chr13.6237_chr13_55087562_55092006_+_1.R fitVsDatCorrelation=0.917850161972622 cont.fitVsDatCorrelation=0.285879775805422 fstatistic=9554.9268125738,38,370 cont.fstatistic=1631.30399681221,38,370 residuals=-0.489346169902275,-0.0816743957350424,0.0067963495245997,0.076003614760788,0.725690163071187 cont.residuals=-0.705111400587496,-0.281011651690992,-0.0304270776043759,0.27020404086384,1.10130010353126 predictedValues: Include Exclude Both chr13.6237_chr13_55087562_55092006_+_1.R.tl.Lung 120.945230624934 69.459194241354 64.9421056099832 chr13.6237_chr13_55087562_55092006_+_1.R.tl.cerebhem 117.357007430039 71.569137684379 63.2048673716689 chr13.6237_chr13_55087562_55092006_+_1.R.tl.cortex 114.271673830431 69.3090030322189 63.869897069558 chr13.6237_chr13_55087562_55092006_+_1.R.tl.heart 130.216053275608 70.2435448368738 61.9861899000556 chr13.6237_chr13_55087562_55092006_+_1.R.tl.kidney 109.134030067175 67.476491269252 66.8740285217413 chr13.6237_chr13_55087562_55092006_+_1.R.tl.liver 121.079191103761 70.1143326471277 65.4986744180366 chr13.6237_chr13_55087562_55092006_+_1.R.tl.stomach 164.616767681841 84.3248370751961 63.802958394052 chr13.6237_chr13_55087562_55092006_+_1.R.tl.testicle 122.891185757468 66.974942591724 68.7775593953133 diffExp=51.4860363835799,45.7878697456599,44.9626707982118,59.972508438734,41.6575387979227,50.9648584566338,80.2919306066448,55.9162431657435 diffExpScore=0.997685397659214 diffExp1.5=1,1,1,1,1,1,1,1 diffExp1.5Score=0.888888888888889 diffExp1.4=1,1,1,1,1,1,1,1 diffExp1.4Score=0.888888888888889 diffExp1.3=1,1,1,1,1,1,1,1 diffExp1.3Score=0.888888888888889 diffExp1.2=1,1,1,1,1,1,1,1 diffExp1.2Score=0.888888888888889 cont.predictedValues: Include Exclude Both Lung 98.415387029076 80.3391161904244 83.5553860296833 cerebhem 96.9060475906774 79.3113515070335 87.7075671872686 cortex 87.7797458536444 82.4980518988038 89.1552154702078 heart 90.2116040964227 91.121761965709 82.7372328358247 kidney 89.254315285706 78.502096354536 97.064807030095 liver 77.9607388494438 78.4837073784899 73.426568856551 stomach 80.1034954608513 78.0633509449836 82.864707577872 testicle 78.9922705624012 86.5456421693291 91.1642415034268 cont.diffExp=18.0762708386515,17.5946960836440,5.28169395484058,-0.910157869286351,10.7522189311701,-0.522968529046054,2.04014451586772,-7.55337160692791 cont.diffExpScore=1.37092531984591 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=1,1,0,0,0,0,0,0 cont.diffExp1.2Score=0.666666666666667 tran.correlation=0.924352528574624 cont.tran.correlation=-0.00288352247050999 tran.covariance=0.00822976717041236 cont.tran.covariance=4.9564487167028e-05 tran.mean=98.1239139468363 cont.tran.mean=84.6555426960958 weightedLogRatios: wLogRatio Lung 2.50569679726844 cerebhem 2.23437858996796 cortex 2.24430591204429 heart 2.81491236419448 kidney 2.14059606024053 liver 2.47115062728302 stomach 3.19029172665788 testicle 2.73615318420858 cont.weightedLogRatios: wLogRatio Lung 0.910741702042988 cerebhem 0.89632576657929 cortex 0.275765108088244 heart -0.045245698379478 kidney 0.568308856313074 liver -0.0291466403356881 stomach 0.112751607772671 testicle -0.403187292643424 varWeightedLogRatios=0.126167697926074 cont.varWeightedLogRatios=0.222376810110607 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.6015058583298 0.0792019156818799 58.0984161647311 4.56665403487303e-188 *** df.mm.trans1 0.21800441796742 0.0652259307426736 3.34229677499707 