chr5.18556_chr5_137013308_137014111_+_2.R fitVsDatCorrelation=0.924085958377606 cont.fitVsDatCorrelation=0.307615865847968 fstatistic=14854.9748115320,52,692 cont.fstatistic=2385.41530668576,52,692 residuals=-0.515045891276749,-0.067164725684311,0.000833799085256705,0.0683530788262975,0.425027673292767 cont.residuals=-0.58539261737422,-0.197238506344119,-0.0860100942565643,0.118826313926597,0.918233221718873 predictedValues: Include Exclude Both chr5.18556_chr5_137013308_137014111_+_2.R.tl.Lung 61.0755345588681 48.2514772775382 49.7491642105366 chr5.18556_chr5_137013308_137014111_+_2.R.tl.cerebhem 59.2579546076951 51.2917625494215 52.0506245270588 chr5.18556_chr5_137013308_137014111_+_2.R.tl.cortex 56.5899093296875 46.3369558714966 48.8061711804055 chr5.18556_chr5_137013308_137014111_+_2.R.tl.heart 60.2276843844032 47.2313194671591 49.4768180465382 chr5.18556_chr5_137013308_137014111_+_2.R.tl.kidney 60.2398913685723 47.5008581288406 49.3546925525251 chr5.18556_chr5_137013308_137014111_+_2.R.tl.liver 60.2465500034703 50.7570142619444 50.7252059216778 chr5.18556_chr5_137013308_137014111_+_2.R.tl.stomach 61.3417089769737 49.1544484040896 49.5201663360203 chr5.18556_chr5_137013308_137014111_+_2.R.tl.testicle 61.6479179003265 48.1643936633339 48.42372422281 diffExp=12.8240572813299,7.96619205827363,10.2529534581909,12.9963649172441,12.7390332397317,9.48953574152586,12.1872605728842,13.4835242369927 diffExpScore=0.989240245272982 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=1,0,1,1,1,0,1,1 diffExp1.2Score=0.857142857142857 cont.predictedValues: Include Exclude Both Lung 53.8892004591318 53.873088787753 57.1819316941338 cerebhem 56.5902526842782 69.429251152071 54.8703552370244 cortex 55.8384392390906 55.98946978796 44.9934101320412 heart 55.1852468674449 54.07600695271 67.0409561647876 kidney 55.9958990945958 53.1540653376416 50.5666820211837 liver 51.6471766113295 63.7700651469933 55.896492900947 stomach 58.8469193399415 54.5714927345562 57.3859593984857 testicle 61.5484956667277 58.1663438631951 51.8362686276293 cont.diffExp=0.0161116713788019,-12.8389984677928,-0.151030548869329,1.10923991473498,2.84183375695421,-12.1228885356638,4.27542660538527,3.38215180353258 cont.diffExpScore=2.53570481170965 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,-1,0,0 cont.diffExp1.2Score=0.666666666666667 tran.correlation=0.276536403522791 cont.tran.correlation=-0.121197698429975 tran.covariance=0.000283362769755913 cont.tran.covariance=-0.000636967247455302 tran.mean=54.3322112971138 cont.tran.mean=57.0357133578388 weightedLogRatios: wLogRatio Lung 0.941388968331852 cerebhem 0.578882010150437 cortex 0.786747501687177 heart 0.966610349950036 kidney 0.945487287383007 liver 0.687766830913877 stomach 0.887236218473315 testicle 0.9867914169611 cont.weightedLogRatios: wLogRatio Lung 0.00119213687009789 cerebhem -0.8461179295088 cortex -0.0108688264203761 heart 0.0812312584876306 kidney 0.208295706118493 liver -0.853906243696644 stomach 0.30451924135884 testicle 0.231249215294553 varWeightedLogRatios=0.0221351514869866 cont.varWeightedLogRatios=0.220516162799276 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.11226220930667 0.0669265462505268 61.4444109204918 1.88525250931800e-282 *** df.mm.trans1 0.0332615964308485 0.0601098258055421 0.553347077372195 0.580204496413976 df.mm.trans2 -0.262744473658714 0.0552791484911573 -4.75304849713349 2.43822496878767e-06 *** df.mm.exp2 -0.0143307528000524 0.0757187435122281 -0.189262950430999 0.849942228205314 df.mm.exp3 -0.097630399270851 0.0757187435122282 -1.28938218916805 0.197696046439627 df.mm.exp4 -0.0298590473074742 0.0757187435122281 -0.394341558278132 0.693450380745806 df.mm.exp5 -0.0214944420121273 0.0757187435122282 -0.283872143343954 0.776593277843822 df.mm.exp6 0.0175280341377150 0.0757187435122282 0.231488708405261 0.817003588147 df.mm.exp7 0.0275032304843521 0.0757187435122281 0.363228828274343 0.716544881753905 df.mm.exp8 0.0345254696062227 0.0757187435122282 0.455969922436008 0.648554662330104 df.mm.trans1:exp2 -0.0158805908182700 0.0724951776038566 -0.219057202743168 0.826670081360427 df.mm.trans2:exp2 0.0754344735306757 0.0630989529268568 1.19549485421918 0.232303259666050 df.mm.trans1:exp3 0.0213497185875719 0.0724951776038566 0.294498465873627 0.76846535599589 df.mm.trans2:exp3 0.057143780486756 0.0630989529268568 0.905621691583315 0.365451325325158 df.mm.trans1:exp4 0.0158797978035457 0.0724951776038566 0.219046263881433 0.826678599035688 df.mm.trans2:exp4 0.0084898234140061 0.0630989529268568 0.134547770132531 0.893008562312774 df.mm.trans1:exp5 0.00771785258722082 0.0724951776038566 0.106460220421755 0.915248069787765 df.mm.trans2:exp5 0.00581577429251528 0.0630989529268568 0.092169109355219 0.926590356018613 df.mm.trans1:exp6 -0.0311940943640004 0.0724951776038566 -0.430291991757821 0.667117223861047 df.mm.trans2:exp6 0.0330953418244433 0.0630989529268568 0.52449906518745 0.60009943769844 df.mm.trans1:exp7 -0.0231545810640486 0.0724951776038566 -0.319394776719836 0.749523565503651 df.mm.trans2:exp7 -0.00896232575839445 0.0630989529268568 -0.142036045650130 0.88709287551377 df.mm.trans1:exp8 -0.0251973830768535 0.0724951776038566 -0.347573230519447 0.72826640265802 df.mm.trans2:exp8 -0.0363318866833084 0.0630989529268568 -0.575792227890432 0.564942823280573 df.mm.trans1:probe2 -0.0632741348654544 0.0362475888019283 -1.74560948622570 0.0813226456551066 . df.mm.trans1:probe3 -0.314267037220366 0.0362475888019283 -8.67001220240192 3.05463417515707e-17 *** df.mm.trans1:probe4 -0.172088443179552 0.0362475888019283 -4.74758318739251 2.50287998492197e-06 *** df.mm.trans1:probe5 -0.2176565336748 0.0362475888019283 -6.00471757898614 3.09460559006837e-09 *** df.mm.trans1:probe6 -0.206112318252454 0.0362475888019283 -5.6862352797792 1.91598431337396e-08 *** df.mm.trans1:probe7 -0.259324108285074 0.0362475888019283 -7.1542443747673 2.14862231707057e-12 *** df.mm.trans1:probe8 0.185442317538924 0.0362475888019283 5.11599043324667 4.04651150528734e-07 *** df.mm.trans1:probe9 -0.331141312067997 0.0362475888019283 -9.1355404045629 7.08364608670903e-19 *** df.mm.trans1:probe10 -0.228019395105852 0.0362475888019283 -6.29060863473825 5.60593231733594e-10 *** df.mm.trans1:probe11 -0.385877619124706 0.0362475888019283 -10.6456079391460 1.29940655394966e-24 *** df.mm.trans1:probe12 -0.242699363083583 0.0362475888019283 -6.6956002069487 4.44483913735183e-11 *** df.mm.trans1:probe13 -0.33249570783137 