chr4.17052_chr4_113610382_113619296_+_2.R fitVsDatCorrelation=0.861374174120877 cont.fitVsDatCorrelation=0.319554303870538 fstatistic=6189.38640513749,40,416 cont.fstatistic=1771.29687766752,40,416 residuals=-0.718774753404258,-0.112808370988062,-0.0154744910932039,0.097350795307564,0.70232929015104 cont.residuals=-0.82599807274171,-0.239277960449159,-0.00733005421700285,0.210269592913297,1.05714009630036 predictedValues: Include Exclude Both chr4.17052_chr4_113610382_113619296_+_2.R.tl.Lung 74.3124227126565 101.405566102948 78.2663267553276 chr4.17052_chr4_113610382_113619296_+_2.R.tl.cerebhem 63.6482186539345 119.772891680267 77.7274086740909 chr4.17052_chr4_113610382_113619296_+_2.R.tl.cortex 81.7659091512924 95.1803398700766 74.1179698897076 chr4.17052_chr4_113610382_113619296_+_2.R.tl.heart 72.8781134794323 89.9627697523994 74.3821077817513 chr4.17052_chr4_113610382_113619296_+_2.R.tl.kidney 72.0407431712012 94.7059760176572 73.3480623490114 chr4.17052_chr4_113610382_113619296_+_2.R.tl.liver 70.2094009196476 96.1652160824783 75.127056094948 chr4.17052_chr4_113610382_113619296_+_2.R.tl.stomach 99.7179009561097 110.730095372968 81.8825668159453 chr4.17052_chr4_113610382_113619296_+_2.R.tl.testicle 69.3902529720069 98.6593174933256 69.7401082134732 diffExp=-27.0931433902913,-56.1246730263326,-13.4144307187842,-17.0846562729671,-22.6652328464559,-25.9558151628307,-11.0121944168585,-29.2690645213187 diffExpScore=0.99508887202611 diffExp1.5=0,-1,0,0,0,0,0,0 diffExp1.5Score=0.5 diffExp1.4=0,-1,0,0,0,0,0,-1 diffExp1.4Score=0.666666666666667 diffExp1.3=-1,-1,0,0,-1,-1,0,-1 diffExp1.3Score=0.833333333333333 diffExp1.2=-1,-1,0,-1,-1,-1,0,-1 diffExp1.2Score=0.857142857142857 cont.predictedValues: Include Exclude Both Lung 84.2258774231082 84.0408390175597 76.557314423198 cerebhem 90.8634004307595 96.8429109084406 85.0337887033333 cortex 90.1210479360397 78.585093014955 77.7730898068789 heart 87.716374027364 75.9801477694488 96.391268443583 kidney 81.571526759772 85.8933966101559 87.3963471428426 liver 71.9632612077628 79.171619378087 70.751400526923 stomach 88.108149064275 91.9006662276735 80.044659385518 testicle 87.7018555567362 73.129651503984 82.3211460800734 cont.diffExp=0.185038405548482,-5.97951047768115,11.5359549210847,11.7362262579151,-4.32186985038388,-7.20835817032415,-3.79251716339841,14.5722040527522 cont.diffExpScore=3.34693501979813 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=0.0883304059375644 cont.tran.correlation=0.226034328514753 tran.covariance=0.000563835597875196 cont.tran.covariance=0.00147978682890552 tran.mean=88.1590708992751 cont.tran.mean=84.2384885522576 weightedLogRatios: wLogRatio Lung -1.38754141614403 cerebhem -2.82572440728979 cortex -0.680542462275974 heart -0.925428971612649 kidney -1.20743002934316 liver -1.38693665405504 stomach -0.487584097578937 testicle -1.55400417809552 cont.weightedLogRatios: wLogRatio Lung 0.00974839285436535 cerebhem -0.289425385530089 cortex 0.607150138008348 heart 0.632329551443985 kidney -0.228566509075123 liver -0.412767598877812 stomach -0.189629322550735 testicle 0.79644725377804 varWeightedLogRatios=0.514259098939862 cont.varWeightedLogRatios=0.234031698773951 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.5766413799944 0.0981660937516982 46.6214066902834 2.82179315334922e-167 *** df.mm.trans1 -0.332672191788549 0.0796232161762807 -4.17808031079822 3.58459658629615e-05 *** df.mm.trans2 0.0243064675499579 0.0796232161762807 0.305268597743464 0.760314272504007 df.mm.exp2 0.0184721128294843 0.107670239882483 