chr13.6407_chr13_70742584_70745054_-_2.R fitVsDatCorrelation=0.871215620150477 cont.fitVsDatCorrelation=0.208030923651683 fstatistic=8827.29341556894,69,1083 cont.fstatistic=2211.71266686121,69,1083 residuals=-0.743223413723377,-0.103898519741306,-0.0106428027089204,0.0922059697973101,1.01929173471867 cont.residuals=-0.731830216979369,-0.239259490316636,-0.0938104834208398,0.155251627712875,1.84184413019084 predictedValues: Include Exclude Both chr13.6407_chr13_70742584_70745054_-_2.R.tl.Lung 61.6970850119727 47.2796753535799 58.8791481242578 chr13.6407_chr13_70742584_70745054_-_2.R.tl.cerebhem 64.219629494332 47.2116665570103 68.5466074257406 chr13.6407_chr13_70742584_70745054_-_2.R.tl.cortex 60.7484565711883 50.4096914377531 57.649630442177 chr13.6407_chr13_70742584_70745054_-_2.R.tl.heart 66.8904981111446 51.3238536339551 60.941625261591 chr13.6407_chr13_70742584_70745054_-_2.R.tl.kidney 112.355551895164 53.9675407720275 103.521267983288 chr13.6407_chr13_70742584_70745054_-_2.R.tl.liver 64.3969782187475 49.1663106422412 58.3254867881928 chr13.6407_chr13_70742584_70745054_-_2.R.tl.stomach 62.1522411505274 50.6904553808733 61.3815935889911 chr13.6407_chr13_70742584_70745054_-_2.R.tl.testicle 62.2024993437403 46.7576519331489 57.6354688712592 diffExp=14.4174096583928,17.0079629373217,10.3387651334353,15.5666444771895,58.3880111231364,15.2306675765064,11.4617857696541,15.4448474105914 diffExpScore=0.993704994411752 diffExp1.5=0,0,0,0,1,0,0,0 diffExp1.5Score=0.5 diffExp1.4=0,0,0,0,1,0,0,0 diffExp1.4Score=0.5 diffExp1.3=1,1,0,1,1,1,0,1 diffExp1.3Score=0.857142857142857 diffExp1.2=1,1,1,1,1,1,1,1 diffExp1.2Score=0.888888888888889 cont.predictedValues: Include Exclude Both Lung 67.8819285228178 67.2755603950615 64.6632785538739 cerebhem 65.0490417313083 65.7188215417197 63.6608245013843 cortex 61.757372424098 63.37224617151 65.3725434970347 heart 69.0933888168376 83.1226976617762 61.4036648581877 kidney 62.7223688284323 71.7096390525956 63.5727681669464 liver 63.6630322702206 70.5255443738779 65.1387272076109 stomach 63.156308926213 64.9756919907813 66.022870903355 testicle 67.4650810650784 71.7818135298102 61.851661316213 cont.diffExp=0.606368127756355,-0.669779810411356,-1.61487374741203,-14.0293088449386,-8.98727022416335,-6.86251210365735,-1.81938306456822,-4.31673246473171 cont.diffExpScore=1.00549798541797 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,-1,0,0,0,0 cont.diffExp1.2Score=0.5 tran.correlation=0.72696392334769 cont.tran.correlation=0.640893324709119 tran.covariance=0.00731981378287981 cont.tran.covariance=0.00227327532294727 tran.mean=59.4668615942129 cont.tran.mean=67.4544085813837 weightedLogRatios: wLogRatio Lung 1.06173920790862 cerebhem 1.23327901610749 cortex 0.748744466152416 heart 1.07830888873889 kidney 3.19347774731341 liver 1.08756515153735 stomach 0.821035896346333 testicle 1.13815457405051 cont.weightedLogRatios: wLogRatio Lung 0.0378050517470983 cerebhem -0.0428221499265807 cortex -0.106764202262810 heart -0.800048047514374 kidney -0.563169004426391 liver -0.430448182547133 stomach -0.118140697884373 testicle -0.263131592397619 varWeightedLogRatios=0.614294141633517 cont.varWeightedLogRatios=0.0838204976142706 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.97158660580438 