chr7.21309_chr7_17942032_17943469_-_0.R fitVsDatCorrelation=0.912418371896051 cont.fitVsDatCorrelation=0.253261577255628 fstatistic=11458.1099900615,40,416 cont.fstatistic=2042.14503765677,40,416 residuals=-0.429563775729911,-0.080815075379062,-0.00217791504047163,0.0719106402578053,0.817019805929942 cont.residuals=-0.632311860309226,-0.22915040521719,-0.0159788417350916,0.224860002739102,0.937283433712622 predictedValues: Include Exclude Both chr7.21309_chr7_17942032_17943469_-_0.R.tl.Lung 95.7928252393067 46.7959516567528 77.6589634480466 chr7.21309_chr7_17942032_17943469_-_0.R.tl.cerebhem 76.1887201785237 45.899366238714 68.6300459489365 chr7.21309_chr7_17942032_17943469_-_0.R.tl.cortex 94.9310272367386 51.3159601301107 78.599026970931 chr7.21309_chr7_17942032_17943469_-_0.R.tl.heart 99.1692928639442 49.3602924632613 75.6992749730042 chr7.21309_chr7_17942032_17943469_-_0.R.tl.kidney 105.683479462715 52.0982348138054 69.0432485642016 chr7.21309_chr7_17942032_17943469_-_0.R.tl.liver 113.738048891881 49.5136167520385 62.8669825068657 chr7.21309_chr7_17942032_17943469_-_0.R.tl.stomach 92.8322113652799 45.7630643009605 68.1249594495695 chr7.21309_chr7_17942032_17943469_-_0.R.tl.testicle 101.277738204232 50.6343924114989 71.7074727544846 diffExp=48.9968735825539,30.2893539398097,43.6150671066279,49.8090004006829,53.5852446489099,64.2244321398428,47.0691470643194,50.6433457927333 diffExpScore=0.997430841230487 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 69.5359253299813 66.7955476948508 77.9120347130801 cerebhem 77.1100879516368 74.4180526624228 74.5148039234867 cortex 66.0381005330131 75.1697604095933 68.4245139362806 heart 71.5855343924305 75.3573285495507 68.9814487247308 kidney 76.9712496632541 71.4632004701948 66.1796932081646 liver 69.5533533962469 72.7021446753593 74.7963742051081 stomach 70.3121830257423 72.3219395400447 74.1143378420927 testicle 67.0300925259874 68.3199579577454 70.2709379660255 cont.diffExp=2.74037763513053,2.69203528921406,-9.13165987658019,-3.77179415712018,5.50804919305932,-3.14879127911242,-2.00975651430242,-1.28986543175802 cont.diffExpScore=3.2186829618885 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=0.631560001010485 cont.tran.correlation=0.208405185670825 tran.covariance=0.00383398669364823 cont.tran.covariance=0.000530798730680804 tran.mean=73.1871388881102 cont.tran.mean=71.5427786736284 weightedLogRatios: wLogRatio Lung 3.01170259734988 cerebhem 2.06750447069835 cortex 2.61166103072489 heart 2.96374480248157 kidney 3.04626788469621 liver 3.59112645368454 stomach 2.95455633915291 testicle 2.96098169834207 cont.weightedLogRatios: wLogRatio Lung 0.169743934980823 cerebhem 0.153778934084139 cortex -0.551094327254233 heart -0.220620817174629 kidney 0.319740443627921 liver -0.188806363668365 stomach -0.120255538613887 testicle -0.0803327966313596 varWeightedLogRatios=0.18549530742252 cont.varWeightedLogRatios=0.0757307692721686 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.13369589619063 0.0690446595309433 59.8698860168621 1.41150893488947e-206 *** df.mm.trans1 0.432941353875128 0.0560026139529964 7.73073475174749 8.120232800676e-14 *** df.mm.trans2 -0.310680574123914 0.0560026139529963 -5.54760844528921 5.16113367862024e-08 *** df.mm.exp2 -0.124723202588568 0.0757293559332695 -1.6469597694515 0.100321458945940 df.mm.exp3 0.0711355881420793 0.0757293559332695 0.939339669081062 0.348101457635676 df.mm.exp4 0.113548632283321 0.0757293559332695 