chr3.15083_chr3_90250130_90251888_-_0.R fitVsDatCorrelation=0.789858151116041 cont.fitVsDatCorrelation=0.294353930594035 fstatistic=9439.09467729045,37,347 cont.fstatistic=3881.54625014654,37,347 residuals=-0.458464158522051,-0.0780468951342716,-4.94220494938311e-05,0.0870110688205487,0.482214607703123 cont.residuals=-0.60569088940348,-0.147328192150886,-0.0204864035873728,0.147921390706937,0.705493558573903 predictedValues: Include Exclude Both chr3.15083_chr3_90250130_90251888_-_0.R.tl.Lung 79.5058771854805 82.0088408644752 61.4571358593315 chr3.15083_chr3_90250130_90251888_-_0.R.tl.cerebhem 74.6415034559952 78.8458152829316 59.479264813488 chr3.15083_chr3_90250130_90251888_-_0.R.tl.cortex 77.7412878214486 73.0887941152571 73.2598101174246 chr3.15083_chr3_90250130_90251888_-_0.R.tl.heart 88.6261832367569 76.507703902319 97.4629239376158 chr3.15083_chr3_90250130_90251888_-_0.R.tl.kidney 85.8138540603306 81.391619655387 68.9194227495308 chr3.15083_chr3_90250130_90251888_-_0.R.tl.liver 81.8583056249666 91.7383715338508 72.6277893589006 chr3.15083_chr3_90250130_90251888_-_0.R.tl.stomach 73.10479041561 76.5820866707893 65.913210491837 chr3.15083_chr3_90250130_90251888_-_0.R.tl.testicle 95.538376207969 84.1659222048921 94.7628338196422 diffExp=-2.50296367899470,-4.20431182693633,4.65249370619145,12.1184793344378,4.42223440494361,-9.88006590888412,-3.47729625517934,11.3724540030768 diffExpScore=3.89824505026437 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 84.891109813801 81.9178919148092 84.4319888772254 cerebhem 79.3566393152996 73.562934790341 74.502943576427 cortex 75.4636241630135 79.8845077437025 80.1659162854021 heart 84.802354257992 78.3435962391055 78.4108394877442 kidney 77.0709642417137 80.3013157338073 72.0531249177524 liver 83.6476527399208 77.0355291090725 79.4360144427796 stomach 69.5797493014171 86.1425584048396 71.5189535664901 testicle 84.404317794513 76.617505397393 78.4303891237634 cont.diffExp=2.97321789899182,5.79370452495853,-4.42088358068894,6.45875801888647,-3.23035149209362,6.61212363084826,-16.5628091034225,7.78681239711992 cont.diffExpScore=8.39841720408669 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,-1,0 cont.diffExp1.2Score=0.5 tran.correlation=0.327983714955001 cont.tran.correlation=-0.573566941841112 tran.covariance=0.00219349599464276 cont.tran.covariance=-0.00197280675631532 tran.mean=81.3224582649037 cont.tran.mean=79.5638906850463 weightedLogRatios: wLogRatio Lung -0.136114121530760 cerebhem -0.237826559560563 cortex 0.266749561028384 heart 0.648562011604632 kidney 0.234156985116714 liver -0.508445249872554 stomach -0.200520989779557 testicle 0.569833744094449 cont.weightedLogRatios: wLogRatio Lung 0.157707933631240 cerebhem 0.328719253023549 cortex -0.247771194494105 heart 0.348620461677476 kidney -0.179234783435665 liver 0.361126227182190 stomach -0.928692969242214 testicle 0.424652290892379 varWeightedLogRatios=0.170645268804282 cont.varWeightedLogRatios=0.216057976327798 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.58891893496901 0.0786094744860004 58.3761558638362 1.61895574798724e-181 *** df.mm.trans1 -0.265567655703846 0.065492479968758 -4.05493357146546 6.19604224010464e-05 *** df.mm.trans2 -0.0919396244970361 0.065492479968758 -1.40381956128237 0.161266896687154 df.mm.exp2 -0.0697548708032492 