chr13.6727_chr13_50967845_50970599_-_2.R fitVsDatCorrelation=0.907669489170286 cont.fitVsDatCorrelation=0.257553859570531 fstatistic=7515.81154471342,50,646 cont.fstatistic=1407.37525229383,50,646 residuals=-0.766426850611743,-0.110206978922339,-0.00785695934002491,0.109086026871195,0.732733837872535 cont.residuals=-0.776853381972726,-0.358764791218548,-0.0420989479373526,0.335071068716744,1.27870466182082 predictedValues: Include Exclude Both chr13.6727_chr13_50967845_50970599_-_2.R.tl.Lung 75.2274299926195 46.4521455338266 91.4036437591885 chr13.6727_chr13_50967845_50970599_-_2.R.tl.cerebhem 86.5085481212635 46.5420445178782 94.9206224764944 chr13.6727_chr13_50967845_50970599_-_2.R.tl.cortex 77.0195682147499 44.7604220973833 103.047308930578 chr13.6727_chr13_50967845_50970599_-_2.R.tl.heart 74.9635397895064 46.543600884096 88.2399599079971 chr13.6727_chr13_50967845_50970599_-_2.R.tl.kidney 82.896153598635 45.8616342493537 100.852472014187 chr13.6727_chr13_50967845_50970599_-_2.R.tl.liver 71.1255655168463 48.3316077934977 69.2299272149593 chr13.6727_chr13_50967845_50970599_-_2.R.tl.stomach 78.8143617904465 44.3885189809561 75.4699691790295 chr13.6727_chr13_50967845_50970599_-_2.R.tl.testicle 73.338639339429 44.6426889693822 76.2278374273486 diffExp=28.7752844587929,39.9665036033853,32.2591461173666,28.4199389054104,37.0345193492813,22.7939577233485,34.4258428094904,28.6959503700469 diffExpScore=0.996053220635826 diffExp1.5=1,1,1,1,1,0,1,1 diffExp1.5Score=0.875 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 68.9584568202368 84.3567804212161 63.2034877300926 cerebhem 74.1814366561694 79.3769647935767 74.115998013822 cortex 65.5520465970123 77.8025995192657 69.8161573180127 heart 70.0450450286562 78.829532039143 63.2227376983745 kidney 71.1107183620244 85.6588345678977 78.4853616400977 liver 67.782620578896 85.653520955119 67.2546064552491 stomach 66.5430547016959 74.1091449860956 74.1518684609148 testicle 75.7893998942136 75.3312652134696 106.433902367861 cont.diffExp=-15.3983236009794,-5.19552813740724,-12.2505529222533,-8.7844870104869,-14.5481162058733,-17.8709003762230,-7.56609028439972,0.458134680743996 cont.diffExpScore=0.998980831865418 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=-1,0,0,0,-1,-1,0,0 cont.diffExp1.2Score=0.75 tran.correlation=-0.191422547976073 cont.tran.correlation=-0.090178898989813 tran.covariance=-0.000377732409724474 cont.tran.covariance=-0.000207554714880169 tran.mean=61.7135293368669 cont.tran.mean=75.067588820918 weightedLogRatios: wLogRatio Lung 1.96668469223358 cerebhem 2.57271740260464 cortex 2.21039329760455 heart 1.94395666777766 kidney 2.43982650990048 liver 1.57297888921259 stomach 2.34240852098340 testicle 2.00886382864642 cont.weightedLogRatios: wLogRatio Lung -0.873578159936079 cerebhem -0.293817579579788 cortex -0.731325514083753 heart -0.509011774775573 kidney -0.81104391718693 liver -1.01401360859381 stomach -0.457863919157281 testicle 0.0262228206794929 varWeightedLogRatios=0.104251770031359 cont.varWeightedLogRatios=0.117160724935125 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.18819306708973 