0.0814717596142027 48.7480155652858 2.24066584121499e-275 *** df.mm.trans1 0.173401405500913 0.0694834324678691 2.49557915235547 0.0127230896908685 * df.mm.trans2 -0.149010277635563 0.0605234076495223 -2.46202722917467 0.0139703287207369 * df.mm.exp2 -0.113394145632863 0.07587989775638 -1.49438980528053 0.135365060121035 df.mm.exp3 0.0697111008118197 0.07587989775638 0.918703146327821 0.358455424030082 df.mm.exp4 0.128465924430275 0.07587989775638 1.69301657262016 0.0907399071000466 . df.mm.exp5 0.167443917590282 0.07587989775638 2.20669666856798 0.0275444909674483 * df.mm.exp6 0.0914060062963128 0.07587989775638 1.20461425224611 0.228615430701886 df.mm.exp7 0.03538431666112 0.07587989775638 0.466320036101325 0.641080218831378 df.mm.exp8 0.0184047586164494 0.07587989775638 0.242551178383763 0.808399031378412 df.mm.trans1:exp2 0.153466379701807 0.0689877060482422 2.2245467851111 0.0263171691449548 * df.mm.trans2:exp2 0.111954673889997 0.0457903496952361 2.44494035610400 0.0146461138059581 * df.mm.trans1:exp3 -0.0852061104062425 0.0689877060482422 -1.23509122548094 0.217064431070471 df.mm.trans2:exp3 -0.00560816039854579 0.0457903496952361 -0.122474723077497 0.902545785838294 df.mm.trans1:exp4 -0.0476456838637835 0.0689877060482422 -0.690640211032173 0.489939659635964 df.mm.trans2:exp4 -0.0463908038168892 0.0457903496952361 -1.01311311500457 0.311232418485009 df.mm.trans1:exp5 0.431987810630693 0.0689877060482423 6.26180859425314 5.47706958225762e-10 *** df.mm.trans2:exp5 -0.0351416551816539 0.045790349695236 -0.767446752766555 0.442983219124821 df.mm.trans1:exp6 -0.0485759816127707 0.0689877060482423 -0.704125189766451 0.481506183114796 df.mm.trans2:exp6 -0.0522778669957432 0.0457903496952361 -1.14167870181568 0.253839960757727 df.mm.trans1:exp7 -0.0280341242649339 0.0689877060482423 -0.406364059203968 0.684555407060184 df.mm.trans2:exp7 0.0342728128157527 0.045790349695236 0.748472397434397 0.454337779139230 df.mm.trans1:exp8 -0.0102462625601127 0.0689877060482423 -0.148523021666318 0.881957667835741 df.mm.trans2:exp8 -0.0295073451712953 0.045790349695236 -0.644400957138033 0.519451922074849 df.mm.trans1:probe2 1.00738105256335 0.0523999243198882 19.2248570134098 4.27156729073841e-71 *** df.mm.trans1:probe3 -0.14434304359136 0.0523999243198882 -2.75464221494257 0.00597407391929577 ** df.mm.trans1:probe4 -0.244115608367631 0.0523999243198882 -4.65870154463139 3.5772677300683e-06 *** df.mm.trans1:probe5 -0.158476676940643 0.0523999243198882 -3.02436843177832 0.00255024176036680 ** df.mm.trans1:probe6 0.0824070933708122 0.0523999243198882 1.57265672499330 0.116090404453667 df.mm.trans1:probe7 -0.338563844871126 0.0523999243198882 -6.46115140938526 1.56724385976920e-10 *** df.mm.trans1:probe8 0.124244662940963 0.0523999243198882 2.37108477833824 0.0179101774508555 * df.mm.trans1:probe9 0.199704854022675 0.0523999243198882 3.81116684069098 0.000146101240531259 *** df.mm.trans1:probe10 0.297954916904024 0.0523999243198882 5.68617074874164 1.67011048963688e-08 *** df.mm.trans1:probe11 -0.286887248586815 0.0523999243198882 -5.47495539946663 5.43748470081528e-08 *** df.mm.trans1:probe12 -0.361578209628744 0.0523999243198882 -6.90035747802615 8.81110127808194e-12 *** df.mm.trans1:probe13 -0.280632268828013 0.0523999243198882 -5.35558538433805 1.04109845989240e-07 *** df.mm.trans1:probe14 -0.3179463776499 0.0523999243198882 -6.06768772620584 1.79151864717547e-09 *** df.mm.trans1:probe15 -0.300531072536934 0.0523999243198882 -5.73533409518434 1.26167614039886e-08 *** df.mm.trans1:probe16 -0.32177924732404 0.0523999243198882 -6.14083419967669 1.15072939926842e-09 *** df.mm.trans1:probe17 0.269730887439876 0.0523999243198881 5.14754345432329 3.13259575814502e-07 *** df.mm.trans1:probe18 0.0197606670578586 0.0523999243198881 0.377112511407932 0.706163874635394 df.mm.trans1:probe19 0.000820939037975634 0.0523999243198882 0.0156667981610815 0.987503100565522 df.mm.trans1:probe20 -0.0318989769304044 0.0523999243198882 -0.608759980943279 0.542811205670436 df.mm.trans1:probe21 -0.0565792362827099 0.0523999243198882 -1.07975797707852 0.280490371817469 df.mm.trans1:probe22 -0.114228955837795 0.0523999243198882 -2.17994505374582 0.0294763210774236 * df.mm.trans2:probe2 0.131572814183762 0.0523999243198882 2.51093519487821 0.0121859329247044 * df.mm.trans2:probe3 0.09950979188781 0.0523999243198882 1.89904457266633 0.0578241592735099 . df.mm.trans2:probe4 0.504057328160639 0.0523999243198882 9.61942855267305 4.47712385025578e-21 *** df.mm.trans2:probe5 0.0623225377243199 0.0523999243198882 1.18936312472241 0.234557496864112 df.mm.trans2:probe6 0.0736461675200713 0.0523999243198882 1.40546324209326 0.160170368353860 df.mm.trans3:probe2 -0.0388155355493748 0.0523999243198882 -0.74075556507326 0.459002232757874 df.mm.trans3:probe3 -0.0822137764857611 0.0523999243198882 -1.56896746613348 0.116947628746928 df.mm.trans3:probe4 0.116703007787044 0.0523999243198882 2.22715985379295 0.0261415329318335 * df.mm.trans3:probe5 -0.235813201888914 0.0523999243198882 -4.50025844406444 7.5205413450999e-06 *** df.mm.trans3:probe6 -0.0902019763545069 0.0523999243198882 -1.7214142486895 0.0854612551875194 . df.mm.trans3:probe7 0.557954379696595 0.0523999243198882 10.6479997240154 3.00356428750949e-25 *** df.mm.trans3:probe8 0.184621908614325 0.0523999243198882 3.52332395534114 0.000443946159829284 *** df.mm.trans3:probe9 0.128739056873796 0.0523999243198882 2.45685577879612 0.0141718904208037 * df.mm.trans3:probe10 -0.00177474048054002 0.0523999243198882 -0.0338691420564977 0.972987741138878 df.mm.trans3:probe11 -0.00931093478717998 0.0523999243198882 -0.177689851808547 0.858999783719409 df.mm.trans3:probe12 0.202825480617602 0.0523999243198882 3.87072086935477 0.000115001492597976 *** df.mm.trans3:probe13 -0.146011216670954 0.0523999243198882 -2.78647762503611 0.00542149515612149 ** df.mm.trans3:probe14 -0.0395003129927352 0.0523999243198882 -0.753823855767346 0.451118853399657 df.mm.trans3:probe15 0.175275380566060 0.0523999243198882 3.34495484184383 0.000851173533667805 *** df.mm.trans3:probe16 0.377422014944565 0.0523999243198882 7.20272061158905 1.10306215626084e-12 *** df.mm.trans3:probe17 0.136711741219447 0.0523999243198882 2.60900646315549 0.00920567975792777 ** df.mm.trans3:probe18 -0.126050978128144 0.0523999243198882 -2.40555649200244 0.0163147076111058 * df.mm.trans3:probe19 0.474083036630494 0.0523999243198882 9.04739926218858 6.62215478136844e-19 *** df.mm.trans3:probe20 0.00554211934602416 