0.000915649733344587 *** df.mm.trans2 -0.436731823124382 0.0652259307426736 -6.6956779022036 7.98851675379439e-11 *** df.mm.exp2 0.026922203495576 0.08916203745873 0.301946930138708 0.762862166445591 df.mm.exp3 -0.0422756877914885 0.08916203745873 -0.474144478933161 0.63567656368002 df.mm.exp4 0.131670757578637 0.08916203745873 1.47675806129467 0.140591092453278 df.mm.exp5 -0.161035718622319 0.08916203745873 -1.80610182553149 0.0717149203765165 . df.mm.exp6 0.00196107156372432 0.08916203745873 0.0219944678208148 0.982464224820459 df.mm.exp7 0.519915981571217 0.08916203745873 5.83113616949218 1.20069467162076e-08 *** df.mm.exp8 -0.0778407272050604 0.08916203745873 -0.873025442482627 0.383215429524591 df.mm.trans1:exp2 -0.0570393727095581 0.0739292559485552 -0.77153992661917 0.440879424682356 df.mm.trans2:exp2 0.003002292697191 0.0739292559485552 0.0406103464544563 0.967628439772369 df.mm.trans1:exp3 -0.0144833987880182 0.0739292559485552 -0.195908894282620 0.844789023811084 df.mm.trans2:exp3 0.0401110525114852 0.0739292559485552 0.542559937832961 0.587759471921408 df.mm.trans1:exp4 -0.0578135420181658 0.0739292559485552 -0.782011685041119 0.434707851247603 df.mm.trans2:exp4 -0.120441788952477 0.0739292559485552 -1.62914921037874 0.104132491972011 df.mm.trans1:exp5 0.0582746754537619 0.0739292559485552 0.788249181005057 0.431055685254878 df.mm.trans2:exp5 0.132075531422934 0.0739292559485552 1.78651238577107 0.0748349800800122 . df.mm.trans1:exp6 -0.000854071769647268 0.0739292559485552 -0.0115525546509164 0.990788826450692 df.mm.trans2:exp6 0.00742671467119088 0.0739292559485553 0.100457046076033 0.92003589268917 df.mm.trans1:exp7 -0.211633632907796 0.0739292559485552 -2.86265065422902 0.0044401938252337 ** df.mm.trans2:exp7 -0.325978979653575 0.0739292559485552 -4.40933667559717 1.36089340603627e-05 *** df.mm.trans1:exp8 0.0938022187275372 0.0739292559485552 1.26881053412483 0.205306277997849 df.mm.trans2:exp8 0.0414198385529753 0.0739292559485552 0.560263159983619 0.575639011975978 df.mm.trans1:probe2 -0.0323094489092084 0.0431653857739479 -0.748503652403553 0.45463195038056 df.mm.trans1:probe3 -0.159115986911265 0.0431653857739479 -3.68619402000798 0.000261681657191273 *** df.mm.trans1:probe4 0.128560974798506 0.0431653857739479 2.97833489712718 0.00308923322846862 ** df.mm.trans1:probe5 -0.00553456959674298 0.0431653857739479 -0.128217772122480 0.89804629699561 df.mm.trans1:probe6 -0.197498168377260 0.0431653857739479 -4.57538291008296 6.49675891647906e-06 *** df.mm.trans2:probe2 0.161542199358017 0.0431653857739479 3.74240138160689 0.000211225859936997 *** df.mm.trans2:probe3 -0.0097947545533425 0.0431653857739479 -0.226912244098465 0.8206172972411 df.mm.trans2:probe4 -0.0602024480549433 0.0431653857739479 -1.39469269127389 0.163945276966127 df.mm.trans2:probe5 0.482022151135863 0.0431653857739479 11.1668676763404 3.78116535862302e-25 *** df.mm.trans2:probe6 0.262052381003605 0.0431653857739479 6.07089167176548 3.15377269112317e-09 *** df.mm.trans3:probe2 0.0899393567991029 0.0431653857739479 2.08359905017657 0.0378825084085152 * df.mm.trans3:probe3 -0.374948862586184 0.0431653857739479 -8.68633178792256 1.22080570149561e-16 *** df.mm.trans3:probe4 -0.333413114891679 0.0431653857739479 -7.72408514168561 1.06715823318601e-13 *** df.mm.trans3:probe5 -0.427988694792529 0.0431653857739479 -9.91509023071995 1.04961496072703e-20 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.63684636832134 