chr2.13198_chr2_26921326_26921702_+_1.R fitVsDatCorrelation=0.799361250506501 cont.fitVsDatCorrelation=0.253109356583653 fstatistic=8936.84236716848,44,508 cont.fstatistic=3440.14612009287,44,508 residuals=-0.498647034367829,-0.106421168684406,-0.00137701800080981,0.0847739505631994,0.670179791977853 cont.residuals=-0.600715923623161,-0.169156199151795,-0.0227454558523096,0.139036638256994,0.913117346497009 predictedValues: Include Exclude Both chr2.13198_chr2_26921326_26921702_+_1.R.tl.Lung 75.8265731201329 84.0366083679995 72.719289825671 chr2.13198_chr2_26921326_26921702_+_1.R.tl.cerebhem 87.9100021548863 96.6508297433566 99.3150332302944 chr2.13198_chr2_26921326_26921702_+_1.R.tl.cortex 83.1053372979856 79.832251037757 96.8388689428636 chr2.13198_chr2_26921326_26921702_+_1.R.tl.heart 81.279417723018 78.1825318460222 83.0117868390355 chr2.13198_chr2_26921326_26921702_+_1.R.tl.kidney 75.9718424468966 83.7880739762121 71.0060489873449 chr2.13198_chr2_26921326_26921702_+_1.R.tl.liver 78.0784151110647 89.0585331648173 71.536504162754 chr2.13198_chr2_26921326_26921702_+_1.R.tl.stomach 92.315880245777 111.276066144168 76.9383947953152 chr2.13198_chr2_26921326_26921702_+_1.R.tl.testicle 91.1358735648264 85.9917150551428 69.8077959526409 diffExp=-8.21003524786659,-8.74082758847028,3.27308626022855,3.09688587699581,-7.81623152931552,-10.9801180537525,-18.9601858983915,5.14415850968359 diffExpScore=1.49845287426724 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,-1,0 diffExp1.2Score=0.5 cont.predictedValues: Include Exclude Both Lung 80.3132864462045 81.934269056929 84.6721273172642 cerebhem 92.777006312168 91.2334648728207 81.2729609653962 cortex 94.196597568617 87.7848415994395 88.0526548049371 heart 93.2491405650656 90.6855733311468 84.2677542309467 kidney 89.7268208280347 93.8650782969293 87.3228947186003 liver 85.3859243255257 91.335707890202 86.6988582733241 stomach 89.79413549745 83.5201482563942 85.5691829489132 testicle 92.00288433822 79.2607667762256 87.0038172978276 cont.diffExp=-1.62098261072457,1.54354143934729,6.4117559691775,2.56356723391887,-4.13825746889459,-5.94978356467641,6.2739872410559,12.7421175619944 cont.diffExpScore=2.19080589763326 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=0.623526014995654 cont.tran.correlation=0.234521314484371 tran.covariance=0.00547496940535494 cont.tran.covariance=0.000792256438135105 tran.mean=85.902496937504 cont.tran.mean=88.5666028725858 weightedLogRatios: wLogRatio Lung -0.450264930833669 cerebhem -0.428807832812429 cortex 0.176798699935840 heart 0.170088546355678 kidney -0.428858289872901 liver -0.582045444161575 stomach -0.86274816726606 testicle 0.260482285238672 cont.weightedLogRatios: wLogRatio Lung -0.0878405471739823 cerebhem 0.0758626967976718 cortex 0.317943074352947 heart 0.126039295278556 kidney -0.203769922565345 liver -0.30183329572595 stomach 0.323140119155902 testicle 0.662985913634319 varWeightedLogRatios=0.172337961595265 cont.varWeightedLogRatios=0.100421703451030 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.31009647305411 0.0834702284643388 51.6363325265789 2.86367611851029e-204 *** df.mm.trans1 -0.0551989646864453 0.0666224120269952 -0.828534467711538 0.407756977948135 df.mm.trans2 0.0930072263980596 0.0666224120269952 1.39603511143327 0.163313692710688 df.mm.exp2 -0.0239732065561039 0.0890066587634834 -0.26934171992466 0.787776092857476 df.mm.exp3 -0.246106587930723 0.0890066587634834 -2.76503568777589 0.00589865376964518 ** df.mm.exp4 -0.135138177130146 0.0890066587634834 -1.51829288962804 0.129562648924149 df.mm.exp5 0.0227937551986674 0.0890066587634834 0.256090448909413 0.79798466444965 df.mm.exp6 0.103704972108793 0.0890066587634834 1.16513723298351 0.244510258101852 df.mm.exp7 