chr19.11824_chr19_4767942_4770615_+_2.R fitVsDatCorrelation=0.873322221813724 cont.fitVsDatCorrelation=0.197944984431993 fstatistic=9105.22409667535,60,876 cont.fstatistic=2237.86655741144,60,876 residuals=-0.723015875998561,-0.0977784092123488,-0.00257783993509194,0.0953391483394322,1.28436031856153 cont.residuals=-0.924855975922906,-0.270579437152171,-0.0422316998253996,0.263017022521772,1.39663197099607 predictedValues: Include Exclude Both chr19.11824_chr19_4767942_4770615_+_2.R.tl.Lung 78.2189459834483 82.4465149818215 67.32020659452 chr19.11824_chr19_4767942_4770615_+_2.R.tl.cerebhem 69.083654639524 62.40471710931 90.1976575751949 chr19.11824_chr19_4767942_4770615_+_2.R.tl.cortex 88.8169336296023 73.0907757594755 86.3060161440598 chr19.11824_chr19_4767942_4770615_+_2.R.tl.heart 89.722914502298 74.2378273607087 88.0583711331964 chr19.11824_chr19_4767942_4770615_+_2.R.tl.kidney 87.235599682374 90.7286059600352 76.1892283671644 chr19.11824_chr19_4767942_4770615_+_2.R.tl.liver 81.6697355673729 94.0506544023865 74.974199067364 chr19.11824_chr19_4767942_4770615_+_2.R.tl.stomach 77.4027872590497 73.9047486529554 78.8126590562225 chr19.11824_chr19_4767942_4770615_+_2.R.tl.testicle 88.380583252257 78.4615660896463 92.2574350313304 diffExp=-4.22756899837327,6.67893753021404,15.7261578701267,15.4850871415894,-3.49300627766125,-12.3809188350136,3.49803860609424,9.9190171626107 diffExpScore=2.21726695645179 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=0,0,1,1,0,0,0,0 diffExp1.2Score=0.666666666666667 cont.predictedValues: Include Exclude Both Lung 88.7089292755755 92.2897080182406 84.0141887763223 cerebhem 89.859972176363 90.9745815696159 90.6684312259696 cortex 84.5584861629782 91.2247099193303 85.5183480556597 heart 82.4470108365805 94.9155609425404 90.5258381311524 kidney 90.0845780574554 92.4403252255273 94.2721790553824 liver 86.6275261851098 87.2741837056352 86.244830219565 stomach 86.3686028761404 83.1387697374502 88.102969751509 testicle 87.0569178811093 81.2899947344972 83.8060266563997 cont.diffExp=-3.58077874266512,-1.11460939325298,-6.6662237563521,-12.4685501059599,-2.35574716807193,-0.646657520525395,3.22983313869025,5.76692314661219 cont.diffExpScore=1.90219174053849 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=0.385808873053099 cont.tran.correlation=-0.0738837125292278 tran.covariance=0.0054433881245369 cont.tran.covariance=-0.000128289282204403 tran.mean=80.6160353020166 cont.tran.mean=88.0787410815093 weightedLogRatios: wLogRatio Lung -0.230860862036939 cerebhem 0.425466533102247 cortex 0.855334282993387 heart 0.833969336826503 kidney -0.176209290955107 liver -0.631400501745738 stomach 0.200054302467271 testicle 0.526425453511538 cont.weightedLogRatios: wLogRatio Lung -0.178278007846992 cerebhem -0.0555284183669881 cortex -0.339602763025076 heart -0.631288959376657 kidney -0.116516956878182 liver -0.0332090641350567 stomach 0.169205602001926 testicle 0.303785741623533 varWeightedLogRatios=0.286004322685737 cont.varWeightedLogRatios=0.0838860168017528 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.54540213603269 0.0855589713533271 53.1259558657134 3.29242213247868e-276 *** df.mm.trans1 -0.416108070536365 0.0737299713519467 -5.64367600999182 2.24765875871627e-08 *** df.mm.trans2 -0.131445472218447 0.0649867038725235 -2.02265177929761 0.0434124486006190 * df.mm.exp2 -0.695245669848855 0.0832496073038809 -8.35133873137734 2.62108428798603e-16 *** df.mm.exp3 -0.241821045503613 0.0832496073038808 -2.90477100535632 0.00376766205885059 ** df.mm.exp4 -0.236201122299158 0.0832496073038809 -2.837264101883 