1.49940047533716 0.134528257243040 df.mm.exp5 0.323189044338358 0.0757293559332695 4.26768510514129 2.44820506603621e-05 *** df.mm.exp6 0.43946709151279 0.0757293559332695 5.80312728263575 1.29160867190845e-08 *** df.mm.exp7 0.0772698282260355 0.0757293559332695 1.02034181162353 0.308159387508308 df.mm.exp8 0.214245190412921 0.0757293559332695 2.82909035436282 0.00489393206585979 ** df.mm.trans1:exp2 -0.104251163883760 0.0610549586646661 -1.70749708400167 0.0884758121597614 . df.mm.trans2:exp2 0.105377816003162 0.0610549586646661 1.72595016535728 0.085098899028785 . df.mm.trans1:exp3 -0.0801727783695555 0.0610549586646661 -1.31312476698069 0.189864759135808 df.mm.trans2:exp3 0.0210695331750535 0.0610549586646661 0.345091269175601 0.730200171014294 df.mm.trans1:exp4 -0.0789080027090845 0.0610549586646661 -1.29240940350927 0.196932814761615 df.mm.trans2:exp4 -0.0601990237183096 0.0610549586646661 -0.985980910231099 0.324715589082159 df.mm.trans1:exp5 -0.224928249205873 0.0610549586646661 -3.6840291783875 0.000259890754597633 *** df.mm.trans2:exp5 -0.215854673007260 0.0610549586646661 -3.53541592244465 0.000452882462874507 *** df.mm.trans1:exp6 -0.267756892942470 0.0610549586646661 -4.38550608826186 1.46787970283759e-05 *** df.mm.trans2:exp6 -0.383016069988724 0.0610549586646661 -6.2732999639288 8.87516173521608e-10 *** df.mm.trans1:exp7 -0.108663932485956 0.0610549586646661 -1.77977243556537 0.0758431154246318 . df.mm.trans2:exp7 -0.099589214898788 0.0610549586646661 -1.6311404851777 0.103617468108820 df.mm.trans1:exp8 -0.158566353427433 0.0610549586646661 -2.59710852149343 0.0097344900827634 ** df.mm.trans2:exp8 -0.135410849199746 0.0610549586646661 -2.2178517873293 0.0271044585147263 * df.mm.trans1:probe2 -0.137423573572405 0.0387997490893022 -3.54186758414618 0.000442267335264528 *** df.mm.trans1:probe3 -0.183275947722643 0.0387997490893022 -4.72363744674771 3.17309083636373e-06 *** df.mm.trans1:probe4 -0.0238053463960587 0.0387997490893022 -0.613543823215659 0.539852140067501 df.mm.trans1:probe5 0.129770446275273 0.0387997490893022 3.34462075970108 0.00089867274549674 *** df.mm.trans1:probe6 0.156891428266939 0.0387997490893022 4.0436196611951 6.27264875239337e-05 *** df.mm.trans2:probe2 0.0627802673468784 0.0387997490893022 1.61805859111053 0.106407890859693 df.mm.trans2:probe3 0.0927369382576096 0.0387997490893022 2.39014273118531 0.0172859687421828 * df.mm.trans2:probe4 0.0206874587545403 0.0387997490893022 0.533185374650895 0.594189991144997 df.mm.trans2:probe5 0.104581275846821 0.0387997490893022 2.69541113799769 0.00731522611867711 ** df.mm.trans2:probe6 0.0153719225019244 0.0387997490893022 0.396186131682041 0.692170850758675 df.mm.trans3:probe2 0.203495566109146 0.0387997490893022 5.2447650019792 2.49663685627975e-07 *** df.mm.trans3:probe3 0.00299002427117979 0.0387997490893022 0.0770629795645816 0.938610492974732 df.mm.trans3:probe4 0.226761008652086 0.0387997490893022 5.84439368744805 1.02787474501373e-08 *** df.mm.trans3:probe5 0.0327182816361322 0.0387997490893022 0.843260134513428 0.399567569925267 df.mm.trans3:probe6 0.095731958169084 0.0387997490893022 2.46733446519836 0.0140140353236802 * df.mm.trans3:probe7 0.112895267913331 0.0387997490893022 2.90969066973834 0.00381203602659607 ** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.22594216872165 0.163206421830907 25.893234600168 9.48196887939899e-89 *** df.mm.trans1 0.0359247820553648 0.132377888435382 0.271380534014945 0.786232988004852 