chr1.1488_chr1_160371730_160372671_+_0.R fitVsDatCorrelation=0.773821415267264 cont.fitVsDatCorrelation=0.334366567190482 fstatistic=10493.2305720706,38,370 cont.fstatistic=4734.46453070974,38,370 residuals=-0.346299270230753,-0.091028486131586,0.000587437039160007,0.0855398028185313,0.342680100921047 cont.residuals=-0.506337655895695,-0.121037323338162,-0.00933222754155947,0.130053921007948,0.540751802447401 predictedValues: Include Exclude Both chr1.1488_chr1_160371730_160372671_+_0.R.tl.Lung 58.7778679915993 58.8165756328659 53.453311269637 chr1.1488_chr1_160371730_160372671_+_0.R.tl.cerebhem 63.4807889929157 64.8170634526158 56.5554786913342 chr1.1488_chr1_160371730_160372671_+_0.R.tl.cortex 62.4268209773382 68.0207559258324 58.9729061693734 chr1.1488_chr1_160371730_160372671_+_0.R.tl.heart 57.923080747226 62.4188576369732 60.5157232607133 chr1.1488_chr1_160371730_160372671_+_0.R.tl.kidney 57.8914007604387 57.598265942602 50.3469137183278 chr1.1488_chr1_160371730_160372671_+_0.R.tl.liver 58.1459552085454 64.2462120144486 55.2574351278638 chr1.1488_chr1_160371730_160372671_+_0.R.tl.stomach 61.9665292465037 62.4726961438733 61.2811136711881 chr1.1488_chr1_160371730_160372671_+_0.R.tl.testicle 65.6302679079047 68.4950775504241 60.4187043191677 diffExp=-0.0387076412665763,-1.33627445970014,-5.59393494849413,-4.49577688974714,0.293134817836744,-6.10025680590314,-0.506166897369646,-2.86480964251943 diffExpScore=0.980883688417092 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=0,0,0,0,0,0,0,0 diffExp1.2Score=0 cont.predictedValues: Include Exclude Both Lung 55.0413719358854 55.5636359334827 57.233484481224 cerebhem 63.0322027759774 68.7557900184392 58.2923816046514 cortex 59.0149478684712 59.9935891324352 57.8853350076219 heart 62.240123638029 59.1842020493984 59.400782556563 kidney 61.1046600194688 62.2908770862719 61.9797119973905 liver 57.2179187256184 62.8434544820106 61.9698285223176 stomach 59.749825018472 68.0431517970663 62.4717753226022 testicle 63.0273724368945 65.8102383450964 62.9005692603089 cont.diffExp=-0.522263997597264,-5.72358724246179,-0.978641263964029,3.05592158863062,-1.18621706680311,-5.62553575639225,-8.29332677859427,-2.78286590820191 cont.diffExpScore=1.22170925923716 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=0.755131780481502 cont.tran.correlation=0.606677509768735 tran.covariance=0.0022603563975105 cont.tran.covariance=0.00219951022607009 tran.mean=62.0705135082567 cont.tran.mean=61.4320850789386 weightedLogRatios: wLogRatio Lung -0.00268207563591195 cerebhem -0.0866833481091394 cortex -0.358453068743837 heart -0.306218894496499 kidney 0.0205900042040135 liver -0.410323385749526 stomach -0.0336038076432907 testicle -0.179675234782715 cont.weightedLogRatios: wLogRatio Lung -0.0378962989423823 cerebhem -0.363922927201186 cortex -0.0672024440752964 heart 0.206708765634874 kidney -0.0792569421561998 liver -0.383911178923301 stomach -0.540069599954036 testicle -0.179961720207166 varWeightedLogRatios=0.0288262030826877 cont.varWeightedLogRatios=0.0568090450959158 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.41903516926015 0.069719693878089 63.3828825609478 8.82546131780416e-201 *** df.mm.trans1 -0.285695191990792 0.0574169435819978 -4.97579937501877 9.97356982129738e-07 *** df.mm.trans2 -0.438465775752976 0.0574169435819978 -7.63652239912071 1.92420185096041e-13 *** df.mm.exp2 