chr4.16819_chr4_21312930_21315023_+_2.R fitVsDatCorrelation=0.630899575374194 cont.fitVsDatCorrelation=0.267469958493205 fstatistic=12005.4961689323,43,485 cont.fstatistic=7779.78163342425,43,485 residuals=-0.364124617273153,-0.0795489879102073,-0.00702365662074018,0.0662414203962664,0.533738536264537 cont.residuals=-0.3947908177938,-0.0994686346586283,-0.0148879510514730,0.0639002417154092,0.56047946573846 predictedValues: Include Exclude Both chr4.16819_chr4_21312930_21315023_+_2.R.tl.Lung 44.3968213833495 43.3461269258754 51.0763820492492 chr4.16819_chr4_21312930_21315023_+_2.R.tl.cerebhem 51.9101416192712 53.8396270298784 51.2731725848491 chr4.16819_chr4_21312930_21315023_+_2.R.tl.cortex 44.7814884268744 42.9666403495954 58.0864119868008 chr4.16819_chr4_21312930_21315023_+_2.R.tl.heart 45.0677401170744 43.4112435625925 48.5361663852065 chr4.16819_chr4_21312930_21315023_+_2.R.tl.kidney 43.299093673025 41.9679776425473 53.6889956966468 chr4.16819_chr4_21312930_21315023_+_2.R.tl.liver 49.2916188751253 47.9523240641208 48.9222139045861 chr4.16819_chr4_21312930_21315023_+_2.R.tl.stomach 45.5958351447223 46.2115779719133 48.3986145531085 chr4.16819_chr4_21312930_21315023_+_2.R.tl.testicle 47.4171643263044 46.8779819164727 49.7271008986124 diffExp=1.05069445747413,-1.92948541060727,1.81484807727898,1.65649655448184,1.33111603047776,1.33929481100453,-0.615742827191028,0.539182409831668 diffExpScore=1.66120098326229 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 47.0321582099664 46.7430051601616 47.3259691078667 cerebhem 45.7780353566149 47.5245645466802 50.011869260259 cortex 47.4125033782511 48.8212160555448 47.9999370054131 heart 47.1274045144982 50.0456027773348 47.0322282004761 kidney 48.1690854490324 51.6006865399593 50.3634630560786 liver 47.1947270763458 47.4024938581442 50.5726800369783 stomach 47.2644308436752 47.1241200370931 44.5088491743913 testicle 45.8833388824985 46.1047013084139 47.3043725303913 cont.diffExp=0.289153049804774,-1.74652919006532,-1.40871267729379,-2.91819826283665,-3.43160109092694,-0.207766781798419,0.140310806582100,-0.221362425915352 cont.diffExpScore=0.986570563751277 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=0.968468392436858 cont.tran.correlation=0.693346021981047 tran.covariance=0.00479591119876453 cont.tran.covariance=0.000443943871308981 tran.mean=46.1458376892964 cont.tran.mean=47.5767546246384 weightedLogRatios: wLogRatio Lung 0.0905615348323783 cerebhem -0.144805774037424 cortex 0.156427675078274 heart 0.141907872039297 kidney 0.117171713521537 liver 0.106991220824334 stomach -0.0513289628958355 testicle 0.0440666582613423 cont.weightedLogRatios: wLogRatio Lung 0.0237289189412069 cerebhem -0.143873098594852 cortex -0.113412934396888 heart -0.233284220356924 kidney -0.269016460298715 liver -0.0169402316209744 stomach 0.0114589393707330 testicle -0.0184260815246184 varWeightedLogRatios=0.0109951763184211 cont.varWeightedLogRatios=0.0127884024965290 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.49048709165018 0.0641669937576049 54.3969241388451 1.39779096714109e-208 *** df.mm.trans1 0.310437482674112 0.0558072210870074 5.5626758800643 4.39783284689741e-08 *** df.mm.trans2 0.251380267106032 0.0523921310114951 4.79805387283976 2.136114880972e-06 *** df.mm.exp2 0.369293240284617 0.071186888057053 5.18765815396574 3.13484183798401e-07 *** df.mm.exp3 -0.128775937422072 0.071186888057053 -1.80898394264495 0.0710725718369071 . df.mm.exp4 0.0675129191015344 0.071186888057053 0.948389808070076 0.343403352771590 df.mm.exp5 -0.107232496642151 0.071186888057053 -1.50635179551898 0.132627900376740 df.mm.exp6 0.248666735475618 0.071186888057053 3.49315361666496 