chr15.8854_chr15_59368298_59373995_-_2.R fitVsDatCorrelation=0.895664309580588 cont.fitVsDatCorrelation=0.260583252464527 fstatistic=12166.7407873687,53,715 cont.fstatistic=2571.08389879244,53,715 residuals=-0.588587143691872,-0.0816768964911206,-0.00307273839881228,0.0794194450124185,0.742824410044692 cont.residuals=-0.640723083098231,-0.226030737687603,-0.0374892233344127,0.180613942057719,1.36112251992749 predictedValues: Include Exclude Both chr15.8854_chr15_59368298_59373995_-_2.R.tl.Lung 66.7913462164745 69.9901860188792 93.9760949004512 chr15.8854_chr15_59368298_59373995_-_2.R.tl.cerebhem 63.9069780875963 64.7395486310708 124.135294990312 chr15.8854_chr15_59368298_59373995_-_2.R.tl.cortex 57.4427419199116 64.8006930320923 78.8373546618298 chr15.8854_chr15_59368298_59373995_-_2.R.tl.heart 63.7266145461767 67.8610648482391 90.177357430651 chr15.8854_chr15_59368298_59373995_-_2.R.tl.kidney 66.4233355313213 66.3887671739584 91.4335719467882 chr15.8854_chr15_59368298_59373995_-_2.R.tl.liver 69.8554479751911 69.3192913693698 105.359651446998 chr15.8854_chr15_59368298_59373995_-_2.R.tl.stomach 64.2141326902655 68.1465887440414 82.6325969294161 chr15.8854_chr15_59368298_59373995_-_2.R.tl.testicle 61.0008617205814 62.4612176751898 80.6475921425727 diffExp=-3.19883980240466,-0.832570543474432,-7.35795111218064,-4.13445030206245,0.0345683573629003,0.536156605821247,-3.93245605377591,-1.46035595460843 diffExpScore=1.00662656221030 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=0,0,0,0,0,0,0,0 diffExp1.2Score=0 cont.predictedValues: Include Exclude Both Lung 67.5813178331388 82.4530687908137 81.5645403404635 cerebhem 69.3190171730931 69.5362295080735 62.5272892939376 cortex 68.7622656685851 60.9011879173944 76.2587724101288 heart 71.8493082462248 64.6669658353248 68.4151222566321 kidney 70.9716092272989 62.2370873358934 77.4921544846544 liver 71.7364563844494 69.4158952054435 70.5106579892251 stomach 69.3512515548953 69.1430468661778 61.7387456414139 testicle 70.949583800104 78.9882548063211 62.3500996830411 cont.diffExp=-14.8717509576749,-0.217212334980331,7.86107775119064,7.18234241089996,8.73452189140548,2.32056117900582,0.208204688717487,-8.03867100621711 cont.diffExpScore=11.8290192246789 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=-1,0,0,0,0,0,0,0 cont.diffExp1.2Score=0.5 tran.correlation=0.719387286064069 cont.tran.correlation=-0.337528774401163 tran.covariance=0.00165330074766898 cont.tran.covariance=-0.000757331480953072 tran.mean=65.4418010112725 cont.tran.mean=69.866409134577 weightedLogRatios: wLogRatio Lung -0.197650200181928 cerebhem -0.0538963518618377 cortex -0.49549545014343 heart -0.263134685305377 kidney 0.00218416100073347 liver 0.0326883488989833 stomach -0.249159738725529 testicle -0.097534644448838 cont.weightedLogRatios: wLogRatio Lung -0.857802050602688 cerebhem -0.0132662275871121 cortex 0.506242619676026 heart 0.44465369961273 kidney 0.551136669438255 liver 0.139969217212866 stomach 0.0127414008590029 testicle -0.463195440840912 varWeightedLogRatios=0.0301332683926141 cont.varWeightedLogRatios=0.245030829062664 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.81416937602301 0.0747148944804833 51.0496521817257 1.21554317740575e-240 *** df.mm.trans1 0.111480452543690 0.066348272277389 