0.0907384667428655 35.1360694260398 5.00350023655723e-152 *** df.mm.trans1 1.06291531579666 0.0788049981448135 13.4879175283201 1.04124350498018e-36 *** df.mm.trans2 0.583341761860208 0.071612537174325 8.14580497881524 1.95021970530249e-15 *** df.mm.exp2 0.103905093440211 0.0948271319411638 1.09573168895037 0.273604537825807 df.mm.exp3 -0.133457592542069 0.0948271319411637 -1.40737771785478 0.159796377893732 df.mm.exp4 0.0336782296733081 0.0948271319411638 0.355153941534412 0.722590191202254 df.mm.exp5 -0.0140944361217668 0.0948271319411637 -0.148632947482918 0.881889657615092 df.mm.exp6 0.261446116775747 0.0948271319411637 2.75708134817325 0.00599674418295067 ** df.mm.exp7 0.192688037442078 0.0948271319411637 2.03199267443450 0.0425630673286761 * df.mm.exp8 0.116398210555777 0.0948271319411638 1.22747791874585 0.220090118628666 df.mm.trans1:exp2 0.0358222128391743 0.0874262958689138 0.409741857219775 0.682131154889737 df.mm.trans2:exp2 -0.101971660566472 0.0719062330226487 -1.41811990810802 0.156637958029078 df.mm.trans1:exp3 0.157001189781613 0.0874262958689138 1.79581198335361 0.0729916199635397 . df.mm.trans2:exp3 0.0963592518054012 0.0719062330226487 1.34006813811329 0.180694340488187 df.mm.trans1:exp4 -0.0371922954663896 0.0874262958689138 -0.425413144829508 0.670677203631352 df.mm.trans2:exp4 -0.0317113573533217 0.0719062330226487 -0.44100985436594 0.659353415358163 df.mm.trans1:exp5 0.111167174113168 0.0874262958689138 1.27155306087600 0.203989565072145 df.mm.trans2:exp5 0.00130069416030243 0.0719062330226487 0.0180887540012386 0.985573634747371 df.mm.trans1:exp6 -0.317515198320139 0.0874262958689138 -3.63180431201407 0.000303759861486971 *** df.mm.trans2:exp6 -0.221783018857131 0.0719062330226487 -3.08433649677177 0.00212712762482949 ** df.mm.trans1:exp7 -0.146108725947946 0.0874262958689137 -1.67122173592966 0.0951622032714582 . df.mm.trans2:exp7 -0.238129837324233 0.0719062330226487 -3.31167170513894 0.000979081666026106 *** df.mm.trans1:exp8 -0.141826525847412 0.0874262958689138 -1.62224104816320 0.105239647768488 df.mm.trans2:exp8 -0.156130311899944 0.0719062330226487 -2.17130428527339 0.030271458788312 * df.mm.trans1:probe2 0.328308619323813 0.0535374537451079 6.13231665605339 1.50850933369948e-09 *** df.mm.trans1:probe3 0.531688649362933 0.0535374537451079 9.93115309320284 1.00015606369631e-21 *** df.mm.trans1:probe4 0.214969628485578 0.0535374537451079 4.01531289681892 6.63379393396975e-05 *** df.mm.trans1:probe5 0.338739180677831 0.0535374537451079 6.32714402688201 4.66791707552072e-10 *** df.mm.trans1:probe6 -0.436280762606559 0.0535374537451079 -8.14907568603644 1.90298641041561e-15 *** df.mm.trans1:probe7 -0.344593536110163 0.0535374537451079 -6.43649467811402 2.38423866067460e-10 *** df.mm.trans1:probe8 -0.369500969533011 0.0535374537451079 -6.90172848511262 1.22921278280121e-11 *** df.mm.trans1:probe9 -0.399823211344384 0.0535374537451079 -7.46810285838292 2.64710409735745e-13 *** df.mm.trans1:probe10 -0.367291609898076 0.0535374537451079 -6.86046093351307 1.61011507242920e-11 *** df.mm.trans1:probe11 -0.432852971894721 