chr1.1082_chr1_163912562_163914322_-_0.R fitVsDatCorrelation=0.854686756288008 cont.fitVsDatCorrelation=0.301758293859152 fstatistic=7995.36603226307,40,416 cont.fstatistic=2363.39123941512,40,416 residuals=-0.493101753478057,-0.100618185486736,0.00543277653819878,0.0937359165149394,0.626500389725463 cont.residuals=-0.622135535996909,-0.198020754981354,-0.0439812523369025,0.125877020055184,1.30274986123488 predictedValues: Include Exclude Both chr1.1082_chr1_163912562_163914322_-_0.R.tl.Lung 80.836212242094 62.0133647130993 89.7542840237728 chr1.1082_chr1_163912562_163914322_-_0.R.tl.cerebhem 78.9623146847072 66.7252143815108 76.6174980530141 chr1.1082_chr1_163912562_163914322_-_0.R.tl.cortex 104.986962122779 75.5754171623636 108.857824369266 chr1.1082_chr1_163912562_163914322_-_0.R.tl.heart 79.2237516776442 59.0340279253177 85.4920855975778 chr1.1082_chr1_163912562_163914322_-_0.R.tl.kidney 61.9742417028991 57.5268019420476 67.376557639214 chr1.1082_chr1_163912562_163914322_-_0.R.tl.liver 58.7325718586685 54.9679966869092 61.3074600280449 chr1.1082_chr1_163912562_163914322_-_0.R.tl.stomach 68.748057840923 55.82764278627 72.7555212685345 chr1.1082_chr1_163912562_163914322_-_0.R.tl.testicle 72.130158211635 59.7999582985575 78.1886747964263 diffExp=18.8228475289947,12.2371003031964,29.4115449604151,20.1897237523264,4.44743976085152,3.76457517175933,12.9204150546529,12.3301999130774 diffExpScore=0.991313702322521 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=1,0,1,1,0,0,0,0 diffExp1.3Score=0.75 diffExp1.2=1,0,1,1,0,0,1,1 diffExp1.2Score=0.833333333333333 cont.predictedValues: Include Exclude Both Lung 68.9010405883469 73.3932100060318 71.0210231529565 cerebhem 72.4950611590425 70.977096115739 68.2229522658838 cortex 70.2674248192204 81.0154886231704 72.19491284007 heart 72.3545413621615 67.543529892689 74.0907070131251 kidney 77.3028369076888 70.697878569931 72.9684518291808 liver 79.7507743678507 90.901373206752 73.0916586114407 stomach 70.7079878895527 80.598918448154 71.8487665099132 testicle 72.6747263045812 68.6935656474099 81.4423801286412 cont.diffExp=-4.49216941768492,1.51796504330351,-10.7480638039500,4.81101146947249,6.60495833775786,-11.1505988389012,-9.89093055860123,3.98116065717129 cont.diffExpScore=2.61195697046484 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=0.925079004115596 cont.tran.correlation=0.362650704752415 tran.covariance=0.0173344918789159 cont.tran.covariance=0.00162059550097988 tran.mean=68.5665433898391 cont.tran.mean=74.2672158692701 weightedLogRatios: wLogRatio Lung 1.12919016228290 cerebhem 0.721504145239077 cortex 1.4757162135501 heart 1.24289237177206 kidney 0.304535280612807 liver 0.267614596033723 stomach 0.859022692861084 testicle 0.784501547822396 cont.weightedLogRatios: wLogRatio Lung -0.269330728752233 cerebhem 0.090420502897959 cortex -0.61536890642362 heart 0.292230898621972 kidney 0.384329355787054 liver -0.581624905956257 stomach -0.566129835781777 testicle 0.239877937081147 varWeightedLogRatios=0.183055898699681 cont.varWeightedLogRatios=0.182478983643418 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.35108522644247 0.0830880691755656 52.3671481310825 3.2153849060479e-185 *** df.mm.trans1 0.0523593587305666 0.0673933233033568 0.776922047528091 0.437646308449816 df.mm.trans2 -0.251044943749311 0.0673933233033568 -3.72507143800114 0.000222197209467339 *** df.mm.exp2 0.208028933708924 0.0911324062882023 2.28271086194126 0.0229512606404763 * df.mm.exp3 0.266225366402231 0.0911324062882023 