chr19.12483_chr19_58351895_58511668_-_2.R fitVsDatCorrelation=0.84590619888074 cont.fitVsDatCorrelation=0.260631737209555 fstatistic=11945.6687271975,42,462 cont.fstatistic=3637.84951040843,42,462 residuals=-0.392130172185167,-0.0771853626623177,0.00087022562834174,0.0720547513489195,0.454861658895781 cont.residuals=-0.555574064595754,-0.135906384772653,-0.0438623532593339,0.0820424681339334,1.25892276567774 predictedValues: Include Exclude Both chr19.12483_chr19_58351895_58511668_-_2.R.tl.Lung 46.6139173288937 44.2835060648389 70.5840381455341 chr19.12483_chr19_58351895_58511668_-_2.R.tl.cerebhem 54.4717920224079 47.6492812907014 66.326562526428 chr19.12483_chr19_58351895_58511668_-_2.R.tl.cortex 51.7567012896807 43.8343529178487 80.7879508885772 chr19.12483_chr19_58351895_58511668_-_2.R.tl.heart 48.9882373615587 46.9289836003665 68.5071433524965 chr19.12483_chr19_58351895_58511668_-_2.R.tl.kidney 47.2846535187314 44.3067724773017 68.4317409723322 chr19.12483_chr19_58351895_58511668_-_2.R.tl.liver 60.7559882101819 52.7992279085374 117.601254761118 chr19.12483_chr19_58351895_58511668_-_2.R.tl.stomach 46.6405042541784 46.2430948776074 65.6156017975391 chr19.12483_chr19_58351895_58511668_-_2.R.tl.testicle 48.9768652734519 47.9719579058208 66.7859932088842 diffExp=2.33041126405481,6.8225107317065,7.922348371832,2.05925376119220,2.97788104142971,7.9567603016445,0.39740937657097,1.00490736763113 diffExpScore=0.969203746433683 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=0,0,0,0,0,0,0,0 diffExp1.2Score=0 cont.predictedValues: Include Exclude Both Lung 51.8508186100822 52.4836952871543 55.6852991010793 cerebhem 50.8418938124174 53.4119005741573 48.0546120043512 cortex 55.0175041756933 55.3073776105211 49.2136918063121 heart 55.8297725574098 51.0717644122312 46.7733379732897 kidney 55.3126200433021 52.1916894078565 53.1052760657661 liver 51.4463432427141 54.1188506860392 45.8135486691335 stomach 49.3082563087922 48.9917027254194 51.0647985490129 testicle 50.478352536268 53.3030947077043 50.0980527218488 cont.diffExp=-0.632876677072034,-2.57000676173988,-0.289873434827726,4.75800814517854,3.12093063544561,-2.67250744332504,0.316553583372823,-2.82474217143623 cont.diffExpScore=9.5766863122942 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=0.792566247537686 cont.tran.correlation=0.229533360061334 tran.covariance=0.00431252424544577 cont.tran.covariance=0.000431881448692022 tran.mean=48.7191147688817 cont.tran.mean=52.5603522936102 weightedLogRatios: wLogRatio Lung 0.195723801505937 cerebhem 0.525998434729236 cortex 0.641864452166118 heart 0.166200789265085 kidney 0.24872249999075 liver 0.566625217700963 stomach 0.0328441687541733 testicle 0.0804582727493218 cont.weightedLogRatios: wLogRatio Lung -0.0479745641545389 cerebhem -0.194952421306850 cortex -0.0210736863976376 heart 0.354321796534567 kidney 0.231379828952332 liver -0.200843814933042 stomach 0.0250852538163014 testicle -0.215009747544562 varWeightedLogRatios=0.0556549539627804 cont.varWeightedLogRatios=0.0437761540623927 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.58801683889711 0.0681286569914336 52.6653099788575 2.15940181513757e-197 *** df.mm.trans1 0.271853500479787 0.0600333160080225 4.52837721713487 7.57392650626341e-06 *** df.mm.trans2 0.199736048345895 0.056760520694035 3.51892558249357 0.000476205149851077 *** df.mm.exp2 0.291252673172663 0.0782040737006575 3.72426472676467 0.000220092038688432 *** df.mm.exp3 -0.0405634967472984 0.0782040737006575 -0.518687771976734 0.604226831855726 df.mm.exp4 0.137570259438413 0.0782040737006574 1.75911884034318 0.0792192419014954 . df.mm.exp5 