chr17.10803_chr17_27895376_27917973_+_2.R fitVsDatCorrelation=0.951873436311998 cont.fitVsDatCorrelation=0.278034970890772 fstatistic=10085.9093565401,54,738 cont.fstatistic=1014.54079370253,54,738 residuals=-0.525669208534549,-0.101663811402005,-0.00212616598216062,0.0886228314527627,1.03115003072306 cont.residuals=-0.964371002202927,-0.406459777204474,-0.137834398900660,0.364821797239304,2.22220838960945 predictedValues: Include Exclude Both chr17.10803_chr17_27895376_27917973_+_2.R.tl.Lung 55.8064684967275 208.475662726683 105.367813415365 chr17.10803_chr17_27895376_27917973_+_2.R.tl.cerebhem 69.4639061071403 227.205871894172 85.2802405884295 chr17.10803_chr17_27895376_27917973_+_2.R.tl.cortex 53.6695645514019 198.161166810606 110.356502796638 chr17.10803_chr17_27895376_27917973_+_2.R.tl.heart 55.4872188265005 210.094463565452 109.970022880018 chr17.10803_chr17_27895376_27917973_+_2.R.tl.kidney 56.9062380212103 181.515549922100 95.3386764611778 chr17.10803_chr17_27895376_27917973_+_2.R.tl.liver 58.1389969212419 201.784636677162 77.0301861421658 chr17.10803_chr17_27895376_27917973_+_2.R.tl.stomach 57.7598500867188 253.791523448415 86.8752535433613 chr17.10803_chr17_27895376_27917973_+_2.R.tl.testicle 59.8521570339403 212.437956392966 87.7341802157683 diffExp=-152.669194229956,-157.741965787032,-144.491602259204,-154.607244738951,-124.609311900889,-143.64563975592,-196.031673361696,-152.585799359025 diffExpScore=0.999185258013784 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 79.9734527882946 79.4221966310619 69.9038547113705 cerebhem 78.4882789218455 74.1524780294096 77.7047468322395 cortex 83.5851967172044 77.4413116733555 83.117330645769 heart 74.5898432471454 79.5476736465334 68.3586024793769 kidney 73.660299837562 76.1852762581583 75.358515356587 liver 85.6084707730229 67.3640283772465 88.8600748686005 stomach 80.6287382716012 57.8406443046681 85.411257119176 testicle 81.2547590316286 94.0872101964112 63.3346704968207 cont.diffExp=0.551256157232714,4.33580089243591,6.14388504384893,-4.95783039938803,-2.52497642059626,18.2444423957763,22.7880939669332,-12.8324511647826 cont.diffExpScore=2.21015784671633 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=0,0,0,0,0,0,1,0 cont.diffExp1.3Score=0.5 cont.diffExp1.2=0,0,0,0,0,1,1,0 cont.diffExp1.2Score=0.666666666666667 tran.correlation=0.371327249880383 cont.tran.correlation=-0.167946957733201 tran.covariance=0.00301604203028335 cont.tran.covariance=-0.00136280129830478 tran.mean=135.034451967652 cont.tran.mean=77.7393661690718 weightedLogRatios: wLogRatio Lung -6.1690524217309 cerebhem -5.72773635050178 cortex -6.05565576535205 heart -6.23344303734477 kidney -5.36049873583588 liver -5.82987029657719 stomach -7.09972886618642 testicle -5.9858341586444 cont.weightedLogRatios: wLogRatio Lung 0.0302836288931467 cerebhem 0.246313556182632 cortex 0.334983064102115 heart -0.279557402762826 kidney -0.145478142942271 liver 1.03777183329349 stomach 1.40298303997792 testicle -0.655581107727903 varWeightedLogRatios=0.254449999069923 cont.varWeightedLogRatios=0.466039501858172 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.13884136624403 0.0829403327648787 61.9582921232273 1.1755183551917e-294 *** df.mm.trans1 -1.27678486394370 0.0730630481593983 -17.4751108269970 1.74079744205018e-57 *** df.mm.trans2 