chr19.12133_chr19_37869186_37871496_-_0.R fitVsDatCorrelation=0.935867087840222 cont.fitVsDatCorrelation=0.353881177820501 fstatistic=6108.12450196666,36,324 cont.fstatistic=859.182192667024,36,324 residuals=-0.64616774246827,-0.085158657959894,0.00838411284451235,0.0871771973421361,0.844956510620989 cont.residuals=-0.980524862834131,-0.415762042576664,-0.0209462012348112,0.415441652029494,1.16442574337676 predictedValues: Include Exclude Both chr19.12133_chr19_37869186_37871496_-_0.R.tl.Lung 244.218027243929 92.4783650158491 69.9060057755441 chr19.12133_chr19_37869186_37871496_-_0.R.tl.cerebhem 190.048123079703 128.431979992249 61.463138567812 chr19.12133_chr19_37869186_37871496_-_0.R.tl.cortex 184.869381404028 93.6272316613691 82.7863680852354 chr19.12133_chr19_37869186_37871496_-_0.R.tl.heart 207.586365076006 98.2831376237431 76.8680039971185 chr19.12133_chr19_37869186_37871496_-_0.R.tl.kidney 269.486747930019 86.3316959385528 74.062406544566 chr19.12133_chr19_37869186_37871496_-_0.R.tl.liver 271.433027466192 88.5783072960987 72.9119289230718 chr19.12133_chr19_37869186_37871496_-_0.R.tl.stomach 241.025670936574 157.911866198124 80.8052760462813 chr19.12133_chr19_37869186_37871496_-_0.R.tl.testicle 245.141446430532 90.0648637262857 76.7585677766614 diffExp=151.73966222808,61.6161430874547,91.2421497426587,109.303227452263,183.155051991466,182.854720170094,83.1138047384496,155.076582704246 diffExpScore=0.999018743319556 diffExp1.5=1,0,1,1,1,1,1,1 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 152.856965544940 130.518562161453 143.215945610295 cerebhem 137.877751449428 141.655552124829 164.526909935738 cortex 122.955586637437 154.616471540403 144.374200238004 heart 96.963758852515 127.046698679937 86.0796275416208 kidney 166.078855092189 129.157426233155 122.895545457557 liver 156.144146659538 132.839328932851 136.611115210567 stomach 100.865806238604 154.346520054562 136.504699230071 testicle 143.437912213424 144.439814061834 122.255825741275 cont.diffExp=22.3384033834874,-3.77780067540121,-31.6608849029662,-30.082939827422,36.9214288590344,23.3048177266873,-53.4807138159578,-1.00190184841074 cont.diffExpScore=5.26979827926334 cont.diffExp1.5=0,0,0,0,0,0,-1,0 cont.diffExp1.5Score=0.5 cont.diffExp1.4=0,0,0,0,0,0,-1,0 cont.diffExp1.4Score=0.5 cont.diffExp1.3=0,0,0,-1,0,0,-1,0 cont.diffExp1.3Score=0.666666666666667 cont.diffExp1.2=0,0,-1,-1,1,0,-1,0 cont.diffExp1.2Score=1.33333333333333 tran.correlation=-0.250957506594036 cont.tran.correlation=-0.397707969172683 tran.covariance=-0.00922285216760502 cont.tran.covariance=-0.0053839078260943 tran.mean=168.094764813703 cont.tran.mean=136.987572279819 weightedLogRatios: wLogRatio Lung 4.86758938997526 cerebhem 1.97950784256687 cortex 3.31965177288248 heart 3.70983824926863 kidney 5.72275428494667 liver 5.64819206170296 stomach 2.22997326567558 testicle 5.00771057889488 cont.weightedLogRatios: wLogRatio Lung 0.78211687805403 cerebhem -0.133529916624749 cortex -1.12875544062834 heart -1.27257442682346 kidney 1.25382131781213 liver 0.80334061647369 stomach -2.0532357382914 testicle -0.0345900585682533 varWeightedLogRatios=2.16937608756444 cont.varWeightedLogRatios=1.36570023079497 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.6638695545869 0.112063590435321 