chr11.4239_chr11_4750240_4751130_+_2.R fitVsDatCorrelation=0.911147288968744 cont.fitVsDatCorrelation=0.249820109593189 fstatistic=9829.30615793164,52,692 cont.fstatistic=1769.32703512504,52,692 residuals=-0.633036809906704,-0.106296016985712,-0.000826968107150163,0.0993648488806371,0.972580996074527 cont.residuals=-0.819632150440526,-0.294319662908523,-0.0366263983232974,0.225712513176385,1.43534061866867 predictedValues: Include Exclude Both chr11.4239_chr11_4750240_4751130_+_2.R.tl.Lung 71.9366456299375 103.665668857239 66.7236069987123 chr11.4239_chr11_4750240_4751130_+_2.R.tl.cerebhem 63.0755038099208 74.6098367890533 75.977583587201 chr11.4239_chr11_4750240_4751130_+_2.R.tl.cortex 89.0506193238889 74.2331919558741 93.5561938167549 chr11.4239_chr11_4750240_4751130_+_2.R.tl.heart 67.3058624801823 79.7012614430258 68.968904823286 chr11.4239_chr11_4750240_4751130_+_2.R.tl.kidney 107.643928073964 108.829513071942 113.437412304387 chr11.4239_chr11_4750240_4751130_+_2.R.tl.liver 114.999963775004 102.768843456952 130.595517025279 chr11.4239_chr11_4750240_4751130_+_2.R.tl.stomach 69.0480493340303 79.3903214760291 67.4986547332252 chr11.4239_chr11_4750240_4751130_+_2.R.tl.testicle 68.7303108326392 84.297777015432 78.217914992821 diffExp=-31.7290232273014,-11.5343329791325,14.8174273680148,-12.3953989628435,-1.18558499797795,12.2311203180519,-10.3422721419988,-15.5674661827928 diffExpScore=1.93636537066917 diffExp1.5=0,0,0,0,0,0,0,0 diffExp1.5Score=0 diffExp1.4=-1,0,0,0,0,0,0,0 diffExp1.4Score=0.5 diffExp1.3=-1,0,0,0,0,0,0,0 diffExp1.3Score=0.5 diffExp1.2=-1,0,0,0,0,0,0,-1 diffExp1.2Score=0.666666666666667 cont.predictedValues: Include Exclude Both Lung 87.5399087758224 83.642266926122 89.747375056379 cerebhem 90.8171665673192 83.9698497138666 85.4653392280329 cortex 87.6804323539406 81.9373475464806 92.4729445351655 heart 79.2452467021595 96.1575123624091 85.4301283996934 kidney 85.5468273572153 75.570828151531 92.8780548152981 liver 95.0808578103594 78.9807434946061 78.8742057079135 stomach 79.0945965071428 87.809162911747 81.1717501864106 testicle 87.9272862487285 80.8512629248138 84.9573344482706 cont.diffExp=3.89764184970048,6.84731685345258,5.74308480746002,-16.9122656602496,9.97599920568436,16.1001143157534,-8.71456640460428,7.07602332391474 cont.diffExpScore=3.00907385707995 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,-1,0,1,0,0 cont.diffExp1.2Score=2 tran.correlation=0.652416515614921 cont.tran.correlation=-0.671611127068542 tran.covariance=0.0230647257120624 cont.tran.covariance=-0.00307389939926093 tran.mean=84.9554560828196 cont.tran.mean=85.1157060221415 weightedLogRatios: wLogRatio Lung -1.62906197183781 cerebhem -0.710100588372597 cortex 0.800445665938453 heart -0.725809983866728 kidney -0.0513106647075929 liver 0.527243160964087 stomach -0.600808074002822 testicle -0.88449930741979 cont.weightedLogRatios: wLogRatio Lung 0.202647978529955 cerebhem 0.350378447691427 cortex 0.300770977359102 heart -0.864535860312481 kidney 0.54396814417401 liver 0.827799948030093 stomach -0.462287784945022 testicle 0.372055091383311 varWeightedLogRatios=0.629960365390485 cont.varWeightedLogRatios=0.304734309845569 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.93594182236411 