0.0535374537451079 -8.08504965431372 3.07087590024714e-15 *** df.mm.trans1:probe12 0.51910659844138 0.0535374537451079 9.69613909755307 7.59592548839703e-21 *** df.mm.trans1:probe13 0.379286662327293 0.0535374537451079 7.08451067047526 3.6596975044194e-12 *** df.mm.trans1:probe14 0.365829131019038 0.0535374537451079 6.83314400346256 1.92370048935135e-11 *** df.mm.trans1:probe15 0.309255253777292 0.0535374537451079 5.77642812916837 1.18648638935137e-08 *** df.mm.trans1:probe16 0.308397816204221 0.0535374537451079 5.76041247072572 1.29868267833169e-08 *** df.mm.trans1:probe17 0.651134990081524 0.0535374537451079 12.1622330636339 8.62744508202207e-31 *** df.mm.trans2:probe2 0.163503444580145 0.0535374537451079 3.05400113644899 0.00235100049109109 ** df.mm.trans2:probe3 0.0547074520542866 0.0535374537451079 1.02185382806491 0.30723259940625 df.mm.trans2:probe4 0.325502283574042 0.0535374537451079 6.07989847861947 2.05738565668790e-09 *** df.mm.trans2:probe5 0.0642865821769792 0.0535374537451079 1.20077772998036 0.230277535180424 df.mm.trans2:probe6 0.194654142683823 0.0535374537451079 3.63584984094635 0.000299126405395314 *** df.mm.trans3:probe2 -0.0415874939713632 0.0535374537451079 -0.776792526767549 0.437565521325658 df.mm.trans3:probe3 -0.693954585369674 0.0535374537451079 -12.9620394102715 2.55673824416360e-34 *** df.mm.trans3:probe4 -0.502951762387799 0.0535374537451079 -9.39439079008791 9.74017477706576e-20 *** df.mm.trans3:probe5 -0.312987777386963 0.0535374537451079 -5.84614611813814 7.98671572163147e-09 *** df.mm.trans3:probe6 -0.363507186925294 0.0535374537451079 -6.78977354163973 2.54865009239421e-11 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.61824654898633 0.208911825794003 22.1061997396938 4.56236416663666e-81 *** df.mm.trans1 -0.471046412972765 0.181436788994679 -2.59620122017580 0.00964044396219412 ** df.mm.trans2 -0.126688946211941 0.164877217214004 -0.768383578717877 0.442540130048867 df.mm.exp2 -0.147109210475426 0.218325369380291 -0.6738072212725 0.500674896001131 df.mm.exp3 -0.231046141168833 0.218325369380291 -1.05826520218264 0.290330101321073 df.mm.exp4 -0.0524377290344763 0.218325369380291 -0.240181565629863 0.81026569958024 df.mm.exp5 -0.170501641840965 0.218325369380291 -0.780952036517463 0.435116788721658 df.mm.exp6 -0.0640693057049096 0.218325369380291 -0.293457905907903 0.76926641975518 df.mm.exp7 -0.324927103671243 0.218325369380291 -1.48827002832304 0.137167668354831 df.mm.exp8 -0.539870413440401 0.218325369380291 -2.47277911391061 0.0136629920812977 * df.mm.trans1:exp2 0.220118901304323 0.201286044915648 1.09356265307199 0.274554442763784 df.mm.trans2:exp2 0.0862622305601622 0.165553408228729 0.521053788521116 0.602507861719908 df.mm.trans1:exp3 0.180386324605282 0.201286044915648 0.896169054744336 0.37049629990444 df.mm.trans2:exp3 0.150165794512351 0.165553408228729 0.907053476693644 0.364716733736701 df.mm.trans1:exp4 0.068072016327351 0.201286044915648 0.338185473095651 0.735333298833608 df.mm.trans2:exp4 -0.0153297623675211 0.165553408228729 -0.0925970810962797 0.92625237094659 df.mm.trans1:exp5 