chr3.14988_chr3_100258571_100260020_-_0.R fitVsDatCorrelation=0.952014547557004 cont.fitVsDatCorrelation=0.346644862631379 fstatistic=11608.2559039628,37,347 cont.fstatistic=1227.44576985346,37,347 residuals=-0.307964335798022,-0.0882508401645785,-0.00133797901458126,0.0748626583762932,0.386537417063689 cont.residuals=-0.769420039012444,-0.309638234776949,-0.0527035257293836,0.316722921432677,1.00755743250558 predictedValues: Include Exclude Both chr3.14988_chr3_100258571_100260020_-_0.R.tl.Lung 48.3498569980208 113.684576382808 71.9080804327043 chr3.14988_chr3_100258571_100260020_-_0.R.tl.cerebhem 53.6499231706635 114.176943277230 71.4459182515003 chr3.14988_chr3_100258571_100260020_-_0.R.tl.cortex 51.080241211152 106.044754370721 73.2748744570496 chr3.14988_chr3_100258571_100260020_-_0.R.tl.heart 52.1964310093808 118.055638569404 69.4017614519191 chr3.14988_chr3_100258571_100260020_-_0.R.tl.kidney 49.4740956254491 120.277657922138 76.7807569532007 chr3.14988_chr3_100258571_100260020_-_0.R.tl.liver 54.8673506517194 123.579846426746 80.0318155380704 chr3.14988_chr3_100258571_100260020_-_0.R.tl.stomach 49.2246262043504 133.736301046089 76.8593755469908 chr3.14988_chr3_100258571_100260020_-_0.R.tl.testicle 54.6052517112223 123.632682180329 82.1638339757942 diffExp=-65.3347193847874,-60.5270201065664,-54.9645131595686,-65.8592075600229,-70.803562296689,-68.7124957750265,-84.5116748417386,-69.0274304691062 diffExpScore=0.998150684530867 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 72.9464828620934 74.4302218197676 79.746527071661 cerebhem 71.5100848174819 87.2878645000858 68.0699049857006 cortex 73.4203886289021 74.5792539349437 82.6626832652607 heart 68.3579680106836 71.2628557836576 57.9280546123295 kidney 93.7657871890728 92.2746104166645 84.8253069747902 liver 93.5505534678234 75.2524224942409 81.4865755753815 stomach 67.5262606404168 68.2419686984964 78.5269778796803 testicle 85.8766466876618 75.1295441269844 70.075598486526 cont.diffExp=-1.48373895767415,-15.7777796826039,-1.15886530604156,-2.90488777297406,1.49117677240825,18.2981309735825,-0.715708058079599,10.7471025606774 cont.diffExpScore=5.53712545437852 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,-1,0,0,0,1,0,0 cont.diffExp1.2Score=2 tran.correlation=0.0313818334511527 cont.tran.correlation=0.481971045164542 tran.covariance=0.000138448220772299 cont.tran.covariance=0.00681368897978242 tran.mean=85.4147610473389 cont.tran.mean=77.838307129936 weightedLogRatios: wLogRatio Lung -3.68143043734658 cerebhem -3.29306096687023 cortex -3.13999177815797 heart -3.56089656627878 kidney -3.86045286710043 liver -3.58151652380282 stomach -4.3938281030558 testicle -3.60274130090233 cont.weightedLogRatios: wLogRatio Lung -0.0865806782124693 cerebhem -0.871165116766703 cortex -0.067404153683183 heart -0.176688181511632 kidney 0.0726651615246997 liver 0.964135928054657 stomach -0.0444689151709166 testicle 0.586408044861521 varWeightedLogRatios=0.142858418455114 cont.varWeightedLogRatios=0.295017171827844 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.44719852566499 0.0709410036051111 62.6886891877095 2.49166669942105e-191 *** df.mm.trans1 -0.596646612013117 0.0591035913666966 -10.0949299055508 3.52556286482116e-21 *** df.mm.trans2 0.316263814470994 