chr9.25335_chr9_101176949_101238710_+_2.R fitVsDatCorrelation=0.869703662953316 cont.fitVsDatCorrelation=0.256839244696707 fstatistic=9408.53710552092,61,899 cont.fstatistic=2443.04985528538,61,899 residuals=-0.572038165350304,-0.103535964036057,-0.0128113996920133,0.0801405735670767,0.878210482928557 cont.residuals=-0.592682012812884,-0.23116765948729,-0.0770676658524305,0.17467916593928,1.81596797645053 predictedValues: Include Exclude Both chr9.25335_chr9_101176949_101238710_+_2.R.tl.Lung 53.7126438033497 125.013648435800 74.504441616926 chr9.25335_chr9_101176949_101238710_+_2.R.tl.cerebhem 68.600999750682 166.517737756673 77.4702529578626 chr9.25335_chr9_101176949_101238710_+_2.R.tl.cortex 62.8610872820733 123.459752473864 74.5470907691905 chr9.25335_chr9_101176949_101238710_+_2.R.tl.heart 55.7807890245781 132.095910293727 73.220254619038 chr9.25335_chr9_101176949_101238710_+_2.R.tl.kidney 54.1498675551325 115.089912415189 70.1834348273893 chr9.25335_chr9_101176949_101238710_+_2.R.tl.liver 54.9413074281818 116.447626767378 68.1322527499396 chr9.25335_chr9_101176949_101238710_+_2.R.tl.stomach 55.2975191973658 221.44628899123 69.6536193828246 chr9.25335_chr9_101176949_101238710_+_2.R.tl.testicle 55.7564966858821 127.728532855459 69.5815605130258 diffExp=-71.3010046324501,-97.916738005991,-60.5986651917911,-76.3151212691486,-60.9400448600563,-61.5063193391964,-166.148769793864,-71.9720361695767 diffExpScore=0.998502318484213 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 69.8042775077298 67.3583405338984 73.2057433139858 cerebhem 66.4654753698145 65.687860379791 62.0582791697071 cortex 70.6115716723947 60.8622723764894 65.6590177492112 heart 65.9382647008016 62.5200838242146 60.404774336374 kidney 67.5619747764533 61.3688782656621 65.8480598466653 liver 66.4832572189592 65.0659601069919 73.2442475559167 stomach 69.4392609627861 57.1996456258546 68.6012658298884 testicle 64.7279653196092 56.1822921332521 75.8682522851243 cont.diffExp=2.44593697383135,0.77761499002348,9.7492992959053,3.41818087658702,6.19309651079121,1.4172971119673,12.2396153369316,8.54567318635711 cont.diffExpScore=0.978159603376814 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=0,0,0,0,0,0,1,0 cont.diffExp1.2Score=0.5 tran.correlation=0.194583790252051 cont.tran.correlation=0.133717279620304 tran.covariance=0.00483018268738866 cont.tran.covariance=0.000283281249319057 tran.mean=99.3062575447853 cont.tran.mean=64.8298362984189 weightedLogRatios: wLogRatio Lung -3.72210654904642 cerebhem -4.14284289967452 cortex -3.02288009653243 heart -3.83847637155242 kidney -3.29384302277897 liver -3.29154382698801 stomach -6.52997921902969 testicle -3.6766036847625 cont.weightedLogRatios: wLogRatio Lung 0.150801698896667 cerebhem 0.0493194551846982 cortex 0.621498158784744 heart 0.221553235917417 kidney 0.40043095158721 liver 0.0902063063808314 stomach 0.803444238468467 testicle 0.58044073218562 varWeightedLogRatios=1.22220323030534 cont.varWeightedLogRatios=0.0781882456591253 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.92983796446483 0.0809511547085686 60.8989208642259 0 *** df.mm.trans1 -0.958289688170123 0.070618637983373 -13.5699259506499 2.69847180418441e-38 *** df.mm.trans2 0.060262768982441 0.0622868398774806 0.967504036181302 0.333552326793756 df.mm.exp2 0.492302312618026 0.0807310121670335 6.09805698458786 1.59259383783477e-09 *** df.mm.exp3 0.144198921018059 0.0807310121670335 1.78616515694997 0.0744094563315464 . df.mm.exp4 0.110273091559079 0.0807310121670335 1.36593223098606 0.172301839267394 df.mm.exp5 -0.0148557171195709 0.0807310121670335 -0.184014998955225 