chr6.20107_chr6_131017496_131019769_-_0.R fitVsDatCorrelation=0.70152467741448 cont.fitVsDatCorrelation=0.252255159128533 fstatistic=9760.33924324831,37,347 cont.fstatistic=5289.48154249117,37,347 residuals=-0.456864934708792,-0.0708108630009865,-0.00303082655970223,0.0644132626590496,0.551709599567958 cont.residuals=-0.40167643389043,-0.105653460905833,-0.0249555349328608,0.0813887233291273,0.960120256794653 predictedValues: Include Exclude Both chr6.20107_chr6_131017496_131019769_-_0.R.tl.Lung 53.8150437647995 61.7962117041644 59.8832283218589 chr6.20107_chr6_131017496_131019769_-_0.R.tl.cerebhem 78.2565246978477 62.637538587734 46.4662781238736 chr6.20107_chr6_131017496_131019769_-_0.R.tl.cortex 50.5457342465869 57.005826966192 53.1627311706739 chr6.20107_chr6_131017496_131019769_-_0.R.tl.heart 52.2478708880143 60.5936404988011 56.6895770837461 chr6.20107_chr6_131017496_131019769_-_0.R.tl.kidney 53.6843629560549 64.7972254342447 58.2657736580724 chr6.20107_chr6_131017496_131019769_-_0.R.tl.liver 53.4620193887519 60.8458764168528 52.5579303274019 chr6.20107_chr6_131017496_131019769_-_0.R.tl.stomach 55.7982156992351 57.2386272342791 55.0337283958099 chr6.20107_chr6_131017496_131019769_-_0.R.tl.testicle 57.5753684644716 63.1640740900253 53.4369268444538 diffExp=-7.98116793936488,15.6189861101138,-6.46009271960512,-8.3457696107868,-11.1128624781897,-7.38385702810097,-1.44041153504392,-5.5887056255537 diffExpScore=1.89743215914794 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=0,1,0,0,-1,0,0,0 diffExp1.2Score=2 cont.predictedValues: Include Exclude Both Lung 61.1032030978227 58.2418484829475 57.3862103297492 cerebhem 58.7602366218273 54.3003877225921 52.1496659985603 cortex 57.9384942582293 60.1734751230653 54.2483580680835 heart 56.531694175384 56.455569455594 58.1655836532938 kidney 56.1881235701411 55.4181113227658 58.2566662465136 liver 58.9213316736743 59.471081138439 55.9772399968795 stomach 58.9111805517598 56.4323071287937 58.4769894577161 testicle 58.4519210392827 56.8971291199458 54.7194213733444 cont.diffExp=2.86135461487515,4.45984889923515,-2.23498086483600,0.076124719790009,0.770012247375291,-0.549749464764687,2.47887342296610,1.55479191933697 cont.diffExpScore=1.43868469702468 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=0.315035644266953 cont.tran.correlation=0.302376711871419 tran.covariance=0.00207983689499709 cont.tran.covariance=0.000279585474301504 tran.mean=58.9665100648785 cont.tran.mean=57.7622559051415 weightedLogRatios: wLogRatio Lung -0.560720116519717 cerebhem 0.94587246632861 cortex -0.479056993198348 heart -0.597222949953181 kidney -0.767087107725199 liver -0.523138385228285 stomach -0.102827251394863 testicle -0.379773299258893 cont.weightedLogRatios: wLogRatio Lung 0.196089096797415 cerebhem 0.318419671622816 cortex -0.154362439316563 heart 0.00543595582140761 kidney 0.0554967017495458 liver -0.0378987022563826 stomach 0.174300784984670 testicle 0.109314035192902 varWeightedLogRatios=0.293323827011219 cont.varWeightedLogRatios=0.0221384124259665 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.13965296504947 0.0717095787162561 57.7280335369065 5.43398518175333e-180 *** df.mm.trans1 -0.197550661987655 0.0597439199072482 -3.30662370822587 0.00104303153670336 ** df.mm.trans2 0.052154826235339 0.0597439199072482 0.872972953838798 