chr3.15197_chr3_95582409_95583040_+_1.R fitVsDatCorrelation=0.968647992404804 cont.fitVsDatCorrelation=0.327333214385249 fstatistic=4709.41053302065,37,347 cont.fstatistic=316.821675276854,37,347 residuals=-1.12673801822609,-0.101893045989688,0.0139057651631567,0.0952829228743759,0.708053296880367 cont.residuals=-1.68933445493247,-0.657485300982751,-0.281615502333846,0.674846624740134,2.22323844105622 predictedValues: Include Exclude Both chr3.15197_chr3_95582409_95583040_+_1.R.tl.Lung 73.5592950039678 458.061446891176 76.7181069993653 chr3.15197_chr3_95582409_95583040_+_1.R.tl.cerebhem 78.2522699530912 332.635662972039 77.0770930975998 chr3.15197_chr3_95582409_95583040_+_1.R.tl.cortex 71.8990764426161 576.68748206553 63.0746323137963 chr3.15197_chr3_95582409_95583040_+_1.R.tl.heart 75.4318852096601 497.598094122327 69.4560765447986 chr3.15197_chr3_95582409_95583040_+_1.R.tl.kidney 89.7051912586037 303.507388428969 84.8245022737168 chr3.15197_chr3_95582409_95583040_+_1.R.tl.liver 93.5150565034536 339.620963806449 82.8759097046517 chr3.15197_chr3_95582409_95583040_+_1.R.tl.stomach 95.7197725057952 829.024037230556 84.444019359838 chr3.15197_chr3_95582409_95583040_+_1.R.tl.testicle 83.1440100764885 602.155950452944 76.8482269006082 diffExp=-384.502151887209,-254.383393018948,-504.788405622914,-422.166208912667,-213.802197170366,-246.105907302995,-733.304264724761,-519.011940376455 diffExpScore=0.99969503496822 diffExp1.5=-1,-1,-1,-1,-1,-1,-1,-1 diffExp1.5Score=0.888888888888889 diffExp1.4=-1,-1,-1,-1,-1,-1,-1,-1 diffExp1.4Score=0.888888888888889 diffExp1.3=-1,-1,-1,-1,-1,-1,-1,-1 diffExp1.3Score=0.888888888888889 diffExp1.2=-1,-1,-1,-1,-1,-1,-1,-1 diffExp1.2Score=0.888888888888889 cont.predictedValues: Include Exclude Both Lung 219.751555211603 191.580259819979 103.432742707631 cerebhem 106.814227286065 118.872251563190 156.5414247251 cortex 91.417301078259 131.109695926187 239.621294090939 heart 204.842275357478 109.801904931532 164.678678393281 kidney 169.764356422831 135.400914229145 185.381487640295 liver 121.018095169528 164.484512454280 202.078929553612 stomach 171.38457599592 140.581607099912 133.274167133481 testicle 187.929404429174 129.837271712432 93.4047511834834 cont.diffExp=28.1712953916233,-12.0580242771246,-39.6923948479278,95.0403704259455,34.3634421936858,-43.4664172847521,30.8029688960079,58.0921327167426 cont.diffExpScore=2.24420016989115 cont.diffExp1.5=0,0,0,1,0,0,0,0 cont.diffExp1.5Score=0.5 cont.diffExp1.4=0,0,-1,1,0,0,0,1 cont.diffExp1.4Score=1.5 cont.diffExp1.3=0,0,-1,1,0,-1,0,1 cont.diffExp1.3Score=4 cont.diffExp1.2=0,0,-1,1,1,-1,1,1 cont.diffExp1.2Score=2 tran.correlation=0.132965486618057 cont.tran.correlation=0.251811586803035 tran.covariance=-0.000469938907974543 cont.tran.covariance=0.0112203147826488 tran.mean=287.532348932729 cont.tran.mean=149.661888042970 weightedLogRatios: wLogRatio Lung -9.5332883275822 cerebhem -7.35637301786101 cortex -11.0686961334667 heart -9.9356036550501 kidney -6.22354770168506 liver -6.68452461299391 stomach -12.1775758231500 testicle -10.7125675373964 cont.weightedLogRatios: wLogRatio Lung 0.730390307002164 cerebhem -0.505331853939668 cortex -1.69327998120691 heart 3.12433397550179 kidney 1.13567938657781 liver -1.51884705897965 stomach 0.999494884648507 testicle 1.86784577334561 varWeightedLogRatios=4.84040292988312 cont.varWeightedLogRatios=2.76560666431790 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 