chr11.4012_chr11_70840095_70841047_-_0.R fitVsDatCorrelation=0.896099076423772 cont.fitVsDatCorrelation=0.308785168257651 fstatistic=6494.1285208717,36,324 cont.fstatistic=1407.18946237039,36,324 residuals=-0.61991746113479,-0.108765252919582,-0.00717047667844721,0.105541108251032,0.866968534200512 cont.residuals=-1.23686701169601,-0.155762065129487,0.0703178577157583,0.248666545965196,1.13718918552071 predictedValues: Include Exclude Both chr11.4012_chr11_70840095_70841047_-_0.R.tl.Lung 192.993384863589 189.732628780069 89.0380622702096 chr11.4012_chr11_70840095_70841047_-_0.R.tl.cerebhem 163.171495213555 181.592270244752 72.790550085418 chr11.4012_chr11_70840095_70841047_-_0.R.tl.cortex 144.593394212474 157.731274625276 74.2873095631147 chr11.4012_chr11_70840095_70841047_-_0.R.tl.heart 148.1593697523 156.139085726129 86.0709584588747 chr11.4012_chr11_70840095_70841047_-_0.R.tl.kidney 196.110821789516 169.053684534020 101.036345305103 chr11.4012_chr11_70840095_70841047_-_0.R.tl.liver 191.011988169815 161.037323613101 99.1951205317995 chr11.4012_chr11_70840095_70841047_-_0.R.tl.stomach 157.461470930503 171.819724338967 78.6587467551745 chr11.4012_chr11_70840095_70841047_-_0.R.tl.testicle 177.439940871793 153.402309029047 83.4498885617803 diffExp=3.26075608351962,-18.4207750311970,-13.1378804128023,-7.9797159738292,27.0571372554959,29.9746645567149,-14.3582534084632,24.037631842746 diffExpScore=4.39742723903348 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 155.779783750829 143.691109017281 153.782202136475 cerebhem 180.357365709803 160.414482710697 150.473503689406 cortex 163.417288206230 147.183334323451 164.392814125120 heart 169.42085262822 140.872597225229 127.091891939712 kidney 131.302453162847 164.528319773469 152.475174159152 liver 160.972229099742 171.86244403973 159.436562699963 stomach 157.916888528119 157.586227428264 151.634199814018 testicle 162.148941939018 123.126450046820 151.426079845393 cont.diffExp=12.0886747335475,19.9428829991059,16.2339538827794,28.5482554029911,-33.2258666106224,-10.8902149399884,0.330661099854382,39.022491892198 cont.diffExpScore=2.19412952596222 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=0,0,0,1,-1,0,0,1 cont.diffExp1.2Score=1.5 tran.correlation=0.347906712199866 cont.tran.correlation=-0.215223178417199 tran.covariance=0.00327535724648697 cont.tran.covariance=-0.00221108729053366 tran.mean=169.465635418432 cont.tran.mean=155.661297974359 weightedLogRatios: wLogRatio Lung 0.0895307321818885 cerebhem -0.550671323081274 cortex -0.436349859634505 heart -0.263579514530032 kidney 0.772671063876993 liver 0.882004693092226 stomach -0.445297072159889 testicle 0.74324936367733 cont.weightedLogRatios: wLogRatio Lung 0.404537873456932 cerebhem 0.60187379059348 cortex 0.527742886664387 heart 0.930053284176444 kidney -1.12570655861616 liver -0.334773082093802 stomach 0.0106083473765720 testicle 1.36298973368645 varWeightedLogRatios=0.374067349184786 cont.varWeightedLogRatios=0.60001377330008 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.33751315253686 0.112109099513091 47.6099904086164 2.56783570619547e-148 *** df.mm.trans1 -0.195216235396807 0.09495523618023 -2.05587646610953 0.040595310252623 * df.mm.trans2 -0.219101111240846 0.09495523618023 -2.30741473619191 0.0216616530952555 * df.mm.exp2 -0.0102283070216832 0.132236679479793 -0.0773484865312744 0.938394062700017 df.mm.exp3 -0.2923295530363 0.132236679479793 -2.21065406501659 0.0277580549913493 * df.mm.exp4 -0.425344185035462 0.132236679479793 -3.21653709627864 0.00142845442071373 ** df.mm.exp5 -0.225791898321439 0.132236679479793 -1.70748312200279 0.0886902465842936 . df.mm.exp6 -0.282324304614821 0.132236679479793 -2.13499239186480 0.0335115058585422 * df.mm.exp7 -0.178700055159177 0.132236679479793 -1.35136526311888 0.177521249377430 df.mm.exp8 -0.231758016071293 0.132236679479793 -1.75260008783499 0.080616531602252 . df.mm.trans1:exp2 -0.157625840384368 0.114520323741601 -1.37640058318407 0.169648114820866 df.mm.trans2:exp2 -0.0336236566024183 0.114520323741601 -0.293604274803531 0.769248288216105 df.mm.trans1:exp3 0.00359926554026111 0.114520323741601 0.0314290548844618 0.974946721541984 df.mm.trans2:exp3 0.107606480407168 0.114520323741601 0.939627804842457 0.348108476532225 df.mm.trans1:exp4 0.160976789093333 0.114520323741601 1.40566131699518 0.160782912324502 df.mm.trans2:exp4 0.230475506081586 0.114520323741601 2.01252929219465 0.0449912678529481 * df.mm.trans1:exp5 0.241815902057994 0.114520323741601 2.11155447485127 0.0354900384275179 * df.mm.trans2:exp5 0.110392358612036 0.114520323741601 0.963954300907502 0.335787738133818 df.mm.trans1:exp6 0.272004582979503 0.114520323741601 2.37516428606370 0.0181227651137936 * df.mm.trans2:exp6 0.118344602262332 0.114520323741601 1.03339388499600 0.302190326706745 df.mm.trans1:exp7 -0.0247750585136528 0.114520323741601 -0.216337656969554 0.828860700807433 df.mm.trans2:exp7 0.0795300038545438 0.114520323741601 0.694461919562785 0.487890236324635 df.mm.trans1:exp8 0.147734293444714 0.114520323741601 1.29002685827239 0.197961298722189 df.mm.trans2:exp8 0.0192060930779096 0.114520323741601 0.167709035832325 0.866916817951665 df.mm.trans1:probe2 0.241014966895531 0.0572601618708005 4.20912129866744 3.32422708847104e-05 *** df.mm.trans1:probe3 0.243896856540424 0.0572601618708005 4.25945104889404 2.68879315744588e-05 *** df.mm.trans1:probe4 0.227478599357037 0.0572601618708005 3.97272015874336 8.76126138336302e-05 *** df.mm.trans1:probe5 0.442778825719267 0.0572601618708005 7.7327553966462 1.34034333848837e-13 *** df.mm.trans1:probe6 -0.0719382857792414 0.0572601618708005 -1.25634094331693 0.209897468863596 df.mm.trans2:probe2 0.0396597729891764 0.0572601618708005 0.69262418570634 0.489041552523461 df.mm.trans2:probe3 0.23495796310568 0.0572601618708005 4.10334088184783 5.15757106628547e-05 *** df.mm.trans2:probe4 0.204223278921110 0.0572601618708005 3.56658577706978 0.000416206401061464 *** df.mm.trans2:probe5 0.320335379524856 0.0572601618708005 5.59438480540185 4.71484044166784e-08 *** df.mm.trans2:probe6 0.345658011179646 0.0572601618708005 6.03662301827883 4.30538123906012e-09 *** df.mm.trans3:probe2 -0.410029178111654 0.0572601618708005 -7.16081067037196 5.41672387517412e-12 *** df.mm.trans3:probe3 -0.892366406786387 0.0572601618708005 -15.5844199113493 2.96537922907872e-41 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.83099771546895 