0.00052105602727941 *** df.mm.exp7 0.144512529744984 0.071186888057053 2.03004420742713 0.0428973166345597 * df.mm.exp8 0.170919270204531 0.071186888057053 2.40099370641890 0.0167261766154063 * df.mm.trans1:exp2 -0.212946938690206 0.0649844406457384 -3.27689115385455 0.00112480930116681 ** df.mm.trans2:exp2 -0.152500837316462 0.0581238507054685 -2.62372219778126 0.00897152490757088 ** df.mm.trans1:exp3 0.137402910282776 0.0649844406457384 2.11439706054908 0.0349910128474268 * df.mm.trans2:exp3 0.119982591234548 0.0581238507054685 2.06425743955845 0.0395245076562107 * df.mm.trans1:exp4 -0.0525141016889593 0.0649844406457384 -0.808102696078266 0.419427645056462 df.mm.trans2:exp4 -0.0660117982497123 0.0581238507054685 -1.13570930777134 0.256639145384232 df.mm.trans1:exp5 0.0821963236822589 0.0649844406457384 1.26486160172326 0.206528360636365 df.mm.trans2:exp5 0.0749220320756868 0.0581238507054685 1.28900668428422 0.198010219241705 df.mm.trans1:exp6 -0.144080547822356 0.0649844406457384 -2.21715454331304 0.0270754452235897 * df.mm.trans2:exp6 -0.147676821794853 0.0581238507054685 -2.54072674130242 0.0113728312711966 * df.mm.trans1:exp7 -0.117864028351821 0.0649844406457384 -1.81372690417318 0.0703376522594952 . df.mm.trans2:exp7 -0.0804995125655738 0.0581238507054685 -1.38496523524378 0.16669981345988 df.mm.trans1:exp8 -0.105102866873548 0.0649844406457384 -1.61735433634821 0.106451982221061 df.mm.trans2:exp8 -0.0925885286838207 0.0581238507054685 -1.59295242073680 0.111822346875527 df.mm.trans1:probe2 -0.0344311866319673 0.0355934440285265 -0.967346306931477 0.333853061910980 df.mm.trans1:probe3 -0.0816042386239862 0.0355934440285265 -2.29267610514409 0.0222938872881691 * df.mm.trans1:probe4 -0.0793808294431679 0.0355934440285265 -2.23020928740551 0.0261903514312869 * df.mm.trans1:probe5 0.0667597389394182 0.0355934440285265 1.87561897314329 0.0613081049902868 . df.mm.trans1:probe6 -0.0294368728978095 0.0355934440285265 -0.827030755276652 0.408626334103745 df.mm.trans1:probe7 0.00728269054199413 0.0355934440285265 0.204607638871849 0.83796452182051 df.mm.trans1:probe8 0.0075567335014737 0.0355934440285265 0.212306892679936 0.831956814523478 df.mm.trans1:probe9 -0.00184547859084978 0.0355934440285265 -0.0518488345598341 0.958670491004273 df.mm.trans1:probe10 0.0249615483982252 0.0355934440285265 0.701296238099905 0.483454508644893 df.mm.trans1:probe11 -0.0363563982470267 0.0355934440285265 -1.02143524571235 0.307557492472958 df.mm.trans1:probe12 0.0323871264307773 0.0355934440285265 0.909918309810663 0.363317562140486 df.mm.trans2:probe2 0.0819889475578454 0.0355934440285265 2.30348452631150 0.0216736723475391 * df.mm.trans2:probe3 0.105238034698587 0.0355934440285265 2.95666906001689 0.00326142217446934 ** df.mm.trans2:probe4 0.0613963470523474 0.0355934440285265 1.72493414807348 0.0851764048588641 . df.mm.trans2:probe5 -0.0110806090214527 0.0355934440285265 -0.311310392233246 0.755698431611115 df.mm.trans2:probe6 0.0359572417970532 0.0355934440285265 1.01022092069076 0.312893178252757 df.mm.trans3:probe2 -0.00855096850115749 0.0355934440285265 -0.240239986170045 0.810245725251624 df.mm.trans3:probe3 -0.232348876140236 0.0355934440285265 -6.52785597128559 1.68461131167969e-10 *** df.mm.trans3:probe4 -0.235030722881822 0.0355934440285265 -6.60320262050099 1.05882770674574e-10 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.92212613736316 0.0796906497825609 49.2168924216936 9.86939955633913e-191 *** df.mm.trans1 -0.0583237755030114 0.0693084318050286 -0.841510534635697 0.400476705170438 df.mm.trans2 -0.0550461642668416 0.0650671430793698 -0.845990182782353 0.397975412378124 df.mm.exp2 -0.0656462706959538 