chr19.11866_chr19_5339644_5340095_+_1.R fitVsDatCorrelation=0.849154949695127 cont.fitVsDatCorrelation=0.266482789428867 fstatistic=7825.86724389374,42,462 cont.fstatistic=2342.08306264694,42,462 residuals=-0.622910800100088,-0.0934549719518926,0.000163950690153361,0.090255764003223,0.778378441409768 cont.residuals=-0.589941986358213,-0.219934610457618,-0.0304349880122881,0.189683774478467,0.967852354734276 predictedValues: Include Exclude Both chr19.11866_chr19_5339644_5340095_+_1.R.tl.Lung 59.414011634853 76.3602634469443 80.6791078805822 chr19.11866_chr19_5339644_5340095_+_1.R.tl.cerebhem 52.8863453949514 89.5250804621207 88.3241193096605 chr19.11866_chr19_5339644_5340095_+_1.R.tl.cortex 54.291467724325 68.3933702247306 78.1434391683444 chr19.11866_chr19_5339644_5340095_+_1.R.tl.heart 64.6649683599317 79.0943534276687 84.4398175369123 chr19.11866_chr19_5339644_5340095_+_1.R.tl.kidney 63.5105136388104 71.1137739485612 77.032242561535 chr19.11866_chr19_5339644_5340095_+_1.R.tl.liver 65.9184055813764 76.1433026922929 83.8787145428888 chr19.11866_chr19_5339644_5340095_+_1.R.tl.stomach 56.5536661935744 77.3518641894165 71.4418794035711 chr19.11866_chr19_5339644_5340095_+_1.R.tl.testicle 61.4654568213617 78.1288581614907 79.2859732004846 diffExp=-16.9462518120913,-36.6387350671693,-14.1019025004057,-14.4293850677370,-7.60326030975081,-10.2248971109165,-20.7981979958422,-16.663401340129 diffExpScore=0.992774881330671 diffExp1.5=0,-1,0,0,0,0,0,0 diffExp1.5Score=0.5 diffExp1.4=0,-1,0,0,0,0,0,0 diffExp1.4Score=0.5 diffExp1.3=0,-1,0,0,0,0,-1,0 diffExp1.3Score=0.666666666666667 diffExp1.2=-1,-1,-1,-1,0,0,-1,-1 diffExp1.2Score=0.857142857142857 cont.predictedValues: Include Exclude Both Lung 82.1867841269623 78.638865947875 70.5550040499464 cerebhem 70.1202901579857 75.6287733017682 76.653498127564 cortex 72.5994195763175 83.3499672719439 78.5139523365563 heart 75.8494069374386 78.4980547272129 73.526740994684 kidney 76.6042211741403 71.815756745372 72.4743429743144 liver 71.7506673391921 84.016916791451 79.7405492858698 stomach 81.2709723279053 84.274591893381 80.9730350968237 testicle 68.5693174321411 74.7333151655622 79.6988317501416 cont.diffExp=3.54791817908736,-5.50848314378257,-10.7505476956263,-2.64864778977424,4.78846442876831,-12.2662494522588,-3.00361956547563,-6.16399773342117 cont.diffExpScore=1.47485798884706 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=-0.258682774268456 cont.tran.correlation=0.216555143058528 tran.covariance=-0.00152707025738896 cont.tran.covariance=0.000861003655151424 tran.mean=68.4259813689006 cont.tran.mean=76.8692075572906 weightedLogRatios: wLogRatio Lung -1.05642431673358 cerebhem -2.22726158512285 cortex -0.948993992980324 heart -0.860057435793899 kidney -0.475793022105105 liver -0.61436417578045 stomach -1.31275838893260 testicle -1.01672916746449 cont.weightedLogRatios: wLogRatio Lung 0.193588465089410 cerebhem -0.324280189110767 cortex -0.601249829866081 heart -0.149168892250661 kidney 0.277969281465147 liver -0.686854041895656 stomach -0.160260935632463 testicle -0.367641297834327 varWeightedLogRatios=0.288618418605033 cont.varWeightedLogRatios=0.117596007293359 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.46156928942629 0.0858971356093381 40.2990072354633 2.47567703227172e-153 *** df.mm.trans1 0.563545566964345 0.0690099183463126 8.16615322070523 3.06405824563222e-15 *** df.mm.trans2 0.813640200673275 0.0690099183463126 11.7901921951303 3.12679046673169e-28 *** df.mm.exp2 -0.0478621011134093 0.0926589392220835 -0.516540568187319 0.605724067570553 df.mm.exp3 -0.168416003782176 0.0926589392220836 -1.81759045804010 0.0697743468772122 . df.mm.exp4 