0.0902348792380587 -0.77303667265095 0.440026929978308 df.mm.exp3 -0.313268663431075 0.0902348792380586 -3.47170258414827 0.000582492057412241 *** df.mm.exp4 -0.421971310945969 0.0902348792380586 -4.67636588544348 4.18851875162091e-06 *** df.mm.exp5 -0.0458033069479748 0.0902348792380586 -0.507600911473889 0.612055722136865 df.mm.exp6 -0.0257351603510697 0.0902348792380586 -0.285201914917788 0.775659604782999 df.mm.exp7 -0.222399841970683 0.0902348792380586 -2.46467711652770 0.0141975202127615 * df.mm.exp8 -0.223377206026781 0.0902348792380586 -2.47550844986965 0.0137814614172606 * df.mm.trans1:exp2 0.00662062411546442 0.0762623921129591 0.0868137483237874 0.93086963252628 df.mm.trans2:exp2 0.0304220540594094 0.0762623921129591 0.398912927021075 0.69020273729929 df.mm.trans1:exp3 0.290824208679281 0.0762623921129591 3.81346821967655 0.000162147943570549 *** df.mm.trans2:exp3 0.198116666285947 0.0762623921129591 2.59782916319355 0.00978118555301603 ** df.mm.trans1:exp4 0.530567700969358 0.0762623921129591 6.95713426066529 1.73788233579956e-11 *** df.mm.trans2:exp4 0.352535694440551 0.0762623921129591 4.62266766977856 5.35146054109125e-06 *** df.mm.trans1:exp5 0.122152823852539 0.0762623921129591 1.60174393260059 0.110122157684475 df.mm.trans2:exp5 0.0382485651469406 0.0762623921129591 0.501539016639909 0.616309868049144 df.mm.trans1:exp6 0.0548939869629113 0.0762623921129591 0.719804158275062 0.472130113462085 df.mm.trans2:exp6 0.137848841604971 0.0762623921129591 1.80755989663674 0.0715408703254087 . df.mm.trans1:exp7 0.138462793151329 0.0762623921129591 1.81561041182972 0.0702931545758796 . df.mm.trans2:exp7 0.153935979023031 0.0762623921129591 2.01850446541229 0.0443076486955376 * df.mm.trans1:exp8 0.407074272115745 0.0762623921129591 5.33781148003842 1.70323437701172e-07 *** df.mm.trans2:exp8 0.249340264071559 0.0762623921129591 3.26950489177207 0.00118525226962702 ** df.mm.trans1:probe2 0.100721702555819 0.0417706324495718 2.41130422617893 0.0164144837546703 * df.mm.trans1:probe3 0.0131261069616665 0.0417706324495718 0.314242475919252 0.753525727466677 df.mm.trans1:probe4 0.125732870042654 0.0417706324495718 3.01007819774926 0.00280301984533808 ** df.mm.trans1:probe5 0.140880228639387 0.0417706324495718 3.37270997295689 0.000828341212433755 *** df.mm.trans1:probe6 0.144335757041004 0.0417706324495718 3.45543623777436 0.00061753797760539 *** df.mm.trans2:probe2 0.154342797016126 0.0417706324495718 3.6950074242342 0.000255394339811449 *** df.mm.trans2:probe3 -0.318381208930418 0.0417706324495718 -7.6221304361333 2.40836146599676e-13 *** df.mm.trans2:probe4 -0.218509161153758 0.0417706324495718 -5.2311671703213 2.91991646439591e-07 *** df.mm.trans2:probe5 -0.180421645625740 0.0417706324495718 -4.31934196456222 2.04555848473269e-05 *** df.mm.trans2:probe6 -0.338553317295797 0.0417706324495718 -8.10505605115077 9.12500294781146e-15 *** df.mm.trans3:probe2 -0.117419325536281 0.0417706324495718 -2.81104974117969 0.00521843673101905 ** df.mm.trans3:probe3 -0.0498611549565089 0.0417706324495718 -1.19368925085596 0.233414975287155 df.mm.trans3:probe4 -0.285006322926092 0.0417706324495718 -6.82312682888319 3.97981874759159e-11 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.43579908582668 0.122498084689865 36.2111709506073 6.60775272070642e-120 *** df.mm.trans1 0.0142297253712933 0.102057715182805 0.139428218099975 0.889192663017404 df.mm.trans2 -0.00742834004081899 0.102057715182805 -0.0727856784517798 0.942018603304034 df.mm.exp2 -0.0498856822510655 0.140614092018285 -0.354770148105629 0.722977309501211 df.mm.exp3 -0.0910062179702433 0.140614092018285 -0.647205530142806 0.517926844888923 df.mm.exp4 0.0283249042421084 0.140614092018285 0.201437166329141 0.84047478601462 df.mm.exp5 0.0419684671949975 0.140614092018285 0.298465584726316 0.765526485202228 df.mm.exp6 -0.0152122056234199 0.140614092018285 -0.108184076041552 0.913912203290758 df.mm.exp7 0.0173741902147468 0.140614092018285 0.123559381320669 0.901735692298461 df.mm.exp8 0.00109221421110519 0.140614092018285 0.00776745911756242 0.993806990216678 df.mm.trans1:exp2 -0.0175315772225317 0.118840598144041 -0.147521785453171 0.882805864005229 df.mm.trans2:exp2 -0.0576904497552735 0.118840598144041 -0.48544395312913 0.627667814565946 df.mm.trans1:exp3 -0.0267124152587586 0.118840598144041 -0.224775166701718 0.822286489202129 df.mm.trans2:exp3 0.0658707288708246 0.118840598144041 0.554277998424293 0.579745640477253 df.mm.trans1:exp4 -0.0293709735693864 0.118840598144041 -0.247145958772333 0.804941425477592 df.mm.trans2:exp4 -0.0729380990277986 0.118840598144041 -0.613747323447447 0.539784436917094 df.mm.trans1:exp5 -0.138611230453648 0.118840598144041 -1.16636261192193 0.244268857168213 df.mm.trans2:exp5 -0.0618998886468165 0.118840598144041 -0.520864835868554 0.602793143865658 df.mm.trans1:exp6 0.000456197955379586 0.118840598144041 0.00383873829738429 0.996939343398957 df.mm.trans2:exp6 -0.0462384894403292 0.118840598144041 -0.389079911767912 0.697455681954173 df.mm.trans1:exp7 -0.216269997740012 0.118840598144041 -1.81983262552989 0.0696459733651658 . df.mm.trans2:exp7 0.0329119620156421 0.118840598144041 0.276942076442186 0.781989480087975 df.mm.trans1:exp8 -0.00684302943108117 0.118840598144041 -0.0575815801834579 0.954115065405837 df.mm.trans2:exp8 -0.0679840610797701 0.118840598144041 -0.572060913033862 0.567651113153356 df.mm.trans1:probe2 0.015940502994746 0.0650916763508976 0.244893109048438 0.80668395285536 df.mm.trans1:probe3 0.0235931960490047 0.0650916763508976 0.362461029914454 0.717228196683534 df.mm.trans1:probe4 -0.0507036296441234 0.0650916763508976 -0.778957195245505 0.436535816523633 df.mm.trans1:probe5 -0.0391311017661652 0.0650916763508976 -0.601169058163695 0.54811989326248 df.mm.trans1:probe6 -0.036293337452388 0.0650916763508976 -0.557572634275649 0.577495751901974 df.mm.trans2:probe2 0.000476166640100799 0.0650916763508976 0.00731532304582032 0.994167472510337 df.mm.trans2:probe3 -0.095347632181912 0.0650916763508976 -1.46482065798874 0.143875270686404 df.mm.trans2:probe4 -0.0387542820526912 0.0650916763508976 -0.59537999672606 0.551977581174778 df.mm.trans2:probe5 -0.0688791584644616 0.0650916763508976 -1.05818688849164 0.290706323870896 df.mm.trans2:probe6 -0.0240282768168407 0.0650916763508976 -0.369145152865761 0.712244680269733 df.mm.trans3:probe2 0.0495394487211925 0.0650916763508976 0.761071944961658 0.447130976878356 df.mm.trans3:probe3 -0.0490102853336627 0.0650916763508976 -0.752942435672681 0.451995014725425 df.mm.trans3:probe4 -0.027145668308878 0.0650916763508976 -0.417037474385212 0.676908877061015