0.00465522384734809 ** df.mm.exp5 0.081063870606655 0.0832496073038808 0.973744780690108 0.330452079531761 df.mm.exp6 0.0671717354806398 0.0832496073038808 0.806871499530886 0.419959529125815 df.mm.exp7 -0.277474993026205 0.0832496073038809 -3.33304867148928 0.00089500870495379 *** df.mm.exp8 -0.242522912128618 0.0832496073038808 -2.91320187545572 0.00366837670799373 ** df.mm.trans1:exp2 0.571051931969302 0.0767523455590304 7.44018867189022 2.39919707574514e-13 *** df.mm.trans2:exp2 0.416736757217018 0.0558455343094922 7.46231121914765 2.04914917949164e-13 *** df.mm.trans1:exp3 0.368886477138646 0.0767523455590304 4.80619158218343 1.80968140807518e-06 *** df.mm.trans2:exp3 0.121373437845701 0.0558455343094922 2.17337768089132 0.0300191715203396 * df.mm.trans1:exp4 0.373415421634721 0.0767523455590304 4.86519882767005 1.35555874447429e-06 *** df.mm.trans2:exp4 0.131325165421647 0.0558455343094922 2.35157863641974 0.0189145673979164 * df.mm.trans1:exp5 0.0280367360234846 0.0767523455590304 0.365288328575202 0.714984368641338 df.mm.trans2:exp5 0.0146590478981931 0.0558455343094921 0.262492750395290 0.793003290704985 df.mm.trans1:exp6 -0.0240001301444265 0.0767523455590304 -0.312695722451478 0.75458626977138 df.mm.trans2:exp6 0.0645119984180661 0.0558455343094922 1.15518634060416 0.248329124831920 df.mm.trans1:exp7 0.266985889861987 0.0767523455590304 3.47853720843811 0.000528998767384568 *** df.mm.trans2:exp7 0.168102296886128 0.0558455343094922 3.01012961850301 0.00268623796689372 ** df.mm.trans1:exp8 0.364663316968367 0.0767523455590304 4.75116837553719 2.36267132195596e-06 *** df.mm.trans2:exp8 0.192982033217714 0.0558455343094922 3.45563948136338 0.00057536866198036 *** df.mm.trans1:probe2 0.378445165816325 0.0534680283950444 7.0779712133803 2.99812307770012e-12 *** df.mm.trans1:probe3 0.0210298379646246 0.0534680283950444 0.393316129206173 0.694181709382656 df.mm.trans1:probe4 0.00126313298305086 0.0534680283950444 0.0236240800524437 0.981157844500561 df.mm.trans1:probe5 -0.0502290584234257 0.0534680283950444 -0.939422303966628 0.347772919055564 df.mm.trans1:probe6 -0.0338499755942566 0.0534680283950444 -0.633088157733415 0.526841307907672 df.mm.trans1:probe7 0.169004884981015 0.0534680283950444 3.16085874220639 0.00162710908899430 ** df.mm.trans1:probe8 -0.0756252651177641 0.0534680283950444 -1.41440160387087 0.157599339626063 df.mm.trans1:probe9 0.36501908943997 0.0534680283950444 6.82686645452969 1.62051414062061e-11 *** df.mm.trans1:probe10 0.633527866138429 0.0534680283950444 11.8487231557831 3.81347491377751e-30 *** df.mm.trans1:probe11 0.887985821132026 0.0534680283950444 16.6077906327724 4.67667635863953e-54 *** df.mm.trans1:probe12 0.843068246669166 0.0534680283950444 15.7677077680931 1.70894014034703e-49 *** df.mm.trans1:probe13 0.844901567790372 0.0534680283950444 15.8019959432183 1.11942945287403e-49 *** df.mm.trans1:probe14 0.707326734465147 0.0534680283950444 13.2289660886524 1.48321624775519e-36 *** df.mm.trans1:probe15 0.525150154907671 0.0534680283950444 9.82176023076144 1.13642315189479e-21 *** df.mm.trans1:probe16 0.660235791447673 0.0534680283950444 12.3482352214219 2.07719356602492e-32 *** df.mm.trans1:probe17 0.573981065736719 0.0534680283950444 10.7350333080529 2.42361458523131e-25 *** df.mm.trans1:probe18 0.345591986323881 0.0534680283950444 6.46352589944969 1.69640747604565e-10 *** df.mm.trans1:probe19 0.342537957562309 0.0534680283950444 6.4064071155101 2.42922310512771e-10 *** df.mm.trans1:probe20 0.105973204836101 0.0534680283950444 1.98199200563609 0.0477922902629458 * df.mm.trans1:probe21 