0.854043185802916 df.mm.exp6 0.0410437817683931 0.0807310121670335 0.508401674482576 0.61129640819354 df.mm.exp7 0.668160852422666 0.0807310121670335 8.27638393830902 4.56013631433272e-16 *** df.mm.exp8 0.127188911067716 0.0807310121670335 1.57546533424554 0.115500891005715 df.mm.trans1:exp2 -0.247643630743834 0.0758826486442038 -3.26350799778981 0.00114193514360403 ** df.mm.trans2:exp2 -0.205623394626841 0.0568076564476973 -3.61964227156876 0.000311485510235208 *** df.mm.trans1:exp3 0.0130799807083441 0.0758826486442038 0.17237116708555 0.863184534234575 df.mm.trans2:exp3 -0.156706627792070 0.0568076564476973 -2.75854766049624 0.00592375879862189 ** df.mm.trans1:exp4 -0.072491990540921 0.0758826486442038 -0.955317082839572 0.339674178165321 df.mm.trans2:exp4 -0.05516775850759 0.0568076564476973 -0.971132448640665 0.331743533661342 df.mm.trans1:exp5 0.0229628182984278 0.0758826486442038 0.302609604549983 0.762257395395714 df.mm.trans2:exp5 -0.0678535317399784 0.0568076564476973 -1.19444342511209 0.232619600589543 df.mm.trans1:exp6 -0.0184267303787039 0.0758826486442038 -0.242831934677222 0.808190986798908 df.mm.trans2:exp6 -0.112025084316075 0.0568076564476973 -1.97200679135947 0.0489150168283514 * df.mm.trans1:exp7 -0.639081232084334 0.0758826486442038 -8.42196791365096 1.45296252012524e-16 *** df.mm.trans2:exp7 -0.0964036987947764 0.0568076564476973 -1.69701946573936 0.0900391174097686 . df.mm.trans1:exp8 -0.0898434014112344 0.0758826486442038 -1.18397819549617 0.236734643432549 df.mm.trans2:exp8 -0.105704655202811 0.0568076564476973 -1.86074662840797 0.0631062672340123 . df.mm.trans1:probe2 0.128468982123108 0.0496768544779717 2.58609333205819 0.00986328745103868 ** df.mm.trans1:probe3 -0.0453706542192811 0.0496768544779717 -0.913315762361723 0.361321361355016 df.mm.trans1:probe4 -0.108528013380783 0.0496768544779717 -2.18467965657745 0.0291699610083713 * df.mm.trans1:probe5 -0.0624110948273258 0.0496768544779717 -1.25634151926831 0.209318540261881 df.mm.trans1:probe6 0.0458376036491719 0.0496768544779717 0.922715500626106 0.356403054335588 df.mm.trans1:probe7 0.00540268241423065 0.0496768544779717 0.108756532010825 0.913419870733828 df.mm.trans1:probe8 0.0170480235309952 0.0496768544779717 0.343178401896497 0.731544484980173 df.mm.trans1:probe9 -0.0281640201573733 0.0496768544779717 -0.566944514771201 0.570893402307885 df.mm.trans1:probe10 0.122504479830690 0.0496768544779717 2.46602731026402 0.0138477772975709 * df.mm.trans1:probe11 0.200997028151363 0.0496768544779717 4.04609008085427 5.65575690052829e-05 *** df.mm.trans1:probe12 -0.0748067709795231 0.0496768544779717 -1.50586770772080 0.132452402993374 df.mm.trans1:probe13 -0.141451680127292 0.0496768544779717 -2.84743632852229 0.00450770549673314 ** df.mm.trans1:probe14 0.174410025068001 0.0496768544779717 3.51089107595047 0.000468808153171647 *** df.mm.trans1:probe15 0.248357340659508 0.0496768544779717 4.99945786160108 6.91112366118601e-07 *** df.mm.trans1:probe16 -0.0543185854058223 0.0496768544779717 -1.09343850323512 0.274494216096943 df.mm.trans1:probe17 -0.166780215777445 0.0496768544779717 -3.35730225937314 0.00082009988826544 *** df.mm.trans1:probe18 -0.00579080605058682 0.0496768544779717 -0.116569499245461 0.9072272438383 df.mm.trans1:probe19 0.0106396334162159 0.0496768544779717 0.214176874281237 0.830457697048253 df.mm.trans1:probe20 0.0220398099260408 0.0496768544779717 0.443663556351256 0.657392604344387 df.mm.trans1:probe21 -0.139262455448867 0.0496768544779717 -2.80336701895287 0.00516606836273491 ** df.mm.trans1:probe22 0.0169833888512407 0.0496768544779717 0.341877299392450 0.732523134594524 