0.0884088381434051 -0.742530634657489 0.458125366386416 df.mm.exp3 0.0374142206942228 0.088408838143405 0.423195479998668 0.672340233587708 df.mm.exp4 0.0765192081674502 0.088408838143405 0.865515368987554 0.387183903896798 df.mm.exp5 0.060549406506937 0.088408838143405 0.684879563836386 0.49374708999331 df.mm.exp6 -0.0488915307116983 0.0884088381434051 -0.553016324367853 0.580507036217263 df.mm.exp7 0.0744179347076387 0.088408838143405 0.841747683494356 0.400344051717631 df.mm.exp8 -0.0380227770747239 0.0884088381434051 -0.430078913751229 0.667329266144914 df.mm.trans1:exp2 0.038619084442108 0.0807058582232768 0.478516495484954 0.632498272537166 df.mm.trans2:exp2 0.0822283741149487 0.072185514067883 1.13912569823388 0.255213039083214 df.mm.trans1:exp3 -0.0293598274003722 0.0807058582232769 -0.363788057604774 0.716174807680437 df.mm.trans2:exp3 0.00608613062513872 0.072185514067883 0.0843123541298791 0.932842879804005 df.mm.trans1:exp4 -0.0744961244941247 0.0807058582232768 -0.923057212129849 0.35643636463302 df.mm.trans2:exp4 -0.00824918516018323 0.072185514067883 -0.114277570322845 0.909065054021978 df.mm.trans1:exp5 -0.0366635569219522 0.0807058582232768 -0.454286190979106 0.649826091009998 df.mm.trans2:exp5 0.0383209486324008 0.072185514067883 0.530867572631871 0.5957535536923 df.mm.trans1:exp6 0.0523421176049878 0.0807058582232768 0.648554129245249 0.516933561233121 df.mm.trans2:exp6 0.0629017487720892 0.072185514067883 0.871390189352072 0.383972272020688 df.mm.trans1:exp7 -0.0694914976899929 0.0807058582232768 -0.861046511614326 0.389637898194296 df.mm.trans2:exp7 -0.0662975843643762 0.072185514067883 -0.918433361879646 0.358848546478904 df.mm.trans1:exp8 0.0132932559624897 0.0807058582232769 0.164712404466517 0.869238978328792 df.mm.trans2:exp8 0.0242730802397506 0.072185514067883 0.336259712951885 0.736820459353355 df.mm.trans1:probe2 -0.0104313649595902 0.0442044190717025 -0.235980139059622 0.813547700167725 df.mm.trans1:probe3 -0.0233551244190642 0.0442044190717025 -0.528343656800028 0.597502502627755 df.mm.trans1:probe4 -0.00702987935221853 0.0442044190717025 -0.159031144393405 0.873710536937263 df.mm.trans1:probe5 -0.0193354077122098 0.0442044190717025 -0.437408931465574 0.662009513919595 df.mm.trans1:probe6 -0.00441902112679893 0.0442044190717025 -0.0999678588611464 0.920411150509508 df.mm.trans1:probe7 -0.0380477268474209 0.0442044190717025 -0.860722245567913 0.389816331681711 df.mm.trans1:probe8 0.0087052024502435 0.0442044190717025 0.196930592756418 0.843964350054668 df.mm.trans1:probe9 -0.0470157272884096 0.0442044190717025 -1.06359789984225 0.288040155416550 df.mm.trans1:probe10 -0.0643470976803133 0.0442044190717025 -1.45567115305685 0.146130521070454 df.mm.trans1:probe11 0.025794694718982 0.0442044190717025 0.583532037309239 0.559806454061851 df.mm.trans1:probe12 -0.0280509779697528 0.0442044190717025 -0.634574066548692 0.526005459246971 df.mm.trans2:probe2 -0.0354744514186436 0.0442044190717025 -0.802509164549854 0.42265154962704 df.mm.trans2:probe3 -0.0884988097320842 0.0442044190717025 -2.00203535281242 0.045837289020618 * df.mm.trans2:probe4 -0.0180551038514602 0.0442044190717025 -0.408445676487087 0.683126775651834 df.mm.trans2:probe5 -0.0445625694078811 0.0442044190717025 -1.00810213873861 0.313908104684123 df.mm.trans2:probe6 -0.0375625735767652 0.0442044190717025 -0.849747024518888 0.395885009871316 df.mm.trans3:probe2 0.045653281250887 0.0442044190717025 1.03277641035921 0.302223256051130 df.mm.trans3:probe3 0.0434147150831503 0.0442044190717025 0.982135180030954 0.326522924533514 df.mm.trans3:probe4 0.104143911695971 0.0442044190717025 2.35596155051926 0.0188718432400501 *