chr2.14417_chr2_126858945_126868661_+_1.R fitVsDatCorrelation=0.894188393511544 cont.fitVsDatCorrelation=0.255816755151097 fstatistic=8969.60883106543,43,485 cont.fstatistic=1914.77996347572,43,485 residuals=-0.746506482866832,-0.0852880907470484,-0.00737680992744521,0.0745703108699278,1.06859861660279 cont.residuals=-0.579135660213201,-0.215142256648992,-0.0793000706801806,0.130401635964009,1.18653649002135 predictedValues: Include Exclude Both chr2.14417_chr2_126858945_126868661_+_1.R.tl.Lung 44.3933557296727 49.4908914176134 69.9059642403625 chr2.14417_chr2_126858945_126868661_+_1.R.tl.cerebhem 48.5642799894984 56.5062289368989 64.1583490410935 chr2.14417_chr2_126858945_126868661_+_1.R.tl.cortex 44.4158942474553 54.3758091586572 75.6060771043844 chr2.14417_chr2_126858945_126868661_+_1.R.tl.heart 45.9814325308103 50.2298109749498 68.0637914375481 chr2.14417_chr2_126858945_126868661_+_1.R.tl.kidney 43.5121581952755 54.8600354490184 89.2399534852622 chr2.14417_chr2_126858945_126868661_+_1.R.tl.liver 49.8738239529641 49.4634355343844 67.1167701991017 chr2.14417_chr2_126858945_126868661_+_1.R.tl.stomach 45.3417637396425 53.6254265939895 77.5029042890657 chr2.14417_chr2_126858945_126868661_+_1.R.tl.testicle 46.5405960257964 58.4555055165716 78.1375619980149 diffExp=-5.09753568794073,-7.94194894740043,-9.95991491120185,-4.24837844413948,-11.3478772537430,0.410388418579672,-8.28366285434701,-11.9149094907752 diffExpScore=0.99698195392311 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,-1,0,-1,0,0,-1 diffExp1.2Score=0.75 cont.predictedValues: Include Exclude Both Lung 56.9813110726705 60.8392058669162 57.7262244904344 cerebhem 67.8964785222169 67.5723681097342 55.2623652205292 cortex 55.613303843552 69.4355363412355 55.1201882150893 heart 58.801423527414 73.2007499080342 58.2766872804301 kidney 61.7270726320094 63.1615505263429 59.0464113841603 liver 60.7374173628113 66.5116455029615 60.6900065449851 stomach 61.5933116654771 58.1496955826563 60.6892359020615 testicle 60.6379161955956 61.5775991120303 58.9211762167894 cont.diffExp=-3.85789479424567,0.324110412482625,-13.8222324976835,-14.3993263806201,-1.43447789433345,-5.77422814015026,3.44361608282082,-0.93968291643479 cont.diffExpScore=1.1744643013985 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,-1,-1,0,0,0,0 cont.diffExp1.2Score=0.666666666666667 tran.correlation=-0.0683783948181038 cont.tran.correlation=-0.0906727071437465 tran.covariance=-0.000217532995086956 cont.tran.covariance=-0.000446981361624726 tran.mean=49.7269029995749 cont.tran.mean=62.7772866107286 weightedLogRatios: wLogRatio Lung -0.418212136147121 cerebhem -0.599582804915674 cortex -0.787995251613613 heart -0.342209987437419 kidney -0.901235053813817 liver 0.0322683693092748 stomach -0.654085214375722 testicle -0.90134569978718 cont.weightedLogRatios: wLogRatio Lung -0.266989007790717 cerebhem 0.0201717190601635 cortex -0.916631443532672 heart -0.916392883808783 kidney -0.0949757046467093 liver -0.377069794172089 stomach 0.235411322300119 testicle -0.0632427857419695 varWeightedLogRatios=0.101801407140538 cont.varWeightedLogRatios=0.179202391436714 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 2.85192619096461 0.0761530002876357 37.4499518100754 3.25743092960252e-145 *** df.mm.trans1 0.917164930627425 0.0609644591928194 15.0442559939161 2.95662908826573e-42 *** df.mm.trans2 1.04356180814624 0.0609644591928194 17.1175439258084 9.95076421919576e-52 *** df.mm.exp2 0.308157445996747 0.0816355641741652 3.77479410002372 0.000179981190084492 *** df.mm.exp3 0.0162526069066756 0.0816355641741651 0.199087334926743 0.842277861776837 df.mm.exp4 0.0766735116698336 0.0816355641741651 0.939217024411747 0.348086836411931 df.mm.exp5 -0.16123080132872 