0.0457791641444383 0.0782040737006574 0.585380811742208 0.558577498278873 df.mm.exp6 -0.069644894211242 0.0782040737006575 -0.890553278309036 0.373632392033647 df.mm.exp7 0.116860601074009 0.0782040737006575 1.49430324462787 0.135779042010552 df.mm.exp8 0.184763897731973 0.0782040737006575 2.36258661459499 0.018561430224966 * df.mm.trans1:exp2 -0.135468834732976 0.0724029033161627 -1.87104147110542 0.0619711851698699 . df.mm.trans2:exp2 -0.217997410406113 0.0660945056252131 -3.29826826517563 0.00104795395436623 ** df.mm.trans1:exp3 0.145218262360106 0.0724029033161627 2.0056966738748 0.0454712094568719 * df.mm.trans2:exp3 0.0303690357810785 0.0660945056252131 0.459478976259921 0.646106371668316 df.mm.trans1:exp4 -0.0878891956605735 0.0724029033161626 -1.21389048829695 0.225409712811237 df.mm.trans2:exp4 -0.0795470717756564 0.0660945056252131 -1.20353531694035 0.229385553174376 df.mm.trans1:exp5 -0.0314925228824349 0.0724029033161626 -0.434962155383689 0.663793002669918 df.mm.trans2:exp5 -0.0452539053151251 0.0660945056252131 -0.68468482950362 0.493886158061959 df.mm.trans1:exp6 0.334611391265572 0.0724029033161626 4.62151897147578 4.94895567525817e-06 *** df.mm.trans2:exp6 0.245529177743524 0.0660945056252131 3.71481979358148 0.000228227633976008 *** df.mm.trans1:exp7 -0.116290399134975 0.0724029033161626 -1.60615657395904 0.108922752169969 df.mm.trans2:exp7 -0.0735607323341942 0.0660945056252132 -1.11296289515074 0.266303108441764 df.mm.trans1:exp8 -0.135315000059246 0.0724029033161627 -1.86891676799705 0.0622669183884974 . df.mm.trans2:exp8 -0.10475955196546 0.0660945056252132 -1.58499637714965 0.113651369343541 df.mm.trans1:probe2 -0.0410506810916184 0.0362014516580813 -1.13395124260037 0.257403046070441 df.mm.trans1:probe3 -0.0193057183655663 0.0362014516580813 -0.53328575185069 0.59409223202172 df.mm.trans1:probe4 -0.00995103868789973 0.0362014516580813 -0.274879548529882 0.783531660417275 df.mm.trans1:probe5 -0.0482567989247146 0.0362014516580813 -1.33300728878208 0.183186372390324 df.mm.trans1:probe6 -0.0128160777095625 0.0362014516580813 -0.354021099225769 0.723484582001358 df.mm.trans1:probe7 -0.104178983516420 0.0362014516580813 -2.87775707174338 0.00419072093210381 ** df.mm.trans1:probe8 -0.0522750941531501 0.0362014516580813 -1.44400546825808 0.149415213904756 df.mm.trans1:probe9 -0.0465383380625767 0.0362014516580813 -1.2855378978204 0.199248385440170 df.mm.trans1:probe10 -0.0386134633764366 0.0362014516580813 -1.06662748613333 0.286697147356073 df.mm.trans1:probe11 0.0878854599092747 0.0362014516580813 2.42767778318237 0.0155769054929799 * df.mm.trans1:probe12 0.0155329183678645 0.0362014516580813 0.42906893664296 0.66807306190374 df.mm.trans2:probe2 -0.0342238700981011 0.0362014516580813 -0.945372865744219 0.344962704006672 df.mm.trans2:probe3 -0.0302978745486925 0.0362014516580813 -0.836924298916313 0.403067815805930 df.mm.trans2:probe4 0.0031069114475551 0.0362014516580813 0.0858228414954055 0.93164442865436 df.mm.trans2:probe5 0.0801585117669974 0.0362014516580813 2.21423473633283 0.0273000794107103 * df.mm.trans2:probe6 0.00699089340305453 0.0362014516580813 0.193110858345757 0.846957013654565 df.mm.trans3:probe2 0.303603580139717 0.0362014516580813 8.38650292278936 6.1207098300608e-16 *** df.mm.trans3:probe3 0.287989347733359 0.0362014516580813 7.95518783206227 1.39122050269475e-14 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.9155022268784 0.123326654415454 31.7490346708678 3.41031427621431e-118 *** df.mm.trans1 0.0168759574115272 0.108672449211293 0.155291957934206 0.876658978747421 df.mm.trans2 0.0707164825387609 