0.421130705087667 0.0890066587634834 4.73145167943821 2.89349108131027e-06 *** df.mm.exp8 0.247762136730235 0.0890066587634834 2.78363596805280 0.00557566487092599 ** df.mm.trans1:exp2 0.171837994850997 0.0693534297668899 2.47771444654687 0.0135467282173646 * df.mm.trans2:exp2 0.163825479396963 0.0693534297668899 2.36218280692983 0.0185438240124334 * df.mm.trans1:exp3 0.337766715061609 0.0693534297668899 4.87022366733566 1.49121874090875e-06 *** df.mm.trans2:exp3 0.194781641274589 0.0693534297668899 2.80853653423179 0.0051683348555271 ** df.mm.trans1:exp4 0.204582197013229 0.0693534297668899 2.94984974356523 0.00332591845275724 ** df.mm.trans2:exp4 0.0629319039919688 0.0693534297668899 0.907408677602461 0.364620954384349 df.mm.trans1:exp5 -0.0208797777626276 0.0693534297668899 -0.301063376862665 0.763489352367493 df.mm.trans2:exp5 -0.0257555909668524 0.0693534297668899 -0.371367228029268 0.71051886378873 df.mm.trans1:exp6 -0.0744401285607507 0.0693534297668899 -1.07334458888274 0.28362612532994 df.mm.trans2:exp6 -0.045663660350333 0.0693534297668899 -0.658419641304219 0.510566801623946 df.mm.trans1:exp7 -0.224363328124984 0.0693534297668899 -3.23507184690234 0.00129533028325044 ** df.mm.trans2:exp7 -0.140369026875124 0.0693534297668899 -2.02396662064056 0.0434964744211117 * df.mm.trans1:exp8 -0.0638594277864966 0.0693534297668899 -0.92078254819034 0.357601017313619 df.mm.trans2:exp8 -0.224763699494271 0.0693534297668899 -3.24084476066642 0.00126990808333195 ** df.mm.trans1:probe2 0.155235460761969 0.0483137176468153 3.21307215264984 0.00139659061230317 ** df.mm.trans1:probe3 0.259940616583381 0.0483137176468152 5.38026525889827 1.13727884424858e-07 *** df.mm.trans1:probe4 0.255306046330742 0.0483137176468153 5.28433866747927 1.87570867888876e-07 *** df.mm.trans1:probe5 0.556659444249683 0.0483137176468152 11.5217679649286 1.89539223150375e-27 *** df.mm.trans1:probe6 0.0232303911942617 0.0483137176468152 0.480823921770652 0.630848658810808 df.mm.trans2:probe2 0.0369228948546202 0.0483137176468152 0.764232119840898 0.44508375201915 df.mm.trans2:probe3 0.0659992245003327 0.0483137176468152 1.36605559900819 0.172525938880103 df.mm.trans2:probe4 0.195382309183635 0.0483137176468152 4.04403384173261 6.06999917521643e-05 *** df.mm.trans2:probe5 0.0197972718719943 0.0483137176468153 0.409765028158609 0.68215105587824 df.mm.trans2:probe6 0.160428211651696 0.0483137176468153 3.32055199776726 0.00096299442230057 *** df.mm.trans3:probe2 -0.360596082793549 0.0483137176468152 -7.46363766559203 3.68089299272440e-13 *** df.mm.trans3:probe3 -0.0178965453266186 0.0483137176468152 -0.3704236849966 0.711221227007296 df.mm.trans3:probe4 -0.271527344626344 0.0483137176468152 -5.62008799677294 3.15079640478944e-08 *** df.mm.trans3:probe5 0.324731118780041 0.0483137176468153 6.72130265681276 4.85052010368375e-11 *** df.mm.trans3:probe6 0.0302207787678923 0.0483137176468152 0.625511350395623 0.531916399675105 df.mm.trans3:probe7 0.076286144793603 0.0483137176468152 1.57897484418965 0.114964269731923 df.mm.trans3:probe8 -0.171216732545866 0.0483137176468152 -3.54385339992880 0.000430718579412233 *** df.mm.trans3:probe9 -0.202655427288725 0.0483137176468152 -4.19457324253507 3.22624399144903e-05 *** df.mm.trans3:probe10 0.0147807530604444 0.0483137176468152 0.305932844342370 0.759781109370618 df.mm.trans3:probe11 -0.0964052218166464 0.0483137176468153 -1.99540061316315 0.0465328000530413 * cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.47088340777329 0.134396515842493 33.2663639361973 1.16907482297157e-129 *** df.mm.trans1 -0.078767847306338 0.107269624370041 -0.734297782516861 0.46310605799984 df.mm.trans2 -0.0612173439720827 0.107269624370041 -0.570686662991427 0.568464403807028 df.mm.exp2 