0.0816355641741651 -1.97500688529257 0.0488340170829117 * df.mm.exp6 0.156568591923045 0.0816355641741651 1.91789685668142 0.0557110093022041 . df.mm.exp7 -0.00179101584409771 0.0816355641741652 -0.0219391617148217 0.982505508745538 df.mm.exp8 0.102392468749754 0.0816355641741652 1.25426301374368 0.210350574567948 df.mm.trans1:exp2 -0.218358977472247 0.0640402053426499 -3.4097170098676 0.000704554009848214 *** df.mm.trans2:exp2 -0.175595208127308 0.0640402053426499 -2.74195260911138 0.00633326089871503 ** df.mm.trans1:exp3 -0.0157450354932848 0.0640402053426499 -0.245861727160935 0.805893281863633 df.mm.trans2:exp3 0.0778781225931863 0.0640402053426499 1.21608171267559 0.224545333219502 df.mm.trans1:exp4 -0.0415256498121522 0.0640402053426499 -0.648430928507606 0.517013151729294 df.mm.trans2:exp4 -0.0618534579823062 0.0640402053426499 -0.965853523600629 0.334598834156904 df.mm.trans1:exp5 0.141181386600779 0.0640402053426499 2.20457423341137 0.0279527595513902 * df.mm.trans2:exp5 0.264227292133363 0.0640402053426499 4.12595947685682 4.3449961963711e-05 *** df.mm.trans1:exp6 -0.0401621093935182 0.0640402053426499 -0.627138985245739 0.530863245426633 df.mm.trans2:exp6 -0.157123512254055 0.0640402053426499 -2.45351356094751 0.0144975888585171 * df.mm.trans1:exp7 0.0229297479557296 0.0640402053426499 0.358052380267099 0.720459893624705 df.mm.trans2:exp7 0.0820257073162917 0.0640402053426499 1.28084703784770 0.200859538317833 df.mm.trans1:exp8 -0.055157316727152 0.0640402053426499 -0.861292002922701 0.38950284513582 df.mm.trans2:exp8 0.0640847657558128 0.0640402053426499 1.00069581933606 0.317472887382843 df.mm.trans1:probe2 0.0726756384844918 0.0438453313167902 1.65754565655799 0.0980558478017563 . df.mm.trans1:probe3 0.0720601242962255 0.0438453313167903 1.64350735031692 0.100926068111374 df.mm.trans1:probe4 0.0449021017725944 0.0438453313167902 1.02410223446982 0.306297505651623 df.mm.trans1:probe5 0.0988324112949816 0.0438453313167903 2.25411482424206 0.0246344815805563 * df.mm.trans1:probe6 0.0955087788718539 0.0438453313167903 2.17831125922589 0.0298637742292491 * df.mm.trans2:probe2 0.178050321806189 0.0438453313167903 4.06087299283348 5.69980177364034e-05 *** df.mm.trans2:probe3 -0.0923080143740483 0.0438453313167903 -2.10530999770777 0.0357779551754232 * df.mm.trans2:probe4 0.0367432524233475 0.0438453313167902 0.838019723419834 0.40243241666042 df.mm.trans2:probe5 -6.31656529123548e-05 0.0438453313167903 -0.0014406471798781 0.998851122614908 df.mm.trans2:probe6 -0.0216121259439644 0.0438453313167903 -0.492917382418962 0.622294051825682 df.mm.trans3:probe2 -0.548514019648533 0.0438453313167903 -12.5102035536104 2.56323711802279e-31 *** df.mm.trans3:probe3 -0.530972415698154 0.0438453313167903 -12.1101243793047 1.11944726281876e-29 *** df.mm.trans3:probe4 -0.0785790783048442 0.0438453313167902 -1.79218803792578 0.073726026486137 . df.mm.trans3:probe5 -0.866474665665652 0.0438453313167903 -19.7620736266131 3.33846898225361e-64 *** df.mm.trans3:probe6 -0.536774407893434 0.0438453313167903 -12.2424529995028 3.23235248215787e-30 *** df.mm.trans3:probe7 -0.816593531740673 0.0438453313167903 -18.6244123881888 8.44566629625449e-59 *** df.mm.trans3:probe8 -0.961607271797608 0.0438453313167902 -21.9318053466132 1.39424418969161e-74 *** df.mm.trans3:probe9 -0.567745043826926 0.0438453313167903 -12.9488140875221 3.80446289536203e-33 *** df.mm.trans3:probe10 -0.747759153538563 0.0438453313167903 -17.0544760657839 1.95428016934203e-51 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.04144243022803 0.164441662634698 24.5767548532147 3.14487486139436e-87 *** df.mm.trans1 0.0159627903569470 0.131644150505258 0.121257118494676 0.90353760401811 df.mm.trans2 0.0714753893874055 