0.381825971670736 0.0534680283950444 7.14120163267745 1.94425919842198e-12 *** df.mm.trans1:probe22 -0.0299758331669981 0.0534680283950444 -0.560630980172374 0.57519248408431 df.mm.trans2:probe2 0.396185600010658 0.0534680283950444 7.40976639504025 2.97833044929755e-13 *** df.mm.trans2:probe3 0.292866358620843 0.0534680283950444 5.47741084554348 5.64118533401876e-08 *** df.mm.trans2:probe4 -0.281469001349399 0.0534680283950444 -5.26424874449806 1.77166419149418e-07 *** df.mm.trans2:probe5 -0.0689011948890327 0.0534680283950444 -1.28864289477745 0.197862485674674 df.mm.trans2:probe6 -0.36939878977561 0.0534680283950444 -6.90877896312794 9.3994589542096e-12 *** df.mm.trans3:probe2 -0.3067264767366 0.0534680283950444 -5.73663338528914 1.32966480591035e-08 *** df.mm.trans3:probe3 0.71795788464688 0.0534680283950444 13.4277979981290 1.61813986327988e-37 *** df.mm.trans3:probe4 0.240169446324024 0.0534680283950444 4.49183284914772 8.00635381541257e-06 *** df.mm.trans3:probe5 0.580415672897226 0.0534680283950444 10.8553782572432 7.6261325792073e-26 *** df.mm.trans3:probe6 0.20083465538566 0.0534680283950444 3.75616347589645 0.000183944276867769 *** df.mm.trans3:probe7 0.325156420532045 0.0534680283950444 6.0813243033697 1.77837549430015e-09 *** df.mm.trans3:probe8 0.106711510964108 0.0534680283950444 1.99580037205932 0.0462648905113333 * df.mm.trans3:probe9 0.0920910118830226 0.0534680283950444 1.72235660538322 0.085357904560647 . df.mm.trans3:probe10 0.138558285346659 0.0534680283950444 2.59142312716174 0.00971703204521129 ** df.mm.trans3:probe11 0.232561882471683 0.0534680283950444 4.34955036593863 1.52459219061378e-05 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.64381775075055 0.172158951724504 26.974012702992 3.86024915415482e-117 *** df.mm.trans1 -0.143773906579049 0.148357026479553 -0.96910749689948 0.332759045595857 df.mm.trans2 -0.103246799665728 0.130764110855446 -0.789565263666746 0.429995358340501 df.mm.exp2 -0.0776839848595676 0.167512125241971 -0.46375141350128 0.642941065824882 df.mm.exp3 -0.0772691921663919 0.167512125241971 -0.461275218464196 0.644715670837916 df.mm.exp4 -0.119799339372179 0.167512125241971 -0.715168165881298 0.474695693634741 df.mm.exp5 -0.0981813147900251 0.167512125241971 -0.586114674673266 0.557949437732917 df.mm.exp6 -0.105825278885502 0.167512125241971 -0.631746977913616 0.527717048218967 df.mm.exp7 -0.178678371347517 0.167512125241971 -1.06665933041812 0.286419578564862 df.mm.exp8 -0.143227329266560 0.167512125241971 -0.8550266379802 0.392770182581324 df.mm.trans1:exp2 0.090576026349237 0.154438548580397 0.586485868857318 0.557700148915712 df.mm.trans2:exp2 0.0633314994171836 0.112370549728952 0.563595173023049 0.573173911959399 df.mm.trans1:exp3 0.0293520785298202 0.154438548580396 0.190056684678957 0.849308743372867 df.mm.trans2:exp3 0.0656623651160453 0.112370549728952 0.584337847188868 0.559143481615445 df.mm.trans1:exp4 0.0465945809453136 0.154438548580397 0.301703048711687 0.76295005139174 df.mm.trans2:exp4 0.147854374013017 0.112370549728952 1.31577512408416 0.188593764304747 df.mm.trans1:exp5 0.113569747500717 0.154438548580397 0.735371761420016 0.462309947204492 df.mm.trans2:exp5 0.0998119888933909 0.112370549728952 0.888239749063673 0.374655623608717 df.mm.trans1:exp6 0.0820823457613055 0.154438548580396 0.531488715193251 0.595214900902716 df.mm.trans2:exp6 0.0499473491731328 0.112370549728952 0.444487895570596 0.656799668066463 df.mm.trans1:exp7 0.151942035958037 0.154438548580396 0.98383491268658 0.32546833537401 df.mm.trans2:exp7 0.0742568780514018 0.112370549728952 