0.408592680971322 0.0659270194861663 6.19765134471244 9.52686558308873e-10 *** df.mm.exp2 0.516466150087402 0.0877951663784345 5.88262624688486 6.12157371460331e-09 *** df.mm.exp3 -0.136044194238266 0.0877951663784345 -1.54956360184862 0.121674997438527 df.mm.exp4 -0.0407527310235793 0.0877951663784345 -0.464179666200729 0.642655919540589 df.mm.exp5 -0.0189441569510379 0.0877951663784345 -0.215776764627116 0.829221382720188 df.mm.exp6 0.32158536236544 0.0877951663784345 3.6629050963839 0.000267198540935501 *** df.mm.exp7 0.424078952399662 0.0877951663784345 4.83032232744683 1.65815238749139e-06 *** df.mm.exp8 0.271961003648915 0.0877951663784345 3.09767627156884 0.00202437505411802 ** df.mm.trans1:exp2 -0.297548654555667 0.0828121074893898 -3.59305738709512 0.000348517014685058 *** df.mm.trans2:exp2 -0.430431927864146 0.0677553606731371 -6.35273613169325 3.69835010328186e-10 *** df.mm.trans1:exp3 0.0970004813998479 0.0828121074893898 1.17133211966953 0.241843341975307 df.mm.trans2:exp3 0.0853025587323278 0.067755360673137 1.2589787418274 0.20843608613395 df.mm.trans1:exp4 0.0350156482912750 0.0828121074893898 0.422832474052919 0.672540666646638 df.mm.trans2:exp4 0.0484876782071835 0.067755360673137 0.715628663554696 0.474447019006256 df.mm.trans1:exp5 0.0384593378293266 0.0828121074893898 0.464416846706312 0.642486093496444 df.mm.trans2:exp5 -0.119536827406385 0.067755360673137 -1.76424162189986 0.0781049600642767 . df.mm.trans1:exp6 -0.280638505749307 0.0828121074893897 -3.38885839592072 0.000739116168907605 *** df.mm.trans2:exp6 -0.354206697669791 0.0677553606731371 -5.22772949846053 2.23641095543588e-07 *** df.mm.trans1:exp7 -0.38967483881915 0.0828121074893897 -4.7055297906659 3.02346509913369e-06 *** df.mm.trans2:exp7 -0.227388105119928 0.067755360673137 -3.35601645184778 0.000831213456169892 *** df.mm.trans1:exp8 -0.20197331717619 0.0828121074893897 -2.43893463527743 0.0149653052724692 * df.mm.trans2:exp8 -0.253133336725818 0.0677553606731371 -3.73598980524914 0.000201405873667128 *** df.mm.trans1:probe2 0.0424573593324116 0.0483518536832103 0.878091657262656 0.380179758386964 df.mm.trans1:probe3 0.0921273116650293 0.0483518536832103 1.90535221810988 0.0571226746471096 . df.mm.trans1:probe4 -0.147403078500787 0.0483518536832104 -3.0485507229265 0.00238162028791937 ** df.mm.trans1:probe5 -0.104966894608927 0.0483518536832103 -2.17089701041546 0.0302570155550208 * df.mm.trans1:probe6 0.169079061756846 0.0483518536832103 3.49684756378961 0.000498961304965313 *** df.mm.trans1:probe7 0.0657723223527984 0.0483518536832103 1.36028543566753 0.174154955360302 df.mm.trans1:probe8 -0.0382281430376785 0.0483518536832103 -0.790624146245562 0.429417339222776 df.mm.trans1:probe9 -0.0170758478939366 0.0483518536832103 -0.353158081711063 0.724070781029205 df.mm.trans1:probe10 0.0469839392858576 0.0483518536832103 0.971709163286375 0.331513622608312 df.mm.trans1:probe11 0.600351489821498 0.0483518536832103 12.4163076302070 2.78489923933077e-32 *** df.mm.trans1:probe12 1.17648455866490 0.0483518536832103 24.3317364081415 1.77955906691627e-96 *** df.mm.trans1:probe13 0.612210874157358 0.0483518536832103 12.6615802192076 2.17193049024587e-33 *** df.mm.trans1:probe14 0.395583144957187 0.0483518536832103 8.1813439366555 1.22674298107351e-15 *** df.mm.trans1:probe15 