chr11.3682_chr11_97797498_97803106_+_2.R fitVsDatCorrelation=0.95609971453308 cont.fitVsDatCorrelation=0.257458498895403 fstatistic=10549.7722675533,52,692 cont.fstatistic=958.173750452033,52,692 residuals=-0.722726601340143,-0.100363629010059,0.0033124210842964,0.105148844902656,0.703832663244665 cont.residuals=-1.43757488120928,-0.441455608169123,-0.136590682713730,0.507262975965867,1.31270258687976 predictedValues: Include Exclude Both chr11.3682_chr11_97797498_97803106_+_2.R.tl.Lung 103.051749406063 333.847528934535 87.6609706034134 chr11.3682_chr11_97797498_97803106_+_2.R.tl.cerebhem 88.6978612904381 194.461066697821 82.9671398320324 chr11.3682_chr11_97797498_97803106_+_2.R.tl.cortex 93.8690348426282 204.372331632841 102.011426990084 chr11.3682_chr11_97797498_97803106_+_2.R.tl.heart 101.121846318510 251.266601988033 99.810571158026 chr11.3682_chr11_97797498_97803106_+_2.R.tl.kidney 114.167162454127 345.399219188324 110.945170630123 chr11.3682_chr11_97797498_97803106_+_2.R.tl.liver 107.010760794156 313.058415060889 102.839729878506 chr11.3682_chr11_97797498_97803106_+_2.R.tl.stomach 95.7264335729672 245.906094060888 84.8786140746791 chr11.3682_chr11_97797498_97803106_+_2.R.tl.testicle 118.542373792136 278.428532757829 119.140055396104 diffExp=-230.795779528472,-105.763205407383,-110.503296790212,-150.144755669524,-231.232056734197,-206.047654266733,-150.179660487921,-159.886158965693 diffExpScore=0.999256810901414 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 126.965267607355 142.775180336217 145.652095996976 cerebhem 119.911997376227 119.428304193981 138.760666208391 cortex 131.63044387697 144.801309646275 137.451513240978 heart 108.862875418265 124.728748042503 114.395391700686 kidney 134.344987757894 127.156526089118 150.016089392662 liver 131.412125475249 130.442314708691 126.703614563424 stomach 114.185104058375 129.973103973774 113.693732718943 testicle 130.572557274795 130.899218982949 164.746500990908 cont.diffExp=-15.8099127288623,0.483693182245403,-13.1708657693046,-15.8658726242375,7.18846166877553,0.969810766557572,-15.7879999153986,-0.326661708154006 cont.diffExpScore=1.30540380016188 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=0.750058940704984 cont.tran.correlation=0.438303286974198 tran.covariance=0.0168055669175536 cont.tran.covariance=0.00221017306338158 tran.mean=186.807938299512 cont.tran.mean=128.005629051165 weightedLogRatios: wLogRatio Lung -6.13934200602655 cerebhem -3.82900252929495 cortex -3.83646897492980 heart -4.61594771017405 kidney -5.85753561256396 liver -5.59236330501063 stomach -4.74861985916155 testicle -4.44212501344602 cont.weightedLogRatios: wLogRatio Lung -0.575356781317318 cerebhem 0.0193393915253567 cortex -0.469924281235338 heart -0.647352505265364 kidney 0.267972363416962 liver 0.0361078075640175 stomach -0.621965464018675 testicle -0.0121763169002187 varWeightedLogRatios=0.788741987031533 cont.varWeightedLogRatios=0.132818070815703 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.7029859387479 0.0958361973931996 59.5076400553491 2.35029896463756e-274 *** df.mm.trans1 -1.37723423856506 0.0860749202507283 -16.00041260048 2.90577430947265e-49 *** df.mm.trans2 -0.00571817878758899 0.079157579216705 -0.0722379188976292 0.942433442198214 df.mm.exp2 -0.635415779396002 0.108426280095782 -5.86034842138534 7.14647846444317e-09 *** df.mm.exp3 -0.735679691279532 0.108426280095782 -6.78506807233119 2.49409509585687e-11 *** df.mm.exp4 -0.432872282196721 0.108426280095782 -3.99231885308919 7.24231023326944e-05 *** df.mm.exp5 -0.0991104089260892 0.108426280095782 -0.914081058932728 0.360992630448985 df.mm.exp6 -0.186291460221704 0.108426280095782 -1.71813936673965 0.0862185188524987 . df.mm.exp7 -0.347216866055799 0.108426280095782 -3.20233125907366 0.00142563289265059 ** df.mm.exp8 -0.348306748939068 0.108426280095782 -3.21238309228518 0.00137738729712697 ** df.mm.trans1:exp2 0.485420273224531 0.103810259756883 4.67603370188412 3.51722315751783e-06 *** df.mm.trans2:exp2 0.0949633626453814 0.090355233413152 1.05100013644100 0.293625406816758 df.mm.trans1:exp3 0.642348972248041 0.103810259756884 6.18772146175511 1.04481515655062e-09 *** df.mm.trans2:exp3 0.244938788062305 0.090355233413152 2.71084229224792 0.00687765685703586 ** df.mm.trans1:exp4 0.413967187640035 0.103810259756883 3.98772904151784 7.38059178153261e-05 *** df.mm.trans2:exp4 0.148702428398531 0.090355233413152 1.64575335352835 0.100268631746256 df.mm.trans1:exp5 0.201542837138377 0.103810259756884 1.94145393345875 0.0526088290388974 . df.mm.trans2:exp5 0.133126925482087 0.090355233413152 1.47337260337052 0.141105305671225 df.mm.trans1:exp6 0.223989574320319 0.103810259756884 2.1576824376019 0.0312959809161005 * df.mm.trans2:exp6 0.121996874383466 0.090355233413152 1.35019156915495 0.177395970246396 df.mm.trans1:exp7 0.273480055782285 0.103810259756883 2.63442222784874 0.00861655886758147 ** df.mm.trans2:exp7 0.0414822090975948 0.090355233413152 0.459101344002026 0.646305564219829 df.mm.trans1:exp8 0.488345946863493 0.103810259756884 4.70421659677151 3.07772266233386e-06 *** df.mm.trans2:exp8 0.166783771949268 0.090355233413152 1.84586731337016 0.0653384189823491 . df.mm.trans1:probe2 -0.487401242335535 0.0519051298784418 -9.39023259313665 8.47918287954637e-20 *** df.mm.trans1:probe3 0.378381798355865 0.0519051298784418 7.28987287464667 8.49729954263307e-13 *** df.mm.trans1:probe4 0.246788283790033 0.0519051298784418 4.75460295288721 2.42013112626490e-06 *** df.mm.trans1:probe5 -0.12306316159555 0.0519051298784418 -2.37092483698154 0.0180165936157883 * df.mm.trans1:probe6 0.221275442247586 0.0519051298784418 4.2630746279953 2.29622694772414e-05 *** df.mm.trans1:probe7 0.0164329652721487 0.0519051298784417 0.316596169022861 0.7516455234011 df.mm.trans1:probe8 -0.0204965317655527 0.0519051298784418 -0.394884509749888 0.693049804612117 df.mm.trans1:probe9 0.0400806945796101 0.0519051298784418 0.772191393672964 0.440264710612215 df.mm.trans1:probe10 -0.0509131219657695 0.0519051298784418 -0.980888056440751 0.326990749194344 df.mm.trans1:probe11 0.928059557072305 0.0519051298784418 17.8799197544782 4.57725987591607e-59 *** df.mm.trans1:probe12 1.18695691514353 0.0519051298784418 22.8678151451177 1.21638252171996e-86 *** df.mm.trans1:probe13 0.960476763860043 0.0519051298784418 18.5044670172180 2.0549744089063e-62 *** df.mm.trans1:probe14 1.01076238222640 0.0519051298784418 19.4732656404778 1.11289579974405e-67 *** df.mm.trans1:probe15 1.10842870411002 0.0519051298784417 21.3548970343758 4.11093623265335e-78 *** df.mm.trans1:probe16 0.972095032584545 0.0519051298784418 18.7283036351344 1.26925326645149e-63 *** df.mm.trans1:probe17 0.435585626358425 0.0519051298784418 8.39195716066093 2.68864018654430e-16 *** df.mm.trans1:probe18 0.156906659284217 0.0519051298784418 3.02295090392185 0.00259571415919993 ** df.mm.trans1:probe19 0.239518635231831 0.0519051298784418 4.61454649651715 4.69494720294883e-06 *** df.mm.trans1:probe20 0.0622744381648758 0.0519051298784418 1.19977424795426 0.230637632505384 df.mm.trans1:probe21 0.344132063482023 0.0519051298784418 6.63002027522052 6.76118803059812e-11 *** df.mm.trans1:probe22 0.110707678236347 0.0519051298784418 2.13288510202396 0.0332854300760895 * df.mm.trans2:probe2 0.133544196005452 0.0519051298784418 2.57285159132062 0.0102936972667326 * df.mm.trans2:probe3 0.311364989565595 0.0519051298784418 5.99873250090676 3.20497097524628e-09 *** df.mm.trans2:probe4 0.282745168647735 0.0519051298784418 5.44734536470489 7.11166159265676e-08 *** df.mm.trans2:probe5 0.118584341135387 0.0519051298784418 2.28463624718989 0.0226360236004953 * df.mm.trans2:probe6 0.174510961977847 0.0519051298784418 3.36211396419851 0.00081603953734287 *** df.mm.trans3:probe2 -0.00957733896687765 0.0519051298784418 -0.184516231619247 0.853662554643053 df.mm.trans3:probe3 0.469907076660712 0.0519051298784418 9.05319142368399 1.39381231013256e-18 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.80020067581804 0.316014930935325 15.1897907532744 3.48163597407184e-45 *** df.mm.trans1 0.0359432725219432 0.283827621693884 0.126637683490541 0.899263956099506 df.mm.trans2 0.0895636890181215 0.261018045473385 0.343132172550322 0.731603241839124 df.mm.exp2 -0.187240197616531 0.357530080992906 -0.523704738623787 0.600651593050169 df.mm.exp3 0.108125709739622 0.357530080992906 0.302424090972551 0.762419669011272 df.mm.exp4 -0.0473942848184255 0.357530080992906 -0.132560272094604 0.894579688506927 df.mm.exp5 -0.0888766268199208 0.357530080992906 -0.24858503254635 0.80375554195398 df.mm.exp6 0.0834549422839052 0.357530080992906 0.233420757358766 0.815503726731219 df.mm.exp7 0.0476761905713653 0.357530080992906 0.133348753310386 0.89395634058606 df.mm.exp8 -0.182015081117688 0.357530080992906 -0.50909025783847 0.610851244811906 df.mm.trans1:exp2 0.130084750515472 0.342308991380928 0.380021424475852 0.704046116930707 df.mm.trans2:exp2 0.008685196403292 0.297941734160755 0.0291506539953409 0.976752841709242 df.mm.trans1:exp3 -0.072040946799947 0.342308991380928 -0.210455899827003 0.833373820042363 df.mm.trans2:exp3 -0.094034412940357 0.297941734160755 -0.315613430945597 0.752391101778994 df.mm.trans1:exp4 -0.106430214262686 0.342308991380928 -0.310918547109528 0.755956175397186 df.mm.trans2:exp4 -0.0877355790648867 0.297941734160755 -0.294472270935863 0.768485361206988 df.mm.trans1:exp5 0.145374088189678 0.342308991380928 0.424686735814961 0.671197062686795 df.mm.trans2:exp5 -0.0269757843516626 0.297941734160755 -0.0905404690203883 