0.240237806276767 20.109231724766 6.01496462456408e-59 *** df.mm.trans1 0.232246142396816 0.203478912358645 1.14137695992529 0.254555965679714 df.mm.trans2 0.108790742892292 0.203478912358645 0.534653648534063 0.593256079762909 df.mm.exp2 0.278342259702934 0.283369056798462 0.982260599825818 0.326704380673663 df.mm.exp3 0.0051552327031542 0.283369056798462 0.0181926451723369 0.985496367815262 df.mm.exp4 0.254759447252385 0.283369056798462 0.89903763710367 0.369300269096321 df.mm.exp5 -0.0269875706593242 0.283369056798462 -0.0952382414799734 0.92418447045149 df.mm.exp6 0.175708198733380 0.283369056798462 0.620068403793106 0.53564860507159 df.mm.exp7 0.119998659528649 0.283369056798462 0.423471288235944 0.672232411201064 df.mm.exp8 -0.0989423571880282 0.283369056798462 -0.349164295868754 0.727192781231733 df.mm.trans1:exp2 -0.131845379311310 0.245404801833904 -0.537256721653502 0.591459066264194 df.mm.trans2:exp2 -0.168247196468336 0.245404801833904 -0.685590482382696 0.493461626379066 df.mm.trans1:exp3 0.0427083797811888 0.245404801833904 0.174032372072715 0.86194870747961 df.mm.trans2:exp3 0.0188578299350182 0.245404801833904 0.0768437691279636 0.938795260533728 df.mm.trans1:exp4 -0.170816942951903 0.245404801833904 -0.696061942045925 0.486889040813833 df.mm.trans2:exp4 -0.274569450449994 0.245404801833904 -1.11884302343778 0.264035919540824 df.mm.trans1:exp5 -0.143952331880020 0.245404801833904 -0.58659134134405 0.557886664225224 df.mm.trans2:exp5 0.162404363389481 0.245404801833904 0.661781522512345 0.508581630679998 df.mm.trans1:exp6 -0.142919706011281 0.245404801833904 -0.582383494305107 0.560713443448763 df.mm.trans2:exp6 0.00332029482357973 0.245404801833904 0.0135298690113936 0.989213382977762 df.mm.trans1:exp7 -0.106373154194234 0.245404801833904 -0.433459954325712 0.664969098051944 df.mm.trans2:exp7 -0.0276917946737468 0.245404801833904 -0.112841291070129 0.910226263546349 df.mm.trans1:exp8 0.139014297400762 0.245404801833904 0.566469345187673 0.571466937530137 df.mm.trans2:exp8 -0.0555116856946899 0.245404801833904 -0.226204561931358 0.821184956657174 df.mm.trans1:probe2 0.0795832744486385 0.122702400916952 0.648587752594201 0.517064292181385 df.mm.trans1:probe3 -0.0313048912170001 0.122702400916952 -0.255128595553628 0.79878565007409 df.mm.trans1:probe4 -0.00198725940042809 0.122702400916952 -0.0161957662244370 0.987088181480473 df.mm.trans1:probe5 0.054825530928932 0.122702400916952 0.446817099903687 0.655305639058154 df.mm.trans1:probe6 -0.234321069667306 0.122702400916952 -1.90966980202694 0.0570586571811595 . df.mm.trans2:probe2 0.0380759617108127 0.122702400916952 0.310311464374552 0.756523625686376 df.mm.trans2:probe3 0.0392163922434199 0.122702400916952 0.319605744878314 0.749473199438605 df.mm.trans2:probe4 0.140118696733788 0.122702400916952 1.14193932381668 0.254322462785964 df.mm.trans2:probe5 -0.081419522835427 0.122702400916952 -0.663552809292899 0.507448424649485 df.mm.trans2:probe6 0.114905620916936 0.122702400916952 0.936457804071061 0.349735003353210 df.mm.trans3:probe2 -0.132388805103507 0.122702400916952 -1.07894225470870 0.281416032685259 df.mm.trans3:probe3 -0.277103008532044 0.122702400916952 -2.2583340379753 0.024589639931426 *