0.292741299496176 0.143310795293971 2.04270235815578 0.0415975565561386 * df.mm.exp3 0.189271990740264 0.143310795293971 1.32070993222816 0.187192755774812 df.mm.exp4 0.25560792338336 0.143310795293971 1.78359154911558 0.0750869314748262 . df.mm.exp5 0.215949538180818 0.143310795293971 1.50686162712198 0.132467702900678 df.mm.exp6 0.146216443679432 0.143310795293971 1.02027515358840 0.308083618576505 df.mm.exp7 0.120216435924732 0.143310795293971 0.838851223162457 0.401947350127958 df.mm.exp8 0.0755452711150165 0.143310795293971 0.527142920113252 0.598324465343596 df.mm.trans1:exp2 -0.148477534582177 0.111666872055816 -1.32964711779480 0.184231304570714 df.mm.trans2:exp2 -0.185236859273694 0.111666872055816 -1.65883449463064 0.0977663824286611 . df.mm.trans1:exp3 -0.0298229964072552 0.111666872055816 -0.26707111839175 0.789522788010888 df.mm.trans2:exp3 -0.120300480882574 0.111666872055816 -1.07731575773380 0.281850540576916 df.mm.trans1:exp4 -0.106268148730205 0.111666872055816 -0.951653312874094 0.341725390117761 df.mm.trans2:exp4 -0.154126967054027 0.111666872055816 -1.38023895732467 0.168120149376925 df.mm.trans1:exp5 -0.105114875290619 0.111666872055816 -0.941325510023049 0.346985479726988 df.mm.trans2:exp5 -0.0800084532077823 0.111666872055816 -0.716492292967521 0.47401667821407 df.mm.trans1:exp6 -0.0849702443813784 0.111666872055816 -0.76092616204837 0.447054224490036 df.mm.trans2:exp6 -0.0375919564465737 0.111666872055816 -0.336643766897882 0.736524481023856 df.mm.trans1:exp7 -0.00863183638147646 0.111666872055816 -0.077299885118676 0.938415417586217 df.mm.trans2:exp7 -0.101045865638446 0.111666872055816 -0.904886684637667 0.36595436233319 df.mm.trans1:exp8 0.0603395895770916 0.111666872055816 0.540353539650786 0.589190057547649 df.mm.trans2:exp8 -0.108719338157424 0.111666872055816 -0.973604222594161 0.330716452262485 df.mm.trans1:probe2 -0.0316217424687739 0.0777905540525032 -0.4064984862742 0.684547562285163 df.mm.trans1:probe3 0.0328788949415138 0.0777905540525032 0.42265922054396 0.672722755711001 df.mm.trans1:probe4 0.0138920348863487 0.0777905540525032 0.178582542000826 0.858336699434355 df.mm.trans1:probe5 -0.0614969500439926 0.0777905540525032 -0.790545211986618 0.429578320930391 df.mm.trans1:probe6 -0.0587206199993197 0.0777905540525032 -0.754855402619801 0.450685549415941 df.mm.trans2:probe2 0.0905409023817614 0.0777905540525032 1.16390612568015 0.245008407942949 df.mm.trans2:probe3 0.0262179186640017 0.0777905540525032 0.337032162623581 0.73623185190126 df.mm.trans2:probe4 -0.0411949230327035 0.0777905540525032 -0.52956202117933 0.596646976663011 df.mm.trans2:probe5 -0.114104432628711 0.0777905540525032 -1.46681604236549 0.143044873812535 df.mm.trans2:probe6 -0.0251879579063152 0.0777905540525032 -0.323791984940936 0.746228784767274 df.mm.trans3:probe2 0.0797255803486633 0.0777905540525032 1.02487482342463 0.305910027858852 df.mm.trans3:probe3 0.164438566653393 0.0777905540525032 2.11386290605937 0.0350137371741031 * df.mm.trans3:probe4 0.167970006290277 0.0777905540525032 2.15925967279920 0.0312974163031831 * df.mm.trans3:probe5 0.130825582207496 0.0777905540525032 1.68176694202741 0.0932286188769621 . df.mm.trans3:probe6 0.113404741324779 0.0777905540525032 1.45782148881776 0.145507664793098 df.mm.trans3:probe7 0.104390030799968 0.0777905540525032 1.34193710369401 0.180215868248610 df.mm.trans3:probe8 0.0751936237409483 0.0777905540525032 0.966616379801046 0.334195787342475 df.mm.trans3:probe9 0.174716072107747 0.0777905540525032 2.24598055941118 0.0251342364053835 * df.mm.trans3:probe10 0.120602521089802 0.0777905540525032 1.55034917232244 0.121680469917284 df.mm.trans3:probe11 0.0555040875758424 0.0777905540525032 0.713506777935801 0.475859876120155