chr10.2386_chr10_76012583_76013513_+_1.R fitVsDatCorrelation=0.953167066460558 cont.fitVsDatCorrelation=0.29131536300543 fstatistic=6011.33703197151,36,324 cont.fstatistic=592.764028618514,36,324 residuals=-0.636149839216903,-0.0886695209893882,-0.00249693033937092,0.0976382497232778,0.707589023667973 cont.residuals=-0.932340763639508,-0.405553729018708,-0.123777440792032,0.346132349440038,1.88934668091536 predictedValues: Include Exclude Both chr10.2386_chr10_76012583_76013513_+_1.R.tl.Lung 44.303289409378 116.521066655761 58.1297788014118 chr10.2386_chr10_76012583_76013513_+_1.R.tl.cerebhem 46.0607003796218 58.0706717885277 64.2469410958999 chr10.2386_chr10_76012583_76013513_+_1.R.tl.cortex 46.9507709114195 81.419936119558 69.2257314919576 chr10.2386_chr10_76012583_76013513_+_1.R.tl.heart 48.7422878885193 100.269493006485 83.8040998118367 chr10.2386_chr10_76012583_76013513_+_1.R.tl.kidney 63.6481910876702 144.665930473235 332.986877548792 chr10.2386_chr10_76012583_76013513_+_1.R.tl.liver 51.5843738586037 129.454007062213 60.5560309449996 chr10.2386_chr10_76012583_76013513_+_1.R.tl.stomach 45.1251728609838 86.4030796833896 65.8528179564326 chr10.2386_chr10_76012583_76013513_+_1.R.tl.testicle 45.6560320423198 121.836953136755 61.0058451706557 diffExp=-72.2177772463826,-12.0099714089059,-34.4691652081385,-51.5272051179654,-81.0177393855647,-77.8696332036094,-41.2779068224058,-76.1809210944355 diffExpScore=0.99776571422085 diffExp1.5=-1,0,-1,-1,-1,-1,-1,-1 diffExp1.5Score=0.875 diffExp1.4=-1,0,-1,-1,-1,-1,-1,-1 diffExp1.4Score=0.875 diffExp1.3=-1,0,-1,-1,-1,-1,-1,-1 diffExp1.3Score=0.875 diffExp1.2=-1,-1,-1,-1,-1,-1,-1,-1 diffExp1.2Score=0.888888888888889 cont.predictedValues: Include Exclude Both Lung 77.3965338308485 80.0486967950016 66.7757054520696 cerebhem 82.1461800882604 85.0642360867433 69.2233573236065 cortex 78.1364502119012 65.002447184999 73.6578638267739 heart 70.0428976117263 63.005307075259 59.0389287246852 kidney 94.128385623424 81.6617570352919 81.7778557796515 liver 82.9691831231873 69.3982993820925 102.470885553308 stomach 78.607886279192 68.1882101323566 79.8623342204949 testicle 93.5746522827993 68.8754273523624 77.4079552309426 cont.diffExp=-2.65216296415319,-2.91805599848288,13.1340030269022,7.03759053646732,12.4666285881321,13.5708837410948,10.4196761468355,24.6992249304369 cont.diffExpScore=1.13210956423492 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=0,0,0,0,0,0,0,1 cont.diffExp1.3Score=0.5 cont.diffExp1.2=0,0,1,0,0,0,0,1 cont.diffExp1.2Score=0.666666666666667 tran.correlation=0.624550865964888 cont.tran.correlation=0.396808781323735 tran.covariance=0.0193499512506664 cont.tran.covariance=0.00479928568063062 tran.mean=76.9194972727775 cont.tran.mean=77.3904093809653 weightedLogRatios: wLogRatio Lung -4.13356109407857 cerebhem -0.91424683144977 cortex -2.27054480655344 heart -3.06357001715054 kidney -3.74721783084907 liver -4.05148100839079 stomach -2.68552698352565 testicle -4.23234621397787 cont.weightedLogRatios: wLogRatio Lung -0.147097223469746 cerebhem -0.154493862957897 cortex 0.785160529888425 heart 0.444327192692741 kidney 0.635584816915071 liver 0.773218834780284 stomach 0.610518983648031 testicle 1.34398966005342 varWeightedLogRatios=1.32887913972029 cont.varWeightedLogRatios=0.248353922657851 