chr8.23513_chr8_110167593_110198944_+_2.R fitVsDatCorrelation=0.72954320530599 cont.fitVsDatCorrelation=0.297780663170385 fstatistic=13240.6940715889,54,738 cont.fstatistic=6789.54550268693,54,738 residuals=-0.419799705462569,-0.0792912999506042,-0.00379510507658601,0.0714664801576428,0.70620937287122 cont.residuals=-0.556297196249544,-0.119650706230742,-0.0239035879797079,0.0903621944361746,0.720606196465094 predictedValues: Include Exclude Both chr8.23513_chr8_110167593_110198944_+_2.R.tl.Lung 48.2859536624347 56.2962283349314 58.2945576891599 chr8.23513_chr8_110167593_110198944_+_2.R.tl.cerebhem 54.7024189695606 56.6863413085844 57.7326491185489 chr8.23513_chr8_110167593_110198944_+_2.R.tl.cortex 47.8193496346827 51.385554819244 51.0624141584751 chr8.23513_chr8_110167593_110198944_+_2.R.tl.heart 50.0547762993922 51.617978371037 52.8920792205937 chr8.23513_chr8_110167593_110198944_+_2.R.tl.kidney 48.6078241740724 48.4699918685268 57.9187365161025 chr8.23513_chr8_110167593_110198944_+_2.R.tl.liver 50.6849291505369 51.2150388809426 56.876362328015 chr8.23513_chr8_110167593_110198944_+_2.R.tl.stomach 50.9271797919087 61.0096449577399 52.8286189800241 chr8.23513_chr8_110167593_110198944_+_2.R.tl.testicle 50.8526504001451 52.1759920551027 54.6389682400159 diffExp=-8.01027467249674,-1.98392233902379,-3.56620518456128,-1.56320207164486,0.137832305545651,-0.530109730405734,-10.0824651658312,-1.32334165495754 diffExpScore=0.974058324282154 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 52.8679183756503 52.8716245016635 54.5772115215596 cerebhem 51.2542675253432 52.690843287151 51.048609877712 cortex 53.0344127110969 57.9355974199662 50.1842850125467 heart 52.4853482963476 57.216969414626 51.2944994822614 kidney 51.4769278086881 51.8448816030423 48.3451282049151 liver 52.760199067459 53.8173071878368 49.0284340716879 stomach 52.9822074822918 51.475192499138 56.4765474659914 testicle 51.1417344555424 53.0545164230368 54.7682179802931 cont.diffExp=-0.00370612601322762,-1.43657576180780,-4.90118470886925,-4.73162111827843,-0.367953794354214,-1.05710812037777,1.50701498315378,-1.91278196749441 cont.diffExpScore=1.14485342671529 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=0.416889057580737 cont.tran.correlation=0.379359654787665 tran.covariance=0.00133994668795217 cont.tran.covariance=0.000259436750781754 tran.mean=51.9244907924276 cont.tran.mean=53.05687175368 weightedLogRatios: wLogRatio Lung -0.606869166627361 cerebhem -0.143203980770746 cortex -0.28075837289415 heart -0.120809432212654 kidney 0.0110244679651330 liver -0.0408987471673576 stomach -0.726282545854726 testicle -0.101265142060902 cont.weightedLogRatios: wLogRatio Lung -0.000278141630989544 cerebhem -0.109206227953616 cortex -0.354901950647123 heart -0.345584592739961 kidney -0.0280961323086656 liver -0.0788695001889732 stomach 0.114141337999574 testicle -0.145149195306887 varWeightedLogRatios=0.0738873190459296 cont.varWeightedLogRatios=0.026584526243413 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.57729267565205 0.0652974657982167 54.7845560608226 2.92748315214143e-262 *** df.mm.trans1 0.247871841709314 0.0575212532824802 4.30922185391276 1.86029617769962e-05 *** df.mm.trans2 0.387883050172746 0.0519031833677332 7.47320347240748 2.21946264821775e-13 *** df.mm.exp2 0.141358856869950 0.0691195909485445 2.04513445363389 0.0411957655054642 * df.mm.exp3 0.0314792628164095 0.0691195909485445 0.455431844783977 0.648932550227924 df.mm.exp4 0.0464748594896043 0.0691195909485445 0.672383312051168 0.501550157515929 df.mm.exp5 -0.136571047916038 0.0691195909485445 -1.97586597434738 0.0485420316905058 * df.mm.exp6 -0.0214775075999568 0.0691195909485445 -0.310729668755499 0.756093879119407 df.mm.exp7 0.232116155242224 0.0691195909485445 3.35818184188939 0.000824826956975485 *** df.mm.exp8 0.0405478719779659 0.0691195909485445 0.586633563965264 0.557629229241094 df.mm.trans1:exp2 -0.0165916298630025 0.0651965162931739 -0.254486448146919 0.79919066496745 df.mm.trans2:exp2 -0.134453109811173 0.0533426042398695 -2.52055766168760 0.0119266604819262 * df.mm.trans1:exp3 -0.0411896050786636 0.0651965162931739 -0.63177616566878 0.527728796614914 df.mm.trans2:exp3 -0.122749705124794 0.0533426042398695 -2.30115696213136 0.0216605879151985 * df.mm.trans1:exp4 -0.0104976316457547 0.0651965162931739 -0.161015223551965 0.872125476250163 df.mm.trans2:exp4 -0.133232370269014 0.0533426042398695 -2.49767277334077 0.0127178123734387 * df.mm.trans1:exp5 0.143214853179385 0.0651965162931739 2.196664198059 0.0283546906004037 * df.mm.trans2:exp5 -0.0131116106165134 0.0533426042398695 -0.245799971774034 0.80590542063208 df.mm.trans1:exp6 0.0699654146730117 0.0651965162931739 1.07314652148580 0.283556151501526 df.mm.trans2:exp6 -0.0731168159676462 0.0533426042398695 -1.37070203094803 0.170884590518139 df.mm.trans1:exp7 -0.178860094002054 0.0651965162931739 -2.74339955831015 0.00622822767963293 ** df.mm.trans2:exp7 -0.151711730133123 0.0533426042398695 -2.84410055142621 0.00457692802380146 ** df.mm.trans1:exp8 0.0112436671669332 0.0651965162931739 0.172458097551915 0.863124683727862 df.mm.trans2:exp8 -0.116552945828931 0.0533426042398695 -2.18498791894035 0.0292035346723455 * df.mm.trans1:probe2 0.301995869864662 0.038066564322934 7.93336291929867 7.91101667169483e-15 *** df.mm.trans1:probe3 0.0646240188963001 0.038066564322934 1.69765830055133 0.089993854820599 . df.mm.trans1:probe4 0.0945872433814848 0.038066564322934 2.48478540324950 0.0131835327066788 * df.mm.trans1:probe5 0.0590588328031982 0.038066564322934 1.55146212571690 0.121219684718203 df.mm.trans1:probe6 -0.0394101105596777 0.038066564322934 -1.03529465452532 0.300870439992047 df.mm.trans1:probe7 0.160012126368542 0.038066564322934 4.20348222159202 2.95079558696844e-05 *** df.mm.trans1:probe8 0.505809648877063 0.038066564322934 13.2875046086659 2.80796243168300e-36 *** df.mm.trans1:probe9 0.0594695950570885 0.038066564322934 1.56225275684414 0.118657145012247 df.mm.trans1:probe10 -0.0332002953693971 0.038066564322934 -0.87216421970067 0.383402450456 df.mm.trans1:probe11 0.0184191514311167 0.0380665643229340 0.483866925180312 0.6286238569766 df.mm.trans1:probe12 -0.0360776335815767 0.038066564322934 -0.947751241102705 0.343566333362782 df.mm.trans1:probe13 0.0898285052733855 0.038066564322934 2.35977443384000 0.0185454526606939 * df.mm.trans1:probe14 -0.00574984903140465 0.038066564322934 -0.151047228287438 0.879979737130217 df.mm.trans1:probe15 0.0877469880603771 0.038066564322934 2.30509344935845 0.0214379317246939 * df.mm.trans1:probe16 -0.0367677819008608 0.038066564322934 -0.965881280720393 0.334419990441641 df.mm.trans1:probe17 -0.040277995084826 0.038066564322934 -1.05809378390788 0.290358891917071 df.mm.trans1:probe18 -0.0215903576300168 0.038066564322934 -0.567173791857262 0.570768583802634 df.mm.trans1:probe19 0.0552805027663855 0.038066564322934 1.45220625369336 0.146869261637049 df.mm.trans1:probe20 0.161336062107992 0.038066564322934 4.23826171280688 2.53812543014325e-05 *** df.mm.trans1:probe21 0.0100206800781762 0.038066564322934 0.263240989997592 0.7924383158844 df.mm.trans1:probe22 -0.0517581646855127 0.038066564322934 -1.35967523221763 0.17434797548353 df.mm.trans2:probe2 0.266982108969849 0.0380665643229340 7.01355937207602 5.25897037938859e-12 *** df.mm.trans2:probe3 0.155635274171788 0.0380665643229340 4.08850330834879 4.81856524066317e-05 *** df.mm.trans2:probe4 0.149622673717418 0.038066564322934 3.93055365984985 9.27207489967945e-05 *** df.mm.trans2:probe5 0.137296114957429 0.038066564322934 3.60673776053679 0.000330957841441081 *** df.mm.trans2:probe6 0.0104337910056251 0.0380665643229340 0.274093320245847 0.784089606130395 df.mm.trans3:probe2 -0.25979016708523 0.038066564322934 -6.82462869202813 1.83958801937359e-11 *** df.mm.trans3:probe3 -0.0650505705131553 0.038066564322934 -1.70886371465796 0.0878966407856272 . df.mm.trans3:probe4 -0.267176023390863 0.038066564322934 -7.0186534598789 5.08235966375276e-12 *** df.mm.trans3:probe5 -0.145677382186915 0.038066564322934 -3.82691174730335 0.000140753938409848 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.93597271808154 0.0911420330961388 43.1850440940875 3.51528923466999e-204 *** df.mm.trans1 0.0365700736639331 0.0802880158719171 0.455486080541248 0.648893557977076 df.mm.trans2 0.0307582519135962 0.0724463284825686 0.424566055421249 0.671276784585625 df.mm.exp2 0.0324151896295386 0.0964769454497859 0.335988971027384 0.736974684037601 df.mm.exp3 0.178524004597014 0.0964769454497859 1.85043176651910 0.0646508179488303 . df.mm.exp4 0.133753980337820 0.096476945449786 1.38638282663536 0.166048717338891 df.mm.exp5 0.0749773932433676 0.096476945449786 0.777153473234615 0.437317260610255 df.mm.exp6 0.122904725450725 0.0964769454497859 1.27392844868513 0.203089813644903 df.mm.exp7 -0.0588163898601453 0.0964769454497859 -0.609641915858104 0.542286684742099 df.mm.exp8 -0.0332362489362937 0.0964769454497859 -0.344499390826924 0.730568898596148 df.mm.trans1:exp2 -0.0634130032575343 0.0910011280393011 -0.696837551619666 0.486123893616414 df.mm.trans2:exp2 -0.0358402969623502 0.0744554683957918 -0.481365542848105 0.63039941470418 df.mm.trans1:exp3 -0.175379702277877 0.091001128039301 -1.92722558562280 0.0543350710512893 . df.mm.trans2:exp3 -0.0870587964170666 0.0744554683957918 -1.16927336961038 0.242671022807538 df.mm.trans1:exp4 -0.141016626726946 0.0910011280393011 -1.54961405166368 0.121662881025406 df.mm.trans2:exp4 -0.0547702539780708 0.0744554683957918 -0.735610898140108 0.462201245142972 df.mm.trans1:exp5 -0.101640386639165 0.091001128039301 -1.11691348040509 0.264394812936927 df.mm.trans2:exp5 -0.0945879750239992 0.0744554683957918 -1.27039661507717 0.204343739522162 df.mm.trans1:exp6 -0.124944321500359 0.091001128039301 -1.37299750225512 0.170170148386767 df.mm.trans2:exp6 -0.105176411191102 