df.mm.trans2 0.00830631735153048 0.132377888435382 0.0627470150015655 0.949998095579605 df.mm.exp2 0.256035327047720 0.179007577029024 1.43030441111555 0.153380320406498 df.mm.exp3 0.196350205747604 0.179007577029024 1.09688209296173 0.273327471730301 df.mm.exp4 0.271397063913421 0.179007577029024 1.51612053756483 0.130248353227480 df.mm.exp5 0.332341415750779 0.179007577029024 1.85657736542009 0.0640780511682806 . df.mm.exp6 0.125796079580093 0.179007577029024 0.702741647409128 0.482609822125239 df.mm.exp7 0.140564085078896 0.179007577029024 0.785240979246957 0.432759267608981 df.mm.exp8 0.0890857546122747 0.179007577029024 0.497664713923425 0.61898333757744 df.mm.trans1:exp2 -0.152644742844794 0.14432052249064 -1.05767870161844 0.290815734940114 df.mm.trans2:exp2 -0.147973198376284 0.14432052249064 -1.02530946966244 0.305813014112595 df.mm.trans1:exp3 -0.247961879721327 0.14432052249064 -1.71813319022185 0.0865164131585064 . df.mm.trans2:exp3 -0.078237604924099 0.14432052249064 -0.54211004487718 0.588032957836303 df.mm.trans1:exp4 -0.24234757422455 0.14432052249064 -1.67923154685272 0.093857788543671 . df.mm.trans2:exp4 -0.150792310503512 0.14432052249064 -1.04484315813984 0.296702213638882 df.mm.trans1:exp5 -0.23075297485875 0.14432052249064 -1.59889231882261 0.110603730042434 df.mm.trans2:exp5 -0.264795204328533 0.14432052249064 -1.83477165796504 0.0672534327110333 . df.mm.trans1:exp6 -0.125545476995675 0.14432052249064 -0.869907306521966 0.384852720383211 df.mm.trans2:exp6 -0.0410616221735408 0.14432052249064 -0.284516861946670 0.77615588764881 df.mm.trans1:exp7 -0.129462531009565 0.14432052249064 -0.897048657913235 0.370211787124522 df.mm.trans2:exp7 -0.0610729775399738 0.14432052249064 -0.423175973077112 0.672385557099057 df.mm.trans1:exp8 -0.125787624117464 0.14432052249064 -0.871585149129588 0.383937461614655 df.mm.trans2:exp8 -0.0665202475513451 0.14432052249064 -0.460920223980337 0.645096713653631 df.mm.trans1:probe2 0.0117464473365649 0.0917140914275066 0.128076799908656 0.898150087031505 df.mm.trans1:probe3 -0.163406967920960 0.0917140914275066 -1.78169968624856 0.0755276141256152 . df.mm.trans1:probe4 -0.0649349842337854 0.0917140914275065 -0.708015346639636 0.479332224440787 df.mm.trans1:probe5 -0.0738624511517457 0.0917140914275066 -0.80535553481581 0.421074616210815 df.mm.trans1:probe6 0.0301534890006275 0.0917140914275066 0.328777056298504 0.742489649964282 df.mm.trans2:probe2 -0.096699664137631 0.0917140914275066 -1.05435994221308 0.292330132710197 df.mm.trans2:probe3 -0.0218694571988191 0.0917140914275066 -0.238452530668151 0.811647543303135 df.mm.trans2:probe4 -0.169576233598289 0.0917140914275066 -1.84896596541358 0.0651720210361598 . df.mm.trans2:probe5 -0.0920970373947347 0.0917140914275066 -1.00417543216389 0.315877793592322 df.mm.trans2:probe6 -0.0437143750158622 0.0917140914275066 -0.476637497416798 0.633870538423358 df.mm.trans3:probe2 0.0926694325186032 0.0917140914275066 1.01041651371373 0.312883110930062 df.mm.trans3:probe3 0.182995411267126 0.0917140914275066 1.99528129667806 0.0466639942358426 * df.mm.trans3:probe4 0.0485291899929592 0.0917140914275066 0.529135591244646 0.596993617469462 df.mm.trans3:probe5 0.141638191563809 0.0917140914275065 1.54434492409232 0.123265142751436 df.mm.trans3:probe6 0.0479840140918336 0.0917140914275065 0.523191293126003 0.601119700343081 df.mm.trans3:probe7 0.0840338950725031 0.0917140914275066 0.91625936390512 0.360061718063782