6.66727900957682 0.129591087088704 51.4485923326897 1.89056583649899e-164 *** df.mm.trans1 -2.31764093384942 0.107967159566726 -21.4661656669504 1.20982049261564e-65 *** df.mm.trans2 -0.436849583546589 0.107967159566726 -4.04613389200635 6.42253117898975e-05 *** df.mm.exp2 -0.262777904473095 0.148756064968485 -1.76650212230853 0.0781907824736328 . df.mm.exp3 0.403287850455847 0.148756064968485 2.71106828848482 0.00704021856327056 ** df.mm.exp4 0.207370818807801 0.148756064968485 1.39403269945151 0.164199740898921 df.mm.exp5 -0.313607245971772 0.148756064968485 -2.10819804919021 0.0357304283526717 * df.mm.exp6 -0.136349184651787 0.148756064968485 -0.916595801863093 0.359991062765513 df.mm.exp7 0.760627816266009 0.148756064968485 5.11325582877682 5.24608115614069e-07 *** df.mm.exp8 0.394300835399046 0.148756064968485 2.65065384381189 0.00840170601108882 ** df.mm.trans1:exp2 0.324623926726714 0.125721821224787 2.58208100681501 0.0102299610777861 * df.mm.trans2:exp2 -0.0571776483384641 0.125721821224787 -0.454794941573685 0.649541159754603 df.mm.trans1:exp3 -0.426116246568628 0.125721821224787 -3.38935788884847 0.0007811659087892 *** df.mm.trans2:exp3 -0.172990694849103 0.125721821224787 -1.37597986700973 0.169715266695167 df.mm.trans1:exp4 -0.182232568149122 0.125721821224787 -1.44949036192608 0.148103840684283 df.mm.trans2:exp4 -0.124581446163101 0.125721821224787 -0.990929378443807 0.322410539231483 df.mm.trans1:exp5 0.512044071193858 0.125721821224787 4.07283370703276 5.75854322294269e-05 *** df.mm.trans2:exp5 -0.097990138375635 0.125721821224787 -0.779420290137474 0.436263424086317 df.mm.trans1:exp6 0.376379824373562 0.125721821224787 2.99375097104748 0.00295339166454082 ** df.mm.trans2:exp6 -0.162823970570386 0.125721821224787 -1.29511304389444 0.196142236220034 df.mm.trans1:exp7 -0.497294745622978 0.125721821224787 -3.9555165585283 9.26105875642887e-05 *** df.mm.trans2:exp7 -0.167382004730968 0.125721821224787 -1.33136796063187 0.183941946211763 df.mm.trans1:exp8 -0.271818485650803 0.125721821224787 -2.16206290207012 0.0312963681319034 * df.mm.trans2:exp8 -0.120787708363268 0.125721821224787 -0.960753727448029 0.337344986283477 df.mm.trans1:probe2 -0.167277541897873 0.0688606774554475 -2.429217197378 0.0156385424136529 * df.mm.trans1:probe3 -0.201391229838209 0.0688606774554474 -2.92461877053865 0.0036755406144519 ** df.mm.trans1:probe4 -0.0772897072899577 0.0688606774554475 -1.12240701291334 0.262465449873076 df.mm.trans1:probe5 0.0995473006025862 0.0688606774554474 1.44563347734987 0.149182556575263 df.mm.trans1:probe6 -0.169051421539766 0.0688606774554474 -2.45497761257347 0.0145795097504558 * df.mm.trans2:probe2 -0.449229394464469 0.0688606774554475 -6.52374346382402 2.42828173476796e-10 *** df.mm.trans2:probe3 9.16755197853017e-05 0.0688606774554474 0.00133131887708504 0.998938526563583 df.mm.trans2:probe4 -0.570867790586375 0.0688606774554474 -8.2901855119814 2.5126649412634e-15 *** df.mm.trans2:probe5 0.072068526383227 0.0688606774554474 1.04658462632545 0.2960196581288 df.mm.trans2:probe6 -0.0863238908253191 0.0688606774554475 -1.25360211393753 0.210830607546983 df.mm.trans3:probe2 0.505468039307803 0.0688606774554475 7.34044534538363 1.52523845918558e-12 *** df.mm.trans3:probe3 0.465433242184054 0.0688606774554474 6.75905697391936 5.88998776870651e-11 *** df.mm.trans3:probe4 0.738495774275954 0.0688606774554475 10.7244918517358 