chr11.3873_chr11_50616527_50618970_-_1.R fitVsDatCorrelation=0.933929565406848 cont.fitVsDatCorrelation=0.294854606690106 fstatistic=6006.60467832265,42,462 cont.fstatistic=831.115751570056,42,462 residuals=-0.89180300622828,-0.125306823655307,0.00961110942309092,0.152167777070543,0.581143471952821 cont.residuals=-1.33233782223927,-0.460944325956611,-0.00261303536511677,0.43630592858079,1.61068068032693 predictedValues: Include Exclude Both chr11.3873_chr11_50616527_50618970_-_1.R.tl.Lung 253.734774465071 94.3428880760865 235.735315830002 chr11.3873_chr11_50616527_50618970_-_1.R.tl.cerebhem 175.498657775324 64.923473606203 230.364878462156 chr11.3873_chr11_50616527_50618970_-_1.R.tl.cortex 438.220623622954 122.860751330342 343.58588197729 chr11.3873_chr11_50616527_50618970_-_1.R.tl.heart 298.124965318946 124.194092803055 264.816684531984 chr11.3873_chr11_50616527_50618970_-_1.R.tl.kidney 246.198800171577 109.189932184123 273.542035865564 chr11.3873_chr11_50616527_50618970_-_1.R.tl.liver 180.419137380457 105.141968791143 206.604578208930 chr11.3873_chr11_50616527_50618970_-_1.R.tl.stomach 189.305769609578 98.6422853327993 198.832309328710 chr11.3873_chr11_50616527_50618970_-_1.R.tl.testicle 145.475245785358 80.2408597394126 158.099649730484 diffExp=159.391886388984,110.575184169120,315.359872292612,173.930872515891,137.008867987454,75.2771685893143,90.6634842767782,65.2343860459458 diffExpScore=0.99911382220254 diffExp1.5=1,1,1,1,1,1,1,1 diffExp1.5Score=0.888888888888889 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 143.343584910273 224.50086556655 162.659942595363 cerebhem 135.672153965569 190.069444885178 151.278687862537 cortex 139.714272428914 206.412723119083 183.777643779478 heart 220.102794157074 139.895875112318 198.172213168038 kidney 190.969946365755 211.604780878216 199.770326404884 liver 146.149933851071 171.629188953513 167.351185580765 stomach 135.081595033947 213.729842268808 187.412366343712 testicle 182.522389162370 194.787440566029 210.202727622315 cont.diffExp=-81.1572806562773,-54.3972909196083,-66.6984506901693,80.2069190447553,-20.6348345124604,-25.4792551024422,-78.6482472348609,-12.2650514036585 cont.diffExpScore=1.61295688839939 cont.diffExp1.5=-1,0,0,1,0,0,-1,0 cont.diffExp1.5Score=1.5 cont.diffExp1.4=-1,-1,-1,1,0,0,-1,0 cont.diffExp1.4Score=1.25 cont.diffExp1.3=-1,-1,-1,1,0,0,-1,0 cont.diffExp1.3Score=1.25 cont.diffExp1.2=-1,-1,-1,1,0,0,-1,0 cont.diffExp1.2Score=1.25 tran.correlation=0.734350392135396 cont.tran.correlation=-0.578406928045885 tran.covariance=0.0564846925485437 cont.tran.covariance=-0.0164507379471368 tran.mean=170.407139124527 cont.tran.mean=177.886676951542 weightedLogRatios: wLogRatio Lung 4.98793786247913 cerebhem 4.64436940633044 cortex 6.92664764586205 heart 4.6057282155358 kidney 4.14624367992461 liver 2.65951841164590 stomach 3.20549433846127 testicle 2.78597299788083 cont.weightedLogRatios: wLogRatio Lung -2.32821978480763 cerebhem -1.71231328477447 cortex -2.00397676964724 heart 2.34189024349577 kidney -0.544153122181476 liver -0.81395940633457 stomach -2.35624730498466 testicle -0.340749391081472 varWeightedLogRatios=1.96652108086752 cont.varWeightedLogRatios=2.42240663522383 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.50652222374566 0.118401087219127 46.5073619936838 2.12394415909916e-176 *** df.mm.trans1 -0.00640247701823908 0.0951236534622967 -0.0673068872483622 0.946366511901955 df.mm.trans2 -0.969389144547708 0.0951236534622967 -10.1908317149733 3.90128654809742e-22 *** df.mm.exp2 -0.719339622722048 0.127721594749814 -5.63209083108552 3.0967861978227e-08 *** df.mm.exp3 0.433821216002944 0.127721594749814 3.39661602920579 