chr12.5222_chr12_99441950_99442557_-_1.R fitVsDatCorrelation=0.602242306773588 cont.fitVsDatCorrelation=0.339087914473522 fstatistic=7137.32958600184,36,324 cont.fstatistic=5137.0860163747,36,324 residuals=-0.378188223150947,-0.0864482685522561,-0.00605543136660554,0.0786084036382616,0.746293008794282 cont.residuals=-0.340619595328901,-0.111134167706802,-0.0189726577419220,0.0808593760457691,0.803002203926927 predictedValues: Include Exclude Both chr12.5222_chr12_99441950_99442557_-_1.R.tl.Lung 47.2546979054928 50.138998336324 50.0622914196892 chr12.5222_chr12_99441950_99442557_-_1.R.tl.cerebhem 56.4885773953512 63.6037432746555 60.2245291310263 chr12.5222_chr12_99441950_99442557_-_1.R.tl.cortex 46.2808862350656 50.1457617075405 50.4658079762739 chr12.5222_chr12_99441950_99442557_-_1.R.tl.heart 45.8412674170878 52.0711844996069 52.4512954708004 chr12.5222_chr12_99441950_99442557_-_1.R.tl.kidney 45.2102965675071 51.3873344374414 54.1849558103781 chr12.5222_chr12_99441950_99442557_-_1.R.tl.liver 51.7102923038123 53.150286158885 54.1359664641389 chr12.5222_chr12_99441950_99442557_-_1.R.tl.stomach 50.0060705789954 51.0453186000678 55.8437807977506 chr12.5222_chr12_99441950_99442557_-_1.R.tl.testicle 49.1283998401909 55.7415554129799 55.1751782527566 diffExp=-2.88430043083122,-7.11516587930435,-3.86487547247486,-6.22991708251914,-6.17703786993427,-1.4399938550727,-1.03924802107236,-6.61315557278903 diffExpScore=0.972500043726579 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 54.7113687570469 51.2219025060858 50.5030149038548 cerebhem 51.1677377505165 49.8790980927749 46.6799009168615 cortex 49.9900068397186 55.3928985557133 52.0059921976739 heart 50.5475448941251 47.5057500323529 49.9450160364504 kidney 51.9447869945723 56.0125740441638 48.8317807383638 liver 53.6309085882862 48.647530982434 51.6824925061341 stomach 48.4533594806481 54.6782389333515 46.4572879228992 testicle 49.8602700733092 52.6940394204639 51.860103209223 cont.diffExp=3.48946625096116,1.28863965774165,-5.40289171599466,3.04179486177215,-4.06778704959145,4.98337760585212,-6.2248794527034,-2.83376934715468 cont.diffExpScore=4.6583967884844 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=0.841966129554526 cont.tran.correlation=-0.372688591120619 tran.covariance=0.00491440471115364 cont.tran.covariance=-0.000921676755349241 tran.mean=51.2002919169378 cont.tran.mean=51.6461259965977 weightedLogRatios: wLogRatio Lung -0.230185152449966 cerebhem -0.48561062112666 cortex -0.310780656961159 heart -0.495550611411717 kidney -0.496305004395169 liver -0.108751182325257 stomach -0.0806821254735925 testicle -0.499797640503727 cont.weightedLogRatios: wLogRatio Lung 0.261582043059764 cerebhem 0.100048200624422 cortex -0.406729954103735 heart 0.241544318328378 kidney -0.300665467363692 liver 0.383599281511331 stomach -0.476329612291336 testicle -0.217621347413301 varWeightedLogRatios=0.0327115438953239 cont.varWeightedLogRatios=0.113217286399511 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.89077537718756 0.0832715335025895 46.7239549163169 5.22254446098024e-146 *** df.mm.trans1 -0.0281577527720223 0.0705301190105897 -0.399230189414462 0.68998661798135 df.mm.trans2 0.0606896578984488 