50.5415678061455 9.92376108050137e-156 *** df.mm.trans1 -0.0647707660681297 0.0949166904667535 -0.682395959547462 0.495476181619558 df.mm.trans2 -1.17987538873847 0.0949166904667535 -12.4306418917097 2.84046557077086e-29 *** df.mm.exp2 0.206354581880380 0.132182999900200 1.56112799706604 0.119469748284518 df.mm.exp3 -0.435177145163095 0.1321829999002 -3.29223232557636 0.00110366036413077 ** df.mm.exp4 -0.196574315208866 0.132182999900200 -1.4871376452137 0.137950962232413 df.mm.exp5 -0.0280765872016056 0.132182999900200 -0.212406945089791 0.831923134582083 df.mm.exp6 0.0204656212985323 0.132182999900200 0.154827937889019 0.87705336972484 df.mm.exp7 0.377013712804384 0.132182999900200 2.85221029246602 0.00462051592379371 ** df.mm.exp8 -0.116184058315255 0.132182999900200 -0.878963697320955 0.380072353224842 df.mm.trans1:exp2 -0.45713864301247 0.114473835862009 -3.99338975207856 8.06404698163624e-05 *** df.mm.trans2:exp2 0.12207011828315 0.114473835862009 1.06635824128666 0.287055686361446 df.mm.trans1:exp3 0.156765293818884 0.114473835862009 1.36944213180604 0.171809544120073 df.mm.trans2:exp3 0.447523697445004 0.114473835862009 3.90939723540378 0.000112708065469605 *** df.mm.trans1:exp4 0.034060404929385 0.114473835862009 0.297538775327164 0.766245893466378 df.mm.trans2:exp4 0.257452062264858 0.114473835862009 2.24900354151844 0.0251836554380684 * df.mm.trans1:exp5 0.126534422950588 0.114473835862009 1.10535671315424 0.269825172352143 df.mm.trans2:exp5 -0.040701331350426 0.114473835862009 -0.355551389048314 0.722407919537352 df.mm.trans1:exp6 0.0851884310570049 0.114473835862009 0.74417381417789 0.457310691078184 df.mm.trans2:exp6 -0.0635533577507507 0.114473835862009 -0.555178021878819 0.579155989769295 df.mm.trans1:exp7 -0.390171647167023 0.114473835862009 -3.40839148290052 0.000735959152634579 *** df.mm.trans2:exp7 0.158048630275810 0.114473835862009 1.38065287221028 0.168337391984657 df.mm.trans1:exp8 0.119958054047651 0.114473835862009 1.04790804941885 0.295462042801509 df.mm.trans2:exp8 0.0897394516891215 0.114473835862009 0.783929803813831 0.433654014612212 df.mm.trans1:probe2 -0.437325425056721 0.0572369179310045 -7.64061799386 2.46375165371188e-13 *** df.mm.trans1:probe3 -0.417310350127096 0.0572369179310045 -7.29092979167986 2.3747320779548e-12 *** df.mm.trans1:probe4 -0.0527584940226144 0.0572369179310045 -0.921756375600298 0.357341510718922 df.mm.trans1:probe5 0.0669329666636021 0.0572369179310045 1.16940200631148 0.243101269106441 df.mm.trans1:probe6 -0.068875368819449 0.0572369179310045 -1.20333818292721 0.229723981669537 df.mm.trans2:probe2 0.0431683420341227 0.0572369179310045 0.754204516849761 0.451274211146698 df.mm.trans2:probe3 0.314498520710018 0.0572369179310045 5.49467951941659 7.93305527321566e-08 *** df.mm.trans2:probe4 -0.274644109388793 0.0572369179310045 -4.79837348544621 2.44525202239448e-06 *** df.mm.trans2:probe5 0.0176053009720283 0.0572369179310045 0.307586460075478 0.758594646826265 df.mm.trans2:probe6 0.286196982004729 0.0572369179310045 5.00021650973104 9.39879515560276e-07 *** df.mm.trans3:probe2 -0.2558232991062 0.0572369179310045 -4.46955056899777 1.08507394084468e-05 *** df.mm.trans3:probe3 -0.260392204981006 0.0572369179310045 -4.54937502565901 7.61626743757594e-06 