0.280739666481735 0.0483518536832103 5.80618208189232 9.4939584207119e-09 *** df.mm.trans1:probe16 0.251513382056642 0.0483518536832103 5.20173194815853 2.56028986446599e-07 *** df.mm.trans1:probe17 0.164387361982642 0.0483518536832103 3.39981509415686 0.00071056704664357 *** df.mm.trans1:probe18 0.0295615400743586 0.0483518536832103 0.611383800671607 0.5411337978039 df.mm.trans1:probe19 0.185060304511982 0.0483518536832103 3.82736731717573 0.000140498858605637 *** df.mm.trans1:probe20 0.143542411181158 0.0483518536832103 2.96870544243481 0.00308741556669117 ** df.mm.trans1:probe21 0.0667555172566115 0.0483518536832103 1.38061960755378 0.167813933869684 df.mm.trans1:probe22 0.300562366220361 0.0483518536832103 6.21614981277807 8.51900106349689e-10 *** df.mm.trans2:probe2 -0.446437595266229 0.0483518536832103 -9.23310196525618 2.73397744121569e-19 *** df.mm.trans2:probe3 -0.599852194239046 0.0483518536832103 -12.4059813336037 3.09850561582204e-32 *** df.mm.trans2:probe4 -0.410718103483101 0.0483518536832103 -8.49436106780987 1.0925360615148e-16 *** df.mm.trans2:probe5 -0.386263492990234 0.0483518536832103 -7.98859740768035 5.24421173993493e-15 *** df.mm.trans2:probe6 -0.44045773555184 0.0483518536832103 -9.10942811908748 7.65803117183007e-19 *** df.mm.trans3:probe2 0.232936192257833 0.0483518536832103 4.8175235180015 1.76462701734349e-06 *** df.mm.trans3:probe3 0.403678881877219 0.0483518536832103 8.34877778465384 3.39518264232087e-16 *** df.mm.trans3:probe4 0.459644707999909 0.0483518536832103 9.50624790957116 2.70675936835635e-20 *** df.mm.trans3:probe5 0.837780371031014 0.0483518536832103 17.3267477296723 1.09234936660342e-56 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.57101363996833 0.259942307268996 17.5847236565386 4.4635225808373e-58 *** df.mm.trans1 -0.175253152217921 0.228986027443358 -0.765344305827881 0.444311229638281 df.mm.trans2 -0.235007985563787 0.206621085126137 -1.13738627120423 0.255745982405875 df.mm.exp2 -0.19319538897323 0.275157783369053 -0.702125837066031 0.482822067307191 df.mm.exp3 -0.154218248789303 0.275157783369053 -0.560472056799713 0.57532759530245 df.mm.exp4 -0.0457583849999127 0.275157783369053 -0.166298712104901 0.86796742861041 df.mm.exp5 -0.198976558142077 0.275157783369053 -0.723136215540745 0.469825317864051 df.mm.exp6 -0.336519361710513 0.275157783369053 -1.22300506127846 0.221718173320435 df.mm.exp7 -0.50928288045587 0.275157783369053 -1.85087579286390 0.0645868142794428 . df.mm.exp8 0.284026786636348 0.275157783369053 1.03223242736841 0.302301394725835 df.mm.trans1:exp2 0.174449950059333 0.259540437963078 0.67214940156705 0.501698957114387 df.mm.trans2:exp2 0.124540992408795 0.212351267424337 0.586485750329557 0.557728475386636 df.mm.trans1:exp3 0.198389940983575 0.259540437963078 0.764389328077645 0.444879596432519 df.mm.trans2:exp3 0.128960745812529 0.212351267424337 0.607299157554968 0.543839199739142 df.mm.trans1:exp4 -0.0239320060180678 0.259540437963078 -0.0922091609534555 0.926556883530969 df.mm.trans2:exp4 0.0473370117083637 0.212351267424337 0.222918432663608 0.823660673041561 df.mm.trans1:exp5 0.116745800255800 0.259540437963078 0.449817381723029 0.652974211128666 df.mm.trans2:exp5 0.157366893473402 0.212351267424337 0.741068774310347 0.45888747145252 df.mm.trans1:exp6 0.40460885813456 