0.117703621334325 0.0784873686911536 1.49965049532348 0.13455771410427 df.mm.exp3 0.107349261516885 0.0784873686911536 1.36772659482703 0.172227821285005 df.mm.exp4 -0.0793003647836387 0.0784873686911536 -1.01035830485902 0.312983920239792 df.mm.exp5 0.0237434793822683 0.0784873686911536 0.302513382448818 0.762430722957633 df.mm.exp6 0.0442956632168427 0.0784873686911536 0.564366775896709 0.572846497736696 df.mm.exp7 -0.0235282274557649 0.0784873686911536 -0.299770878398893 0.764520262667193 df.mm.exp8 0.140119624814873 0.0784873686911536 1.78525063524860 0.0750397003220844 . df.mm.trans1:exp2 -0.0407316861030475 0.0650782881827111 -0.625887484758217 0.531774631676373 df.mm.trans2:exp2 -0.0205584414507482 0.0650782881827111 -0.315903230168396 0.752254080961367 df.mm.trans1:exp3 -0.0471196444839443 0.0650782881827111 -0.72404554268012 0.469495318605999 df.mm.trans2:exp3 0.0380399175913703 0.0650782881827111 0.584525479289975 0.559223063754589 df.mm.trans1:exp4 0.064650911793536 0.0650782881827111 0.993432888277958 0.321148269811744 df.mm.trans2:exp4 0.138744086528007 0.0650782881827111 2.13195660799306 0.0336686231422251 * df.mm.trans1:exp5 -0.0389400140009381 0.0650782881827111 -0.598356457865205 0.549968214721656 df.mm.trans2:exp5 -0.0446747309935391 0.0650782881827111 -0.686476738111369 0.492842500460636 df.mm.trans1:exp6 -0.0551047339136523 0.0650782881827111 -0.846745288673583 0.397684436887937 df.mm.trans2:exp6 0.044003388150107 0.0650782881827111 0.676160811522345 0.499360975872163 df.mm.trans1:exp7 0.0763572265164462 0.0650782881827111 1.17331338375203 0.241424911882809 df.mm.trans2:exp7 0.0838341133514354 0.0650782881827111 1.28820403382563 0.198479952880043 df.mm.trans1:exp8 -0.0298480235920467 0.0650782881827111 -0.458647951959748 0.646756284147126 df.mm.trans2:exp8 0.0122185435966749 0.0650782881827111 0.187751459632292 0.851174409001502 df.mm.trans1:probe2 -0.117687225404332 0.0379975339785599 -3.09723324336619 0.00210247950814119 ** df.mm.trans1:probe3 -0.0878161523504808 0.0379975339785599 -2.31110135726258 0.0213762720815142 * df.mm.trans1:probe4 -0.179472848713496 0.0379975339785599 -4.72327622141909 3.30033464871724e-06 *** df.mm.trans1:probe5 -0.0830629690213014 0.0379975339785599 -2.18600946756623 0.0294410467168551 * df.mm.trans1:probe6 -0.187281271627427 0.0379975339785599 -4.92877437080786 1.25108887939637e-06 *** df.mm.trans2:probe2 0.276269851670537 0.0379975339785599 7.27073109077083 2.1454753486483e-12 *** df.mm.trans2:probe3 0.107602008098611 0.0379975339785599 2.83181556359223 0.00488151607485189 ** df.mm.trans2:probe4 0.101643007244384 0.0379975339785599 2.67498957436911 0.00780490897444661 ** df.mm.trans2:probe5 0.176384543981361 0.0379975339785599 4.64199976979784 4.79896531603404e-06 *** df.mm.trans2:probe6 0.370498111090892 0.0379975339785599 9.75058305888864 3.83358699253223e-20 *** df.mm.trans3:probe2 0.357168459972022 0.0379975339785599 9.39978000081675 5.82200781635161e-19 *** df.mm.trans3:probe3 0.267415195807327 0.0379975339785599 7.03769870850609 9.53860615370678e-12 *** df.mm.trans3:probe4 0.392422477090418 0.0379975339785599 10.3275775031043 3.86893571322277e-22 *** df.mm.trans3:probe5 0.402665791250987 0.0379975339785599 10.5971558964377 4.30450204931917e-23 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.94945828482957 0.103736101596271 38.0721679729244 4.93453308304489e-130 *** df.mm.trans1 