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.38773175764255 0.100344351349820 43.7267439434241 5.93025519234865e-138 *** df.mm.trans1 -0.563643212851442 0.084990617382147 -6.6318286678294 1.38945497436803e-10 *** df.mm.trans2 0.125426624431744 0.084990617382147 1.47577024729427 0.140976728754118 df.mm.exp2 -0.75756620241946 0.118359739616894 -6.40053961652456 5.42629235995358e-10 *** df.mm.exp3 -0.475105789206237 0.118359739616894 -4.01408275097644 7.41903396885196e-05 *** df.mm.exp4 -0.420526388232406 0.118359739616894 -3.55295127881798 0.000437522991442449 *** df.mm.exp5 -1.16675795817743 0.118359739616894 -9.8577266387539 3.20511188963311e-20 *** df.mm.exp6 0.216522449715449 0.118359739616894 1.82935895614749 0.068264743073071 . df.mm.exp7 -0.405411591005711 0.118359739616894 -3.42524909498741 0.000693276539129005 *** df.mm.exp8 0.0263968170086734 0.118359739616894 0.223021925311043 0.82365897868986 df.mm.trans1:exp2 0.796467375178846 0.102502541293541 7.77022076845845 1.04499913617377e-13 *** df.mm.trans2:exp2 0.0611548640139998 0.102502541293541 0.596618027633751 0.551179065183235 df.mm.trans1:exp3 0.533146487236412 0.102502541293541 5.20130018737403 3.51567854252428e-07 *** df.mm.trans2:exp3 0.116653861380294 0.102502541293542 1.13805823649022 0.255937006149733 df.mm.trans1:exp4 0.51601444867536 0.102502541293542 5.03416249161691 7.97825732522408e-07 *** df.mm.trans2:exp4 0.270315793151045 0.102502541293541 2.63716186681586 0.0087632977936038 ** df.mm.trans1:exp5 1.52906993577391 0.102502541293541 14.9173856226163 1.13385341194043e-38 *** df.mm.trans2:exp5 1.38311302838086 0.102502541293542 13.4934510981535 3.10244672811297e-33 *** df.mm.trans1:exp6 -0.064362582616296 0.102502541293541 -0.62791206738941 0.530503859211379 df.mm.trans2:exp6 -0.111268875801303 0.102502541293542 -1.08552309432658 0.278497042717848 df.mm.trans1:exp7 0.423792911037909 0.102502541293541 4.13446247956206 4.53660089412744e-05 *** df.mm.trans2:exp7 0.106362824342925 0.102502541293541 1.03766036432529 0.300201984808743 df.mm.trans1:exp8 0.00367999071822086 0.102502541293541 0.0359014583617229 0.971383041464172 df.mm.trans2:exp8 0.0182147978592590 0.102502541293542 0.177700939209852 0.859068892270072 df.mm.trans1:probe2 9.77853824315022e-05 0.0512512706467707 0.00190796015781637 0.99847884315777 df.mm.trans1:probe3 -0.0905854431978248 0.0512512706467707 -1.76747702163619 0.0780896144741823 . df.mm.trans1:probe4 -0.0597180743560941 0.0512512706467707 -1.16520183016881 0.244794430012201 df.mm.trans1:probe5 -0.077008661869692 0.0512512706467707 -1.50257078308251 0.133923765862493 df.mm.trans1:probe6 -0.0700521631283367 0.0512512706467707 -1.36683758752332 0.172623869282377 df.mm.trans2:probe2 0.467531204607043 0.0512512706467707 9.122333918886 7.99094342805257e-18 *** df.mm.trans2:probe3 0.808946331235738 0.0512512706467707 15.7839273256479 4.97189432934116e-42 *** df.mm.trans2:probe4 0.0639395561867296 0.0512512706467707 1.24757016518494 0.213089459024043 df.mm.trans2:probe5 0.302071924618266 0.0512512706467707 5.89394020492053 9.46065625869766e-09 *** df.mm.trans2:probe6 0.561734321574555 0.0512512706467707 10.9603979469326 5.47446852770117e-24 *** df.mm.trans3:probe2 0.196235386775981 0.0512512706467707 3.82888822656624 0.000154516424529693 *** df.mm.trans3:probe3 0.143253334954181 0.0512512706467707 