0.102748027470359 0.688251485500888 0.49163985274747 df.mm.exp2 0.145259064285112 0.141565197335013 1.02609304419191 0.305384660843777 df.mm.exp3 0.235228733255148 0.141565197335013 1.66162826516239 0.0972656871053863 . df.mm.exp4 0.221068639413419 0.141565197335013 1.56160301807980 0.119066241548147 df.mm.exp5 0.106490988395842 0.141565197335013 0.752239889468257 0.452289884624226 df.mm.exp6 0.217984986725204 0.141565197335013 1.53982045607823 0.124288730623873 df.mm.exp7 -0.0325099924622899 0.141565197335013 -0.229646785186582 0.818467884204976 df.mm.exp8 0.0943997379044734 0.141565197335013 0.666828709891719 0.505214433026088 df.mm.trans1:exp2 -0.164909090811621 0.131063905121023 -1.25823422291092 0.208942569861570 df.mm.trans2:exp2 -0.127728041356999 0.119644428849168 -1.06756363489370 0.286274911058344 df.mm.trans1:exp3 -0.175948063510973 0.131063905121023 -1.34246010256222 0.180106116498589 df.mm.trans2:exp3 -0.182824978349789 0.119644428849168 -1.52806929757064 0.127179664140923 df.mm.trans1:exp4 -0.147132076536215 0.131063905121023 -1.12259799065468 0.262191324405707 df.mm.trans2:exp4 -0.248339405855480 0.119644428849168 -2.07564537892988 0.0384793935023919 * df.mm.trans1:exp5 -0.0418606179505832 0.131063905121023 -0.319390894937318 0.749574481216871 df.mm.trans2:exp5 -0.112070268331049 0.119644428849168 -0.93669441535245 0.349405146538202 df.mm.trans1:exp6 -0.22581632356567 0.131063905121023 -1.72294823168251 0.0855670288158835 . df.mm.trans2:exp6 -0.187304975450997 0.119644428849168 -1.56551355756920 0.118147205151919 df.mm.trans1:exp7 -0.0177691923390756 0.131063905121023 -0.135576551932187 0.892215093437784 df.mm.trans2:exp7 -0.0363416113027036 0.119644428849168 -0.303746790822314 0.761457553535832 df.mm.trans1:exp8 -0.121225878768337 0.131063905121023 -0.924937179739905 0.355481443756998 df.mm.trans2:exp8 -0.0789079017629866 0.119644428849168 -0.659520067269184 0.509890477552014 df.mm.trans1:probe2 0.0460489426966949 0.0655319525605113 0.702694500887546 0.482600062612761 df.mm.trans1:probe3 0.0234824636809613 0.0655319525605113 0.358336090463318 0.720255486812292 df.mm.trans1:probe4 0.0625941990276309 0.0655319525605113 0.955170669908427 0.339990905864913 df.mm.trans1:probe5 -0.0135188789282172 0.0655319525605113 -0.20629446247209 0.836651782687873 df.mm.trans1:probe6 0.0266531641426053 0.0655319525605113 0.406720128138927 0.684401903391266 df.mm.trans1:probe7 0.0532863665746872 0.0655319525605113 0.813135645935214 0.416559127368681 df.mm.trans1:probe8 -0.0535150243998545 0.0655319525605113 -0.816624902950044 0.414563693532489 df.mm.trans1:probe9 0.0450053045234689 0.0655319525605113 0.686768862592818 0.492572950451597 df.mm.trans1:probe10 0.0394718744637163 0.0655319525605113 0.602330205669799 0.547249862071578 df.mm.trans1:probe11 0.0199185023656299 0.0655319525605113 0.303950997755445 0.761302069353143 df.mm.trans1:probe12 -0.00953883957234211 0.0655319525605113 -0.145560130587198 0.88433212806298 df.mm.trans2:probe2 -0.0909342118807463 0.0655319525605113 -1.38763165643171 0.165918140869578 df.mm.trans2:probe3 -0.0493023190136598 0.0655319525605113 -0.752340149915947 0.45222966310668 df.mm.trans2:probe4 -0.0801908734561097 0.0655319525605113 -1.22369119678011 0.221692459552940 df.mm.trans2:probe5 0.0206954529389215 0.0655319525605113 0.315807054883823 0.752291577326773 df.mm.trans2:probe6 -0.0317134347156679 0.0655319525605113 -0.483938498343752 0.628658822379834 df.mm.trans3:probe2 0.0424400947737965 0.0655319525605113 0.647624450600764 0.51754956150388 df.mm.trans3:probe3 0.00742445114492846 0.0655319525605113 0.113295130922168 0.90984579062194