1.68023143206521 0.0933490995856965 . df.mm.trans2 0.511740081096442 0.0603523815950528 8.47920276833598 1.2947885190744e-16 *** df.mm.exp2 -0.400459340938659 0.081363978928885 -4.92182592604861 1.06525520446671e-06 *** df.mm.exp3 -0.0521700878814408 0.081363978928885 -0.641193911215174 0.521602174120476 df.mm.exp4 -0.0366017487493479 0.081363978928885 -0.449852001231886 0.652953506726664 df.mm.exp5 -0.0309245290240007 0.081363978928885 -0.380076410115463 0.704001569314777 df.mm.exp6 -0.0791165456380049 0.081363978928885 -0.972378031157444 0.331191352626143 df.mm.exp7 0.062592068355712 0.081363978928885 0.769284752045124 0.441978336348522 df.mm.exp8 -0.0515432275244087 0.081363978928885 -0.63348951468388 0.526616606037341 df.mm.trans1:exp2 0.356314375115666 0.0772589152044531 4.61195156795481 4.72599885392273e-06 *** df.mm.trans2:exp2 0.322476584896816 0.0650578287042572 4.95676832933888 8.95801657369208e-07 *** df.mm.trans1:exp3 -0.0986147776363922 0.0772589152044532 -1.27641939283543 0.202221734358750 df.mm.trans2:exp3 -0.0248686463679859 0.0650578287042573 -0.382254478258641 0.702386206827656 df.mm.trans1:exp4 -0.0103694896521564 0.0772589152044532 -0.134217386106383 0.89326844825863 df.mm.trans2:exp4 0.00570916733181242 0.0650578287042573 0.0877552701269113 0.930095761232088 df.mm.trans1:exp5 0.0253994379979735 0.0772589152044531 0.32875737292917 0.742435350206897 df.mm.trans2:exp5 -0.0219026303613643 0.0650578287042573 -0.336664023340376 0.736468974945325 df.mm.trans1:exp6 0.123971099156394 0.0772589152044532 1.60461868806111 0.109019324864598 df.mm.trans2:exp6 0.069484755343025 0.0650578287042573 1.06804602500480 0.285860214978794 df.mm.trans1:exp7 -0.101942271016650 0.0772589152044532 -1.31948877028465 0.187428113947556 df.mm.trans2:exp7 -0.089285999069242 0.0650578287042573 -1.37240975986337 0.170366270939675 df.mm.trans1:exp8 -0.039142306328162 0.0772589152044531 -0.506638052379822 0.612564997780647 df.mm.trans2:exp8 -0.0622659580208346 0.0650578287042573 -0.957086322445312 0.338847180856817 df.mm.trans1:probe2 0.350360626489676 0.0423164506258579 8.27953718489765 6.06698124780229e-16 *** df.mm.trans1:probe3 0.456572661213521 0.0423164506258578 10.7894838640963 3.00473438835654e-25 *** df.mm.trans1:probe4 0.0129656081731992 0.0423164506258578 0.306396400960823 0.75939204721604 df.mm.trans1:probe5 0.696649565483668 0.0423164506258578 16.4628544024903 7.1265005465382e-52 *** df.mm.trans1:probe6 0.283712533628981 0.0423164506258578 6.70454467312095 4.10283518813530e-11 *** df.mm.trans1:probe7 0.0252832951580178 0.0423164506258579 0.597481470777423 0.550375144090238 df.mm.trans1:probe8 1.17563384911683 0.0423164506258578 27.7819578846824 8.84472384646299e-116 *** df.mm.trans1:probe9 0.492199002449762 0.0423164506258579 11.6313867342409 9.22525468255373e-29 *** df.mm.trans1:probe10 0.315612065677499 0.0423164506258578 7.45837755789097 2.54372014691752e-13 *** df.mm.trans1:probe11 0.341765669278667 0.0423164506258578 8.07642569790171 2.83273418351945e-15 *** df.mm.trans1:probe12 0.496542276221616 0.0423164506258579 11.7340246849106 3.34614282293862e-29 *** df.mm.trans1:probe13 0.52722945338356 0.0423164506258578 12.4592078396431 2.19341363418926e-32 *** df.mm.trans1:probe14 0.577144156563496 0.0423164506258578 