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.093369446826 0.297462864547207 17.1227069119335 2.93273546202144e-47 *** df.mm.trans1 0.0551679017627119 0.251947938932733 0.218965481505452 0.82681480523004 df.mm.trans2 -0.206948541836745 0.251947938932733 -0.82139406543031 0.412025826775198 df.mm.exp2 -0.159972761474892 0.350868053058235 -0.455934246736167 0.648742697603728 df.mm.exp3 -0.0563021359280655 0.350868053058235 -0.160465267320079 0.87261457848149 df.mm.exp4 0.0269547706157224 0.350868053058235 0.0768230974030815 0.938811692738069 df.mm.exp5 0.225495480820122 0.350868053058235 0.642678861340207 0.520887020240321 df.mm.exp6 0.0861171546376747 0.350868053058235 0.245440284138327 0.806270932396673 df.mm.exp7 -0.200032326933219 0.350868053058235 -0.570106982353331 0.56900024651482 df.mm.exp8 0.195984928137616 0.350868053058235 0.558571595303058 0.576839944208617 df.mm.trans1:exp2 0.0568375765513686 0.303860647324818 0.18705145615849 0.851737362958499 df.mm.trans2:exp2 0.241855727631106 0.303860647324818 0.795942909226312 0.426647984112196 df.mm.trans1:exp3 -0.161377276568207 0.303860647324818 -0.531089754428449 0.595720455459332 df.mm.trans2:exp3 0.225734353925392 0.303860647324818 0.742887754346448 0.458087923605048 df.mm.trans1:exp4 -0.482120100416469 0.303860647324818 -1.58664869788518 0.113567654247874 df.mm.trans2:exp4 -0.0539155010360807 0.303860647324818 -0.177434957473933 0.859277624369418 df.mm.trans1:exp5 -0.142535392992688 0.303860647324818 -0.46908144982763 0.639326899215992 df.mm.trans2:exp5 -0.235978917526798 0.303860647324818 -0.7766024314249 0.437959942029468 df.mm.trans1:exp6 -0.0648401753943671 0.303860647324818 -0.213387866988432 0.831158652308337 df.mm.trans2:exp6 -0.0684922652696289 0.303860647324818 -0.22540682998155 0.821804906686703 df.mm.trans1:exp7 -0.215679309181535 0.303860647324818 -0.709796780466214 0.478340675608702 df.mm.trans2:exp7 0.367717076386545 0.303860647324818 1.21015037525892 0.227103324253707 df.mm.trans1:exp8 -0.259585272481399 0.303860647324818 -0.854290526814781 0.39357523203399 df.mm.trans2:exp8 -0.0946374744658715 0.303860647324818 -0.311450249642583 0.755658660688122 df.mm.trans1:probe2 -0.111886398709604 0.151930323662409 -0.736432306681692 0.462000512500154 df.mm.trans1:probe3 -0.117299737289128 0.151930323662409 -0.772062709151924 0.440640057000306 df.mm.trans1:probe4 -0.32215412654349 0.151930323662409 -2.12040703118175 0.0347312769309117 * df.mm.trans1:probe5 -0.152449846550901 0.151930323662409 -1.00341948121987 0.316407301250285 df.mm.trans1:probe6 -0.367522462482955 0.151930323662409 -2.41901980870912 0.0161128895310478 * df.mm.trans2:probe2 0.0631844864975978 0.151930323662409 0.415878048400624 0.677774559503124 df.mm.trans2:probe3 -0.0342981326536777 0.151930323662409 -0.225749092260796 0.821538906995101 df.mm.trans2:probe4 0.113140952859373 0.151930323662409 0.744689737585062 0.456999101072153 df.mm.trans2:probe5 -0.207687038394590 0.151930323662409 -1.36698871817106 0.172576538339901 df.mm.trans2:probe6 -0.0684893143163687 0.151930323662409 -0.450794236893438 0.652439384886627 df.mm.trans3:probe2 0.0661538120813047 0.151930323662409 0.435422044043685 0.663546031897897 df.mm.trans3:probe3 0.00214056872648525 0.151930323662409 0.0140891474123469 0.988767530215943