chr8.23266_chr8_71378312_71378600_-_1.R fitVsDatCorrelation=0.819223401651032 cont.fitVsDatCorrelation=0.288828379433104 fstatistic=10152.4092933287,43,485 cont.fstatistic=3635.50522793575,43,485 residuals=-0.361597109867488,-0.08673076243935,-0.00256525500114603,0.0792808456777514,0.719891725501466 cont.residuals=-0.451498249435435,-0.158129147276575,-0.0485392506453414,0.107561496806919,0.899064988081772 predictedValues: Include Exclude Both chr8.23266_chr8_71378312_71378600_-_1.R.tl.Lung 51.8552104561725 49.6909780397452 62.6083656602307 chr8.23266_chr8_71378312_71378600_-_1.R.tl.cerebhem 50.4698719330268 61.007300731587 59.6480551889468 chr8.23266_chr8_71378312_71378600_-_1.R.tl.cortex 46.6445177068105 48.929341318336 56.2647093261392 chr8.23266_chr8_71378312_71378600_-_1.R.tl.heart 49.8612181934263 48.248381441722 59.8328097691074 chr8.23266_chr8_71378312_71378600_-_1.R.tl.kidney 49.3156815386899 51.0848803344312 60.376035188565 chr8.23266_chr8_71378312_71378600_-_1.R.tl.liver 44.8893143282769 50.5453058729902 64.9723130759269 chr8.23266_chr8_71378312_71378600_-_1.R.tl.stomach 47.7228366067715 51.8071909976858 61.246109263249 chr8.23266_chr8_71378312_71378600_-_1.R.tl.testicle 47.687045416255 50.268752650476 57.9153754681916 diffExp=2.16423241642728,-10.5374287985602,-2.28482361152544,1.61283675170432,-1.76919879574132,-5.65599154471335,-4.08435439091438,-2.58170723422104 diffExpScore=1.27154541587876 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=0,0,0,0,0,0,0,0 diffExp1.3Score=0 diffExp1.2=0,-1,0,0,0,0,0,0 diffExp1.2Score=0.5 cont.predictedValues: Include Exclude Both Lung 55.5239551354901 57.4293860758747 50.1878854970135 cerebhem 56.5792200783997 59.5479121056524 56.3240165670146 cortex 51.8004289936594 58.325003047998 52.5711472610019 heart 53.6524415389668 56.6119653375189 54.878659201396 kidney 48.5275630186536 55.441132134615 58.9444926334472 liver 56.308871015746 59.8594869001984 58.1116773527395 stomach 54.9131393883797 58.0658445691754 55.1813059364973 testicle 52.6646129756291 56.8253658911177 57.2306156449813 cont.diffExp=-1.90543094038463,-2.96869202725268,-6.52457405433861,-2.95952379855215,-6.91356911596134,-3.55061588445242,-3.1527051807957,-4.1607529154886 cont.diffExpScore=0.96982121840861 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=0.266628746415310 cont.tran.correlation=0.787021773165767 tran.covariance=0.000882321203269645 cont.tran.covariance=0.00104948775174784 tran.mean=50.0017392229002 cont.tran.mean=55.7547705129422 weightedLogRatios: wLogRatio Lung 0.167421934075886 cerebhem -0.761536873750255 cortex -0.184901544614542 heart 0.128000139983422 kidney -0.138020372115911 liver -0.458486856426702 stomach -0.320795071176857 testicle -0.205149793209002 cont.weightedLogRatios: wLogRatio Lung -0.136102888992306 cerebhem -0.207688133454575 cortex -0.475326332192162 heart -0.215276855736269 kidney -0.525930256915883 liver -0.248347432323550 stomach -0.225179214309246 testicle -0.304305522547356 varWeightedLogRatios=0.0913782971249461 cont.varWeightedLogRatios=0.0188788798096465 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.34644403062691 0.070129407130425 47.718128065781 2.48578327639534e-185 *** df.mm.trans1 0.575980958683681 0.0561422578633921 10.2593123362652 1.75691057668188e-22 *** df.mm.trans2 0.538662793959002 0.056142257863392 9.59460510600947 4.46461212990508e-20 *** df.mm.exp2 0.226528656780136 0.0751783080728008 3.01321834166274 0.00272012770585632 ** df.mm.exp3 -0.0145147647409060 0.0751783080728008 -0.19307118120895 0.846984046106425 df.mm.exp4 -0.0233282797072627 0.0751783080728008 -0.310305995243631 0.75646157057223 df.mm.exp5 0.0137585232634405 0.0751783080728008 0.183011876911583 