0.000741191617823967 *** df.mm.exp4 0.319804736791886 0.127721594749814 2.50392063627402 0.0126263053439399 * df.mm.exp5 -0.0327428875803184 0.127721594749814 -0.256361405794035 0.79778590010672 df.mm.exp6 -0.100728295316251 0.127721594749814 -0.788655164489308 0.430718074992324 df.mm.exp7 -0.0781140241654474 0.127721594749814 -0.611596060309615 0.541105873715559 df.mm.exp8 -0.318702515233318 0.127721594749814 -2.49529076001286 0.0129333133525940 * df.mm.trans1:exp2 0.350681491147165 0.100972786449604 3.47302974868572 0.000563055383750006 *** df.mm.trans2:exp2 0.345612979014357 0.100972786449604 3.42283293515777 0.000674869694263393 *** df.mm.trans1:exp3 0.112611748009783 0.100972786449604 1.11526830118715 0.265315245891424 df.mm.trans2:exp3 -0.169705495820150 0.100972786449604 -1.68070528493191 0.0934960822991503 . df.mm.trans1:exp4 -0.158581517927569 0.100972786449604 -1.57053720614829 0.116974773978008 df.mm.trans2:exp4 -0.044895021267388 0.100972786449604 -0.444624961298809 0.656799019553273 df.mm.trans1:exp5 0.00259270148188534 0.100972786449604 0.0256772302028068 0.97952587246783 df.mm.trans2:exp5 0.178895859653114 0.100972786449604 1.77172351029851 0.0770995641879822 . df.mm.trans1:exp6 -0.240278546089108 0.100972786449604 -2.37963667774022 0.0177347107021427 * df.mm.trans2:exp6 0.209103925085243 0.100972786449604 2.07089387584255 0.0389234578649632 * df.mm.trans1:exp7 -0.214811965875461 0.100972786449604 -2.12742436282745 0.0339138588556055 * df.mm.trans2:exp7 0.122678160300042 0.100972786449604 1.21496261134945 0.225000911736307 df.mm.trans1:exp8 -0.237581071136331 0.100972786449604 -2.35292180685643 0.0190449237363459 * df.mm.trans2:exp8 0.156799482556863 0.100972786449604 1.55288853630996 0.121134495038146 df.mm.trans1:probe2 -0.110636076432446 0.0677346043136652 -1.63337599080247 0.103071205062760 df.mm.trans1:probe3 -0.214107928673149 0.0677346043136652 -3.16098293985241 0.00167573775579989 ** df.mm.trans1:probe4 0.425359668297673 0.0677346043136652 6.27979852555009 7.82954304521909e-10 *** df.mm.trans1:probe5 0.284674394368787 0.0677346043136652 4.20279113243975 3.16599006788874e-05 *** df.mm.trans1:probe6 0.157256638243376 0.0677346043136652 2.32165877156605 0.0206853648547673 * df.mm.trans2:probe2 -0.152024281168551 0.0677346043136652 -2.24441085482035 0.0252785639507771 * df.mm.trans2:probe3 -0.237902310860578 0.0677346043136652 -3.51227136071986 0.000487968543613569 *** df.mm.trans2:probe4 0.419815937397677 0.0677346043136652 6.1979536405586 1.26840634903014e-09 *** df.mm.trans2:probe5 0.0294460717730441 0.0677346043136652 0.434727154183781 0.663963467320158 df.mm.trans2:probe6 0.0877067579630785 0.0677346043136652 1.29485894029773 0.196015626355838 df.mm.trans3:probe2 1.39441990062187 0.0677346043136652 20.5865216863834 2.66476403373220e-67 *** df.mm.trans3:probe3 0.583238884297305 0.0677346043136652 8.61064872537595 1.15280845863502e-16 *** df.mm.trans3:probe4 1.23276514374496 0.0677346043136652 18.1999312793838 3.37185459315919e-56 *** df.mm.trans3:probe5 1.52520559909159 0.0677346043136652 22.5173766724712 2.4966143109762e-76 *** df.mm.trans3:probe6 0.503829596055748 0.0677346043136652 7.43828950004071 5.00755221512846e-13 *** df.mm.trans3:probe7 0.818904979261033 0.0677346043136652 12.0899057071161 1.99193272701161e-29 *** df.mm.trans3:probe8 0.86057632734357 0.0677346043136652 12.7051207586364 6.28187374882169e-32 *** df.mm.trans3:probe9 1.46887084275722 0.0677346043136652 21.6856783565927 1.92918622553123e-72 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.20556428493716 0.316505762729907 16.4469810598026 3.51088114679287e-48 *** df.mm.trans1 -0.315753407230045 