0.0523999243198882 0.105765789129597 0.91578776693802 cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.28151041318379 0.162332965199504 26.3748672854087 8.26471873109221e-119 *** df.mm.trans1 -0.0514483230170921 0.138446152116523 -0.371612516711846 0.710254058973243 df.mm.trans2 -0.0507073706317556 0.120593249418570 -0.420482662804403 0.674216308834524 df.mm.exp2 -0.0504159400131812 0.151191147216624 -0.333458280734824 0.73885292422845 df.mm.exp3 -0.165236379887516 0.151191147216624 -1.09289718961368 0.274681983692953 df.mm.exp4 0.280933928585891 0.151191147216624 1.85813742244692 0.0634206990721161 . df.mm.exp5 0.00178471121468188 0.151191147216624 0.0118043367454893 0.990583894758682 df.mm.exp6 -0.0243136332926412 0.151191147216624 -0.160813868670532 0.872269993200703 df.mm.exp7 -0.127748634329353 0.151191147216624 -0.844947847021209 0.398326578512788 df.mm.exp8 0.103128936400426 0.151191147216624 0.682109622811875 0.495315489872076 df.mm.trans1:exp2 0.00778756287090604 0.137458414279426 0.0566539553924682 0.954831303580055 df.mm.trans2:exp2 0.0270042750262308 0.0912375438894296 0.295977663087437 0.767303881806837 df.mm.trans1:exp3 0.0706798890236076 0.137458414279426 0.51419106930718 0.607223312864843 df.mm.trans2:exp3 0.105465361446010 0.0912375438894295 1.15594257528263 0.247959586493323 df.mm.trans1:exp4 -0.263244728706691 0.137458414279426 -1.91508631964549 0.0557446718505253 . df.mm.trans2:exp4 -0.06941315378911 0.0912375438894295 -0.760795949014492 0.446944562525628 df.mm.trans1:exp5 -0.0808364183040385 0.137458414279426 -0.588079083610798 0.556601818649256 df.mm.trans2:exp5 0.0620434367414748 0.0912375438894295 0.680020900350683 0.496636558438455 df.mm.trans1:exp6 -0.039852164447938 0.137458414279426 -0.289921607613822 0.77193170877908 df.mm.trans2:exp6 0.0714915825352893 0.0912375438894295 0.783576359989806 0.433460058117395 df.mm.trans1:exp7 0.0555915312267145 0.137458414279426 0.404424360037412 0.685980545131337 df.mm.trans2:exp7 0.0929648384146897 0.0912375438894295 1.01893183936816 0.308462888720005 df.mm.trans1:exp8 -0.109288640659995 0.137458414279426 -0.795066938847647 0.426748770089655 df.mm.trans2:exp8 -0.0382948123808564 0.0912375438894295 -0.419726471673391 0.674768532823962 df.mm.trans1:probe2 -0.0350286593887809 0.104407160608253 -0.335500545984697 0.737312511689915 df.mm.trans1:probe3 -0.114762186197812 0.104407160608253 -1.09917926633799 0.271934164896181 df.mm.trans1:probe4 -0.0713285260727146 0.104407160608253 -0.683176571962789 0.494641395180225 df.mm.trans1:probe5 -0.0395441549515015 0.104407160608253 -0.378749452826089 0.704948162432856 df.mm.trans1:probe6 -0.0200230406522443 0.104407160608253 -0.1917784233916 0.847951722933276 df.mm.trans1:probe7 -0.090448293310924 0.104407160608253 -0.866303544546104 0.386515600587116 df.mm.trans1:probe8 -0.0887664167972658 0.104407160608253 -0.850194721129587 0.39540475193335 df.mm.trans1:probe9 -0.0583364792049188 0.104407160608253 -0.558740213459147 0.576454535624252 df.mm.trans1:probe10 0.0268107785665444 0.104407160608253 0.256790611011264 0.797389192875395 df.mm.trans1:probe11 -0.0321518045371639 0.104407160608253 -0.307946354922925 0.75818236685763 df.mm.trans1:probe12 -0.0236967159414166 0.104407160608253 -0.226964470668149 0.820494203283741 df.mm.trans1:probe13 -0.0133544526556831 0.104407160608253 -0.127907440235737 0.89824596902893 df.mm.trans1:probe14 -0.0300987728756514 0.104407160608253 -0.288282649392078 0.773185549628981 df.mm.trans1:probe15 0.0064566066586832 0.104407160608253 0.0618406498277363 0.950701141982844 df.mm.trans1:probe16 0.0285873770160558 0.104407160608253 0.273806670438235 0.784285407867288 df.mm.trans1:probe17 0.156112224234957 0.104407160608253 1.49522526353060 0.135146981892132 df.mm.trans1:probe18 0.0138356155616466 0.104407160608253 0.132515964240799 0.894600812658215 df.mm.trans1:probe19 -0.071004843348607 0.104407160608253 -0.68007637536495 0.49660144747789 df.mm.trans1:probe20 0.0200573593368147 0.104407160608253 0.192107123878908 0.847694308579986 df.mm.trans1:probe21 -0.0274576798249159 0.104407160608253 -0.262986558249008 0.792610961109931 df.mm.trans1:probe22 -0.052131992008182 0.104407160608253 -0.499314335381525 0.617659371555176 df.mm.trans2:probe2 -0.0785020128484185 0.104407160608253 -0.751883418637985 0.45228453879534 df.mm.trans2:probe3 0.0257464251043288 0.104407160608253 0.246596353682409 0.805267359214863 df.mm.trans2:probe4 -0.121333552842842 0.104407160608253 -1.16211907436213 0.245443134016595 df.mm.trans2:probe5 -0.212426138299737 0.104407160608253 -2.0345935763619 0.0421349955819865 * df.mm.trans2:probe6 -0.185641138629511 0.104407160608253 -1.77804987270995 0.0756761834901976 . df.mm.trans3:probe2 -0.0835394282877658 0.104407160608253 -0.800131215149263 0.423810249398754 df.mm.trans3:probe3 0.086857873354291 0.104407160608253 0.831914907447691 0.405640369016978 df.mm.trans3:probe4 0.0333117275357822 0.104407160608253 0.31905596648463 0.749745599885552 df.mm.trans3:probe5 0.00636914979744831 0.104407160608253 0.0610029978819752 0.951368076852344 df.mm.trans3:probe6 -0.0502840087984085 0.104407160608253 -0.481614560777872 0.630177081301547 df.mm.trans3:probe7 -0.0773665422139924 0.104407160608253 -0.741008009060605 0.458849218598865 df.mm.trans3:probe8 0.000638644226277375 0.104407160608253 0.00611686231630833 0.995120606949342 df.mm.trans3:probe9 0.0314091124641632 0.104407160608253 0.300832934074451 0.763599635958587 df.mm.trans3:probe10 -0.000687000952160486 0.104407160608253 -0.0065800175788535 0.994751155268666 df.mm.trans3:probe11 -0.0370395530726016 0.104407160608253 -0.354760658721273 0.722837972846765 df.mm.trans3:probe12 -0.0172491433302366 0.104407160608253 -0.165210347927737 0.8688092530052 df.mm.trans3:probe13 -0.0660497808387983 0.104407160608253 -0.632617345917721 0.527117096534692 df.mm.trans3:probe14 -0.0374583373710041 0.104407160608253 -0.358771727463712 0.719835792316879 df.mm.trans3:probe15 -0.0770041008174387 0.104407160608253 -0.737536586272722 0.460955864411882 df.mm.trans3:probe16 0.093994934793725 0.104407160608253 0.900272876363377 0.368175191572609 df.mm.trans3:probe17 -0.0881004093682262 0.104407160608253 -0.843815777145674 0.398958698157286 df.mm.trans3:probe18 0.122875169065973 0.104407160608253 1.17688450054698 0.239500201268685 df.mm.trans3:probe19 -0.0158617815755265 0.104407160608253 -0.151922353630913 0.879276472975847 df.mm.trans3:probe20 -0.0280414047936638 0.104407160608253 -0.268577410115368 0.788306048789216