0.0489283953646906 0.0854308095956992 0.572725408974162 0.567178490978697 df.mm.trans2 0.0732509705044423 0.0854308095956993 0.857430367932857 0.391762114364391 df.mm.exp2 0.330260336689381 0.116781546212845 2.82801818780042 0.00493853596533893 ** df.mm.exp3 0.135089446482175 0.116781546212845 1.1567704903989 0.248112433021457 df.mm.exp4 0.148872158060206 0.116781546212845 1.27479180476745 0.203182897496547 df.mm.exp5 0.139121049563258 0.116781546212845 1.19129309445601 0.234302165472316 df.mm.exp6 0.0823913117888012 0.116781546212845 0.70551653459559 0.480932777341449 df.mm.exp7 0.197118534855904 0.116781546212845 1.68792537218712 0.0922682229920913 . df.mm.exp8 0.210314368775551 0.116781546212845 1.80092125507770 0.072529449012417 . df.mm.trans1:exp2 -0.194699705194054 0.0968301428063892 -2.01073446295906 0.0450785664210811 * df.mm.trans2:exp2 -0.117228342551150 0.0968301428063892 -1.21065960612644 0.226798662866680 df.mm.trans1:exp3 -0.0653838004373288 0.0968301428063892 -0.675242218407785 0.49994364185046 df.mm.trans2:exp3 -0.0583806950737519 0.0968301428063892 -0.602918609657361 0.546932203085421 df.mm.trans1:exp4 -0.0259574111950009 0.0968301428063892 -0.268071598808880 0.788793592220433 df.mm.trans2:exp4 -0.085746466368961 0.0968301428063892 -0.885534853959785 0.376443367380396 df.mm.trans1:exp5 -0.0346180370380892 0.0968301428063892 -0.357513022647376 0.720911619389915 df.mm.trans2:exp5 -0.0248350270171623 0.0968301428063892 -0.256480330374186 0.797722514925022 df.mm.trans1:exp6 -0.0436093175013651 0.0968301428063892 -0.45036923665972 0.652707997974393 df.mm.trans2:exp6 0.0407265154362722 0.0968301428063892 0.420597494291674 0.674293198812175 df.mm.trans1:exp7 -0.115037392084855 0.0968301428063892 -1.18803286611764 0.235582501362624 df.mm.trans2:exp7 0.00549459699480033 0.0968301428063892 0.056744695768824 0.95477919970195 df.mm.trans1:exp8 -0.0748303730943169 0.0968301428063892 -0.772800400015308 0.440133900875664 df.mm.trans2:exp8 -0.0410679019108913 0.0968301428063892 -0.424123116218119 0.671722505138661 df.mm.trans1:probe2 -0.0279565673519362 0.0565366229533376 -0.494485979026553 0.621256470665644 df.mm.trans1:probe3 0.098168305134788 0.0565366229533376 1.73636662408738 0.0833313951575076 . df.mm.trans1:probe4 0.000799175355491009 0.0565366229533376 0.0141355339909603 0.988729470060894 df.mm.trans1:probe5 0.0330430777498244 0.0565366229533376 0.584454394757474 0.559270824585159 df.mm.trans1:probe6 0.00262884120159259 0.0565366229533376 0.0464980231267491 0.96293839584104 df.mm.trans2:probe2 0.00278032935318314 0.0565366229533376 0.0491774925339612 0.96080438304051 df.mm.trans2:probe3 -0.00672353761175708 0.0565366229533376 -0.118923580159826 0.905400439579875 df.mm.trans2:probe4 -0.0552263238105424 0.0565366229533376 -0.976823887343313 0.329294571281056 df.mm.trans2:probe5 0.0533337067074096 0.0565366229533376 0.94334793840496 0.346118519739423 df.mm.trans2:probe6 -0.0511474528771103 0.0565366229533376 -0.904678245804047 0.36622454560374 df.mm.trans3:probe2 0.0177686621018795 0.0565366229533376 0.314285876546691 0.753481059090568 df.mm.trans3:probe3 -0.0556114839217027 0.0565366229533376 -0.983636464590422 0.32593704736664 df.mm.trans3:probe4 -0.0705673670607637 0.0565366229533376 -1.2481708912647 0.212757752858532 df.mm.trans3:probe5 -0.0140824639204914 0.0565366229533376 -0.249085693217197 0.803432706960852