df.mm.trans1:probe23 0.154044956751435 0.0496768544779717 3.10094023404286 0.00198922210286232 ** df.mm.trans1:probe24 0.0661011794985773 0.0496768544779717 1.33062328911925 0.183650396436542 df.mm.trans1:probe25 0.0265793655342711 0.0496768544779717 0.535045260284288 0.592750873818952 df.mm.trans1:probe26 -0.00112510024768998 0.0496768544779717 -0.0226483794014954 0.981935778365167 df.mm.trans2:probe2 -0.472526043541337 0.0496768544779717 -9.51199604940506 1.65811008902272e-20 *** df.mm.trans2:probe3 -0.5543732761616 0.0496768544779717 -11.1595889471510 3.568428983389e-27 *** df.mm.trans2:probe4 -0.382074880831972 0.0496768544779717 -7.69120518694267 3.8220759220514e-14 *** df.mm.trans2:probe5 -0.507674454894771 0.0496768544779717 -10.2195370505975 2.86416958971842e-23 *** df.mm.trans2:probe6 -0.346840749237572 0.0496768544779717 -6.98193862881098 5.65558202731602e-12 *** df.mm.trans3:probe2 0.124487313268400 0.0496768544779717 2.50594194371952 0.0123882661784266 * df.mm.trans3:probe3 0.481247248645779 0.0496768544779717 9.68755477179376 3.53755580804561e-21 *** df.mm.trans3:probe4 0.47183769482161 0.0496768544779717 9.49813952151173 1.87133561241967e-20 *** df.mm.trans3:probe5 -0.0259862639373715 0.0496768544779717 -0.523106066405525 0.601029346336106 df.mm.trans3:probe6 0.219828645344471 0.0496768544779717 4.42517239979336 1.08184258346213e-05 *** df.mm.trans3:probe7 0.484033062756558 0.0496768544779717 9.74363348571503 2.14955674099762e-21 *** df.mm.trans3:probe8 0.476933877903456 0.0496768544779717 9.60072619160988 7.61625771852139e-21 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.22832263086721 0.158508226001697 26.6757299449049 5.97558501754868e-116 *** df.mm.trans1 0.0638248150040738 0.138276409641080 0.461574141024792 0.644498404009384 df.mm.trans2 -0.0447753875617528 0.121962145293354 -0.36712528673594 0.713611965830927 df.mm.exp2 0.0910747046081607 0.158077170955578 0.576140780212684 0.564664231785039 df.mm.exp3 0.0188844193815304 0.158077170955578 0.119463292943401 0.904935009744965 df.mm.exp4 0.0606904745264186 0.158077170955578 0.383929407134148 0.701121554235865 df.mm.exp5 -0.0198499506632565 0.158077170955578 -0.125571267142898 0.900099383404508 df.mm.exp6 -0.083896187718929 0.158077170955578 -0.530729309056935 0.595737450568425 df.mm.exp7 -0.103759002024079 0.158077170955578 -0.656381951909025 0.511746367215303 df.mm.exp8 -0.292651499686404 0.158077170955578 -1.85132045264551 0.0644512473008349 . df.mm.trans1:exp2 -0.140087349367945 0.148583723903689 -0.942817595948452 0.346027500442373 df.mm.trans2:exp2 -0.116187303560676 0.111233507159413 -1.04453510931884 0.296518663601829 df.mm.trans1:exp3 -0.00738567384144152 0.148583723903689 -0.0497071526234519 0.960366797677566 df.mm.trans2:exp3 -0.120297671694098 0.111233507159413 -1.08148771684142 0.279770236019636 df.mm.trans1:exp4 -0.117666843801492 0.148583723903689 -0.7919228345479 0.428614575057272 df.mm.trans2:exp4 -0.135229362066839 0.111233507159413 -1.21572505911403 0.224408816896820 df.mm.trans1:exp5 -0.0128000180954059 0.148583723903689 -0.0861468386921221 0.93136887230431 df.mm.trans2:exp5 -0.0732739451735914 0.111233507159413 -0.658739862158436 0.510231504913064 df.mm.trans1:exp6 0.0351510423012521 0.148583723903689 0.236573975787797 0.813041203121893 df.mm.trans2:exp6 0.0492709801082694 0.111233507159413 0.442950882036445 0.657907825317805 df.mm.trans1:exp7 0.0985161392661787 0.148583723903689 0.663034528129313 0.507478403292061 df.mm.trans2:exp7 -0.0597200288127408 0.111233507159413 -0.536888841661295 0.591477240876375 df.mm.trans1:exp8 0.217149548168926 0.148583723903689 