chr6.19632_chr6_42872202_42876376_-_1.R fitVsDatCorrelation=0.86364004476694 cont.fitVsDatCorrelation=0.324624119233451 fstatistic=4619.04368822165,39,393 cont.fstatistic=1304.87288084069,39,393 residuals=-0.765440183804652,-0.110547892751287,0.00473445222110461,0.097919143026802,0.649451901454377 cont.residuals=-0.76508383115323,-0.292577486423729,-0.062350999125831,0.225651164307048,1.38944478750269 predictedValues: Include Exclude Both chr6.19632_chr6_42872202_42876376_-_1.R.tl.Lung 115.263122361684 79.0886900187918 67.5077414289018 chr6.19632_chr6_42872202_42876376_-_1.R.tl.cerebhem 93.338226603927 78.1796146058671 89.6228150027974 chr6.19632_chr6_42872202_42876376_-_1.R.tl.cortex 170.929936336858 199.140149301045 175.758991161301 chr6.19632_chr6_42872202_42876376_-_1.R.tl.heart 109.253445755661 77.5866948581814 61.5518852061484 chr6.19632_chr6_42872202_42876376_-_1.R.tl.kidney 113.178087150060 71.7560582918201 60.9783399658073 chr6.19632_chr6_42872202_42876376_-_1.R.tl.liver 125.173490891295 62.8169505945879 56.4518519109256 chr6.19632_chr6_42872202_42876376_-_1.R.tl.stomach 120.734181295938 90.5195675783566 64.6068993039662 chr6.19632_chr6_42872202_42876376_-_1.R.tl.testicle 110.303806554453 71.3053819349431 57.1177879760438 diffExp=36.1744323428922,15.1586119980599,-28.2102129641872,31.6667508974796,41.4220288582401,62.3565402967071,30.2146137175817,38.9984246195103 diffExpScore=1.24224205663495 diffExp1.5=0,0,0,0,1,1,0,1 diffExp1.5Score=0.75 diffExp1.4=1,0,0,1,1,1,0,1 diffExp1.4Score=0.833333333333333 diffExp1.3=1,0,0,1,1,1,1,1 diffExp1.3Score=0.857142857142857 diffExp1.2=1,0,0,1,1,1,1,1 diffExp1.2Score=0.857142857142857 cont.predictedValues: Include Exclude Both Lung 88.7123384703029 91.2595291450712 96.2929243264258 cerebhem 114.673648938678 92.066498362913 85.6000461434114 cortex 78.0782050172621 77.658759010159 115.249164746373 heart 80.4329733755701 107.100364847648 85.6895783677667 kidney 77.2768231525602 87.8174751907747 93.5625835414062 liver 108.863759677529 91.4156838948962 88.6930810274814 stomach 81.841757347115 95.9649739568463 88.798580685569 testicle 92.6255984798756 88.049388800194 86.7385983786264 cont.diffExp=-2.54719067476836,22.6071505757654,0.419446007103176,-26.6673914720783,-10.5406520382144,17.4480757826326,-14.1232166097314,4.57620967968157 cont.diffExpScore=10.0665113987531 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,-1,0,0,0,0 cont.diffExp1.3Score=0.5 cont.diffExp1.2=0,1,0,-1,0,0,0,0 cont.diffExp1.2Score=2 tran.correlation=0.884336721461698 cont.tran.correlation=0.0361713796641758 tran.covariance=0.0494721163913194 cont.tran.covariance=0.00105049554130957 tran.mean=105.535462758342 cont.tran.mean=90.8648611042123 weightedLogRatios: wLogRatio Lung 1.71709662071854 cerebhem 0.788210702382737 cortex -0.797019796209638 heart 1.54794741157947 kidney 2.05111547688455 liver 3.09227311382341 stomach 1.33919599382390 testicle 1.95670169255117 cont.weightedLogRatios: wLogRatio Lung -0.127375300144237 cerebhem 1.01715657666236 cortex 0.0234587747598288 heart -1.29730051272407 kidney -0.564060691289016 liver 0.80401020947576 stomach -0.71389476990558 testicle 0.228168175400702 varWeightedLogRatios=1.27061167590883 cont.varWeightedLogRatios=0.601583903803928 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.87648277276923 0.115125912114874 42.3578209560975 1.43836141422112e-148 *** df.mm.trans1 -0.0663714814118877 0.0939999136179801 -0.70608023834601 0.480556593291339 df.mm.trans2 -0.566412827513633 