2.79511772384139 0.00549737265536533 ** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.49215198783758 0.317387793799042 14.1535121249239 9.69513220973284e-36 *** df.mm.trans1 -0.0106964274643518 0.268824145870435 -0.0397896826928156 0.968285308185648 df.mm.trans2 -0.153778553605942 0.268824145870435 -0.572041447794869 0.567690564889084 df.mm.exp2 0.0843308617537979 0.374370217419343 0.225260605224204 0.82191855604576 df.mm.exp3 -0.296787164843397 0.374370217419343 -0.792763823172816 0.428495544415027 df.mm.exp4 -0.216108028627028 0.374370217419343 -0.577257534311174 0.564166386176936 df.mm.exp5 0.0130011289121128 0.374370217419343 0.0347280000042041 0.972318018554884 df.mm.exp6 -0.501484933951226 0.374370217419343 -1.33954281248152 0.181332861293511 df.mm.exp7 -0.323798456340688 0.374370217419343 -0.864915106155446 0.387725305456774 df.mm.exp8 -0.108268378919705 0.374370217419343 -0.289201367742429 0.772612245542808 df.mm.trans1:exp2 -0.0247725146273192 0.324214118705454 -0.0764078835500216 0.93914175679066 df.mm.trans2:exp2 -0.0235593314301351 0.324214118705454 -0.0726659638519278 0.942116770964787 df.mm.trans1:exp3 0.306301827827297 0.324214118705454 0.944751663037752 0.345489659304755 df.mm.trans2:exp3 0.0885769236076574 0.324214118705454 0.273205016367991 0.784869684976804 df.mm.trans1:exp4 0.116273908955964 0.324214118705454 0.358633083038551 0.720103164243628 df.mm.trans2:exp4 -0.0233081686621991 0.324214118705454 -0.0718912820800824 0.942732784666467 df.mm.trans1:exp5 0.182716528954091 0.324214118705454 0.563567464870607 0.573438367172394 df.mm.trans2:exp5 0.00694951379949279 0.324214118705454 0.021434951158948 0.982911887352182 df.mm.trans1:exp6 0.571012188085312 0.324214118705454 1.76121937676648 0.0791444983033436 . df.mm.trans2:exp6 0.358712137160288 0.324214118705454 1.10640504674065 0.269372044042534 df.mm.trans1:exp7 0.339328488037826 0.324214118705454 1.04661847976492 0.296055732687995 df.mm.trans2:exp7 0.163434974863789 0.324214118705454 0.504095797913933 0.614536666584945 df.mm.trans1:exp8 0.2980859197377 0.324214118705454 0.919410668875 0.358564788326431 df.mm.trans2:exp8 -0.0420673082961281 0.324214118705454 -0.129751623600161 0.89684345224763 df.mm.trans1:probe2 -0.0975565503410647 0.162107059352727 -0.601803220233564 0.547726000186246 df.mm.trans1:probe3 -0.177886342123157 0.162107059352727 -1.09733865282261 0.273308245078868 df.mm.trans1:probe4 -0.403723712796771 0.162107059352727 -2.49047582757215 0.0132577307755139 * df.mm.trans1:probe5 -0.348598294562164 0.162107059352727 -2.15042019733177 0.032261528352669 * df.mm.trans1:probe6 -0.164857170124292 0.162107059352727 -1.01696478106842 0.309928974238231 df.mm.trans2:probe2 0.188295264821002 0.162107059352727 1.16154882811915 0.246273762088092 df.mm.trans2:probe3 0.0926344244541884 0.162107059352727 0.571439793085297 0.568097744855977 df.mm.trans2:probe4 0.161408363377619 0.162107059352727 0.995689910248833 0.320143859035706 df.mm.trans2:probe5 -0.057743364960048 0.162107059352727 -0.356205122655423 0.721918789065994 df.mm.trans2:probe6 0.0137608390263804 0.162107059352727 0.0848873521074635 0.932403374953736 df.mm.trans3:probe2 -0.276956225520049 0.162107059352727 -1.70847726573969 0.0885055404155136 . df.mm.trans3:probe3 -0.102056824120518 0.162107059352727 -0.62956434178757 0.52942333675866