chr7.20893_chr7_131445845_131446335_-_0.R fitVsDatCorrelation=0.932849073108609 cont.fitVsDatCorrelation=0.365900402059154 fstatistic=8089.76984759843,37,347 cont.fstatistic=1204.32564499633,37,347 residuals=-0.524106485014081,-0.0860505021467765,-0.000355147817644578,0.0910317918741887,0.634523731377674 cont.residuals=-0.826903352102854,-0.302137558001016,-0.0220508809270111,0.246922043020964,1.09594088473400 predictedValues: Include Exclude Both chr7.20893_chr7_131445845_131446335_-_0.R.tl.Lung 55.099883653617 80.0471495471652 74.0823253914426 chr7.20893_chr7_131445845_131446335_-_0.R.tl.cerebhem 50.7519095984913 78.1560591607126 67.7844908186355 chr7.20893_chr7_131445845_131446335_-_0.R.tl.cortex 49.3417683613488 142.128475867742 119.855557748453 chr7.20893_chr7_131445845_131446335_-_0.R.tl.heart 49.1472347023674 95.5676351936634 74.0221437230943 chr7.20893_chr7_131445845_131446335_-_0.R.tl.kidney 53.803325540889 85.6906578836292 79.4549763585851 chr7.20893_chr7_131445845_131446335_-_0.R.tl.liver 49.8948574885932 74.9986740298893 63.7726108277114 chr7.20893_chr7_131445845_131446335_-_0.R.tl.stomach 51.2110553852508 97.424182727331 74.5391130233823 chr7.20893_chr7_131445845_131446335_-_0.R.tl.testicle 49.4909321106022 128.374016437905 109.813468305222 diffExp=-24.9472658935482,-27.4041495622213,-92.7867075063933,-46.420400491296,-31.8873323427402,-25.1038165412961,-46.2131273420802,-78.8830843273026 diffExpScore=0.997330812794992 diffExp1.5=0,-1,-1,-1,-1,-1,-1,-1 diffExp1.5Score=0.875 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 58.2410823424845 74.7456865192759 75.8831103106811 cerebhem 60.1624974210712 69.8649125352368 66.8017177659277 cortex 86.3291267234564 69.4054797257497 83.9274717207471 heart 70.0079290066865 70.2599728885017 76.3034381006094 kidney 62.8438275201228 71.8862563264339 71.9419104976102 liver 69.9315689962847 78.0390274831304 65.9161618372082 stomach 71.5780568174054 85.8881984788403 67.9924527151432 testicle 76.129855594524 80.6887025928092 82.897032139593 cont.diffExp=-16.5046041767913,-9.70241511416565,16.9236469977067,-0.252043881815169,-9.0424288063111,-8.10745848684566,-14.3101416614349,-4.55884699828523 cont.diffExpScore=1.70556961547479 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=-1,0,1,0,0,0,0,0 cont.diffExp1.2Score=2 tran.correlation=-0.501561719482608 cont.tran.correlation=0.0955754595527853 tran.covariance=-0.00501929496381092 cont.tran.covariance=0.00123129926617785 tran.mean=74.4454886055749 cont.tran.mean=72.2501363107508 weightedLogRatios: wLogRatio Lung -1.56702850068871 cerebhem -1.78870072597097 cortex -4.68438566312784 heart -2.81123036588238 kidney -1.96311159155953 liver -1.67654632018473 stomach -2.73808887622161 testicle -4.17327956611755 cont.weightedLogRatios: wLogRatio Lung -1.04524280809401 cerebhem -0.623744980345502 cortex 0.948971617824761 heart -0.0152749105218311 kidney -0.565673815715911 liver -0.471934280437692 stomach -0.79499381295767 testicle -0.253657534035128 varWeightedLogRatios=1.40311896007042 cont.varWeightedLogRatios=0.375184785803466 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.97833998782824 0.083700011053702 47.530937424557 5.4001749920317e-154 *** df.mm.trans1 0.095224000788861 0.0697335955132946 1.36553981030143 0.172967966225511 df.mm.trans2 0.330652131967068 