0.38328150500987 df.mm.exp2 0.641631473156189 0.0823145710867944 7.79487112287371 7.58536344816861e-14 *** df.mm.exp3 -0.0243242077415476 0.0823145710867944 -0.295503061249017 0.767786356743045 df.mm.exp4 0.00560007464031635 0.0823145710867944 0.0680326042689514 0.94579886411151 df.mm.exp5 0.0723710593808472 0.0823145710867944 0.87920107491707 0.379900688142924 df.mm.exp6 0.108400894558241 0.0823145710867944 1.31691015487332 0.18873776510922 df.mm.exp7 0.0440259791233008 0.0823145710867944 0.534850373901344 0.593095879103825 df.mm.exp8 0.203329872105476 0.0823145710867944 2.47015649138328 0.0139856725725322 * df.mm.trans1:exp2 -0.267192316453273 0.0695685099801572 -3.84070776461194 0.000145823361634180 *** df.mm.trans2:exp2 -0.6281087801215 0.0695685099801572 -9.02863638017622 1.22324115385739e-17 *** df.mm.trans1:exp3 -0.0383502891273543 0.0695685099801572 -0.551259314570526 0.581810700714727 df.mm.trans2:exp3 -0.0563643654711234 0.0695685099801572 -0.810199406127858 0.418380852255974 df.mm.trans1:exp4 -0.0351539851416896 0.0695685099801572 -0.505314619383345 0.613658675115996 df.mm.trans2:exp4 -0.0252521926352815 0.0695685099801572 -0.362983088792387 0.716838523720333 df.mm.trans1:exp5 -0.0748023448568075 0.0695685099801572 -1.07523281551011 0.283017559063340 df.mm.trans2:exp5 -0.0249503376114774 0.0695685099801572 -0.358644128192394 0.720079432424407 df.mm.trans1:exp6 -0.114982462695921 0.0695685099801572 -1.65279467288744 0.0992771040197269 . df.mm.trans2:exp6 -0.123898907082670 0.0695685099801572 -1.7809624946403 0.07579327158655 . df.mm.trans1:exp7 -0.00783713892481704 0.0695685099801572 -0.112653540043511 0.910370377915972 df.mm.trans2:exp7 -0.120639070651686 0.0695685099801572 -1.73410456377598 0.0837876515319755 . df.mm.trans1:exp8 -0.135788078650213 0.0695685099801572 -1.9518612471209 0.0517587546937867 . df.mm.trans2:exp8 -0.181436243822489 0.0695685099801572 -2.60802256472417 0.00950017959945977 ** df.mm.trans1:probe2 0.068017470071943 0.0381042422081554 1.78503668175260 0.0751287617229512 . df.mm.trans1:probe3 0.169480460425269 0.0381042422081554 4.44781081065550 1.1697129802563e-05 *** df.mm.trans1:probe4 -0.04217510998737 0.0381042422081554 -1.10683502789470 0.269131960444205 df.mm.trans1:probe5 0.133578217390580 0.0381042422081554 3.50559963011126 0.000515351889837752 *** df.mm.trans1:probe6 0.105606451094440 0.0381042422081554 2.77151427175837 0.00588041286300821 ** df.mm.trans2:probe2 -0.118052236035221 0.0381042422081554 -3.09813892611553 0.00210630746024370 ** df.mm.trans2:probe3 -0.194135664493448 0.0381042422081554 -5.09485698292926 5.74282519565444e-07 *** df.mm.trans2:probe4 -0.259659055706918 0.0381042422081554 -6.8144395652446 4.19774476513944e-11 *** df.mm.trans2:probe5 -0.0695422694041342 0.0381042422081554 -1.82505320599842 0.0688525637046319 . df.mm.trans2:probe6 -0.0382680542143334 0.0381042422081554 -1.00429904904769 0.315934298973604 df.mm.trans3:probe2 0.10754741071678 0.0381042422081554 2.82245242220725 0.00504049531351338 ** df.mm.trans3:probe3 0.182534929706913 0.0381042422081554 4.7904096533337 2.47050437039268e-06 *** df.mm.trans3:probe4 0.102475027543136 0.0381042422081554 2.68933382753912 0.00750524488610736 ** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.12921000449783 0.0973704007276924 42.4072405334517 