13.638765728873 8.17486319064564e-38 *** df.mm.trans1:probe15 0.452630138639746 0.0423164506258578 10.6963162539715 7.16564393050704e-25 *** df.mm.trans1:probe16 0.55800017398654 0.0423164506258578 13.1863652488276 1.07010172675997e-35 *** df.mm.trans1:probe17 0.195819982295010 0.0423164506258578 4.62751434486691 4.39406628573997e-06 *** df.mm.trans1:probe18 0.090855510291167 0.0423164506258578 2.14704940862051 0.0321250007645121 * df.mm.trans1:probe19 0.0168901475359224 0.0423164506258578 0.399139041344870 0.689909940587542 df.mm.trans1:probe20 0.0394617843662654 0.0423164506258578 0.932540035438414 0.351372292144072 df.mm.trans1:probe21 0.0463809699362882 0.0423164506258578 1.09605057253896 0.273425675732381 df.mm.trans1:probe22 0.0223066241946918 0.0423164506258579 0.527138355527889 0.598261025390209 df.mm.trans2:probe2 -0.248420729599190 0.0423164506258578 -5.87054740946042 6.64829904843816e-09 *** df.mm.trans2:probe3 -0.220075354880075 0.0423164506258578 -5.20070449258322 2.59504916808087e-07 *** df.mm.trans2:probe4 -0.0841301361908688 0.0423164506258579 -1.98811892175712 0.0471794482066429 * df.mm.trans2:probe5 -0.224264858846536 0.0423164506258578 -5.29970863646813 1.5466947079451e-07 *** df.mm.trans2:probe6 0.00134683322377759 0.0423164506258579 0.0318276510401512 0.974618377696696 df.mm.trans3:probe2 0.369664114249597 0.0423164506258578 8.73570700713992 1.70602533837342e-17 *** df.mm.trans3:probe3 0.194144493060687 0.0423164506258578 4.58792006865655 5.28627615235484e-06 *** df.mm.trans3:probe4 -0.141206484530150 0.0423164506258579 -3.33691702497999 0.000890954327882727 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.31353559429843 0.162196109010292 26.5945688871286 7.06205358477997e-109 *** df.mm.trans1 -0.0476891303663367 0.144033283828822 -0.331097987205606 0.740667482578572 df.mm.trans2 0.115250355580288 0.131017001794454 0.879659540378573 0.37933932079307 df.mm.exp2 0.120797864214116 0.176630387924964 0.683901935749775 0.494258673282415 df.mm.exp3 -0.218390882855624 0.176630387924964 -1.23642871094412 0.216705245518187 df.mm.exp4 -0.00593864128314944 0.176630387924964 -0.0336218549532501 0.973188077884548 df.mm.exp5 -0.181111927173044 0.176630387924964 -1.02537241355085 0.305534270828221 df.mm.exp6 0.0331848420148727 0.176630387924964 0.187877309248567 0.85102613593222 df.mm.exp7 0.128283756143392 0.176630387924964 0.726283612069571 0.467902606055856 df.mm.exp8 0.274337197772577 0.176630387924964 1.55317100865521 0.120824783067084 df.mm.trans1:exp2 -0.0954101590202686 0.167718839993700 -0.568869657242158 0.569623237114515 df.mm.trans2:exp2 -0.291179227915709 0.141231902284825 -2.06171001880640 0.0395962465168761 * df.mm.trans1:exp3 0.235714431775650 0.167718839993700 1.40541415493038 0.160332510972750 df.mm.trans2:exp3 -0.084585704920974 0.141231902284825 -0.59891358505098 0.549420211714055 df.mm.trans1:exp4 0.0671780445742974 0.167718839993700 0.400539644662583 0.688878740339796 df.mm.trans2:exp4 -0.237040130347835 0.141231902284825 -1.67837525738195 0.0937108330374216 . df.mm.trans1:exp5 0.230060272768567 0.167718839993700 1.37170202689935 0.170586480452289 df.mm.trans2:exp5 -0.100166259689289 0.141231902284825 -0.709232532231155 0.478411384743178 df.mm.trans1:exp6 0.0264826521764727 