0.259540437963078 1.55894342057063 0.119438475214491 df.mm.trans2:exp6 0.171852649824253 0.212351267424337 0.80928478510488 0.418612189686037 df.mm.trans1:exp7 0.517443281199886 0.259540437963078 1.99369040624604 0.0465535270853456 * df.mm.trans2:exp7 0.192196713942597 0.212351267424337 0.905088612249882 0.365713817789597 df.mm.trans1:exp8 -0.268132133901286 0.259540437963078 -1.03310349634006 0.301893890057737 df.mm.trans2:exp8 -0.114582550162559 0.212351267424337 -0.539589669288817 0.589642802676328 df.mm.trans1:probe2 -0.228360152299054 0.151538967691107 -1.50694013413459 0.132253915378436 df.mm.trans1:probe3 -0.0649662753758179 0.151538967691107 -0.428710029939253 0.668259363348577 df.mm.trans1:probe4 -0.0231868219512275 0.151538967691107 -0.153008973893044 0.878433023131407 df.mm.trans1:probe5 0.134891758203078 0.151538967691107 0.890145685022995 0.373677743828689 df.mm.trans1:probe6 -0.130783995221497 0.151538967691107 -0.86303871020214 0.388396557939053 df.mm.trans1:probe7 -0.0768650856967927 0.151538967691107 -0.507229835783708 0.612145093893522 df.mm.trans1:probe8 0.0460677179346256 0.151538967691107 0.303999153726115 0.761214227256293 df.mm.trans1:probe9 0.102715468518616 0.151538967691107 0.677815548592023 0.498101095922657 df.mm.trans1:probe10 -0.0626984197913451 0.151538967691107 -0.413744535459341 0.679181413034478 df.mm.trans1:probe11 0.276504419712118 0.151538967691107 1.82464236047680 0.0684591680011377 . df.mm.trans1:probe12 -0.309031785022536 0.151538967691107 -2.03928923187901 0.0417769057612394 * df.mm.trans1:probe13 0.0124681292186020 0.151538967691107 0.0822767200316208 0.934448975707103 df.mm.trans1:probe14 -0.0902307796839332 0.151538967691107 -0.595429552271052 0.551738916438 df.mm.trans1:probe15 -0.142224262687951 0.151538967691107 -0.938532608839313 0.348277819459993 df.mm.trans1:probe16 -0.0645433934353542 0.151538967691107 -0.425919447774765 0.670290729439212 df.mm.trans1:probe17 -0.107988321917549 0.151538967691107 -0.712610911654547 0.47631179511018 df.mm.trans1:probe18 -0.0251568162203115 0.151538967691107 -0.166008892653872 0.868195419586206 df.mm.trans1:probe19 0.113067186653418 0.151538967691107 0.746126150759398 0.455828808958878 df.mm.trans1:probe20 0.0826974589225258 0.151538967691107 0.545717449330223 0.585425082306896 df.mm.trans1:probe21 0.0941226635525998 0.151538967691107 0.621111948871508 0.534717752686408 df.mm.trans1:probe22 0.0837261026505534 0.151538967691107 0.552505430954358 0.580769406612317 df.mm.trans2:probe2 0.131417086188007 0.151538967691107 0.86721645389511 0.386105300029855 df.mm.trans2:probe3 0.0527954520123528 0.151538967691107 0.348395220165217 0.727642751369848 df.mm.trans2:probe4 0.147186499230926 0.151538967691107 0.971278222845934 0.331727970906844 df.mm.trans2:probe5 0.021899172179233 0.151538967691107 0.144511821037819 0.885135776838335 df.mm.trans2:probe6 0.0731963129956612 0.151538967691107 0.483019741462557 0.62922497356 df.mm.trans3:probe2 0.0080403418854389 0.151538967691107 0.0530579164418497 0.957700120527654 df.mm.trans3:probe3 0.187700554264158 0.151538967691107 1.23862896206843 0.215876759880188 df.mm.trans3:probe4 -0.0830483487937536 0.151538967691107 -0.548032958512937 0.583834991994719 df.mm.trans3:probe5 0.319148910734498 0.151538967691107 2.10605176739123 0.0355370080377906 *