chr17.10681_chr17_55249958_55250433_-_0.R fitVsDatCorrelation=0.927377233564598 cont.fitVsDatCorrelation=0.341235010339436 fstatistic=6533.69070586918,36,324 cont.fstatistic=1027.47901096094,36,324 residuals=-0.601943879423306,-0.122559975793294,-0.00807847390797238,0.116440943887596,0.61547140598728 cont.residuals=-1.05091590757381,-0.365581179379271,0.0534122650283609,0.311821017190099,1.12285074912156 predictedValues: Include Exclude Both chr17.10681_chr17_55249958_55250433_-_0.R.tl.Lung 179.460786872484 162.074372942678 70.8724234908003 chr17.10681_chr17_55249958_55250433_-_0.R.tl.cerebhem 157.547643030925 121.162346428050 65.1541368532833 chr17.10681_chr17_55249958_55250433_-_0.R.tl.cortex 148.400544081120 137.046947283416 74.9084603335561 chr17.10681_chr17_55249958_55250433_-_0.R.tl.heart 168.740074896522 153.179668133754 72.2702083274238 chr17.10681_chr17_55249958_55250433_-_0.R.tl.kidney 172.721157318449 152.392914856296 60.3244408303031 chr17.10681_chr17_55249958_55250433_-_0.R.tl.liver 190.818869783878 151.303755575105 60.5609928167863 chr17.10681_chr17_55249958_55250433_-_0.R.tl.stomach 181.629867109727 157.195547831162 62.3376961738422 chr17.10681_chr17_55249958_55250433_-_0.R.tl.testicle 170.674128007533 132.311991821329 64.5500470658672 diffExp=17.3864139298056,36.3852966028745,11.3535967977043,15.5604067627675,20.3282424621531,39.5151142087731,24.4343192785651,38.3621361862039 diffExpScore=0.995105848894866 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=0,1,0,0,0,0,0,0 diffExp1.3Score=0.5 diffExp1.2=0,1,0,0,0,1,0,1 diffExp1.2Score=0.75 cont.predictedValues: Include Exclude Both Lung 115.699850604162 103.342428666781 121.409880816971 cerebhem 132.356401220115 141.716080057455 142.176842319350 cortex 108.981909412603 118.581587469308 118.645731726079 heart 140.120577120801 145.422098940527 137.390916090302 kidney 108.518942105421 129.819245580801 151.008632276631 liver 114.505704321329 153.541382394570 181.491003078820 stomach 119.70925299976 124.461246918168 116.314224061804 testicle 152.001530472759 139.475403296715 110.163305309509 cont.diffExp=12.3574219373807,-9.35967883733991,-9.59967805670414,-5.30152181972636,-21.3003034753798,-39.0356780732407,-4.75199391840768,12.5261271760436 cont.diffExpScore=1.74493043569658 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,-1,0,0 cont.diffExp1.3Score=0.5 cont.diffExp1.2=0,0,0,0,0,-1,0,0 cont.diffExp1.2Score=0.5 tran.correlation=0.673069685601958 cont.tran.correlation=0.447272605803357 tran.covariance=0.00536899776742589 cont.tran.covariance=0.00719445214766345 tran.mean=158.541288498277 cont.tran.mean=128.015852598830 weightedLogRatios: wLogRatio Lung 0.523671931137571 cerebhem 1.29418864552662 cortex 0.394783080183789 heart 0.491478330833999 kidney 0.637234733948254 liver 1.19157204831196 stomach 0.74114534994818 testicle 1.27613880588317 cont.weightedLogRatios: wLogRatio Lung 0.530252640596659 cerebhem -0.33614734874191 cortex -0.399589724248294 heart -0.184240437916890 kidney -0.856042404991421 liver -1.43366660467081 stomach -0.187033087520561 testicle 0.428368068511016 varWeightedLogRatios=0.141019819175428 cont.varWeightedLogRatios=0.407346817128781 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 6.09458606933878 0.107715510923934 