chr7.22076_chr7_91899109_91901887_+_1.R fitVsDatCorrelation=0.774574865604215 cont.fitVsDatCorrelation=0.316509757586138 fstatistic=5007.54966480276,39,393 cont.fstatistic=2220.60989067367,39,393 residuals=-0.752421396019709,-0.093351225200253,-0.00802174012130389,0.0776552546753757,1.10512786826024 cont.residuals=-0.561330693781573,-0.189459953920792,-0.0400687584143744,0.123944338001087,1.62780079352284 predictedValues: Include Exclude Both chr7.22076_chr7_91899109_91901887_+_1.R.tl.Lung 63.129756645342 64.439662168844 64.6966686024363 chr7.22076_chr7_91899109_91901887_+_1.R.tl.cerebhem 96.5915853494826 102.515078017276 64.0093906214789 chr7.22076_chr7_91899109_91901887_+_1.R.tl.cortex 55.7993981939537 56.3564886975873 62.6324814591108 chr7.22076_chr7_91899109_91901887_+_1.R.tl.heart 55.1275288950968 57.6501480063398 62.13368391334 chr7.22076_chr7_91899109_91901887_+_1.R.tl.kidney 55.2953432921147 59.8491243920402 63.9495607568537 chr7.22076_chr7_91899109_91901887_+_1.R.tl.liver 59.1963002643933 60.6275953530723 60.4615307011686 chr7.22076_chr7_91899109_91901887_+_1.R.tl.stomach 56.4476051049984 63.0980482147643 62.9288379582839 chr7.22076_chr7_91899109_91901887_+_1.R.tl.testicle 60.3076737962288 61.5466283377194 60.1873196201787 diffExp=-1.30990552350211,-5.92349266779364,-0.557090503633589,-2.52261911124305,-4.55378109992547,-1.43129508867901,-6.65044310976588,-1.23895454149052 diffExpScore=0.960297895444937 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 63.2265658602039 53.987583391774 58.2891507010503 cerebhem 67.8465993516554 54.6982645686041 61.1921548211551 cortex 64.8943830234146 56.8099040930249 64.4865213794134 heart 67.1799938721522 62.474861387858 67.9893993001607 kidney 66.1211206963112 76.6962513826287 59.6006519755201 liver 55.8133996618463 62.7476625512576 68.1008449123157 stomach 68.7903156616765 65.1654019028895 63.1897353094386 testicle 69.0000504584573 60.4666992107793 66.1940899190476 cont.diffExp=9.23898246842985,13.1483347830513,8.08447893038971,4.70513248429425,-10.5751306863175,-6.93426288941127,3.62491375878703,8.533351247678 cont.diffExpScore=2.10358164409420 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=0,1,0,0,0,0,0,0 cont.diffExp1.2Score=0.5 tran.correlation=0.989778560332392 cont.tran.correlation=0.0522436243301288 tran.covariance=0.0353805130556410 cont.tran.covariance=0.000330618240179663 tran.mean=64.2486227955784 cont.tran.mean=63.4949410671583 weightedLogRatios: wLogRatio Lung -0.0853410228094636 cerebhem -0.273798925969794 cortex -0.040002744129733 heart -0.180407158198188 kidney -0.320687999145101 liver -0.0977816608429869 stomach -0.455420592332798 testicle -0.0835722116847415 cont.weightedLogRatios: wLogRatio Lung 0.642582715885635 cerebhem 0.885266072906926 cortex 0.546336298684318 heart 0.302866534647816 kidney -0.632874549283107 liver -0.477864461305404 stomach 0.227580337197005 testicle 0.550249424945186 varWeightedLogRatios=0.0211270462402738 cont.varWeightedLogRatios=0.292565311174492 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.22534578138176 0.101960263926054 41.4411028245882 1.62493567645281e-145 *** df.mm.trans1 -0.149231400372604 0.0832502068861117 -1.79256491910892 0.0738114982545168 . df.mm.trans2 -0.0422225864649682 0.0832502068861117 -0.5071769554006 0.612315130083347 df.mm.exp2 0.900259875536924 0.113114756813917 7.95881899846124 1.87977385973003e-14 *** df.mm.exp3 -0.225035391657585 0.113114756813917 -1.98944326979182 0.0473450280205478 * df.mm.exp4 -0.206458076563871 0.113114756813917 -1.82520903884815 0.0687283599466379 . df.mm.exp5 -0.194791003736593 0.113114756813917 -1.72206535401071 0.0858444886880782 . df.mm.exp6 -0.0576099469382363 0.113114756813917 -0.50930531577776 0.610824075484457 df.mm.exp7 -0.105213672681379 0.113114756813917 -0.930149837606635 0.352864498156908 df.mm.exp8 -0.0194191077762005 0.113114756813917 -0.171676166073951 0.863780487417018 df.mm.trans1:exp2 -0.47496048385014 0.0923578121910342 -5.14261298078094 4.28333704873224e-07 *** df.mm.trans2:exp2 -0.435979300895298 0.0923578121910342 -4.72054599987181 3.27674274316506e-06 *** df.mm.trans1:exp3 0.101606238377958 0.0923578121910342 1.10013691281247 0.271945884491094 df.mm.trans2:exp3 0.0910034597010628 0.0923578121910342 0.985335810173047 0.32506537399696 df.mm.trans1:exp4 0.0709150473724989 0.0923578121910342 0.767829441713249 0.443049607488417 df.mm.trans2:exp4 0.0951215748756896 0.0923578121910342 1.02992451444106 0.303678870468478 df.mm.trans1:exp5 0.0622874630658486 0.0923578121910342 0.674414666049174 0.500444234652458 df.mm.trans2:exp5 0.120888489866572 0.0923578121910342 1.30891461153849 0.191328118232042 df.mm.trans1:exp6 -0.00672324621276859 0.0923578121910342 -0.0727956417900213 0.942005772918985 df.mm.trans2:exp6 -0.00336921049873432 0.0923578121910342 -0.0364799730396969 0.97091816945004 df.mm.trans1:exp7 -0.00666570024351711 0.0923578121910342 -0.072172565432036 0.942501293027999 df.mm.trans2:exp7 0.0841741944040549 0.0923578121910342 0.911392251582874 0.362647418636903 df.mm.trans1:exp8 -0.0263137738394032 0.0923578121910342 -0.284911186343126 0.775862264102193 df.mm.trans2:exp8 -0.0265151360606102 0.0923578121910342 -0.287091426611166 0.774193623566135 df.mm.trans1:probe2 0.0511454497288255 0.0565573784069583 0.904310828567913 0.366384608107485 df.mm.trans1:probe3 0.300776170148622 0.0565573784069583 5.31807128655059 1.76382687574912e-07 *** df.mm.trans1:probe4 0.445800656842679 0.0565573784069583 7.88227229407493 3.19641793004549e-14 *** df.mm.trans1:probe5 -0.019488413181173 0.0565573784069583 -0.344577732032490 0.73059616640905 df.mm.trans1:probe6 0.0507004150008869 0.0565573784069584 0.896442098784571 0.370565468065225 df.mm.trans2:probe2 0.046144011854461 0.0565573784069584 0.815879610303574 0.415063211364366 df.mm.trans2:probe3 -0.138283743318805 0.0565573784069583 -2.4450168521565 0.0149227844777584 * df.mm.trans2:probe4 -0.266913987424183 0.0565573784069584 -4.71934864985439 3.29504353117554e-06 *** df.mm.trans2:probe5 0.265915580619212 0.0565573784069583 4.7016956603932 3.5765498950303e-06 *** df.mm.trans2:probe6 -0.115588412021571 0.0565573784069584 -2.04373709102737 0.0416457580540629 * df.mm.trans3:probe2 0.087411748266185 0.0565573784069584 1.54554101919672 0.123020297643344 df.mm.trans3:probe3 -0.0596602790381703 0.0565573784069583 -1.05486287940868 0.292136102075948 df.mm.trans3:probe4 0.279673545072427 0.0565573784069584 4.94495241734928 1.13052975466676e-06 *** df.mm.trans3:probe5 0.471190263689665 0.0565573784069583 8.33118996957776 1.35138381904255e-15 *** df.mm.trans3:probe6 0.0362922163361353 0.0565573784069584 0.641688447349784 0.521449570649812 cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.07984654990419 0.152918778385478 26.6798269838366 3.09886546830324e-90 *** df.mm.trans1 0.07331438164857 