2.28621012919405e-23 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 6.07711232642976 0.492888169351986 12.3295966596632 3.24066048035210e-29 *** df.mm.trans1 -0.677136925601851 0.410643485014921 -1.64896546593755 0.100059696097188 df.mm.trans2 -0.882233851279366 0.410643485014921 -2.14841799145385 0.0323722179674574 * df.mm.exp2 -1.61306301084885 0.565780457510437 -2.85104052187786 0.00461833604858921 ** df.mm.exp3 -2.09647351258061 0.565780457510436 -3.70545409398827 0.000245479959586086 *** df.mm.exp4 -1.09196087234477 0.565780457510436 -1.93000811153791 0.0544206162331236 . df.mm.exp5 -1.18864722124424 0.565780457510436 -2.10089833515028 0.0363708951060662 * df.mm.exp6 -1.41878473692854 0.565780457510436 -2.50765949600224 0.0126094406200503 * df.mm.exp7 -0.81159311940279 0.565780457510436 -1.43446651192935 0.152339765765441 df.mm.exp8 -0.443476792205647 0.565780457510436 -0.783831937492232 0.433673430482727 df.mm.trans1:exp2 0.891656529065556 0.478171760907192 1.86472017371728 0.0630646531499214 . df.mm.trans2:exp2 1.13580557890378 0.478171760907192 2.37530877346023 0.0180770574367544 * df.mm.trans1:exp3 1.21941064909802 0.478171760907192 2.55015195122468 0.0111967351679154 * df.mm.trans2:exp3 1.71720102671296 0.478171760907192 3.59118033958147 0.000376668245590921 *** df.mm.trans1:exp4 1.02170355312569 0.478171760907192 2.13668735097886 0.0333224255459847 * df.mm.trans2:exp4 0.535331918223352 0.478171760907192 1.11953896484333 0.263684603952536 df.mm.trans1:exp5 0.930560944300202 0.478171760907192 1.94608092818935 0.0524519684355157 . df.mm.trans2:exp5 0.841580501611692 0.478171760907192 1.75999624071283 0.0792894932953498 . df.mm.trans1:exp6 0.822227204473715 0.478171760907192 1.7195227148374 0.0864109482459398 . df.mm.trans2:exp6 1.26629432133798 0.478171760907192 2.64819971579994 0.0084617032974017 ** df.mm.trans1:exp7 0.563005519435933 0.478171760907192 1.17741273212746 0.239837741727545 df.mm.trans2:exp7 0.5020744408599 0.478171760907192 1.04998764441330 0.294454500885707 df.mm.trans1:exp8 0.287045562433075 0.478171760907192 0.600298022385281 0.548699473933225 df.mm.trans2:exp8 0.0544518703524295 0.478171760907192 0.113875127734693 0.909402639293704 df.mm.trans1:probe2 0.0992355178555543 0.261905459810836 0.378898240331562 0.704995161283037 df.mm.trans1:probe3 -0.120222780937833 0.261905459810836 -0.459031213112798 0.646499154253927 df.mm.trans1:probe4 0.145906342739271 0.261905459810836 0.557095460494232 0.577821355406873 df.mm.trans1:probe5 0.052757618848757 0.261905459810836 0.201437644281497 0.840474412613435 df.mm.trans1:probe6 -0.252454569523378 0.261905459810836 -0.963914878695983 0.335759858636043 df.mm.trans2:probe2 0.170539191109105 0.261905459810836 0.651147903645378 0.515381982605707 df.mm.trans2:probe3 0.151510958920677 0.261905459810836 0.578494847072328 0.563305342484053 df.mm.trans2:probe4 0.290622988070786 0.261905459810836 1.10964845208149 0.267918946258468 df.mm.trans2:probe5 0.0193291648941571 0.261905459810836 0.0738020692967524 0.941210404823597 df.mm.trans2:probe6 -0.0277187330030749 0.261905459810836 -0.105834880353754 0.915774515890988 df.mm.trans3:probe2 0.451927888937989 0.261905459810836 1.72553825057484 0.0853207816242747 . df.mm.trans3:probe3 0.0285326052915805 0.261905459810836 0.108942384447382 0.913311159097589 df.mm.trans3:probe4 0.00425959782953764 0.261905459810836 0.0162638756466329 0.987033223844868