0.171561917663095 0.863865370820365 df.mm.exp3 0.0866871328481287 0.107670239882483 0.80511692871441 0.421212125674998 df.mm.exp4 -0.0883198037842828 0.107670239882483 -0.820280551809669 0.412525949177831 df.mm.exp5 -0.0344958087735172 0.107670239882483 -0.320383875908214 0.748838212371618 df.mm.exp6 -0.0689194903800887 0.107670239882483 -0.640097862281266 0.522461358427446 df.mm.exp7 0.336866106949311 0.107670239882483 3.12868353703850 0.00187947689585050 ** df.mm.exp8 0.0193548353434484 0.107670239882483 0.179760306697312 0.857428273479 df.mm.trans1:exp2 -0.173378909220528 0.0868065225753715 -1.99730278413110 0.0464431797788774 * df.mm.trans2:exp2 0.147997285264747 0.0868065225753715 1.70490973343905 0.0889578465279066 . df.mm.trans1:exp3 0.00889513093201333 0.0868065225753715 0.102470766805455 0.918432390859498 df.mm.trans2:exp3 -0.150041708532083 0.0868065225753715 -1.72846122711351 0.0846475686917748 . df.mm.trans1:exp4 0.068830036683353 0.0868065225753715 0.792913189485155 0.428280378143391 df.mm.trans2:exp4 -0.0314122630725780 0.0868065225753715 -0.361865239392623 0.717636473606572 df.mm.trans1:exp5 0.0034495107002155 0.0868065225753715 0.039737920583334 0.96832113281113 df.mm.trans2:exp5 -0.0338550704829067 0.0868065225753715 -0.390006067268866 0.696731666127079 df.mm.trans1:exp6 0.0121235742612486 0.0868065225753715 0.139662019645149 0.888994626768305 df.mm.trans2:exp6 0.0158592212974723 0.0868065225753715 0.182696194098804 0.855125402877825 df.mm.trans1:exp7 -0.0427990323115785 0.0868065225753715 -0.493039359737252 0.622244926505494 df.mm.trans2:exp7 -0.2488984221132 0.0868065225753715 -2.86727788107269 0.00435066613629045 ** df.mm.trans1:exp8 -0.0878865592024676 0.0868065225753715 -1.01244188334072 0.311915315714883 df.mm.trans2:exp8 -0.0468101395111216 0.0868065225753715 -0.539246799921949 0.590005053059865 df.mm.trans1:probe2 -0.0854913173153415 0.0551645823517433 -1.54975010542502 0.121961906961763 df.mm.trans1:probe3 0.277077752583038 0.0551645823517433 5.02274721879195 7.57375528248871e-07 *** df.mm.trans1:probe4 -0.099252792518523 0.0551645823517433 -1.79921225335600 0.0727097075724318 . df.mm.trans1:probe5 0.569524789970368 0.0551645823517433 10.3241022716158 2.12717334800848e-22 *** df.mm.trans1:probe6 0.174157868050354 0.0551645823517433 3.15705948682579 0.00170972129552287 ** df.mm.trans2:probe2 -0.0815884652418055 0.0551645823517433 -1.4790008691007 0.139896882504844 df.mm.trans2:probe3 0.180432854251362 0.0551645823517433 3.27080975798704 0.00116170035327071 ** df.mm.trans2:probe4 -0.320101716433571 0.0551645823517433 -5.80266726923666 1.29489188932521e-08 *** df.mm.trans2:probe5 0.430964470778411 0.0551645823517433 7.81233995447428 4.62611032825984e-14 *** df.mm.trans2:probe6 0.0266346069679865 0.0551645823517433 0.482820785230594 0.629476969523534 df.mm.trans3:probe2 -0.290310792186411 0.0551645823517433 -5.26263011175026 2.27948097083875e-07 *** df.mm.trans3:probe3 0.441523773688978 0.0551645823517433 8.00375449004057 1.21593500943135e-14 *** df.mm.trans3:probe4 0.0227198914110870 0.0551645823517433 0.411856492744188 0.680656738227373 df.mm.trans3:probe5 0.168321985134413 0.0551645823517433 3.05126909257011 0.00242471857496801 ** df.mm.trans3:probe6 -0.292147264359616 0.0551645823517433 -5.29592089534569 1.92265752137407e-07 *** df.mm.trans3:probe7 0.592785010026697 0.0551645823517433 10.7457536113833 6.18861729929971e-24 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.3713806674765 0.183118812804455 23.8718272608316 5.85952796504927e-80 *** df.mm.trans1 0.0271211472275246 0.148528970244584 0.182598365711847 0.855202118321152 df.mm.trans2 0.0363723331606099 0.148528970244584 0.244883763084840 0.80666718240076 df.mm.exp2 0.112633385622797 0.200847825844248 0.56078966824436 0.575242843462634 df.mm.exp3 -0.0152251109651943 0.200847825844248 -0.0758042109801128 0.939611306807178 df.mm.exp4 -0.290600339522484 0.200847825844248 -1.44686823619309 0.148686908179367 df.mm.exp5 -0.142631667590359 0.200847825844248 -0.710147929114083 0.478010297166413 df.mm.exp6 -0.138164108422449 0.200847825844248 -0.687904426357052 0.491896347538783 df.mm.exp7 0.0899231862812946 0.200847825844248 0.447717996962673 0.654589784006552 df.mm.exp8 -0.171216440550526 0.200847825844248 -0.852468478714327 0.394444638913454 df.mm.trans1:exp2 -0.0367783078912455 0.161928694014171 -0.227126564041991 0.820436902358787 df.mm.trans2:exp2 0.0291539454652607 0.161928694014171 0.180041873633028 0.857207363029095 df.mm.trans1:exp3 0.0828766478438628 0.161928694014171 0.511809524237934 0.609055900241741 df.mm.trans2:exp3 -0.0518957233621318 0.161928694014171 -0.320485036194946 0.748761592400629 df.mm.trans1:exp4 0.331206719613224 0.161928694014171 2.04538622156885 0.0414453535947034 * df.mm.trans2:exp4 0.189769572649552 0.161928694014171 1.17193295360577 0.241894707269392 df.mm.trans1:exp5 0.110609725053084 0.161928694014171 0.683076743911762 0.494938584730084 df.mm.trans2:exp5 0.164435761158477 0.161928694014171 1.01548253791318 0.310466102465749 df.mm.trans1:exp6 -0.0191823706394753 0.161928694014171 -0.118461837515942 0.905758910565123 df.mm.trans2:exp6 0.0784791423603375 0.161928694014171 0.484652475202879 0.628177965596991 df.mm.trans1:exp7 -0.0448603665721786 0.161928694014171 -0.277037784101765 0.781888699150658 df.mm.trans2:exp7 -0.000517766938084689 0.161928694014171 -0.00319749962313275 0.997450301504604 df.mm.trans1:exp8 0.211657290859153 0.161928694014171 1.30710182125368 0.191900161808064 df.mm.trans2:exp8 0.0321474949132147 0.161928694014171 0.198528711102934 0.842728408724365 df.mm.trans1:probe2 0.101585371203894 0.102903889143802 0.987186898854085 0.324124841588395 df.mm.trans1:probe3 -0.0231126586415122 0.102903889143802 -0.224604325782223 0.822397377360566 df.mm.trans1:probe4 0.0532350931437306 0.102903889143802 0.517328291347062 0.605201965532978 df.mm.trans1:probe5 0.272709672856512 0.102903889143802 2.65013961207449 0.00835265114542161 ** df.mm.trans1:probe6 0.0505876192991448 0.102903889143802 0.491600654941735 0.623260959113153 df.mm.trans2:probe2 0.0614404785910938 0.102903889143802 0.597066632780365 0.550787710252152 df.mm.trans2:probe3 0.0552417702362104 0.102903889143802 0.536828789425183 0.591672865402596 df.mm.trans2:probe4 0.103807924925568 0.102903889143802 1.00878524406889 0.313664032231331 df.mm.trans2:probe5 0.021244827068778 0.102903889143802 0.206453101486666 0.836538000627232 df.mm.trans2:probe6 0.0644131640992168 0.102903889143802 0.625954612941823 0.53168799021971 df.mm.trans3:probe2 -0.126564197087733 0.102903889143802 -1.22992627529235 0.219419812500309 df.mm.trans3:probe3 -0.0357520809582662 0.102903889143802 -0.347431775958485 0.72844267338609 df.mm.trans3:probe4 -0.140143500920301 0.102903889143802 -1.36188731141598 0.173970473178976 df.mm.trans3:probe5 -0.127077886559736 0.102903889143802 -1.23491820976905 0.217557981835198 df.mm.trans3:probe6 -0.035568802539094 0.102903889143802 -0.34565071189281 0.729779953084414 df.mm.trans3:probe7 -0.21273488774948 0.102903889143802 -2.06731630378125 0.0393222958532895 *