0.0939999136179801 -6.0256739151438 3.87746616175174e-09 *** df.mm.exp2 -0.505916384942628 0.127720732081458 -3.96111403918328 8.85769356425806e-05 *** df.mm.exp3 0.36060376255906 0.127720732081458 2.82337688394297 0.00499382941937993 ** df.mm.exp4 0.0196407095814422 0.127720732081458 0.153778554674395 0.87786327645066 df.mm.exp5 -0.0138289982243416 0.127720732081458 -0.108275281537861 0.913832587557513 df.mm.exp6 0.0309924194069572 0.127720732081458 0.242657702487885 0.808397166440909 df.mm.exp7 0.225290980952234 0.127720732081458 1.76393430636263 0.078519937822677 . df.mm.exp8 0.0195495152904896 0.127720732081458 0.153064541456130 0.8784259363116 df.mm.trans1:exp2 0.294928590602261 0.104283541058096 2.82814131175270 0.00492158787903858 ** df.mm.trans2:exp2 0.494355434497825 0.104283541058096 4.7404933653185 2.98587824636709e-06 *** df.mm.trans1:exp3 0.0334324455910748 0.104283541058096 0.320591775575108 0.74869016732297 df.mm.trans2:exp3 0.562835200906678 0.104283541058096 5.39716234408575 1.17317491361121e-07 *** df.mm.trans1:exp4 -0.0731878713719689 0.104283541058096 -0.701816131571481 0.483209243857989 df.mm.trans2:exp4 -0.0388146363289822 0.104283541058096 -0.372202899279749 0.709942408569488 df.mm.trans1:exp5 -0.00442596652423411 0.104283541058096 -0.0424416593388251 0.96616817308423 df.mm.trans2:exp5 -0.083468595800508 0.104283541058096 -0.800400475028055 0.423962378953387 df.mm.trans1:exp6 0.0514907473786936 0.104283541058096 0.493757182161739 0.621753504988545 df.mm.trans2:exp6 -0.261337349649436 0.104283541058096 -2.50602680919557 0.0126129154686912 * df.mm.trans1:exp7 -0.178917236128071 0.104283541058096 -1.71568048335064 0.0870086784702534 . df.mm.trans2:exp7 -0.0902948185052858 0.104283541058096 -0.86585876917032 0.387095885027594 df.mm.trans1:exp8 -0.0635286140731575 0.104283541058096 -0.609191186150514 0.542749717687619 df.mm.trans2:exp8 -0.123147588983387 0.104283541058096 -1.18089190042733 0.238359842008407 df.mm.trans1:probe2 -0.206683776491908 0.0638603660407288 -3.23649533045409 0.00131267181188994 ** df.mm.trans1:probe3 -0.113314740331762 0.0638603660407288 -1.77441420018627 0.0767687667639948 . df.mm.trans1:probe4 -0.00664703920748635 0.0638603660407288 -0.104087082796347 0.917153338860833 df.mm.trans1:probe5 -0.274117366581139 0.0638603660407288 -4.2924490349196 2.22835146411076e-05 *** df.mm.trans1:probe6 -0.15396214927865 0.0638603660407288 -2.41091867811181 0.0163704876518605 * df.mm.trans2:probe2 0.235407149855532 0.0638603660407288 3.68627936935711 0.000259517533196097 *** df.mm.trans2:probe3 0.216753479943234 0.0638603660407288 3.3941784769131 0.000758382386509638 *** df.mm.trans2:probe4 0.200715266711572 0.0638603660407288 3.14303345182142 0.00179892882211329 ** df.mm.trans2:probe5 0.046815981896626 0.0638603660407288 0.733099178710747 0.463934987077552 df.mm.trans2:probe6 0.0263073532016162 0.0638603660407288 0.411951180875442 0.680599800622668 df.mm.trans3:probe2 0.00218177534436675 0.0638603660407288 0.0341647798099882 0.972763097027293 df.mm.trans3:probe3 0.147501689885540 0.0638603660407288 2.30975327938877 0.0214193746153285 * df.mm.trans3:probe4 -0.0924548556438699 0.0638603660407288 -1.44776582684954 0.148479807108337 df.mm.trans3:probe5 0.0578858876945924 0.0638603660407288 0.906444658611476 0.365255958818396 df.mm.trans3:probe6 -0.303851605515385 0.0638603660407288 -4.75806238444664 2.75042562408895e-06 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.56573544567198 0.216006960029791 