0.660821525128394 0.508900519646335 df.mm.trans1:exp8 0.124428910006337 0.154438548580396 0.805685569762804 0.420642814566601 df.mm.trans2:exp8 0.0163176427203690 0.112370549728952 0.145212804954044 0.884576260445414 df.mm.trans1:probe2 0.0213714544314872 0.10758661042398 0.198644183948784 0.84258718065464 df.mm.trans1:probe3 -0.0395001947338345 0.107586610423980 -0.367147868848839 0.713597396344686 df.mm.trans1:probe4 -0.120045608110187 0.107586610423980 -1.11580435183438 0.264811875579489 df.mm.trans1:probe5 -0.0609760873472357 0.10758661042398 -0.566762788668029 0.571020539280197 df.mm.trans1:probe6 0.005312003787366 0.107586610423980 0.0493742089878316 0.960632336243378 df.mm.trans1:probe7 -0.0493728700721699 0.107586610423980 -0.458912776205144 0.646410645424763 df.mm.trans1:probe8 0.0263751005132656 0.107586610423980 0.245152258346331 0.806395958216678 df.mm.trans1:probe9 0.0146000383705314 0.107586610423980 0.135704975860799 0.892085691000368 df.mm.trans1:probe10 -0.0925913064135018 0.10758661042398 -0.860621094470917 0.389682246810016 df.mm.trans1:probe11 0.106413918356987 0.107586610423980 0.98910001846539 0.322887326488852 df.mm.trans1:probe12 0.00912538054372131 0.107586610423980 0.0848189240999395 0.932424728660048 df.mm.trans1:probe13 0.111712840064561 0.107586610423980 1.03835263165482 0.29939243267251 df.mm.trans1:probe14 -0.102327643371360 0.107586610423980 -0.951118758813059 0.341806432611451 df.mm.trans1:probe15 -0.085986193722428 0.107586610423980 -0.799227649087294 0.424375069527712 df.mm.trans1:probe16 0.00630171694892781 0.10758661042398 0.0585734314343937 0.953305231457762 df.mm.trans1:probe17 -0.123442430830368 0.107586610423980 -1.14737726510672 0.251538995629225 df.mm.trans1:probe18 0.0134813892839491 0.107586610423980 0.125307315016444 0.900309011845264 df.mm.trans1:probe19 -0.0754782685797087 0.107586610423980 -0.701558198387905 0.48314106191898 df.mm.trans1:probe20 -0.00122461536402773 0.107586610423980 -0.0113826001135433 0.990920786912806 df.mm.trans1:probe21 0.0569915273001218 0.107586610423980 0.529726952782769 0.596435482484108 df.mm.trans1:probe22 -0.105288775584758 0.107586610423980 -0.978641999871858 0.328027084857158 df.mm.trans2:probe2 -0.032528943483251 0.107586610423980 -0.302351225259911 0.762456105258764 df.mm.trans2:probe3 -0.00145569831777237 0.107586610423980 -0.0135304784864558 0.989207650332595 df.mm.trans2:probe4 -0.0169791175666551 0.10758661042398 -0.157818129038022 0.874636482966441 df.mm.trans2:probe5 -0.0344199289630982 0.107586610423980 -0.319927626936617 0.749099482285469 df.mm.trans2:probe6 -0.18046777809501 0.10758661042398 -1.67741856894476 0.0938173930553075 . df.mm.trans3:probe2 0.0572644274547435 0.107586610423980 0.532263515218803 0.59467846692305 df.mm.trans3:probe3 -0.0165889310653234 0.107586610423980 -0.154191409134923 0.87749433095461 df.mm.trans3:probe4 0.0496660523085489 0.107586610423980 0.461637857283761 0.644455652814469 df.mm.trans3:probe5 0.0440836709856716 0.107586610423980 0.40975053319317 0.68208913410436 df.mm.trans3:probe6 0.146359946203765 0.107586610423980 1.36039183339810 0.174055902164633 df.mm.trans3:probe7 0.0859922058675249 0.10758661042398 0.799283530995583 0.424342690493737 df.mm.trans3:probe8 0.0565230475659928 0.107586610423980 0.525372510047908 0.599457208647899 df.mm.trans3:probe9 0.0368799794351677 0.10758661042398 0.342793394919964 0.731836133655722 df.mm.trans3:probe10 -0.0516044104254967 0.107586610423980 -0.479654579897376 0.631592758659343 df.mm.trans3:probe11 -0.0325007934834905 0.10758661042398 -0.30208957560249 0.762655485018256