0.0705301190105897 0.860478597651829 0.390161558284357 df.mm.exp2 0.231547910539367 0.0982217423331188 2.35739974713616 0.0189977088218954 * df.mm.exp3 -0.0287161194453134 0.0982217423331189 -0.2923601105336 0.770198429079957 df.mm.exp4 -0.0391717301638969 0.0982217423331188 -0.398809156032338 0.690296538142648 df.mm.exp5 -0.0987698427471341 0.0982217423331188 -1.00558023509862 0.315367932567474 df.mm.exp6 0.0701984161083901 0.0982217423331188 0.714693248571302 0.47531322664167 df.mm.exp7 -0.0347830484059684 0.0982217423331188 -0.35412778861122 0.723473466816751 df.mm.exp8 0.0475668870338607 0.0982217423331188 0.484280627730444 0.628513913116186 df.mm.trans1:exp2 -0.0530615383883957 0.0850625240644503 -0.623794543742812 0.533201443189275 df.mm.trans2:exp2 0.0063252994008541 0.0850625240644503 0.0743605891127982 0.940769355701307 df.mm.trans1:exp3 0.00789309543692009 0.0850625240644503 0.0927916908618846 0.926126401629711 df.mm.trans2:exp3 0.0288510027760163 0.0850625240644503 0.339174073345818 0.734698326267583 df.mm.trans1:exp4 0.0088043753344589 0.0850625240644503 0.103504750550172 0.917626415839236 df.mm.trans2:exp4 0.0769843301023436 0.0850625240644503 0.90503228006747 0.366120764567769 df.mm.trans1:exp5 0.0545426282403553 0.0850625240644503 0.641206322528466 0.521841943042654 df.mm.trans2:exp5 0.123362457927346 0.0850625240644503 1.45025625895931 0.147954421108334 df.mm.trans1:exp6 0.0199063474673540 0.0850625240644503 0.234020183227473 0.815117110603641 df.mm.trans2:exp6 -0.0118740425419997 0.0850625240644503 -0.139591937490627 0.889069142289503 df.mm.trans1:exp7 0.091375382475701 0.0850625240644503 1.07421433211255 0.283525976520595 df.mm.trans2:exp7 0.0526977713667486 0.0850625240644503 0.6195180773947 0.536010515978868 df.mm.trans1:exp8 -0.00868168686491086 0.0850625240644503 -0.102062417737956 0.918770266472911 df.mm.trans2:exp8 0.0583599242267263 0.0850625240644503 0.686082677049509 0.493151626895987 df.mm.trans1:probe2 0.153005089878568 0.0425312620322252 3.59747354222970 0.000371465899857760 *** df.mm.trans1:probe3 -0.0908871871466305 0.0425312620322252 -2.13695015863312 0.0333506142310061 * df.mm.trans1:probe4 -0.0234298076257070 0.0425312620322252 -0.550884373192468 0.582092588485167 df.mm.trans1:probe5 -0.0740038713330184 0.0425312620322252 -1.73998766547174 0.0828107118950299 . df.mm.trans1:probe6 -0.0282741633962948 0.0425312620322252 -0.664785431828287 0.506660623469001 df.mm.trans2:probe2 0.0288306297904232 0.0425312620322252 0.677869134675072 0.49833846253809 df.mm.trans2:probe3 -0.161303425346226 0.0425312620322252 -3.79258497488293 0.000177829612799092 *** df.mm.trans2:probe4 -0.0904044865214475 0.0425312620322252 -2.12560084516066 0.0342926211989718 * df.mm.trans2:probe5 -0.00905011788974344 0.0425312620322252 -0.212787428759728 0.831626585321035 df.mm.trans2:probe6 -0.0980658790645338 0.0425312620322252 -2.30573640138473 0.0217565043890014 * df.mm.trans3:probe2 -0.0612433298359434 0.0425312620322252 -1.43996032352721 0.150844143298526 df.mm.trans3:probe3 0.0311256581590151 0.0425312620322252 0.731830109706872 0.464801267360078 cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.02270314501961 0.098129494786215 40.9938230476319 