0.191210106269657 24.2500067532109 1.91527085106503e-78 *** df.mm.trans1 -0.0274788220597598 0.157469134950447 -0.174502908575747 0.861565688467381 df.mm.trans2 -0.299461110508059 0.157469134950447 -1.90171306016442 0.057985152855201 . df.mm.exp2 -0.0768290625957718 0.215255938078318 -0.356919596651585 0.721355467460578 df.mm.exp3 -0.152717450455816 0.215255938078318 -0.709469164099211 0.478480213810254 df.mm.exp4 0.0487409322715249 0.215255938078318 0.226432463172241 0.820990120599266 df.mm.exp5 -0.270707843884128 0.215255938078318 -1.25760918049859 0.209326290331682 df.mm.exp6 -0.127133512207731 0.215255938078318 -0.590615586927386 0.555138592374051 df.mm.exp7 -0.226313142567254 0.215255938078318 -1.05136770947017 0.293775908313358 df.mm.exp8 -0.232584869176751 0.215255938078318 -1.08050384696996 0.280621655380274 df.mm.trans1:exp2 0.0613738261014864 0.178480795125439 0.343867955419809 0.73114092175059 df.mm.trans2:exp2 0.0639536993561429 0.178480795125439 0.35832258205257 0.720306268345592 df.mm.trans1:exp3 0.0383510753667322 0.178480795125439 0.214875081320534 0.829983096240226 df.mm.trans2:exp3 0.179235502165207 0.178480795125439 1.00422850558928 0.315924774436696 df.mm.trans1:exp4 -0.13578002903841 0.178480795125439 -0.760754281394711 0.447288380541524 df.mm.trans2:exp4 0.0771990954373487 0.178480795125439 0.432534466148541 0.665604998301083 df.mm.trans1:exp5 0.173000449835102 0.178480795125439 0.969294481871368 0.333031461194143 df.mm.trans2:exp5 0.247576545464627 0.178480795125439 1.38713269005008 0.166236303743084 df.mm.trans1:exp6 -0.105858299988952 0.178480795125439 -0.59310751005201 0.553471556346973 df.mm.trans2:exp6 0.103767938131541 0.178480795125439 0.581395539271387 0.5613279133608 df.mm.trans1:exp7 0.0204354703216286 0.178480795125439 0.114496746315290 0.90890613136974 df.mm.trans2:exp7 0.197577203205469 0.178480795125439 1.10699418986008 0.269015604923216 df.mm.trans1:exp8 0.0127377117947191 0.178480795125439 0.0713674083856859 0.94314390724437 df.mm.trans2:exp8 0.307000171085704 0.178480795125439 1.72007397697853 0.0862551576721699 . df.mm.trans1:probe2 0.0412794686328886 0.104210332918697 0.396116848269681 0.692247158694321 df.mm.trans1:probe3 -0.000189034074541618 0.104210332918697 -0.00181396670797605 0.998553642362628 df.mm.trans1:probe4 -0.16187578953038 0.104210332918697 -1.55335641866409 0.121192918155827 df.mm.trans1:probe5 -0.0458061382797948 0.104210332918697 -0.439554667918888 0.660516293281668 df.mm.trans1:probe6 -0.0552827107449894 0.104210332918697 -0.530491643166707 0.596089339363053 df.mm.trans2:probe2 0.0900169874057106 0.104210332918697 0.863800977163559 0.388256841897288 df.mm.trans2:probe3 0.0747533115784544 0.104210332918697 0.717331088816071 0.473622437104621 df.mm.trans2:probe4 0.0734004793468363 0.104210332918697 0.704349341289426 0.481658320535701 df.mm.trans2:probe5 0.145122264706401 0.104210332918697 1.39258997300798 0.164580085504852 df.mm.trans2:probe6 0.154292029067262 0.104210332918697 1.48058282461911 0.139568778492103 df.mm.trans3:probe2 0.219515209183559 0.104210332918697 2.10646298726269 0.0358370796843587 * df.mm.trans3:probe3 0.217059918318471 0.104210332918697 2.08290207159991 0.0379463955640439 * df.mm.trans3:probe4 0.142200570944521 0.104210332918697 1.36455346568620 0.173222746366859 df.mm.trans3:probe5 -0.00075928865667351 0.104210332918697 -0.00728611679290853 0.994190498138428