0.167718839993700 0.157899089794965 0.874580897086955 df.mm.trans2:exp6 -0.205298231519751 0.141231902284825 -1.45362505353587 0.146489057109116 df.mm.trans1:exp7 -0.102431144049478 0.167718839993700 -0.610731293236499 0.541571571093617 df.mm.trans2:exp7 -0.304335522888472 0.141231902284825 -2.15486386549346 0.031505744598269 * df.mm.trans1:exp8 -0.225699241723561 0.167718839993700 -1.34569999251151 0.178825848985882 df.mm.trans2:exp8 -0.317267298031198 0.141231902284825 -2.24642798757578 0.0249810404545979 * df.mm.trans1:probe2 -0.0631661773939782 0.0918633919831493 -0.687609895850188 0.491921461816639 df.mm.trans1:probe3 -0.118332445979596 0.0918633919831493 -1.28813495153001 0.198115696966088 df.mm.trans1:probe4 -0.0568785325613049 0.0918633919831493 -0.619164297479221 0.536005355194047 df.mm.trans1:probe5 -0.122775097968184 0.0918633919831493 -1.33649645759548 0.181812194001922 df.mm.trans1:probe6 -0.0355181961326461 0.0918633919831493 -0.386641461477509 0.699136696617168 df.mm.trans1:probe7 0.0480104001533892 0.0918633919831493 0.522628210399588 0.601394900820908 df.mm.trans1:probe8 0.0342236272383423 0.0918633919831493 0.37254913518347 0.709594438303263 df.mm.trans1:probe9 -0.0163103144285066 0.0918633919831493 -0.177549664522495 0.85912694454503 df.mm.trans1:probe10 -0.0693994501694456 0.0918633919831493 -0.755463614735408 0.450219646763215 df.mm.trans1:probe11 -0.0669394672485957 0.0918633919831493 -0.728684907050619 0.466433023616024 df.mm.trans1:probe12 -0.0291580187174645 0.0918633919831493 -0.317406293061909 0.751027998189703 df.mm.trans1:probe13 0.0224324638412618 0.0918633919831493 0.244193724583745 0.807150841353441 df.mm.trans1:probe14 -0.149672076179539 0.0918633919831493 -1.62928967620740 0.103692172780689 df.mm.trans1:probe15 -0.0698369325351609 0.0918633919831493 -0.760225929257775 0.447370151591346 df.mm.trans1:probe16 -0.196964351022165 0.0918633919831493 -2.14410056900897 0.0323613831039264 * df.mm.trans1:probe17 0.00266899147312227 0.0918633919831493 0.0290539181659202 0.976829695720911 df.mm.trans1:probe18 -0.0806663996076626 0.0918633919831493 -0.878112574184714 0.380177605860491 df.mm.trans1:probe19 -0.136015544465212 0.0918633919831493 -1.48062837142092 0.139146133031607 df.mm.trans1:probe20 -0.0368369888531838 0.0918633919831493 -0.400997481781871 0.688541781270106 df.mm.trans1:probe21 -0.103535287106450 0.0918633919831493 -1.12705708848028 0.260096439352006 df.mm.trans1:probe22 -0.120717147172880 0.0918633919831493 -1.31409416272179 0.189235945931247 df.mm.trans2:probe2 -0.123326070611655 0.0918633919831493 -1.34249419653780 0.179861881744233 df.mm.trans2:probe3 -0.0173724367408211 0.0918633919831493 -0.189111640293097 0.850058985657868 df.mm.trans2:probe4 -0.0180643613817559 0.0918633919831493 -0.196643744496932 0.844162215729483 df.mm.trans2:probe5 -0.0496354626972937 0.0918633919831493 -0.540318201034842 0.589145866020394 df.mm.trans2:probe6 0.0428315159939344 0.0918633919831493 0.46625228036203 0.641176944517524 df.mm.trans3:probe2 0.085990713591385 0.0918633919831493 0.936071613893362 0.349552365268394 df.mm.trans3:probe3 0.0231506892271542 0.0918633919831493 0.252012131572507 0.801104108040017 df.mm.trans3:probe4 -0.0279502293774862 0.0918633919831493 -0.304258625488303 0.761019392487397