21.1369830168541 8.72893324864527e-67 *** df.mm.trans1 -0.0990375876276826 0.176368944320917 -0.56153643153568 0.574751971629019 df.mm.trans2 -0.0137763159376761 0.176368944320917 -0.07811078073138 0.937779685186571 df.mm.exp2 0.383204002551347 0.239638206229081 1.59909393656963 0.110603335191313 df.mm.exp3 -0.468772695559001 0.239638206229081 -1.95616843797804 0.0511532778766303 . df.mm.exp4 0.178747822302286 0.239638206229081 0.745907028411876 0.456169493243147 df.mm.exp5 -0.147687517631244 0.239638206229081 -0.616293703559368 0.538057496797778 df.mm.exp6 0.288620808870833 0.239638206229081 1.20440230884940 0.229158957866517 df.mm.exp7 0.0506886398073533 0.239638206229081 0.211521529079123 0.832589980337272 df.mm.exp8 0.111852900688582 0.239638206229081 0.466757377501217 0.640932117460552 df.mm.trans1:exp2 -0.126512726819972 0.195663776045698 -0.646582261554764 0.518279763997743 df.mm.trans2:exp2 -0.374400294307234 0.195663776045698 -1.91348803480002 0.0564118362656782 . df.mm.trans1:exp3 0.341084665351709 0.195663776045698 1.74321825043409 0.0820775532843741 . df.mm.trans2:exp3 0.307389623955863 0.195663776045698 1.57100936191720 0.116985199660454 df.mm.trans1:exp4 -0.276722596607785 0.195663776045698 -1.41427607194474 0.158072584848582 df.mm.trans2:exp4 -0.0186888542443801 0.195663776045698 -0.0955151465543384 0.923954343734494 df.mm.trans1:exp5 0.00968261538905796 0.195663776045698 0.0494859885909416 0.960557142780774 df.mm.trans2:exp5 0.109240616533800 0.195663776045698 0.55830782141446 0.576952134403186 df.mm.trans1:exp6 -0.0839226026747142 0.195663776045698 -0.428912312594406 0.668222049409572 df.mm.trans2:exp6 -0.286911164904785 0.195663776045698 -1.46634788872610 0.143353214807542 df.mm.trans1:exp7 -0.131300028460841 0.195663776045698 -0.671049241276911 0.502583360025627 df.mm.trans2:exp7 -0.000412785528696026 0.195663776045698 -0.00210966759938037 0.998317800489685 df.mm.trans1:exp8 -0.0686863387991673 0.195663776045698 -0.351042692660319 0.725744426639367 df.mm.trans2:exp8 -0.147662423276116 0.195663776045698 -0.754674300273288 0.45089641408849 df.mm.trans1:probe2 0.215153863682204 0.119819103114540 1.79565576848400 0.0733173501710377 . df.mm.trans1:probe3 -0.0251090562981208 0.119819103114540 -0.209558039122676 0.8341212193176 df.mm.trans1:probe4 -0.000934487753681786 0.119819103114540 -0.00779915497104387 0.993781195144522 df.mm.trans1:probe5 -0.0381382073267706 0.119819103114540 -0.318298220696182 0.7504278102227 df.mm.trans1:probe6 0.0734413874907136 0.119819103114540 0.612935546851053 0.54027348673257 df.mm.trans2:probe2 -0.154692451421403 0.119819103114540 -1.29104998619065 0.197445250407750 df.mm.trans2:probe3 -0.117849827127665 0.119819103114540 -0.983564590823277 0.325934762340550 df.mm.trans2:probe4 -0.0358950101602586 0.119819103114540 -0.299576688751751 0.764658441776945 df.mm.trans2:probe5 -0.189095961152158 0.119819103114540 -1.57817873975732 0.115329090609691 df.mm.trans2:probe6 0.0385126850181284 0.119819103114540 0.321423579521476 0.748060291958265 df.mm.trans3:probe2 0.129798404385284 0.119819103114540 1.08328639600318 0.279345490505656 df.mm.trans3:probe3 0.0862608156061877 0.119819103114540 0.719925398905107 0.471998856608014 df.mm.trans3:probe4 0.114992084427225 0.119819103114540 0.959714114345344 0.337789177398007 df.mm.trans3:probe5 0.172135114431599 0.119819103114540 1.43662496177298 0.151620166591679 df.mm.trans3:probe6 0.183653373201724 0.119819103114540 1.53275536561279 0.126140718214104