56.5803941982195 5.355998670851e-170 *** df.mm.trans1 -0.949520205965397 0.0912339125412558 -10.4075357453954 4.48060838541755e-22 *** df.mm.trans2 -0.786417479313643 0.0912339125412558 -8.61979342339424 3.01569349045442e-16 *** df.mm.exp2 -0.337027178756188 0.127054285110792 -2.65262347084398 0.00838014821035907 ** df.mm.exp3 -0.41315893425471 0.127054285110792 -3.25182998664259 0.00126733783377257 ** df.mm.exp4 -0.137571581479885 0.127054285110792 -1.08277797446912 0.279712139206270 df.mm.exp5 0.0612726561516989 0.127054285110792 0.482255723199489 0.629949921322192 df.mm.exp6 0.149832451835501 0.127054285110792 1.17927901215490 0.239152318606889 df.mm.exp7 0.109764519060776 0.127054285110792 0.863918276861432 0.388271888815247 df.mm.exp8 -0.159652724203658 0.127054285110792 -1.25657095362381 0.209814230622854 df.mm.trans1:exp2 0.2067983601857 0.110032238565617 1.87943427200546 0.0610825428129284 . df.mm.trans2:exp2 0.0461032089661115 0.110032238565617 0.418997282679279 0.675495753240052 df.mm.trans1:exp3 0.223117204767996 0.110032238565617 2.0277439382908 0.0434044446817528 * df.mm.trans2:exp3 0.245427160161454 0.110032238565617 2.23050229060909 0.0263985074413219 * df.mm.trans1:exp4 0.0759743675467098 0.110032238565617 0.690473706043918 0.490390664674151 df.mm.trans2:exp4 0.0811277933268554 0.110032238565617 0.73730930484047 0.461467874171267 df.mm.trans1:exp5 -0.099550895948864 0.110032238565617 -0.904742984843465 0.366273809014379 df.mm.trans2:exp5 -0.122865826544660 0.110032238565617 -1.11663479854942 0.264977903456347 df.mm.trans1:exp6 -0.0884645260011699 0.110032238565617 -0.80398733275262 0.421993774545604 df.mm.trans2:exp6 -0.218598331426798 0.110032238565617 -1.98667530785933 0.0478004184904113 * df.mm.trans1:exp7 -0.0977503264815564 0.110032238565617 -0.888378967435658 0.374995976659190 df.mm.trans2:exp7 -0.140329283271996 0.110032238565617 -1.2753469810424 0.203100135508924 df.mm.trans1:exp8 0.109452051885455 0.110032238565617 0.994727120999042 0.320611303639415 df.mm.trans2:exp8 -0.043239889774914 0.110032238565617 -0.392974734846718 0.694596571724881 df.mm.trans1:probe2 -0.0613492790707357 0.0550161192828083 -1.11511462223230 0.265627730273644 df.mm.trans1:probe3 -0.225606669734925 0.0550161192828083 -4.10073761428359 5.21303015816603e-05 *** df.mm.trans1:probe4 0.0759089225435894 0.0550161192828083 1.37975785157405 0.168612636107262 df.mm.trans1:probe5 0.119166830987479 0.0550161192828083 2.16603483744294 0.0310374908332895 * df.mm.trans1:probe6 0.495897963667048 0.0550161192828083 9.01368490056348 1.76968652060385e-17 *** df.mm.trans2:probe2 -0.502807270246195 0.0550161192828083 -9.13927184979249 7.0559415135896e-18 *** df.mm.trans2:probe3 -0.406368753667269 0.0550161192828083 -7.3863580158816 1.28875950413060e-12 *** df.mm.trans2:probe4 -0.970571938529546 0.0550161192828083 -17.6415921584792 2.7153158496513e-49 *** df.mm.trans2:probe5 -0.085752312783079 0.0550161192828083 -1.55867614620858 0.120049264386866 df.mm.trans2:probe6 -0.0155191359153103 0.0550161192828083 -0.282083435138977 0.778059631580532 df.mm.trans3:probe2 -0.151894924087601 0.0550161192828083 -2.76091672890978 0.00609236053342499 ** df.mm.trans3:probe3 -0.141406002520682 0.0550161192828083 -2.57026493987679 0.0106085092103168 * cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.53800492487339 0.270630154171926 16.7682900627196 7.15766649946207e-46 *** df.mm.trans1 0.229353735229779 0.229220913543121 1.00057944837844 0.317776848758509 df.mm.trans2 0.100090585891719 0.229220913543121 0.436655557927047 0.662652011292546 df.mm.exp2 0.292377160618513 0.319217914604882 0.915917143874611 0.360391546799156 df.mm.exp3 0.100766015338728 0.319217914604882 0.315665289222421 0.752459809078482 df.mm.exp4 0.409438491761109 0.319217914604882 1.28263005623572 0.200538552104379 df.mm.exp5 -0.0541443002585041 0.319217914604882 -0.169615481404050 0.865418398737487 df.mm.exp6 -0.0164864200279869 0.319217914604882 -0.05164628698359 0.95884236294051 df.mm.exp7 0.262889850555866 0.319217914604882 0.82354353727692 0.410804739779460 df.mm.exp8 0.669939895001534 0.319217914604882 2.09869140906695 0.0366178432426492 * df.mm.trans1:exp2 -0.157878210230236 0.276450823390919 -0.571089672635869 0.568334759359873 df.mm.trans2:exp2 0.0234004349330837 0.276450823390919 0.08464592235992 0.932595167026712 df.mm.trans1:exp3 -0.160583458539866 0.276450823390919 -0.580875312904352 0.561728314551779 df.mm.trans2:exp3 0.036787185884935 0.276450823390919 0.133069547175541 0.89422098660483 df.mm.trans1:exp4 -0.21793451764348 0.276450823390919 -0.788330144834862 0.431080017112223 df.mm.trans2:exp4 -0.0678459752928018 0.276450823390919 -0.245417881056058 0.806288262199533 df.mm.trans1:exp5 -0.0099303033460345 0.276450823390919 -0.0359206864505968 0.97136772141424 df.mm.trans2:exp5 0.282239340282405 0.276450823390919 1.0209386856602 0.308045185180141 df.mm.trans1:exp6 0.00611171821734551 0.276450823390919 0.0221077953119465 0.982375576988869 df.mm.trans2:exp6 0.412408518575284 0.276450823390919 1.49179703470122 0.136725357267434 df.mm.trans1:exp7 -0.228823282358498 0.276450823390919 -0.827717854306865 0.408439541773332 df.mm.trans2:exp7 -0.0769434771327301 0.276450823390919 -0.278326091378383 0.780939587570375 df.mm.trans1:exp8 -0.397048648270464 0.276450823390919 -1.43623608495827 0.151899988663708 df.mm.trans2:exp8 -0.370099654033603 0.276450823390919 -1.33875403044200 0.181589323258911 df.mm.trans1:probe2 0.0859987580314293 0.138225411695460 0.622163153479356 0.534272167976676 df.mm.trans1:probe3 -0.148927532996700 0.138225411695460 -1.07742513601493 0.282091912131735 df.mm.trans1:probe4 -0.172773925087804 0.138225411695460 -1.24994328444080 0.212222344874808 df.mm.trans1:probe5 0.0385478537036864 0.138225411695460 0.27887675088728 0.780517324206979 df.mm.trans1:probe6 0.0499209920990316 0.138225411695460 0.361156400163368 0.718217911009768 df.mm.trans2:probe2 -0.0987043277287759 0.138225411695460 -0.714082356623707 0.475690358909858 df.mm.trans2:probe3 -0.0730390692461238 0.138225411695460 -0.528405510609327 0.597579657624809 df.mm.trans2:probe4 -0.124641785440278 0.138225411695460 -0.901728444223347 0.367870961487066 df.mm.trans2:probe5 0.104241190752255 0.138225411695460 0.754139122999473 0.451313417940959 df.mm.trans2:probe6 0.191716613418913 0.138225411695460 1.38698529501439 0.166399664666502 df.mm.trans3:probe2 -0.0668066510890613 0.138225411695460 -0.483316709059625 0.629197322820468 df.mm.trans3:probe3 -0.138024289201693 0.138225411695460 -0.998544967301603 0.318760331407347