0.131644150505258 0.542943906835806 0.587417846285582 df.mm.exp2 0.323845008820395 0.176280486024409 1.83710072580328 0.0668066965726061 . df.mm.exp3 0.154059011388474 0.176280486024409 0.87394251549285 0.382582083808197 df.mm.exp4 0.206923406406425 0.176280486024409 1.17383047365647 0.241039025121462 df.mm.exp5 0.094848397968357 0.176280486024409 0.538053871460418 0.590786675882239 df.mm.exp6 0.102911759001601 0.176280486024409 0.583795525656491 0.559629289445309 df.mm.exp7 -0.0174386030407801 0.176280486024409 -0.0989253174532629 0.921238440142184 df.mm.exp8 0.0537717913457163 0.176280486024409 0.305035415765025 0.760470037502344 df.mm.trans1:exp2 -0.148584176460764 0.138285790477551 -1.07447175843338 0.283145552399863 df.mm.trans2:exp2 -0.218880279601928 0.138285790477551 -1.58281106718236 0.114116376614244 df.mm.trans1:exp3 -0.178359899145997 0.138285790477551 -1.28979194847175 0.197737580234431 df.mm.trans2:exp3 -0.0218946383965334 0.138285790477551 -0.158328909434030 0.874263530248372 df.mm.trans1:exp4 -0.175480680298422 0.138285790477551 -1.26897116249199 0.205060003365907 df.mm.trans2:exp4 -0.0219521553402347 0.138285790477551 -0.158744837516754 0.87393598932992 df.mm.trans1:exp5 -0.0148491229689179 0.138285790477551 -0.107379962305877 0.91453195450498 df.mm.trans2:exp5 -0.0573870741939947 0.138285790477551 -0.414988944242329 0.678333505359154 df.mm.trans1:exp6 -0.0390751579868269 0.138285790477551 -0.282568135539352 0.777628458918018 df.mm.trans2:exp6 -0.0137691208201595 0.138285790477551 -0.0995700337150313 0.9207268272202 df.mm.trans1:exp7 0.0952685526727947 0.138285790477551 0.688925104624257 0.491199827775804 df.mm.trans2:exp7 -0.0277751675381294 0.138285790477551 -0.200853373598341 0.84089742826578 df.mm.trans1:exp8 0.00842524771543466 0.138285790477551 0.0609263445386489 0.951442966212188 df.mm.trans2:exp8 -0.0417080522158245 0.138285790477551 -0.301607649432321 0.763080452258235 df.mm.trans1:probe2 -0.108896303173223 0.0946778085337345 -1.15017769062982 0.250637492658310 df.mm.trans1:probe3 -0.0583848083355116 0.0946778085337345 -0.616668353859379 0.537742849667777 df.mm.trans1:probe4 -0.0813652531508103 0.0946778085337345 -0.859390964059114 0.390549416594464 df.mm.trans1:probe5 0.0413500746262681 0.0946778085337345 0.436745159891768 0.662490546485726 df.mm.trans1:probe6 -0.0276138288714413 0.0946778085337345 -0.291661048128319 0.770670498255933 df.mm.trans2:probe2 -0.0548116334273404 0.0946778085337345 -0.57892799037285 0.562906524294637 df.mm.trans2:probe3 0.044694413501277 0.0946778085337345 0.472068525808263 0.637090196598123 df.mm.trans2:probe4 0.0110982686908484 0.0946778085337345 0.117221436181573 0.906733106490047 df.mm.trans2:probe5 -0.0164843774809795 0.0946778085337345 -0.174110255996324 0.861851463103918 df.mm.trans2:probe6 -0.0594311532287102 0.0946778085337345 -0.627719992140866 0.53048281775171 df.mm.trans3:probe2 -0.0921090869765203 0.0946778085337345 -0.972868810579842 0.331103458279255 df.mm.trans3:probe3 -0.0144201571986309 0.0946778085337345 -0.152307678240069 0.879007607791472 df.mm.trans3:probe4 -0.0812214881410597 0.0946778085337345 -0.857872498306927 0.391386601600587 df.mm.trans3:probe5 -0.0281068641850959 0.0946778085337345 -0.296868554737208 0.766693958513795 df.mm.trans3:probe6 -0.0366903832106950 0.0946778085337345 -0.387528860024489 0.698534731868931 df.mm.trans3:probe7 -0.133479363680802 0.0946778085337345 -1.40982734759056 0.159231599893724 df.mm.trans3:probe8 -0.0686164446038582 0.0946778085337345 -0.72473629952482 0.468963305914063 df.mm.trans3:probe9 -0.162868934459810 0.0946778085337345 -1.72024402531221 0.0860259685173046 . df.mm.trans3:probe10 -0.114177702306971 0.0946778085337345 -1.20596055269159 0.22842067623866