2.51723357650870e-139 *** df.mm.trans1 -0.00881067346162324 0.0811229061242996 -0.108608947614909 0.913575438953395 df.mm.trans2 -0.0612916701992745 0.0811229061242996 -0.755540859265583 0.450437071276319 df.mm.exp2 -0.0134854260886311 0.111770322960109 -0.120653011743055 0.904035708780718 df.mm.exp3 0.0356765259574369 0.111770322960109 0.31919497960268 0.749770729054669 df.mm.exp4 -0.122402841257723 0.111770322960109 -1.09512827748926 0.274219973133723 df.mm.exp5 -0.148611052998372 0.111770322960109 -1.32961101894115 0.184519858904394 df.mm.exp6 0.00938378154165917 0.111770322960109 0.0839559311733247 0.933139883066768 df.mm.exp7 -0.0869250178675961 0.111770322960109 -0.777711073614952 0.437269273841669 df.mm.exp8 -0.0201336549716124 0.111770322960109 -0.180134175498429 0.857152383019394 df.mm.trans1:exp2 -0.0256134843567485 0.0944631640021164 -0.271147855646405 0.786438542748342 df.mm.trans2:exp2 -0.0565873490640986 0.0944631640021164 -0.599041432307209 0.54953613454593 df.mm.trans1:exp3 -0.0888588105661085 0.0944631640021164 -0.94067154646776 0.347527574041517 df.mm.trans2:exp3 -0.00304902576092735 0.0944631640021164 -0.0322774045643764 0.97426938579892 df.mm.trans1:exp4 0.0446399923247832 0.0944631640021164 0.472565076517901 0.636820580357268 df.mm.trans2:exp4 0.09125264628686 0.0944631640021164 0.966013019475142 0.334710430158628 df.mm.trans1:exp5 0.0647521745280769 0.0944631640021164 0.685475393632021 0.493501657495203 df.mm.trans2:exp5 0.0989133700623202 0.0944631640021164 1.04711049123978 0.295777431328171 df.mm.trans1:exp6 -0.045744877479533 0.0944631640021164 -0.484261542187049 0.628505765066694 df.mm.trans2:exp6 0.0115022391253381 0.0944631640021164 0.121764279725803 0.903156187003911 df.mm.trans1:exp7 0.0503916244585432 0.0944631640021164 0.533452642528617 0.594061800665219 df.mm.trans2:exp7 0.0553626913581941 0.0944631640021164 0.586077037997093 0.55820475972435 df.mm.trans1:exp8 -0.0242260799442314 0.0944631640021164 -0.256460602396175 0.797747178785903 df.mm.trans2:exp8 -0.00322560244933998 0.0944631640021164 -0.0341466695871812 0.972779826578845 df.mm.trans1:probe2 0.0220011469845172 0.0517396057772692 0.425228345945051 0.670933800572424 df.mm.trans1:probe3 -0.0319111200025934 0.0517396057772692 -0.616763879878902 0.537794919383928 df.mm.trans1:probe4 -0.0554110842324025 0.0517396057772692 -1.07096069635587 0.284931427777612 df.mm.trans1:probe5 0.0328387999586089 0.0517396057772692 0.634693663882457 0.52604646648487 df.mm.trans1:probe6 -0.0458681664393966 0.0517396057772692 -0.886519441931038 0.375951662021883 df.mm.trans2:probe2 -0.00665413610320795 0.0517396057772692 -0.128608171694484 0.897742206270819 df.mm.trans2:probe3 0.0359419816689793 0.0517396057772692 0.694670574486089 0.487726629834832 df.mm.trans2:probe4 -0.00314970323026645 0.0517396057772692 -0.0608760577694663 0.951492963446206 df.mm.trans2:probe5 -0.0229345715317681 0.0517396057772692 -0.443269158843186 0.657847293178692 df.mm.trans2:probe6 -0.0363454893257783 0.0517396057772692 -0.702469390320443 0.482857440172812 df.mm.trans3:probe2 -0.0126328579978025 0.0517396057772692 -0.244162239120741 0.807249471466387 df.mm.trans3:probe3 0.0261588189311575 0.0517396057772692 0.505585973031318 0.61346832784648 df.mm.trans3:probe4 -0.0507404590569736 0.0517396057772692 -0.980688938284595 0.327429403385722