0.0697335955132946 4.74164754496317 3.09999901788666e-06 *** df.mm.exp2 -0.0172630436044883 0.0960782455173395 -0.179676923860697 0.857511085451297 df.mm.exp3 -0.017371428270296 0.0960782455173394 -0.180805011340064 0.856626182777475 df.mm.exp4 0.0637040585014566 0.0960782455173394 0.663043524144701 0.507742879470681 df.mm.exp5 -0.0256978925910004 0.0960782455173394 -0.267468379055305 0.789267459988853 df.mm.exp6 -0.0145218808124902 0.0960782455173394 -0.151146398795026 0.879948060972684 df.mm.exp7 0.117119447148135 0.0960782455173394 1.21900068550897 0.223671950122973 df.mm.exp8 -0.0286321689103537 0.0960782455173394 -0.298008865130519 0.765874749837342 df.mm.trans1:exp2 -0.0649353162320724 0.0812009379858305 -0.799686775088775 0.424439379373591 df.mm.trans2:exp2 -0.006645200490319 0.0812009379858304 -0.081836499123675 0.93482391418377 df.mm.trans1:exp3 -0.0930052255585908 0.0812009379858304 -1.14537132040051 0.252844699359370 df.mm.trans2:exp3 0.591487006051709 0.0812009379858304 7.28423859038332 2.19169300273377e-12 *** df.mm.trans1:exp4 -0.178031080511793 0.0812009379858304 -2.19247566503308 0.0290087720243248 * df.mm.trans2:exp4 0.113514329834058 0.0812009379858304 1.39794357860579 0.163022956900524 df.mm.trans1:exp5 0.00188556626903045 0.0812009379858304 0.0232209912323855 0.981487341772943 df.mm.trans2:exp5 0.0938258723233033 0.0812009379858304 1.15547769090643 0.248689864676436 df.mm.trans1:exp6 -0.0847077826885627 0.0812009379858304 -1.04318724376490 0.297587792331737 df.mm.trans2:exp6 -0.050623515812509 0.0812009379858304 -0.6234351113203 0.533408196249205 df.mm.trans1:exp7 -0.190311617525085 0.0812009379858304 -2.34371205857615 0.0196567316071821 * df.mm.trans2:exp7 0.0793391849012465 0.0812009379858304 0.977072271198286 0.329214047358980 df.mm.trans1:exp8 -0.0787259725881227 0.0812009379858304 -0.969520482655759 0.332960846113063 df.mm.trans2:exp8 0.5009643450935 0.0812009379858304 6.16944037248582 1.90936270152215e-09 *** df.mm.trans1:probe2 -0.00411970730727115 0.0444755854254174 -0.09262851220204 0.926252146197458 df.mm.trans1:probe3 -0.208838514154415 0.0444755854254174 -4.69557650915294 3.83487231180765e-06 *** df.mm.trans1:probe4 -0.195219114395332 0.0444755854254174 -4.38935457573011 1.51092739081277e-05 *** df.mm.trans1:probe5 -0.219286690240253 0.0444755854254174 -4.93049586964924 1.27378727402138e-06 *** df.mm.trans1:probe6 -0.0166998140033869 0.0444755854254174 -0.375482724817448 0.707530911393088 df.mm.trans2:probe2 -0.0425691367500780 0.0444755854254174 -0.957134939155857 0.339165511701308 df.mm.trans2:probe3 0.143416587577232 0.0444755854254174 3.22461382363887 0.00138124610352104 ** df.mm.trans2:probe4 0.175744812068817 0.0444755854254174 3.95148957316208 9.41144632009523e-05 *** df.mm.trans2:probe5 0.180013268704716 0.0444755854254174 4.04746260184897 6.38783506451993e-05 *** df.mm.trans2:probe6 0.279631574481662 0.0444755854254174 6.28730508675565 9.70765608695556e-10 *** df.mm.trans3:probe2 -0.291277800335158 0.0444755854254174 -6.54916169284858 2.08747221212074e-10 *** df.mm.trans3:probe3 0.0725658077785798 0.0444755854254174 1.63158746724690 0.103673596154787 df.mm.trans3:probe4 -0.177444569306057 0.0444755854254174 -3.9897073328831 8.07291225362755e-05 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.08561788876587 