2.921302939816 0.00367556260435538 ** df.mm.exp4 -0.0207328336787299 0.0911324062882023 -0.22750231803562 0.820144933860803 df.mm.exp5 -0.0540265447237376 0.0911324062882023 -0.592835709318164 0.55361323481286 df.mm.exp6 -0.0588551343734923 0.0911324062882023 -0.645820041087969 0.518751979582807 df.mm.exp7 -0.0570863722402241 0.0911324062882023 -0.626411334511358 0.531388748896022 df.mm.exp8 -0.0123468090045581 0.0911324062882023 -0.135482091469327 0.892296254064665 df.mm.trans1:exp2 -0.231483260805411 0.073473294871815 -3.15057683487949 0.00174720601993784 ** df.mm.trans2:exp2 -0.134795947216229 0.073473294871815 -1.83462504916106 0.0672752141853513 . df.mm.trans1:exp3 -0.00481423065505107 0.073473294871815 -0.0655235438052724 0.947788637482107 df.mm.trans2:exp3 -0.0684442276100122 0.073473294871815 -0.9315524467689 0.352108169109311 df.mm.trans1:exp4 0.000583946018039442 0.073473294871815 0.00794773147247883 0.99366250441675 df.mm.trans2:exp4 -0.0285030658759218 0.073473294871815 -0.387937766036621 0.698260518705444 df.mm.trans1:exp5 -0.211679649403274 0.073473294871815 -2.88104201359936 0.00416871639827372 ** df.mm.trans2:exp5 -0.021072417046312 0.073473294871815 -0.286803757515924 0.774405376618555 df.mm.trans1:exp6 -0.260575442266802 0.073473294871815 -3.54653269220353 0.000434737373686892 *** df.mm.trans2:exp6 -0.0617436498749135 0.0734732948718151 -0.840354988606871 0.40119210497526 df.mm.trans1:exp7 -0.104890177640025 0.073473294871815 -1.42759594248524 0.154158413849044 df.mm.trans2:exp7 -0.0479944123069913 0.0734732948718151 -0.653222540117802 0.513973678092376 df.mm.trans1:exp8 -0.101605987500122 0.073473294871815 -1.38289684268807 0.167438317706010 df.mm.trans2:exp8 -0.0239981490917311 0.0734732948718151 -0.326624103813493 0.744116477305596 df.mm.trans1:probe2 -0.0523544339649225 0.0466914640209318 -1.12128490855314 0.262813445742358 df.mm.trans1:probe3 0.0337879533799586 0.0466914640209318 0.723643048862453 0.4696916151125 df.mm.trans1:probe4 -0.0248166170986473 0.0466914640209318 -0.53150222677794 0.595354484564242 df.mm.trans1:probe5 -0.0350808291303171 0.0466914640209318 -0.751332815663915 0.452877205645102 df.mm.trans1:probe6 -0.064790206698339 0.0466914640209318 -1.38762422761671 0.165994324407079 df.mm.trans2:probe2 0.104470137964102 0.0466914640209318 2.23745689184789 0.025785303258279 * df.mm.trans2:probe3 0.0551600983417784 0.0466914640209318 1.18137435821353 0.238128964641261 df.mm.trans2:probe4 0.174378283857667 0.0466914640209318 3.73469300040567 0.000214138599023378 *** df.mm.trans2:probe5 -0.0328336640343446 0.0466914640209318 -0.703204851739609 0.482321452435827 df.mm.trans2:probe6 0.0538504510129101 0.0466914640209318 1.15332539131283 0.249439074679337 df.mm.trans3:probe2 0.941808161896873 0.0466914640209318 20.1708852280721 1.34006052540675e-63 *** df.mm.trans3:probe3 0.484521797053239 0.0466914640209318 10.3770958399597 1.36975454702177e-22 *** df.mm.trans3:probe4 0.0976385189590593 0.0466914640209318 2.09114280321748 0.0371213847832723 * df.mm.trans3:probe5 0.329805461297220 0.0466914640209318 7.06350653621329 6.86826647238695e-12 *** df.mm.trans3:probe6 0.419189187722627 0.0466914640209318 8.97785487160361 9.6256806593196e-18 *** df.mm.trans3:probe7 0.139769696697194 0.0466914640209318 2.99347428117771 0.00292269479116529 ** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.36126367622219 0.152587463021942 28.5820577251163 3.44276937114046e-100 *** df.mm.trans1 -0.0966048605140013 0.123764775490785 -0.780552141196215 0.435509864728759 df.mm.trans2 -0.0332391264199289 0.123764775490785 -0.268566935043676 0.788396092605006 df.mm.exp2 0.0575678495174462 0.167360522546491 0.343975082304458 0.731038822708865 df.mm.exp3 0.102052315975363 0.167360522546491 0.609775318710625 0.542343569058758 df.mm.exp4 -0.0764663866661265 0.167360522546491 -0.456896199310593 0.647984138161414 df.mm.exp5 0.0505922688075138 0.167360522546491 0.302295117377276 0.762578181497023 df.mm.exp6 0.331440537013666 0.167360522546491 1.98039855499134 0.0483171413245813 * df.mm.exp7 0.107953563821599 0.167360522546491 0.645036010757022 0.519259415527781 df.mm.exp8 -0.149773332798752 0.167360522546491 -0.894914347301629 0.371350368140337 df.mm.trans1:exp2 -0.00672069270579426 0.134930366965974 -0.049808600220357 0.960298818679682 df.mm.trans2:exp2 -0.0910420390502676 0.134930366965974 -0.674733502156902 0.500219903249604 df.mm.trans1:exp3 -0.0824152791714554 0.134930366965974 -0.610798599489753 0.541666490282789 df.mm.trans2:exp3 -0.00324338662431539 0.134930366965974 -0.0240374846466792 0.980834234689385 df.mm.trans1:exp4 0.125373326335077 0.134930366965974 0.929170572601295 0.353339529276022 df.mm.trans2:exp4 -0.00659276061839867 0.134930366965974 -0.0488604660807096 0.961053944034938 df.mm.trans1:exp5 0.0644671052982052 0.134930366965974 0.477780552649517 0.63305735156579 df.mm.trans2:exp5 -0.0880081270498388 0.134930366965974 -0.652248482152518 0.51460111545097 df.mm.trans1:exp6 -0.185205366238481 0.134930366965974 -1.37259958898048 0.170616394750227 df.mm.trans2:exp6 -0.117496853771036 0.134930366965974 -0.870796221881359 0.384367652721877 df.mm.trans1:exp7 -0.0820662952063834 0.134930366965974 -0.608212199015796 0.543378662393068 df.mm.trans2:exp7 -0.0142997577680910 0.134930366965974 -0.105978795504921 0.915650260234582 df.mm.trans1:exp8 0.203095732433435 0.134930366965974 1.50518920981406 0.133034308215719 df.mm.trans2:exp8 0.0835974443306132 0.134930366965974 0.619559897526213 0.535886752106724 df.mm.trans1:probe2 -0.181436790549733 0.0857467517349581 -2.11596109331991 0.0349416489709779 * df.mm.trans1:probe3 -0.105897508488657 0.0857467517349581 -1.23500314992672 0.217526400842860 df.mm.trans1:probe4 -0.0395604863804069 0.0857467517349582 -0.461364256720624 0.644778427275829 df.mm.trans1:probe5 0.00647560635903301 0.0857467517349581 0.07552013607523 0.939837180597136 df.mm.trans1:probe6 -0.0954187749503465 0.0857467517349581 -1.11279754649231 0.266438004093737 df.mm.trans2:probe2 -0.11354556617201 0.0857467517349581 -1.32419670570120 0.186164811373419 df.mm.trans2:probe3 -0.0253506420273529 0.0857467517349581 -0.295645508598522 0.767648328364823 df.mm.trans2:probe4 -0.0652545352855866 0.0857467517349581 -0.761014661958127 0.447079462086752 df.mm.trans2:probe5 -0.129089455237918 0.0857467517349581 -1.50547341591354 0.132961293961522 df.mm.trans2:probe6 -0.0852704287550632 0.0857467517349581 -0.994445002635584 0.320584341942803 df.mm.trans3:probe2 -0.0110791277404116 0.0857467517349582 -0.129207550329802 0.89725586841327 df.mm.trans3:probe3 0.082872087350578 0.0857467517349581 0.966474947141256 0.334368095288998 df.mm.trans3:probe4 0.0218856154994849 0.0857467517349581 0.255235505213457 0.798667349859214 df.mm.trans3:probe5 0.115675412100673 0.0857467517349582 1.34903550000615 0.178059388236523 df.mm.trans3:probe6 0.0831189123367518 0.0857467517349581 0.96935348167673 0.332932094621202 df.mm.trans3:probe7 -0.0715791868588042 0.0857467517349581 -0.834774325680049 0.404323913240071