0.254281317848203 -1.24174835140086 0.214959447924023 df.mm.trans2 0.198670092346230 0.254281317848203 0.781300388197723 0.435026017424542 df.mm.exp2 -0.148955126059348 0.341421026722123 -0.436279884368633 0.662837474883 df.mm.exp3 -0.231711691468748 0.341421026722123 -0.678668486511623 0.497687746157125 df.mm.exp4 -0.241605559026208 0.341421026722123 -0.707646981633754 0.479521328320919 df.mm.exp5 0.0222057988041048 0.341421026722123 0.0650393416518478 0.948170809097626 df.mm.exp6 -0.27758742470804 0.341421026722123 -0.813035527931804 0.416616466554895 df.mm.exp7 -0.250181777913284 0.341421026722123 -0.732766169427822 0.464072662975732 df.mm.exp8 -0.156752896158794 0.341421026722123 -0.459119046251281 0.646364613154039 df.mm.trans1:exp2 0.0939520288448489 0.269917021378780 0.348077451228998 0.727940559183148 df.mm.trans2:exp2 -0.0175349318682942 0.269917021378780 -0.064964157424096 0.9482306381769 df.mm.trans1:exp3 0.206066677266984 0.269917021378780 0.763444543861522 0.445587996316525 df.mm.trans2:exp3 0.147709803489948 0.269917021378781 0.547241529027781 0.584477050794885 df.mm.trans1:exp4 0.670455802329898 0.269917021378780 2.48393302098956 0.0133474545619951 * df.mm.trans2:exp4 -0.231375606986030 0.269917021378780 -0.857210137412327 0.391773193628841 df.mm.trans1:exp5 0.264665827899815 0.269917021378781 0.980545156240455 0.327330277039285 df.mm.trans2:exp5 -0.0813650678379475 0.269917021378780 -0.301444745582629 0.763211009425894 df.mm.trans1:exp6 0.29697602356366 0.269917021378780 1.10024933606135 0.271796446385388 df.mm.trans2:exp6 0.00904413338827346 0.269917021378780 0.0335070880008772 0.973284684661047 df.mm.trans1:exp7 0.190816341338152 0.269917021378780 0.706944454126793 0.479957402628268 df.mm.trans2:exp7 0.201015013402808 0.269917021378780 0.744728925860217 0.456814260163606 df.mm.trans1:exp8 0.39838130190679 0.269917021378780 1.47593990135114 0.140641239962795 df.mm.trans2:exp8 0.0147822491032135 0.269917021378780 0.0547659018601469 0.956348640422678 df.mm.trans1:probe2 0.313889539945953 0.181065842426165 1.73356573354773 0.0836623198414854 . df.mm.trans1:probe3 0.381569717335971 0.181065842426165 2.10735339268403 0.0356252562171444 * df.mm.trans1:probe4 0.147573825213793 0.181065842426165 0.815028518004278 0.415475928413904 df.mm.trans1:probe5 0.237055904240224 0.181065842426165 1.30922487126135 0.191108951369457 df.mm.trans1:probe6 0.0514144490327105 0.181065842426165 0.283954435269459 0.776572511841951 df.mm.trans2:probe2 0.0508972435801746 0.181065842426165 0.281097985672971 0.77876109243204 df.mm.trans2:probe3 -0.200385594231426 0.181065842426165 -1.10670014590487 0.268999494610955 df.mm.trans2:probe4 0.088425245205993 0.181065842426165 0.488359615602545 0.625526848664482 df.mm.trans2:probe5 0.252526176974288 0.181065842426165 1.39466491078936 0.163787115678692 df.mm.trans2:probe6 -0.0467852902023166 0.181065842426165 -0.258388272329137 0.796222335577953 df.mm.trans3:probe2 0.100054689066420 0.181065842426165 0.552587322521749 0.580813268471879 df.mm.trans3:probe3 -0.142921735192142 0.181065842426165 -0.789335709469457 0.430320715742969 df.mm.trans3:probe4 -0.0345310400366084 0.181065842426165 -0.190709852139502 0.848836693142175 df.mm.trans3:probe5 -0.111174212370817 0.181065842426165 -0.613998813255743 0.539518323334717 df.mm.trans3:probe6 0.102187453037432 0.181065842426165 0.564366264051717 0.572778775570147 df.mm.trans3:probe7 0.0561310127762419 0.181065842426165 0.310003322681532 0.756698214508684 df.mm.trans3:probe8 0.0157371490326627 0.181065842426165 0.0869139580486028 0.93077756084902 df.mm.trans3:probe9 0.0431439716474282 0.181065842426165 0.238277805848563 0.811771280041138