0.216216480200499 18.895959664949 2.91656824439469e-55 *** df.mm.trans1 -0.060667210538425 0.180137999789941 -0.3367818595142 0.736484939867666 df.mm.trans2 0.251743616555385 0.180137999789941 1.39750422925170 0.163154837819260 df.mm.exp2 0.0923955941300929 0.248192321698381 0.372274184381810 0.709915970970966 df.mm.exp3 0.218691516655028 0.248192321698381 0.881137317861086 0.378853398613255 df.mm.exp4 0.116604411567981 0.248192321698381 0.469814741931002 0.638782485938655 df.mm.exp5 0.0903904634067533 0.248192321698381 0.364195244994732 0.715934036867668 df.mm.exp6 0.366854213704197 0.248192321698381 1.47810460530693 0.140286874427483 df.mm.exp7 0.454949922258198 0.248192321698381 1.83305397662979 0.067651114831747 . df.mm.exp8 0.255951461314799 0.248192321698381 1.03126260942854 0.303135926198931 df.mm.trans1:exp2 -0.05993739025994 0.209760796674336 -0.285741621934226 0.775246519151322 df.mm.trans2:exp2 -0.159923542687508 0.209760796674336 -0.762409111821773 0.446333797980902 df.mm.trans1:exp3 0.174884542085336 0.209760796674336 0.833733208769478 0.405004877682064 df.mm.trans2:exp3 -0.29281719885307 0.209760796674336 -1.39595769798531 0.163619707898563 df.mm.trans1:exp4 0.0674131076977137 0.209760796674336 0.321380871766882 0.748115267797789 df.mm.trans2:exp4 -0.178493655782274 0.209760796674336 -0.85093906302899 0.395390014568247 df.mm.trans1:exp5 -0.0143287307901022 0.209760796674336 -0.0683098606473556 0.94557831939354 df.mm.trans2:exp5 -0.129396871970212 0.209760796674336 -0.616878244275108 0.53771956514543 df.mm.trans1:exp6 -0.183928023463835 0.209760796674336 -0.876846514601068 0.381176646048695 df.mm.trans2:exp6 -0.323736664979303 0.209760796674336 -1.54336115285603 0.123654622340843 df.mm.trans1:exp7 -0.248752352186502 0.209760796674336 -1.18588580960008 0.236478791009048 df.mm.trans2:exp7 -0.315994994626692 0.209760796674336 -1.50645401636842 0.132860440052161 df.mm.trans1:exp8 0.0118980592810212 0.209760796674336 0.056722035145078 0.954799267625784 df.mm.trans2:exp8 -0.179444393670969 0.209760796674336 -0.855471549097735 0.392880442308448 df.mm.trans1:probe2 0.179605917723991 0.114890720018788 1.56327610876335 0.118899162524130 df.mm.trans1:probe3 0.221614698395070 0.114890720018788 1.92891730819364 0.0545564352807903 . df.mm.trans1:probe4 -0.0263706307230676 0.114890720018788 -0.229527943760429 0.818593836666251 df.mm.trans1:probe5 0.0768324045186465 0.114890720018788 0.668743345903672 0.504103845244419 df.mm.trans1:probe6 -0.0552792932588667 0.114890720018788 -0.48114672142212 0.63071547514107 df.mm.trans2:probe2 0.0247926521851682 0.114890720018788 0.215793339802499 0.829275629009647 df.mm.trans2:probe3 -0.0544873136329106 0.114890720018788 -0.474253391605521 0.635617513118971 df.mm.trans2:probe4 -0.180801063901193 0.114890720018788 -1.57367856926674 0.116473064830710 df.mm.trans2:probe5 0.0550727036484174 0.114890720018788 0.47934858132503 0.631992621418184 df.mm.trans2:probe6 -0.0772769797317658 0.114890720018788 -0.672612894401989 0.501641241970644 df.mm.trans3:probe2 -0.0876783417577543 0.114890720018788 -0.763145550340498 0.445895102609371 df.mm.trans3:probe3 -0.0160834909658682 0.114890720018788 -0.139989469673774 0.888749529868216 df.mm.trans3:probe4 0.313761189944815 0.114890720018788 2.73095329103608 0.00663769791444484 **