0.0799512710453917 61.7368774482869 1.16984710770281e-283 *** df.mm.trans1 -0.76000248856046 0.0669209838789561 -11.3567142099273 1.58090940550675e-27 *** df.mm.trans2 -0.267289016896491 0.0614275054001824 -4.35129206623613 1.55743944384768e-05 *** df.mm.exp2 -0.590231492874209 0.079513977313596 -7.42299043281898 3.37144185917196e-13 *** df.mm.exp3 -0.458543903384286 0.079513977313596 -5.76683394387165 1.21759210682579e-08 *** df.mm.exp4 -0.362520982531803 0.079513977313596 -4.55921078003749 6.07136746145188e-06 *** df.mm.exp5 -0.0790378658283983 0.079513977313596 -0.994012229028363 0.320564357475771 df.mm.exp6 -0.211088838850083 0.079513977313596 -2.65473877652438 0.00811947349848514 ** df.mm.exp7 -0.319326563164581 0.079513977313596 -4.0159802584794 6.56755155430639e-05 *** df.mm.exp8 -0.411350900740301 0.079513977313596 -5.17331561868638 3.01555538206341e-07 *** df.mm.trans1:exp2 0.458778164992212 0.068635719042514 6.68424795998768 4.78076898344759e-11 *** df.mm.trans2:exp2 0.261332853540701 0.0556709194170418 4.6942435346362 3.22684291156736e-06 *** df.mm.trans1:exp3 0.671963058032777 0.068635719042514 9.79028219426904 2.76736002549793e-21 *** df.mm.trans2:exp3 0.124584286183189 0.0556709194170418 2.23787010323834 0.0255469269393253 * df.mm.trans1:exp4 0.295982515198422 0.068635719042514 4.31236853532614 1.84999081612026e-05 *** df.mm.trans2:exp4 0.0996353972997844 0.0556709194170418 1.78972070774323 0.0739359733673341 . df.mm.trans1:exp5 0.482080873867615 0.068635719042514 7.02376081423445 5.17421506008611e-12 *** df.mm.trans2:exp5 0.127649425024872 0.0556709194170418 2.29292827137674 0.0221512217842003 * df.mm.trans1:exp6 0.680234842362126 0.068635719042514 9.91079938917489 9.6680470843226e-22 *** df.mm.trans2:exp6 0.202400068427360 0.0556709194170418 3.63565162111195 0.000297849999832435 *** df.mm.trans1:exp7 0.2783433827194 0.068635719042514 4.05537213862348 5.5746224619747e-05 *** df.mm.trans2:exp7 0.0525320299264094 0.0556709194170418 0.943617071111789 0.345694690766338 df.mm.trans1:exp8 0.365755398530062 0.068635719042514 5.32893664745478 1.33810240167337e-07 *** df.mm.trans2:exp8 0.204535397183244 0.0556709194170418 3.67400789002655 0.000257222419914826 *** df.mm.trans1:probe2 -0.0452026918548905 0.0491672247499921 -0.919366347902274 0.358224335998514 df.mm.trans1:probe3 -0.0408228139426465 0.0491672247499921 -0.830285096428045 0.4066639610285 df.mm.trans1:probe4 -0.00211787470713187 0.0491672247499921 -0.0430749288352342 0.965654230368578 df.mm.trans1:probe5 0.00376186253394987 0.0491672247499921 0.0765115898462517 0.939034208596302 df.mm.trans1:probe6 -0.0588384918321739 0.049167224749992 -1.19670150453598 0.231832743075222 df.mm.trans1:probe7 0.534948476820991 0.0491672247499921 10.8801845038259 1.46744198323319e-25 *** df.mm.trans1:probe8 0.246140060974309 0.0491672247499921 5.00618170388698 7.05163233885096e-07 *** df.mm.trans1:probe9 0.561647304314827 0.0491672247499921 11.4232053399540 8.31440164233948e-28 *** df.mm.trans1:probe10 0.370506507002444 0.0491672247499921 7.53564003025214 1.52558301171692e-13 *** df.mm.trans1:probe11 0.502770142509249 0.0491672247499921 10.2257173364118 5.92530320202961e-23 *** df.mm.trans1:probe12 0.423369419369532 0.0491672247499921 8.61080570486338 