483713 0.108683251698329 -1.54641604715896 0.122980286286251 df.mm.trans3:probe3 -0.203189867686547 0.108683251698329 -1.86956007030908 0.0624467422317725 .