0.0743091543897092 0.0926589392220836 0.801964225077152 0.422985952931825 df.mm.exp5 0.0417495589466572 0.0926589392220836 0.450572381868009 0.652509148808414 df.mm.exp6 0.0621500657013774 0.0926589392220835 0.670740095053507 0.502721283423193 df.mm.exp7 0.0851575871832281 0.0926589392220835 0.919043406908898 0.358552439965815 df.mm.exp8 0.0742607222819227 0.0926589392220835 0.801441532844831 0.423288073089719 df.mm.trans1:exp2 -0.0685227990802204 0.0732533233792236 -0.935422393404408 0.350059334939449 df.mm.trans2:exp2 0.206918466848213 0.0732533233792236 2.82469732843411 0.00493732332532957 ** df.mm.trans1:exp3 0.0782530015663242 0.0732533233792236 1.06825189570196 0.285964749975219 df.mm.trans2:exp3 0.0582294482576298 0.0732533233792236 0.794905208002414 0.427076807343109 df.mm.trans1:exp4 0.0103803685248807 0.0732533233792236 0.141705086486558 0.88737472711625 df.mm.trans2:exp4 -0.0391301163185626 0.0732533233792236 -0.53417530445671 0.593477191781432 df.mm.trans1:exp5 0.0249258177015785 0.0732533233792236 0.340268762586245 0.733808795716505 df.mm.trans2:exp5 -0.112930963394952 0.0732533233792236 -1.54164969158221 0.123843378502026 df.mm.trans1:exp6 0.0417375477711205 0.0732533233792236 0.569770023334645 0.569110629165626 df.mm.trans2:exp6 -0.0649953880307831 0.0732533233792236 -0.887268795905816 0.375395852647324 df.mm.trans1:exp7 -0.134497640373747 0.0732533233792236 -1.83606195827415 0.0669909232365834 . df.mm.trans2:exp7 -0.072255358667404 0.0732533233792236 -0.986376526473028 0.324464665674778 df.mm.trans1:exp8 -0.0403154676313795 0.0732533233792236 -0.550356840776646 0.58234063532272 df.mm.trans2:exp8 -0.0513636798939941 0.0732533233792236 -0.701178834277465 0.483544433404125 df.mm.trans1:probe2 0.265134286100228 0.0491398231961156 5.39550753046232 1.0936329621535e-07 *** df.mm.trans1:probe3 -0.113076705666063 0.0491398231961156 -2.30112154076700 0.0218290985659719 * df.mm.trans1:probe4 0.693448856062963 0.0491398231961156 14.1117491061258 7.4489764833234e-38 *** df.mm.trans1:probe5 0.0405015330474952 0.0491398231961156 0.824209987200295 0.410245552155007 df.mm.trans1:probe6 0.00522045450302465 0.0491398231961156 0.106236737608721 0.91544063583264 df.mm.trans2:probe2 0.0176209553312343 0.0491398231961156 0.358588089763969 0.72006705877191 df.mm.trans2:probe3 0.417211235019013 0.0491398231961156 8.49028767063194 2.83636876397864e-16 *** df.mm.trans2:probe4 0.351627397394886 0.0491398231961156 7.15565043837362 3.29031754162382e-12 *** df.mm.trans2:probe5 -0.0327362009557454 0.0491398231961156 -0.666184752539629 0.505625522373443 df.mm.trans2:probe6 0.150070995462265 0.0491398231961156 3.05395879963459 0.00238889233672796 ** df.mm.trans3:probe2 -0.232003396520480 0.0491398231961156 -4.72129082749365 3.11223884776247e-06 *** df.mm.trans3:probe3 -0.689343244684625 0.0491398231961156 -14.0281995304191 1.70320510225675e-37 *** df.mm.trans3:probe4 -0.360131054792726 0.0491398231961156 -7.3287006620975 1.04590504777971e-12 *** df.mm.trans3:probe5 -0.67871333563833 0.0491398231961156 -13.8118798866981 1.43637957915718e-36 *** df.mm.trans3:probe6 -0.315913391883697 0.0491398231961156 -6.42886708450082 3.21001167866978e-10 *** df.mm.trans3:probe7 -0.727228738497736 0.0491398231961156 -14.7991728744197 7.70548704158998e-41 *** df.mm.trans3:probe8 -0.623519840019218 0.0491398231961156 -12.6886870864547 7.3396709779255e-32 *** df.mm.trans3:probe9 -0.40762561184997 0.0491398231961156 -8.29521934222571 1.19727271676414e-15 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.57072834506352 0.156758571713248 29.1577570215718 8.69629648042762e-107 *** df.mm.trans1 -0.178362447937595 0.125940127773478 -1.41624795123605 