0.0362475888019283 -9.17290553168275 5.20249509033901e-19 *** df.mm.trans1:probe14 -0.305090392700332 0.0362475888019283 -8.4168465485379 2.21803179796638e-16 *** df.mm.trans1:probe15 -0.321569625711772 0.0362475888019283 -8.87147631995497 6.10394890776844e-18 *** df.mm.trans1:probe16 -0.312934792764076 0.0362475888019283 -8.63325818647083 4.08504062785356e-17 *** df.mm.trans1:probe17 0.384557969448221 0.0362475888019283 10.6092013885283 1.81741408751776e-24 *** df.mm.trans1:probe18 0.568257080762235 0.0362475888019283 15.6771001753365 1.26447296863217e-47 *** df.mm.trans1:probe19 0.319526171850062 0.0362475888019283 8.81510142912082 9.60640012469408e-18 *** df.mm.trans1:probe20 0.240152572364422 0.0362475888019283 6.62533923778254 6.96575800458121e-11 *** df.mm.trans1:probe21 0.552707761109188 0.0362475888019283 15.248124892649 1.78516256438827e-45 *** df.mm.trans1:probe22 0.606596007465542 0.0362475888019283 16.7347960930652 4.85677295972787e-53 *** df.mm.trans2:probe2 -0.0421880165406623 0.0362475888019283 -1.16388476958274 0.244871841627060 df.mm.trans2:probe3 -0.000456714094463852 0.0362475888019283 -0.0125998475915053 0.989950673709953 df.mm.trans2:probe4 0.101742953506517 0.0362475888019283 2.80688886818051 0.00514299192393577 ** df.mm.trans2:probe5 0.112945223528345 0.0362475888019283 3.11593756333765 0.00190942641009087 ** df.mm.trans2:probe6 0.0701349329748154 0.0362475888019283 1.93488547219131 0.0534115515020769 . df.mm.trans3:probe2 -0.0382668966111304 0.0362475888019283 -1.05570874852494 0.291469727049708 df.mm.trans3:probe3 0.110909891400542 0.0362475888019283 3.0597867352391 0.00230053966327281 ** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.8963206337 0.166624464367782 23.3838449142729 1.43321700969154e-89 *** df.mm.trans1 0.0710754292677515 0.149653136000728 0.474934446194335 0.634983552265289 df.mm.trans2 0.0560635644925127 0.137626383312342 0.407360588451104 0.683869150125852 df.mm.exp2 0.343848597020231 0.188514061865656 1.82399442045482 0.0685840580094668 . df.mm.exp3 0.313786904344786 0.188514061865656 1.66452784073161 0.0964596754746305 . df.mm.exp4 -0.131540674077131 0.188514061865656 -0.697776456436831 0.48555138667931 df.mm.exp5 0.147856946990288 0.188514061865656 0.784328476756592 0.433115791295397 df.mm.exp6 0.148894573589328 0.188514061865656 0.789832716539934 0.429896024986432 df.mm.exp7 0.0973282572194284 0.188514061865656 0.516291762302534 0.605815583938213 df.mm.exp8 0.307719044862488 0.188514061865656 1.63234000592372 0.103062805853419 df.mm.trans1:exp2 -0.294941936000726 0.180488473023434 -1.63413170414729 0.102686019836983 df.mm.trans2:exp2 -0.0901714048241725 0.157095051554713 -0.573992649238652 0.566159289224542 df.mm.trans1:exp3 -0.278254492171043 0.180488473023434 -1.54167458735670 0.123609831329730 df.mm.trans2:exp3 -0.275254343649358 0.157095051554713 -1.75215158545903 0.0801906499051153 . df.mm.trans1:exp4 0.155306229443506 0.180488473023434 0.860477275040948 0.389824026292378 df.mm.trans2:exp4 0.135300194294852 0.157095051554713 0.861263247669706 0.389391395961698 df.mm.trans1:exp5 -0.109508584690665 0.180488473023434 -0.606734506953511 0.544226118213776 df.mm.trans2:exp5 -0.161293429976444 0.157095051554713 -1.02672508382779 0.304908686785838 df.mm.trans1:exp6 -0.191389138684040 0.180488473023434 -1.06039535643470 0.289334733710989 df.mm.trans2:exp6 0.0197582354730878 0.157095051554713 0.125772487914467 0.899948551253457 df.mm.trans1:exp7 -0.0093188678482741 0.180488473023434 -0.0516313739718113 0.958837319857026 df.mm.trans2:exp7 -0.0844476947621014 0.157095051554713 -0.537557955685764 0.591055082628878 df.mm.trans1:exp8 -0.174823728664126 0.180488473023434 -0.968614370411499 0.3330760401407 df.mm.trans2:exp8 -0.231043214390761 0.157095051554713 -1.47072241998847 0.141820746921679 df.mm.trans1:probe2 -0.0138585335456744 0.0902442365117171 -0.153566965397010 0.87799595640621 df.mm.trans1:probe3 -0.0567751827465251 0.0902442365117171 -0.629128074446655 0.529472836817428 df.mm.trans1:probe4 -0.0624040229174027 0.0902442365117171 -0.69150147787333 0.489482373537807 df.mm.trans1:probe5 0.191844254429194 0.0902442365117171 2.12583386867355 0.0338705729821422 * df.mm.trans1:probe6 -0.0317613110381986 0.0902442365117171 -0.351948359982799 0.724984138414313 df.mm.trans1:probe7 -0.0687671442830521 0.0902442365117171 -0.762011480634816 0.446312784146721 df.mm.trans1:probe8 0.0642145122619484 0.0902442365117171 0.711563582829037 0.476974858868281 df.mm.trans1:probe9 0.0550066790836328 0.0902442365117171 0.60953121451131 0.542372462990961 df.mm.trans1:probe10 0.142437523813754 0.0902442365117171 1.57835590747405 0.114940853504781 df.mm.trans1:probe11 0.0771040937840983 0.0902442365117171 0.854393552036836 0.393182646632434 df.mm.trans1:probe12 -0.0158172356246821 0.0902442365117171 -0.17527142160074 0.86091763775629 df.mm.trans1:probe13 -0.0209451168824922 0.0902442365117171 -0.232093679243136 0.81653387308414 df.mm.trans1:probe14 -0.00579436569157665 0.0902442365117171 -0.0642075983525477 0.948823469977084 df.mm.trans1:probe15 -0.0571875183487302 0.0902442365117171 -0.63369718177299 0.526487856444385 df.mm.trans1:probe16 0.0938562255068723 0.0902442365117171 1.04002459475278 0.298691708739245 df.mm.trans1:probe17 0.0526214292821477 0.0902442365117171 0.583100165907166 0.56001584299658 df.mm.trans1:probe18 -0.0634785507395725 0.0902442365117171 -0.70340836371673 0.482037887451031 df.mm.trans1:probe19 0.154056954710494 0.0902442365117171 1.70711128671903 0.088249956208514 . df.mm.trans1:probe20 0.0591540321019007 0.0902442365117171 0.655488199451056 0.51237133233151 df.mm.trans1:probe21 -0.0589421130107524 0.0902442365117171 -0.653139915512494 0.5138830183112 df.mm.trans1:probe22 0.0537861981707159 0.0902442365117171 0.596007016622412 0.551365431227642 df.mm.trans2:probe2 0.089406145787238 0.0902442365117171 0.990713083107858 0.322171982835513 df.mm.trans2:probe3 0.00101178805203593 0.0902442365117171 0.0112116639371707 0.99105780526832 df.mm.trans2:probe4 0.103983961696727 0.0902442365117171 1.15225044519299 0.249616073889528 df.mm.trans2:probe5 0.0193187498108131 0.0902442365117171 0.214071840569063 0.830554095743257 df.mm.trans2:probe6 0.0945012266368083 0.090244236511717 1.04717187811255 0.295385926817542 df.mm.trans3:probe2 0.0924573246496734 0.0902442365117171 1.02452331831373 0.305946166380341 df.mm.trans3:probe3 -0.0241222999940619 0.0902442365117171 -0.267300172581436 0.789317696769827