0.124857659711387 0.587183692358472 0.557417521230107 df.mm.trans2 -0.130802285269170 0.124857659711387 -1.04761122042111 0.295461617818753 df.mm.exp2 0.0349995954608141 0.169648152753893 0.206306964695263 0.836657974685264 df.mm.exp3 -0.0240471408912961 0.169648152753893 -0.141747142547322 0.887352370127001 df.mm.exp4 0.0527252906870208 0.169648152753893 0.310792011767489 0.75612351295027 df.mm.exp5 0.373611882520563 0.169648152753893 2.20227498181226 0.0282260158512959 * df.mm.exp6 -0.129916974946886 0.169648152753893 -0.765802473165478 0.444253527156638 df.mm.exp7 0.191787124817603 0.169648152753893 1.13049934057240 0.258955325115995 df.mm.exp8 0.0735461803575426 0.169648152753893 0.433521846030562 0.664873558317643 df.mm.trans1:exp2 0.0355251107489714 0.138517136684259 0.256467261736349 0.797724257875947 df.mm.trans2:exp2 -0.0219216958223957 0.138517136684259 -0.158259810642526 0.874333362583534 df.mm.trans1:exp3 0.050083653958872 0.138517136684259 0.361570092753466 0.717867628411753 df.mm.trans2:exp3 0.0750037363177477 0.138517136684259 0.541476225347584 0.58848620232454 df.mm.trans1:exp4 0.00792564356023394 0.138517136684259 0.0572177836616704 0.954400791641214 df.mm.trans2:exp4 0.0932848844144935 0.138517136684259 0.673453744767557 0.501054518969605 df.mm.trans1:exp5 -0.328848219002915 0.138517136684259 -2.3740616278584 0.0180733135548849 * df.mm.trans2:exp5 -0.0225131320367400 0.138517136684259 -0.162529579918024 0.870972371055836 df.mm.trans1:exp6 0.0052063940933478 0.138517136684259 0.0375866424759808 0.970036343003297 df.mm.trans2:exp6 0.280284219150517 0.138517136684259 2.02346240948806 0.0437018443173877 * df.mm.trans1:exp7 -0.107448709239002 0.138517136684259 -0.775706976126173 0.438388553546779 df.mm.trans2:exp7 -0.00361252532373197 0.138517136684259 -0.0260799884419103 0.97920677597913 df.mm.trans1:exp8 0.0138364967999096 0.138517136684259 0.0998901445057233 0.92048247570802 df.mm.trans2:exp8 0.0397925239356991 0.138517136684259 0.28727509742281 0.774053099340607 df.mm.trans1:probe2 -0.0490523646148278 0.0848240763769467 -0.57828350994175 0.563403945913761 df.mm.trans1:probe3 -0.0758093807259008 0.0848240763769467 -0.893724800362271 0.372016119793462 df.mm.trans1:probe4 -0.0378349011685458 0.0848240763769467 -0.446039647993485 0.655814245526795 df.mm.trans1:probe5 0.0982938155251045 0.0848240763769467 1.15879617820181 0.247242911309447 df.mm.trans1:probe6 -0.0128336429906143 0.0848240763769467 -0.151297173382511 0.879818930099347 df.mm.trans2:probe2 0.0538484569983713 0.0848240763769467 0.634825149867545 0.525911855676003 df.mm.trans2:probe3 0.0905034097961785 0.0848240763769467 1.06695426183002 0.28664748008826 df.mm.trans2:probe4 0.147811428947434 0.0848240763769467 1.74256455549931 0.082191915192479 . df.mm.trans2:probe5 0.124667551150954 0.0848240763769467 1.46971893447974 0.142437962567684 df.mm.trans2:probe6 0.0596869727103537 0.0848240763769467 0.703656028568032 0.48206368781656 df.mm.trans3:probe2 -0.00589333773317232 0.0848240763769467 -0.0694771813014871 0.94464513277451 df.mm.trans3:probe3 0.00961284181591635 0.0848240763769467 0.113326807983127 0.909829331805987 df.mm.trans3:probe4 0.0606753476412141 0.0848240763769467 0.715308085072227 0.474843427158547 df.mm.trans3:probe5 0.117967852124354 0.0848240763769467 1.39073547467963 0.165092611077905 df.mm.trans3:probe6 0.0759813087529955 0.0848240763769467 0.895751678041796 0.370933720225426