0.0591035913666966 5.35100841011162 1.59237991064725e-07 *** df.mm.exp2 0.114786279507245 0.0814323328732328 1.40959095063548 0.159556098948317 df.mm.exp3 -0.0334611650646635 0.0814323328732328 -0.410907607384319 0.681393917838931 df.mm.exp4 0.149755538171182 0.0814323328732328 1.83901815025131 0.0667668082120831 . df.mm.exp5 0.0137956884851303 0.0814323328732328 0.169412910061244 0.865570586903052 df.mm.exp6 0.102879331690764 0.0814323328732328 1.26337203001317 0.207303675645999 df.mm.exp7 0.113784167567036 0.0814323328732328 1.39728488122975 0.163220710455516 df.mm.exp8 0.0722274018294355 0.0814323328732328 0.88696220875648 0.375713562233245 df.mm.trans1:exp2 -0.0107695067320086 0.0688228826002816 -0.156481482976485 0.875744514194639 df.mm.trans2:exp2 -0.110464640105679 0.0688228826002816 -1.60505686382318 0.109390963682795 df.mm.trans1:exp3 0.0883956541877097 0.0688228826002816 1.28439337104064 0.199861167774600 df.mm.trans2:exp3 -0.0361053585734389 0.0688228826002815 -0.524612704514809 0.600187428236852 df.mm.trans1:exp4 -0.0732046813409914 0.0688228826002816 -1.06366775954676 0.288218867743502 df.mm.trans2:exp4 -0.112027251221650 0.0688228826002816 -1.62776168316426 0.104483027524245 df.mm.trans1:exp5 0.00919025915828213 0.0688228826002815 0.133534935054356 0.893847746287 df.mm.trans2:exp5 0.0425794578757913 0.0688228826002815 0.618681698107441 0.536531981236109 df.mm.trans1:exp6 0.0235758698664576 0.0688228826002816 0.342558593533266 0.732137961973115 df.mm.trans2:exp6 -0.0194195944505441 0.0688228826002815 -0.282167699416656 0.777983142549832 df.mm.trans1:exp7 -0.0958534009378543 0.0688228826002816 -1.39275481229934 0.164585647142017 df.mm.trans2:exp7 0.0486580511895634 0.0688228826002816 0.707003969481574 0.480038515301214 df.mm.trans1:exp8 0.0494393972299799 0.0688228826002816 0.718356967363898 0.473020608290959 df.mm.trans2:exp8 0.0116597874876262 0.0688228826002815 0.169417307835614 0.865567130614771 df.mm.trans1:probe2 0.103810963080592 0.037695845272704 2.7539099423183 0.00619892772844608 ** df.mm.trans1:probe3 0.0732948201841237 0.037695845272704 1.94437396625238 0.0526581634489956 . df.mm.trans1:probe4 0.047722327769062 0.037695845272704 1.26598375560551 0.206368169469849 df.mm.trans1:probe5 0.0947518376956162 0.037695845272704 2.51358835463565 0.0124032609423562 * df.mm.trans1:probe6 -0.0404664427164846 0.037695845272704 -1.07349874830335 0.283793347248592 df.mm.trans2:probe2 -0.0059047593205673 0.037695845272704 -0.156642178411184 0.87561795522523 df.mm.trans2:probe3 -0.215276819650632 0.037695845272704 -5.7108898366186 2.41715853546754e-08 *** df.mm.trans2:probe4 0.312873047339211 0.037695845272704 8.29993451733966 2.34646151440656e-15 *** df.mm.trans2:probe5 -0.283400310364733 0.037695845272704 -7.51807814135809 4.78908588231848e-13 *** df.mm.trans2:probe6 -0.108637162476152 0.037695845272704 -2.88193995094778 0.00419841762249599 ** df.mm.trans3:probe2 0.440498331416835 0.037695845272704 11.6855936836043 7.92550408807764e-27 *** df.mm.trans3:probe3 -0.156262635316602 0.037695845272704 -4.14535432714528 4.26879668087585e-05 *** df.mm.trans3:probe4 0.150055962343071 0.037695845272704 3.98070294637294 8.3709525623379e-05 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.21158682168046 0.217421356327320 