1.46146255097012 0.144237977305210 df.mm.trans2:exp8 0.111226386487712 0.111233507159413 0.999935984471916 0.317610551958948 df.mm.trans1:probe2 -0.127333111556955 0.0972708802610108 -1.30905684430198 0.190849593907369 df.mm.trans1:probe3 -0.144589469997019 0.0972708802610108 -1.48646202860544 0.137507559494361 df.mm.trans1:probe4 0.00697484327241652 0.0972708802610108 0.071705357797736 0.942852340817089 df.mm.trans1:probe5 -0.0447788177480638 0.0972708802610108 -0.460351727340259 0.645375103344007 df.mm.trans1:probe6 -0.0687871236234421 0.0972708802610108 -0.707170773399633 0.479643622506149 df.mm.trans1:probe7 -0.130335905061635 0.0972708802610108 -1.33992727023647 0.180607566620396 df.mm.trans1:probe8 0.0688614161753415 0.0972708802610108 0.707934543108512 0.479169401821261 df.mm.trans1:probe9 -0.127511968008352 0.0972708802610109 -1.31089559039863 0.190227795879435 df.mm.trans1:probe10 -0.0659051753824773 0.0972708802610108 -0.677542705541795 0.49823600811399 df.mm.trans1:probe11 -0.0148629045763924 0.0972708802610108 -0.152799116616506 0.878590981674588 df.mm.trans1:probe12 0.0895099052221672 0.0972708802610108 0.920212760303821 0.357708438077891 df.mm.trans1:probe13 -0.0968879002710186 0.0972708802610108 -0.996062747772359 0.319487677664432 df.mm.trans1:probe14 -0.0276944501498001 0.0972708802610108 -0.284714706759993 0.775928293792331 df.mm.trans1:probe15 -0.125845655396563 0.0972708802610108 -1.2937649485527 0.196078911468334 df.mm.trans1:probe16 -0.085731486212461 0.0972708802610108 -0.881368462816562 0.378353995121077 df.mm.trans1:probe17 -0.0808939523766876 0.0972708802610108 -0.831635862239774 0.405835348284436 df.mm.trans1:probe18 -0.0544557155002288 0.0972708802610108 -0.559835742763976 0.575730940378524 df.mm.trans1:probe19 -0.153018309832696 0.0972708802610108 -1.57311529845413 0.116043967515268 df.mm.trans1:probe20 -0.0847736076573256 0.0972708802610108 -0.87152092619959 0.383702463653272 df.mm.trans1:probe21 -0.083909142797138 0.0972708802610108 -0.86263373552271 0.388568931177467 df.mm.trans1:probe22 -0.140333502994146 0.0972708802610108 -1.44270826600504 0.149450980671974 df.mm.trans1:probe23 0.0396708778833327 0.0972708802610108 0.407839198914231 0.683488838579501 df.mm.trans1:probe24 0.111845923237715 0.0972708802610108 1.14983973556725 0.250515672152188 df.mm.trans1:probe25 -0.129570461442904 0.0972708802610108 -1.33205807426871 0.183178691011882 df.mm.trans1:probe26 -0.109017596793832 0.0972708802610109 -1.12076293029631 0.262688086169459 df.mm.trans2:probe2 0.0760058009726097 0.0972708802610108 0.78138288425745 0.434783056308229 df.mm.trans2:probe3 0.0441855741754912 0.0972708802610108 0.454252845835529 0.649756501565048 df.mm.trans2:probe4 0.154170418008283 0.0972708802610108 1.58495962609356 0.113327181654351 df.mm.trans2:probe5 0.106780187660428 0.0972708802610108 1.09776109123204 0.272602756659363 df.mm.trans2:probe6 -0.0104291131766127 0.0972708802610108 -0.107217218026894 0.914640577838247 df.mm.trans3:probe2 -0.0219465514754336 0.0972708802610108 -0.225623037609443 0.82154590173198 df.mm.trans3:probe3 0.0351676299219741 0.0972708802610108 0.3615432473481 0.717778335088988 df.mm.trans3:probe4 -0.059516216357957 0.0972708802610108 -0.611860571203373 0.540784713862377 df.mm.trans3:probe5 0.0939974849426642 0.0972708802610108 0.966347633438054 0.334130139828143 df.mm.trans3:probe6 0.139485209843645 0.0972708802610109 1.43398732970606 0.151923598574791 df.mm.trans3:probe7 0.0511918795437231 0.0972708802610108 0.526281651881404 0.598822336840334 df.mm.trans3:probe8 0.128835124808907 0.0972708802610109 1.32449839523605 0.185674177718815