0.0744554683957918 -1.41260828058999 0.158192494350097 df.mm.trans1:exp7 0.0609758422014294 0.091001128039301 0.67005589397854 0.503031761105266 df.mm.trans2:exp7 0.0320495863131209 0.0744554683957918 0.430453088317853 0.666991760729857 df.mm.trans1:exp8 4.04370870852825e-05 0.091001128039301 0.00044435808606481 0.999645573647327 df.mm.trans2:exp8 0.0366894494686514 0.0744554683957918 0.492770380190438 0.622321416350311 df.mm.trans1:probe2 0.0946723508212662 0.0531332115720776 1.78179236714948 0.0751942066381005 . df.mm.trans1:probe3 0.0134291650193010 0.0531332115720776 0.252745215694025 0.800535485101562 df.mm.trans1:probe4 -0.050178911544677 0.0531332115720776 -0.944398240949675 0.345275253678705 df.mm.trans1:probe5 0.0145246227858971 0.0531332115720776 0.273362410367267 0.784651126308197 df.mm.trans1:probe6 -0.0169490918861306 0.0531332115720776 -0.31899242271735 0.749822522493953 df.mm.trans1:probe7 0.0454118852774116 0.0531332115720776 0.854679849641844 0.393005767209038 df.mm.trans1:probe8 -0.00755927664561363 0.0531332115720776 -0.142270275444561 0.886905354715172 df.mm.trans1:probe9 -0.0615427276950353 0.0531332115720776 -1.15827230980664 0.247127611319779 df.mm.trans1:probe10 -0.0590290173058664 0.0531332115720776 -1.11096272104296 0.266946209965514 df.mm.trans1:probe11 0.0286103113026290 0.0531332115720776 0.538463805520541 0.590419252900651 df.mm.trans1:probe12 -0.102270224839952 0.0531332115720776 -1.92478906909697 0.0546398485512963 . df.mm.trans1:probe13 -0.0514403502762434 0.0531332115720776 -0.96813930034066 0.333291967592883 df.mm.trans1:probe14 0.064024138508451 0.0531332115720776 1.20497400051942 0.228599587822989 df.mm.trans1:probe15 -0.00247432612733800 0.0531332115720776 -0.046568352526206 0.962869853942252 df.mm.trans1:probe16 0.00947387503916986 0.0531332115720776 0.178304204825227 0.85853300939358 df.mm.trans1:probe17 -0.00760062802405078 0.0531332115720776 -0.143048534036761 0.886290897551103 df.mm.trans1:probe18 -0.0109503676354369 0.0531332115720776 -0.206092711346504 0.83677533186669 df.mm.trans1:probe19 -0.0259329859539943 0.0531332115720776 -0.488074881730328 0.625641775522339 df.mm.trans1:probe20 -0.0165229946249330 0.0531332115720776 -0.310973007956027 0.755908954242483 df.mm.trans1:probe21 0.043772400348817 0.0531332115720776 0.823823726322994 0.410305873772975 df.mm.trans1:probe22 -0.029612405561174 0.0531332115720776 -0.557323841059438 0.577475179261562 df.mm.trans2:probe2 -0.0501773425323052 0.0531332115720776 -0.94436871116359 0.345290328179507 df.mm.trans2:probe3 0.108464231951057 0.0531332115720776 2.04136412503355 0.0415698257915212 * df.mm.trans2:probe4 0.0236194164472176 0.0531332115720776 0.444532068519457 0.656788279026154 df.mm.trans2:probe5 -0.036749541586448 0.0531332115720776 -0.691649168177904 0.48937519970808 df.mm.trans2:probe6 -0.0326626769434486 0.0531332115720776 -0.614731840538948 0.538921309120761 df.mm.trans3:probe2 0.0142804881355223 0.0531332115720776 0.26876764481195 0.788183608297752 df.mm.trans3:probe3 -0.0388257305907094 0.0531332115720776 -0.730724333085731 0.465179464096365 df.mm.trans3:probe4 0.0548875292569531 0.0531332115720776 1.03301734702213 0.301934176216298 df.mm.trans3:probe5 -0.0487653839612655 0.0531332115720776 -0.917794775027161 0.359026157909294