0.92788393648448 df.mm.trans1:exp6 -0.0490301270278964 0.342308991380928 -0.143233535380129 0.88614744236746 df.mm.trans2:exp6 -0.173795073760002 0.297941734160755 -0.583318997754879 0.559868630019207 df.mm.trans1:exp7 -0.153768904822875 0.342308991380928 -0.449210826167748 0.653420229081655 df.mm.trans2:exp7 -0.141619881660341 0.297941734160755 -0.475327439639354 0.634703599493406 df.mm.trans1:exp8 0.210030582167137 0.342308991380928 0.613570158703225 0.539701034062777 df.mm.trans2:exp8 0.0951715598690075 0.297941734160755 0.319430106484033 0.74949678990281 df.mm.trans1:probe2 0.0474676832949776 0.171154495690464 0.277338220672998 0.781603242848433 df.mm.trans1:probe3 -0.060478247510272 0.171154495690464 -0.353354711871829 0.723930150981604 df.mm.trans1:probe4 -0.120990585922743 0.171154495690464 -0.706908605787117 0.479861241507625 df.mm.trans1:probe5 0.0544872517682737 0.171154495690464 0.318351274084059 0.750314548013625 df.mm.trans1:probe6 -0.0695682083750005 0.171154495690464 -0.406464394022205 0.68452708511536 df.mm.trans1:probe7 0.0528203947075452 0.171154495690464 0.308612370913539 0.7577092912315 df.mm.trans1:probe8 -0.152929603963685 0.171154495690464 -0.893517890644606 0.37189052904527 df.mm.trans1:probe9 0.154912383728998 0.171154495690464 0.905102627331274 0.365726026910208 df.mm.trans1:probe10 0.0581874130681973 0.171154495690464 0.339970111994197 0.733982200701341 df.mm.trans1:probe11 -0.109390579058313 0.171154495690464 -0.639133541990904 0.522947558719099 df.mm.trans1:probe12 -0.120162051511332 0.171154495690464 -0.702067748945649 0.482872979446232 df.mm.trans1:probe13 0.140204676373589 0.171154495690464 0.819170281259522 0.412971291931061 df.mm.trans1:probe14 0.0871999979468226 0.171154495690464 0.509481200567033 0.610577400594616 df.mm.trans1:probe15 0.113759286986731 0.171154495690464 0.664658480209989 0.506490379824458 df.mm.trans1:probe16 -0.0409168348955052 0.171154495690464 -0.239063746064282 0.811126936815167 df.mm.trans1:probe17 0.00173763060373308 0.171154495690464 0.0101524099423927 0.991902614087406 df.mm.trans1:probe18 -0.192814046303291 0.171154495690464 -1.12654970309397 0.260323422039040 df.mm.trans1:probe19 0.149374821728553 0.171154495690464 0.872748455282766 0.383102927755634 df.mm.trans1:probe20 0.0665724933009435 0.171154495690464 0.388961406081562 0.697424349395834 df.mm.trans1:probe21 0.232094760835469 0.171154495690464 1.35605413050450 0.175524260656986 df.mm.trans1:probe22 -0.0973282040900868 0.171154495690464 -0.568657011885371 0.569773420728221 df.mm.trans2:probe2 -0.142892854495334 0.171154495690464 -0.834876430904614 0.404075417606873 df.mm.trans2:probe3 0.434446069609625 0.171154495690464 2.53832695341716 0.0113564791853296 * df.mm.trans2:probe4 0.0660940332642049 0.171154495690464 0.386165919846693 0.699492490096543 df.mm.trans2:probe5 0.191336781489477 0.171154495690464 1.11791852570156 0.263989738925412 df.mm.trans2:probe6 0.0945777352758202 0.171154495690464 0.552586918002235 0.580724742582266 df.mm.trans3:probe2 0.188421048274478 0.171154495690464 1.10088284572577 0.271330432560465 df.mm.trans3:probe3 -0.0218813385177567 0.171154495690464 -0.127845537620756 0.898308354473607