0.854865177730586 df.mm.exp6 -0.164271271108919 0.0751783080728008 -2.18508869539659 0.0293601318889185 * df.mm.exp7 -0.0193412279194677 0.0751783080728008 -0.257271391379786 0.797078387883258 df.mm.exp8 0.00568063647484503 0.0751783080728009 0.0755621750537939 0.939798587849168 df.mm.trans1:exp2 -0.253607514502931 0.0589747169018617 -4.30027523362176 2.06336541680725e-05 *** df.mm.trans2:exp2 -0.0213585038929866 0.0589747169018618 -0.362163737530589 0.717387423411613 df.mm.trans1:exp3 -0.0913852551389005 0.0589747169018618 -1.54956666076027 0.121897816713269 df.mm.trans2:exp3 -0.000931380011596389 0.0589747169018618 -0.0157928695638552 0.987406131426238 df.mm.trans1:exp4 -0.0158836308015428 0.0589747169018618 -0.269329496366626 0.78779067776707 df.mm.trans2:exp4 -0.00613282656864636 0.0589747169018618 -0.103990775892182 0.91721965624646 df.mm.trans1:exp5 -0.0639718294283473 0.0589747169018618 -1.08473313292544 0.278578769533228 df.mm.trans2:exp5 0.0139066580486684 0.0589747169018618 0.235807118359043 0.813681886014753 df.mm.trans1:exp6 0.0200156287144045 0.0589747169018618 0.339393383569980 0.734460313211426 df.mm.trans2:exp6 0.181317962946136 0.0589747169018617 3.0745033205986 0.00222741645789308 ** df.mm.trans1:exp7 -0.0637041544785013 0.0589747169018618 -1.08019432436632 0.280592510309456 df.mm.trans2:exp7 0.0610468016501566 0.0589747169018618 1.03513513683742 0.301121648945335 df.mm.trans1:exp8 -0.0894762806158635 0.0589747169018618 -1.51719728921732 0.129868395096373 df.mm.trans2:exp8 0.00587963967254755 0.0589747169018618 0.0996976328403864 0.920625575158824 df.mm.trans1:probe2 0.00450599841222595 0.0403772284620386 0.111597516319436 0.911188710428119 df.mm.trans1:probe3 0.0495700975824165 0.0403772284620386 1.22767459458048 0.220164653230798 df.mm.trans1:probe4 0.00213955611761366 0.0403772284620386 0.0529891772939593 0.957762349176269 df.mm.trans1:probe5 0.353460426408754 0.0403772284620386 8.75395463908739 3.43752715748066e-17 *** df.mm.trans1:probe6 0.00681082186409123 0.0403772284620386 0.168679776287631 0.86611884925983 df.mm.trans2:probe2 0.0901307561003944 0.0403772284620386 2.23221750311893 0.0260564476733072 * df.mm.trans2:probe3 -0.0128572898538455 0.0403772284620386 -0.318429232108725 0.75029644152336 df.mm.trans2:probe4 0.00720051524502685 0.0403772284620386 0.17833109203611 0.858537425366127 df.mm.trans2:probe5 0.320860054312876 0.0403772284620386 7.94655964597815 1.35269295851867e-14 *** df.mm.trans2:probe6 -0.0738690171956224 0.0403772284620386 -1.82947220523251 0.0679426429450574 . df.mm.trans3:probe2 0.120983372878198 0.0403772284620386 2.99632682792833 0.002872496758522 ** df.mm.trans3:probe3 -0.42651462825737 0.0403772284620386 -10.5632467730757 1.29246406434776e-23 *** df.mm.trans3:probe4 -0.324392098270553 0.0403772284620386 -8.03403578270699 7.22591891021274e-15 *** df.mm.trans3:probe5 -0.429207093319234 0.0403772284620386 -10.6299295337411 7.24537698449365e-24 *** df.mm.trans3:probe6 -0.420594241399461 0.0403772284620386 -10.4166198973981 4.57845556786814e-23 *** df.mm.trans3:probe7 -0.555374784957655 0.0403772284620386 -13.7546534547264 1.39673992717850e-36 *** df.mm.trans3:probe8 -0.370610325427174 0.0403772284620386 -9.17869649660601 1.26006273569211e-18 *** df.mm.trans3:probe9 -0.331121619378987 0.0403772284620386 -8.2007020291226 2.15785666788215e-15 *** df.mm.trans3:probe10 -0.505057355340122 0.0403772284620386 -12.5084701099522 2.60587522039314e-31 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.08609855795521 0.117076788120412 34.9010134592409 2.2340712688046e-134 *** df.mm.trans1 -0.089485154886534 0.0937260914846988 -0.954751803569476 0.340178842441059 df.mm.trans2 -0.0160655975687985 0.0937260914846988 -0.171410087781386 0.863972815088298 df.mm.exp2 -0.0602950145730169 0.125505621758948 -0.480416842911008 0.631147636067093 df.mm.exp3 -0.100335140700190 0.125505621758948 -0.799447381671062 0.424422397302608 df.mm.exp4 -0.137974214121403 0.125505621758948 -1.09934688333247 0.272162184195202 df.mm.exp5 -0.330739480241555 0.125505621758948 -2.6352562985329 0.00867651332314036 ** df.mm.exp6 -0.0911116141995064 0.125505621758948 -0.725956438624715 0.468215644588861 df.mm.exp7 -0.0948909682664132 0.125505621758948 -0.756069464750076 0.449974613407092 df.mm.exp8 -0.194759439394306 0.125505621758948 -1.55179853033492 0.121362703715169 df.mm.trans1:exp2 0.0791222442546413 0.0984547099099185 0.803641027707404 0.421998013051052 df.mm.trans2:exp2 0.0965201236976548 0.0984547099099186 0.980350496039917 0.327401899720824 df.mm.trans1:exp3 0.0309190199698070 0.0984547099099186 0.314043076233697 0.753623355246434 df.mm.trans2:exp3 0.115809886002642 0.0984547099099186 1.17627573235046 0.240061734561264 df.mm.trans1:exp4 0.103686639118250 0.0984547099099186 1.05314046644512 0.292801006524503 df.mm.trans2:exp4 0.123638453847395 0.0984547099099186 1.25579013904482 0.209796696465979 df.mm.trans1:exp5 0.196056874728773 0.0984547099099186 1.99134073837763 0.0470039211175636 * df.mm.trans2:exp5 0.295505130949338 0.0984547099099186 3.00143214295904 0.00282563999432270 ** df.mm.trans1:exp6 0.105149152127531 0.0984547099099186 1.06799514440434 0.286053992322535 df.mm.trans2:exp6 0.132555420059514 0.0984547099099185 1.34635935833640 0.178815538331308 df.mm.trans1:exp7 0.0838290695755641 0.0984547099099186 0.85144803790762 0.394940714734828 df.mm.trans2:exp7 0.105912461231265 0.0984547099099186 1.07574804017166 0.282574793905548 df.mm.trans1:exp8 0.141888637166845 0.0984547099099186 1.44115641899373 0.150185801638691 df.mm.trans2:exp8 0.184186123159285 0.0984547099099186 1.87077005587449 0.0619789171314304 . df.mm.trans1:probe2 0.0808842317214852 0.0674073318878623 1.19993225449188 0.230751463840510 df.mm.trans1:probe3 0.0500189132408527 0.0674073318878623 0.7420396541442 0.45842250319414 df.mm.trans1:probe4 0.121216938731316 0.0674073318878623 1.79827528158169 0.0727551125999575 . df.mm.trans1:probe5 0.0500164485821232 0.0674073318878623 0.742003090484723 0.458444635514651 df.mm.trans1:probe6 0.0210818457039225 0.0674073318878623 0.312753006438437 0.75460275440682 df.mm.trans2:probe2 -0.113295549792179 0.0674073318878623 -1.68076003928854 0.0934533855244571 . df.mm.trans2:probe3 -0.0842732346957074 0.0674073318878623 -1.25020872856833 0.21182618447663 df.mm.trans2:probe4 -0.0332902396470022 0.0674073318878623 -0.493866745866508 0.621623871626206 df.mm.trans2:probe5 -0.0919913980887997 0.0674073318878623 -1.36470908300947 0.172977304697263 df.mm.trans2:probe6 0.0112210538635649 0.0674073318878623 0.166466370189998 0.867859321755018 df.mm.trans3:probe2 -0.0855811000830907 0.0674073318878623 -1.26961114890976 0.204832021302001 df.mm.trans3:probe3 0.0409973976600657 0.0674073318878623 0.60820383349794 0.543337000966714 df.mm.trans3:probe4 -0.0716494791240134 0.0674073318878623 -1.06293302401003 0.288341278899536 df.mm.trans3:probe5 -0.190042696098878 0.0674073318878623 -2.81931788095441 0.00500948834247142 ** df.mm.trans3:probe6 -0.0795202842417633 0.0674073318878623 -1.17969784613418 0.238698735432463 df.mm.trans3:probe7 -0.0335806989987229 0.0674073318878623 -0.498175763054784 0.618585986727407 df.mm.trans3:probe8 -0.0444886670694392 0.0674073318878623 -0.659997448696676 0.509568767412086 df.mm.trans3:probe9 -0.0865304877494335 0.0674073318878623 -1.28369548721175 0.199861479871060 df.mm.trans3:probe10 -0.0973453111585474 0.0674073318878623 -1.44413535489714 0.149346569958562