19.3706216023235 3.47065907113812e-57 *** df.mm.trans1 0.0382817337911932 0.181141826950938 0.211335694442134 0.832749393790244 df.mm.trans2 0.098141922519179 0.181141826950938 0.541796028952279 0.588306742261907 df.mm.exp2 0.297779804144816 0.249575384649908 1.19314572854421 0.233627454831494 df.mm.exp3 -0.0274391619986094 0.249575384649908 -0.109943382585986 0.912517832459996 df.mm.exp4 0.211196630651623 0.249575384649908 0.84622380106868 0.398011087442191 df.mm.exp5 0.404240210299192 0.249575384649908 1.61971185926946 0.106202608204663 df.mm.exp6 0.238176840492275 0.249575384649908 0.95432825166784 0.340581839256984 df.mm.exp7 -0.148600846268415 0.249575384649908 -0.595414673914518 0.551954433340928 df.mm.exp8 0.301816232262149 0.249575384649908 1.20931891053888 0.227363642225933 df.mm.trans1:exp2 -0.317667378805203 0.210929698212376 -1.50603438727418 0.13296809244913 df.mm.trans2:exp2 -0.138430426738904 0.210929698212376 -0.656287037397285 0.512074408902243 df.mm.trans1:exp3 0.0339147724700931 0.210929698212376 0.160787090473840 0.87235465815904 df.mm.trans2:exp3 0.0294394665311066 0.210929698212376 0.139570040542443 0.889080684584883 df.mm.trans1:exp4 -0.276164558487701 0.210929698212376 -1.30927299867297 0.191308179204384 df.mm.trans2:exp4 -0.254683462341587 0.210929698212376 -1.20743292433462 0.228087822564081 df.mm.trans1:exp5 -0.153166223754949 0.210929698212376 -0.72614821456167 0.468237415387767 df.mm.trans2:exp5 -0.189333249987617 0.210929698212376 -0.89761305113605 0.370014237432316 df.mm.trans1:exp6 0.0105990676759094 0.210929698212376 0.0502492904779944 0.959952644483615 df.mm.trans2:exp6 -0.227190811381119 0.210929698212376 -1.07709257305422 0.282187144764628 df.mm.trans1:exp7 0.0713913542000257 0.210929698212376 0.338460419775242 0.735220947012943 df.mm.trans2:exp7 0.0617985320478074 0.210929698212376 0.292981654890461 0.769711299342872 df.mm.trans1:exp8 -0.138630367313896 0.210929698212376 -0.657234938886204 0.511465551525951 df.mm.trans2:exp8 -0.292464420303017 0.210929698212376 -1.38654927580917 0.166469402156332 df.mm.trans1:probe2 0.00180427869192164 0.115530953758675 0.0156172751390114 0.98754869915232 df.mm.trans1:probe3 0.0865438429781288 0.115530953758675 0.749096585482227 0.454306486262590 df.mm.trans1:probe4 0.0710752953576774 0.115530953758675 0.615205648748834 0.538822161862604 df.mm.trans1:probe5 -0.00248173014004185 0.115530953758675 -0.0214810841536526 0.982874239310937 df.mm.trans1:probe6 0.241633366521642 0.115530953758675 2.09150326090420 0.0372096468897914 * df.mm.trans2:probe2 0.088704086717026 0.115530953758675 0.76779498334545 0.443131143199441 df.mm.trans2:probe3 -0.0773486048707928 0.115530953758675 -0.669505464590563 0.503618322412337 df.mm.trans2:probe4 -0.102290259998164 0.115530953758675 -0.885392673307544 0.376558008624853 df.mm.trans2:probe5 0.0849755938659397 0.115530953758675 0.735522308968724 0.462518308438262 df.mm.trans2:probe6 0.00729240843111569 0.115530953758675 0.0631208190867037 0.949706639682837 df.mm.trans3:probe2 -0.0486622318590106 0.115530953758675 -0.421205142655169 0.673866064908375 df.mm.trans3:probe3 0.140092142840246 0.115530953758675 1.21259401296794 0.226109983648229 df.mm.trans3:probe4 0.0319409491592375 0.115530953758675 0.276470920736591 0.782350989280028