4.87648441839398e-17 *** df.mm.trans2:probe2 -0.206206920661564 0.0491672247499921 -4.19399145894639 3.09720630625875e-05 *** df.mm.trans2:probe3 0.116751666793844 0.0491672247499921 2.37458321854668 0.0178405057522363 * df.mm.trans2:probe4 -0.308279688748491 0.0491672247499921 -6.27002419428892 6.35399595968309e-10 *** df.mm.trans2:probe5 0.00940792204493862 0.0491672247499921 0.191345395083340 0.848311125672581 df.mm.trans2:probe6 -0.133827315737553 0.0491672247499921 -2.72188061087533 0.0066544888908642 ** df.mm.trans3:probe2 0.287953412969907 0.0491672247499921 5.85661310830755 7.30123685876067e-09 *** df.mm.trans3:probe3 0.122506660316304 0.0491672247499921 2.49163260564800 0.0129488161099148 * df.mm.trans3:probe4 -0.0288750190658358 0.0491672247499921 -0.587281857226249 0.557205986526661 df.mm.trans3:probe5 0.280579610203916 0.0491672247499921 5.70663916116114 1.70912092326646e-08 *** df.mm.trans3:probe6 -0.133527545303085 0.0491672247499921 -2.71578365429516 0.00677693445584506 ** df.mm.trans3:probe7 0.500621072073379 0.0491672247499921 10.1820079253804 8.76311690483875e-23 *** df.mm.trans3:probe8 1.32648600019262 0.0491672247499921 26.9790700398 4.21609243556092e-110 *** df.mm.trans3:probe9 0.294899387368759 0.0491672247499921 5.99788556031539 3.22089560045573e-09 *** df.mm.trans3:probe10 0.179612915339003 0.0491672247499921 3.6531025749838 0.000278670852268771 *** df.mm.trans3:probe11 -0.101049671484838 0.0491672247499921 -2.05522422708747 0.0402321502122261 * df.mm.trans3:probe12 0.557046556615843 0.0491672247499921 11.3296318726213 2.05240733379315e-27 *** df.mm.trans3:probe13 0.508557139147497 0.0491672247499921 10.3434176269544 2.05342964383443e-23 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.36911458450203 0.187866530342721 23.2564820169487 7.58422988998692e-89 *** df.mm.trans1 0.107654196717640 0.157248445009997 0.684612154420958 0.493817917642733 df.mm.trans2 0.0583609840408215 0.144340073100141 0.404329738702096 0.686095193496586 df.mm.exp2 0.089550237094039 0.186838993756262 0.479290940791838 0.631883092187369 df.mm.exp3 -0.0489074426610713 0.186838993756262 -0.261762502986250 0.793582443277596 df.mm.exp4 0.0891912153854804 0.186838993756262 0.477369384154539 0.633249843485947 df.mm.exp5 -0.158798129656073 0.186838993756262 -0.849919636493178 0.395663720961997 df.mm.exp6 0.154432495826844 0.186838993756262 0.826553883223686 0.408774863619936 df.mm.exp7 0.0475981465335452 0.186838993756262 0.254754885886609 0.798988110125255 df.mm.exp8 0.0253272163849327 0.186838993756262 0.135556373301673 0.892211417470292 df.mm.trans1:exp2 -0.0527966999213273 0.161277666077057 -0.327365227967161 0.743490669287527 df.mm.trans2:exp2 -0.0856414122261981 0.130813460938363 -0.654683482967785 0.512889099252287 df.mm.trans1:exp3 0.0505114072160908 0.161277666077057 0.313195301275981 0.754226659907104 df.mm.trans2:exp3 0.0283133660096582 0.130813460938363 0.216440768454241 0.828707979147559 df.mm.trans1:exp4 -0.188738572625080 0.161277666077057 -1.17027098181656 0.242294805067016 df.mm.trans2:exp4 0.0502474077253156 0.130813460938363 0.384114963130523 0.701011240363518 df.mm.trans1:exp5 0.135767254384167 0.161277666077057 0.84182303530669 0.400177839432492 df.mm.trans2:exp5 