0.157376773744857 df.mm.trans2 -0.190956641688248 0.125940127773478 -1.51624938821495 0.130140199139477 df.mm.exp2 -0.280714195988562 0.169098571982409 -1.66006248720873 0.097580420743507 . df.mm.exp3 -0.172739164356213 0.169098571982409 -1.02152940933282 0.30753828654904 df.mm.exp4 -0.123293394405243 0.169098571982409 -0.729121440588326 0.466296838443388 df.mm.exp5 -0.187944484131646 0.169098571982409 -1.11144926848464 0.266953074251077 df.mm.exp6 -0.192030868068355 0.169098571982409 -1.13561496006206 0.256706513208427 df.mm.exp7 -0.0797148339091797 0.169098571982409 -0.471410449979862 0.63757018629999 df.mm.exp8 -0.353951743914870 0.169098571982409 -2.09316814308574 0.0368789097319921 * df.mm.trans1:exp2 0.1219318819615 0.133684159136587 0.912089231431831 0.362197424132402 df.mm.trans2:exp2 0.241684951064596 0.133684159136587 1.80788025017731 0.0712753312576395 . df.mm.trans1:exp3 0.0487015792465763 0.133684159136587 0.364303291886792 0.715798217722606 df.mm.trans2:exp3 0.230921325965119 0.133684159136587 1.72736491336407 0.0847704768239903 . df.mm.trans1:exp4 0.0430487691905826 0.133684159136587 0.322018476000580 0.747584351907888 df.mm.trans2:exp4 0.121501183411826 0.133684159136587 0.908867469388704 0.363893955046750 df.mm.trans1:exp5 0.117602153980022 0.133684159136587 0.879701489986305 0.379478380631215 df.mm.trans2:exp5 0.09718233445796 0.133684159136587 0.726954749804481 0.467621858130569 df.mm.trans1:exp6 0.0562335114676304 0.133684159136587 0.420644538820609 0.674210256840172 df.mm.trans2:exp6 0.258182982080088 0.133684159136587 1.93129076584383 0.0540584727346307 . df.mm.trans1:exp7 0.0685092306785127 0.133684159136587 0.512470820185329 0.608566447030554 df.mm.trans2:exp7 0.148929197529384 0.133684159136587 1.11403773260242 0.265842226874603 df.mm.trans1:exp8 0.172802398747743 0.133684159136587 1.29261686548208 0.196789686748040 df.mm.trans2:exp8 0.303011667853805 0.133684159136587 2.26662358360809 0.0238747901399225 * df.mm.trans1:probe2 0.0300865616762709 0.0896780602032923 0.335495232703153 0.737403832126969 df.mm.trans1:probe3 0.112479126546547 0.0896780602032923 1.25425467825204 0.210383659975960 df.mm.trans1:probe4 0.0818109599255439 0.0896780602032923 0.912273969130082 0.362100295000294 df.mm.trans1:probe5 0.0704112014548934 0.0896780602032923 0.785155268694231 0.432764978592387 df.mm.trans1:probe6 -0.0453586251141058 0.0896780602032923 -0.505794003698137 0.613242504944336 df.mm.trans2:probe2 -0.0239384126957634 0.0896780602032923 -0.266937226803268 0.789636602007956 df.mm.trans2:probe3 -0.120911957812053 0.0896780602032923 -1.34828917505526 0.178226019715187 df.mm.trans2:probe4 0.0181283883885865 0.0896780602032923 0.202149648949710 0.839888718405706 df.mm.trans2:probe5 -0.109743576832636 0.0896780602032923 -1.22375056489689 0.221670077235201 df.mm.trans2:probe6 0.0128808322680207 0.0896780602032923 0.143634153535670 0.885851997160533 df.mm.trans3:probe2 0.0828572554270415 0.0896780602032923 0.923941209691773 0.355999229468899 df.mm.trans3:probe3 -0.000926536647878236 0.0896780602032923 -0.0103318096508539 0.991761015100223 df.mm.trans3:probe4 -0.00963285896282342 0.0896780602032923 -0.107416004995944 0.914505587786396 df.mm.trans3:probe5 0.177941067365916 0.0896780602032923 1.98422074432185 0.0478224903952265 * df.mm.trans3:probe6 0.135761325396963 0.0896780602032923 1.51387446482678 0.130741470074819 df.mm.trans3:probe7 0.0309802895268461 0.0896780602032923 0.345461191473326 0.72990491863639 df.mm.trans3:probe8 -0.0289489963346926 0.0896780602032923 -0.322810242204925 0.746984998453016 df.mm.trans3:probe9 0.106818599488471 0.0896780602032923 1.19113414414097 0.234212513184979