2.93695224907321e-130 *** df.mm.trans1 -0.040083882909143 0.0831146570094756 -0.48227213287511 0.629938278360347 df.mm.trans2 -0.0617063971791435 0.0831146570094756 -0.742424975321845 0.45836778697207 df.mm.exp2 -0.0148081488277126 0.115747237342171 -0.127935224785858 0.89827960387717 df.mm.exp3 -0.0412901381422748 0.115747237342171 -0.356726770248635 0.721528568668776 df.mm.exp4 -0.143363302121549 0.115747237342171 -1.23858940751856 0.216394196673586 df.mm.exp5 0.0711705079239604 0.115747237342171 0.614878674931714 0.539066432381003 df.mm.exp6 -0.0945981910483923 0.115747237342171 -0.817282496071524 0.414367571703801 df.mm.exp7 0.0273284139339669 0.115747237342171 0.236104243708029 0.813500963494496 df.mm.exp8 -0.0910286448696487 0.115747237342171 -0.78644334810818 0.432182614816853 df.mm.trans1:exp2 -0.0521541659671704 0.100240047956187 -0.520292707660777 0.603214908512171 df.mm.trans2:exp2 -0.0117570359583747 0.100240047956186 -0.117288810192046 0.906703864204176 df.mm.trans1:exp3 -0.048958265780298 0.100240047956187 -0.488410239006439 0.625589680465551 df.mm.trans2:exp3 0.119574314869951 0.100240047956187 1.19287966544285 0.233789325014557 df.mm.trans1:exp4 0.0642061523678755 0.100240047956187 0.640523959006276 0.522284753645411 df.mm.trans2:exp4 0.0680468352542264 0.100240047956186 0.678838813843831 0.497724598273709 df.mm.trans1:exp5 -0.123060668175044 0.100240047956187 -1.22765970970836 0.220465905103790 df.mm.trans2:exp5 0.0182384702153147 0.100240047956187 0.181947939842233 0.85573736177366 df.mm.trans1:exp6 0.0746522195215861 0.100240047956186 0.744734475328818 0.456972087526306 df.mm.trans2:exp6 0.0430320238802940 0.100240047956187 0.429289737561805 0.667997702589256 df.mm.trans1:exp7 -0.148798265044954 0.100240047956187 -1.4844193321814 0.138669906171477 df.mm.trans2:exp7 0.0379701667303785 0.100240047956186 0.378792383927975 0.70509013978634 df.mm.trans1:exp8 -0.00181838658663276 0.100240047956187 -0.0181403203979666 0.98553807783877 df.mm.trans2:exp8 0.119363766149960 0.100240047956187 1.19077922031853 0.234611931578591 df.mm.trans1:probe2 -0.00819017777082153 0.0501200239780933 -0.163411289954716 0.870296495016114 df.mm.trans1:probe3 0.068594135620271 0.0501200239780933 1.36859742226485 0.172073330167101 df.mm.trans1:probe4 0.0527843458446915 0.0501200239780933 1.05315883064547 0.293052971715689 df.mm.trans1:probe5 0.0420343426404053 0.0501200239780933 0.838673633890876 0.402270791578673 df.mm.trans1:probe6 0.0198477301992534 0.0501200239780933 0.396004004465930 0.69236272316155 df.mm.trans2:probe2 -0.0521770228477499 0.0501200239780933 -1.04104145821151 0.298632503231238 df.mm.trans2:probe3 -0.078657746919594 0.0501200239780933 -1.56938765540045 0.117533697689127 df.mm.trans2:probe4 -0.0538103253171629 0.0501200239780933 -1.07362928119673 0.283787815350918 df.mm.trans2:probe5 0.0386435616979848 0.0501200239780933 0.771020415211202 0.441256726610736 df.mm.trans2:probe6 -0.0774641821294259 0.0501200239780933 -1.54557352493056 0.123183752221845 df.mm.trans3:probe2 0.0042559694005606 0.0501200239780933 0.0849155499690267 0.932380974796564 df.mm.trans3:probe3 -0.00089545749741069 0.0501200239780933 -0.0178662623505943 0.985756540347916