0.0573194897964961 0.130813460938363 0.438177305189592 0.661394505120868 df.mm.trans1:exp6 -0.0717996210668384 0.161277666077057 -0.445192585020008 0.656319810542309 df.mm.trans2:exp6 -0.211777403871498 0.130813460938363 -1.61892669418236 0.105918674990651 df.mm.trans1:exp7 -0.149048375942537 0.161277666077057 -0.924172450953767 0.355718677791421 df.mm.trans2:exp7 0.00101873227771242 0.130813460938363 0.00778767162343047 0.993788644336073 df.mm.trans1:exp8 -0.0209118257792935 0.161277666077057 -0.129663494567822 0.896870345049539 df.mm.trans2:exp8 -0.0592649874586223 0.130813460938363 -0.453049609982774 0.650655034009435 df.mm.trans1:probe2 -0.0909035618064599 0.115531320510434 -0.786830457791312 0.431650499557402 df.mm.trans1:probe3 -0.115694716322639 0.115531320510434 -1.00141429883673 0.316976590243586 df.mm.trans1:probe4 0.128103483919128 0.115531320510434 1.10882039046336 0.267892879549408 df.mm.trans1:probe5 -0.0279064359859909 0.115531320510434 -0.241548662844812 0.809201462665274 df.mm.trans1:probe6 -0.129533652367665 0.115531320510434 -1.12119944440492 0.262591900769009 df.mm.trans1:probe7 0.0983589108840584 0.115531320510434 0.851361435578631 0.394863117203729 df.mm.trans1:probe8 -0.0740565242822929 0.115531320510434 -0.641008204139797 0.521729577113879 df.mm.trans1:probe9 0.121804089207573 0.115531320510434 1.05429496234808 0.292115858557088 df.mm.trans1:probe10 -0.0204890478211142 0.115531320510434 -0.177346261867263 0.859288311062542 df.mm.trans1:probe11 0.115435448216668 0.115531320510434 0.99917016188041 0.318061519760865 df.mm.trans1:probe12 -0.121967782219143 0.115531320510434 -1.05571183364192 0.291468318136711 df.mm.trans2:probe2 0.0312571964257614 0.115531320510434 0.270551710892444 0.786816512735543 df.mm.trans2:probe3 0.0472025889554799 0.115531320510434 0.408569630702150 0.682981921127902 df.mm.trans2:probe4 -0.0157485379355676 0.115531320510434 -0.136314013083103 0.891612692115823 df.mm.trans2:probe5 -0.0394837380508137 0.115531320510434 -0.341757870301912 0.732636874445211 df.mm.trans2:probe6 -0.0408327379514505 0.115531320510434 -0.353434356770488 0.723870476951471 df.mm.trans3:probe2 -0.0290470054947471 0.115531320510434 -0.251421046400345 0.80156324014033 df.mm.trans3:probe3 -0.109709863021389 0.115531320510434 -0.94961143468866 0.342641246030721 df.mm.trans3:probe4 -0.120548636647731 0.115531320510434 -1.04342818999323 0.297114393324966 df.mm.trans3:probe5 0.070831482297389 0.115531320510434 0.613093332478543 0.540016071331567 df.mm.trans3:probe6 -0.0369781190713791 0.115531320510434 -0.320070080632718 0.749011820893393 df.mm.trans3:probe7 0.0461988684529359 0.115531320510434 0.399881765817464 0.689367003196852 df.mm.trans3:probe8 -0.045955014328627 0.115531320510434 -0.39777104706837 0.690921634976627 df.mm.trans3:probe9 0.076222981033143 0.115531320510434 0.659760320373545 0.509627165028258 df.mm.trans3:probe10 -0.134076884510448 0.115531320510434 -1.16052412383133 0.246235681774653 df.mm.trans3:probe11 -0.129476906409526 0.115531320510434 -1.12070827060124 0.262800839130028 df.mm.trans3:probe12 -0.114390660258911 0.115531320510434 -0.99012683100579 0.322458205618378 df.mm.trans3:probe13 0.0312269451267480 0.115531320510434 0.270289865889031 0.787017850820047