0.201235469600929 0.201286044915648 0.99974873909048 0.317806447333406 df.mm.trans2:exp5 0.185818818484407 0.165553408228729 1.12241010603466 0.262105101995534 df.mm.trans1:exp6 0.0468708859393231 0.201286044915648 0.232857106209052 0.815946124883481 df.mm.trans2:exp6 0.0793244481446397 0.165553408228729 0.479147176692641 0.63199608058844 df.mm.trans1:exp7 0.289272032749758 0.201286044915648 1.43711916477361 0.151168292171447 df.mm.trans2:exp7 0.195410852349074 0.165553408228729 1.18034931711641 0.238295747052283 df.mm.trans1:exp8 0.634324605017268 0.201286044915648 3.151359078485 0.00170027026715731 ** df.mm.trans2:exp8 0.42671048062253 0.165553408228729 2.57747928712519 0.0101729217991836 * df.mm.trans1:probe2 0.103409579001543 0.123262025596569 0.838941097236213 0.401812693774131 df.mm.trans1:probe3 0.100319053131931 0.123262025596569 0.81386828300446 0.416020297121054 df.mm.trans1:probe4 0.04278133570321 0.123262025596569 0.347076364323523 0.72864698623812 df.mm.trans1:probe5 0.174923238335049 0.123262025596569 1.41911701911800 0.156347211015537 df.mm.trans1:probe6 0.074497096115692 0.123262025596569 0.604379943905172 0.545803266160294 df.mm.trans1:probe7 0.19634404740735 0.123262025596569 1.59289973093559 0.111671838920107 df.mm.trans1:probe8 0.0948118696799626 0.123262025596569 0.769189612300206 0.442061892062216 df.mm.trans1:probe9 0.20052917182547 0.123262025596569 1.62685280283965 0.104256007677648 df.mm.trans1:probe10 0.0260639511823257 0.123262025596569 0.211451589053322 0.832601594154211 df.mm.trans1:probe11 0.208205426649186 0.123262025596569 1.68912871293089 0.0916773118783717 . df.mm.trans1:probe12 0.0488840616753114 0.123262025596569 0.396586551605982 0.691803342396248 df.mm.trans1:probe13 0.101978079048063 0.123262025596569 0.827327626286405 0.408356890059937 df.mm.trans1:probe14 0.0954907810534337 0.123262025596569 0.774697483602704 0.438801891837549 df.mm.trans1:probe15 0.222505403752556 0.123262025596569 1.80514154846690 0.071518017064076 . df.mm.trans1:probe16 0.085371550488969 0.123262025596569 0.692602203117987 0.488808120456842 df.mm.trans1:probe17 0.208879935427551 0.123262025596569 1.69460086686557 0.090633119306074 . df.mm.trans2:probe2 -0.0899554893097533 0.123262025596569 -0.729790775986222 0.465782622815378 df.mm.trans2:probe3 -0.170593616059933 0.123262025596569 -1.38399166518875 0.166838962905506 df.mm.trans2:probe4 -0.0886803555907117 0.123262025596569 -0.719445872818598 0.472126423293251 df.mm.trans2:probe5 -0.1635678682272 0.123262025596569 -1.32699318736292 0.18497976887044 df.mm.trans2:probe6 -0.165231622585151 0.123262025596569 -1.34049089154147 0.180557023201458 df.mm.trans3:probe2 0.103531311383562 0.123262025596569 0.839928687545799 0.401259111140656 df.mm.trans3:probe3 0.197012462819122 0.123262025596569 1.59832245061375 0.110460206106048 df.mm.trans3:probe4 0.22277461967065 0.123262025596569 1.80732564301500 0.0711765929871764 . df.mm.trans3:probe5 0.113581283437125 0.123262025596569 0.921462087673874 0.357153217181373 df.mm.trans3:probe6 0.118190095277007 0.123262025596569 0.958852450338912 0.337991802437814