chr5.18267_chr5_133197103_133198258_+_1.R fitVsDatCorrelation=0.637201227423421 cont.fitVsDatCorrelation=0.263091051401913 fstatistic=9895.25158928566,42,462 cont.fstatistic=6310.62508293967,42,462 residuals=-0.413257366336543,-0.0778182319273274,-0.00238160546986159,0.0646675741277185,0.619484136444179 cont.residuals=-0.382126514631273,-0.109725557681104,-0.0177260588995437,0.092468110320785,0.7705398228748 predictedValues: Include Exclude Both chr5.18267_chr5_133197103_133198258_+_1.R.tl.Lung 52.3522217830823 54.681806111181 57.6425598699312 chr5.18267_chr5_133197103_133198258_+_1.R.tl.cerebhem 61.6814314153386 57.3359183967682 66.0088529549097 chr5.18267_chr5_133197103_133198258_+_1.R.tl.cortex 48.9619336884492 53.0255089539296 54.8147590925681 chr5.18267_chr5_133197103_133198258_+_1.R.tl.heart 48.9896080724827 49.4385328453807 53.7504701560326 chr5.18267_chr5_133197103_133198258_+_1.R.tl.kidney 52.0051957496527 58.0322455700641 60.2038867532199 chr5.18267_chr5_133197103_133198258_+_1.R.tl.liver 52.5769864299632 49.8009295980973 56.9989167916468 chr5.18267_chr5_133197103_133198258_+_1.R.tl.stomach 50.2126347565431 48.9022949417737 51.6266637975043 chr5.18267_chr5_133197103_133198258_+_1.R.tl.testicle 52.4442316299863 54.6593387458265 59.2713042406988 diffExp=-2.32958432809871,4.34551301857041,-4.06357526548039,-0.448924772898003,-6.02704982041141,2.77605683186586,1.31033981476933,-2.21510711584025 diffExpScore=3.07307002386346 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 53.941985615728 54.3415933003332 52.5296222614087 cerebhem 54.7277425660473 51.1831600815068 53.056251732849 cortex 54.5354544569218 52.1407890723559 56.5159598051946 heart 53.1818324614969 52.2823779619619 51.7703810671552 kidney 54.2122621728542 50.2876070516988 53.8169451479743 liver 54.4904450934782 54.6638703742156 56.8451591392529 stomach 53.0492961231987 57.1577885966414 53.2518838279343 testicle 53.6654391358188 53.9266107278965 52.3644608703162 cont.diffExp=-0.399607684605158,3.54458248454051,2.39466538456598,0.899454499534912,3.92465512115538,-0.173425280737355,-4.1084924734427,-0.261171592077652 cont.diffExpScore=2.30271754696239 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=0.581379666431002 cont.tran.correlation=-0.538092337770986 tran.covariance=0.00286450459419280 cont.tran.covariance=-0.000258098632091742 tran.mean=52.8188011680325 cont.tran.mean=53.6117659245096 weightedLogRatios: wLogRatio Lung -0.173265593956239 cerebhem 0.298465621865799 cortex -0.313411170757781 heart -0.0355406283261252 kidney -0.439297435828185 liver 0.213461963625298 stomach 0.103205721471262 testicle -0.164669540144645 cont.weightedLogRatios: wLogRatio Lung -0.0294611814969969 cerebhem 0.265757650348505 cortex 0.178554199782044 heart 0.0676360775942184 kidney 0.29723716052149 liver -0.0127092509734536 stomach -0.299011709569394 testicle -0.0193475669402785 varWeightedLogRatios=0.066037352662183 cont.varWeightedLogRatios=0.0372976657827634 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.87750058612367 0.0753415670464763 51.4656216764345 1.93140165490801e-193 *** df.mm.trans1 -0.0264320492901959 0.0663891569682557 -0.398138046892726 0.690712345678992 df.mm.trans2 0.115038257275208 0.0627698646107212 1.83269882751284 0.0674907639657562 . df.mm.exp2 0.0758571051053363 0.0864836872208786 0.877126167292081 0.38087398047178 df.mm.exp3 -0.0474074904590266 0.0864836872208786 -0.548166850679577 0.5838421028038 df.mm.exp4 -0.097278319078315 0.0864836872208785 -1.12481697074116 0.261250639913446 df.mm.exp5 0.00934129404196348 0.0864836872208785 0.108012208338272 0.914032899741207 df.mm.exp6 -0.077984347589461 0.0864836872208785 -0.901723204634993 0.367673766297663 df.mm.exp7 -0.0432115069103799 0.0864836872208786 -0.499649220552057 0.617559961199422 df.mm.exp8 -0.0265190851906681 0.0864836872208786 -0.306636847281252 0.759257952224411 df.mm.trans1:exp2 0.0881314536497913 0.0800683359315319 1.10070295110360 0.271599116697203 df.mm.trans2:exp2 -0.0284608715338979 0.0730920562193357 -0.389383922221207 0.697171582550124 df.mm.trans1:exp3 -0.0195437541997423 0.0800683359315319 -0.244088427371022 0.807270692432416 df.mm.trans2:exp3 0.0166495473673221 0.0730920562193357 0.227788739686839 0.819911255387287 df.mm.trans1:exp4 0.0308921371898166 0.0800683359315319 0.385822145925864 0.699805989369812 df.mm.trans2:exp4 -0.00352258554326708 0.0730920562193357 -0.0481938219482628 0.961582600259652 df.mm.trans1:exp5 -0.0159920395430163 0.0800683359315319 -0.199729885190713 0.841779718792242 df.mm.trans2:exp5 0.0501264782483769 0.0730920562193357 0.685799262480134 0.493183688911916 df.mm.trans1:exp6 0.0822684738967332 0.0800683359315319 1.02747825266511 0.304732957197589 df.mm.trans2:exp6 -0.0155130437988728 0.0730920562193357 -0.212239805544956 0.832013558261597 df.mm.trans1:exp7 0.00148381296367424 0.0800683359315319 0.0185318321707483 0.985222583948384 df.mm.trans2:exp7 -0.0684952082586001 0.0730920562193357 -0.937108788581055 0.349192206709248 df.mm.trans1:exp8 0.0282750581754325 0.0800683359315319 0.353136578230014 0.724147120005057 df.mm.trans2:exp8 0.0261081261559869 0.0730920562193357 0.357195124975568 0.721108836847102 df.mm.trans1:probe2 0.0508243339908428 0.0400341679657659 1.26952392352212 0.204893374374293 df.mm.trans1:probe3 0.154627270348384 0.0400341679657660 3.86238251487101 0.000128315339284795 *** df.mm.trans1:probe4 0.197152035877794 0.040034167965766 4.92459431269765 1.17906159261728e-06 *** df.mm.trans1:probe5 -0.0374398925078167 0.0400341679657659 -0.935198466965326 0.350174578758735 df.mm.trans1:probe6 0.0647098516190962 0.0400341679657659 1.61636559237177 0.106697886444513 df.mm.trans1:probe7 0.112149812604839 0.040034167965766 2.80135240229648 0.00530251092283797 ** df.mm.trans1:probe8 0.239942796953126 0.0400341679657659 5.99345032369116 4.14122398266131e-09 *** df.mm.trans1:probe9 0.125284749279148 0.0400341679657659 3.12944556225775 0.00186222868107682 ** df.mm.trans1:probe10 0.183791771721401 0.0400341679657660 4.59087277344107 5.69727390295968e-06 *** df.mm.trans1:probe11 0.193902491882424 0.0400341679657659 4.84342504753025 1.74425222524566e-06 *** df.mm.trans1:probe12 0.105090704991501 0.0400341679657660 2.62502533039692 0.0089514593743495 ** df.mm.trans2:probe2 0.155423925994437 0.0400341679657659 3.88228190797778 0.000118558364552447 *** df.mm.trans2:probe3 0.104204685266776 0.0400341679657660 2.60289374206261 0.00954128646204655 ** df.mm.trans2:probe4 -0.00546164306683518 0.0400341679657659 -0.136424542943057 0.89154509885853 df.mm.trans2:probe5 -0.0565750144299374 0.0400341679657659 -1.41316823365271 0.158279628376865 df.mm.trans2:probe6 -0.116662167495737 0.0400341679657660 -2.91406499556823 0.00374069245584479 ** df.mm.trans3:probe2 0.127792984348287 0.0400341679657659 3.19209792139468 0.00150877603095465 ** df.mm.trans3:probe3 0.136670177796435 0.0400341679657660 3.41383834711649 0.000696973387117497 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.06461851679805 0.0943137380195224 43.0967810432527 5.63413000522492e-164 *** df.mm.trans1 -0.0148576888957512 0.0831069727256735 -0.178777885999948 0.858190480780635 df.mm.trans2 -0.069641099947138 0.0785762866169814 -0.886286473253722 0.375924268704927 df.mm.exp2 -0.0553931823966626 0.108261616253358 -0.511660404801545 0.6091331653193 df.mm.exp3 -0.103546309010008 0.108261616253358 -0.956445253576159 0.339347535049015 df.mm.exp4 -0.0382637849646049 0.108261616253358 -0.353438146305322 0.723921211361216 df.mm.exp5 -0.0967444039620772 0.108261616253358 -0.893616845103 0.371992187083214 df.mm.exp6 -0.0629245211225678 0.108261616253358 -0.581226507604593 0.561371248691557 df.mm.exp7 0.0201822710556425 0.108261616253358 0.186421298278156 0.8521962197671 df.mm.exp8 -0.00965667822818865 0.108261616253358 -0.0891976174232401 0.928963512179057 df.mm.trans1:exp2 0.0698548113667283 0.100230780361221 0.69693971367856 0.486191048723183 df.mm.trans2:exp2 -0.0044861688336441 0.0914977656003113 -0.049030364886078 0.960916286133433 df.mm.trans1:exp3 0.114488211066022 0.100230780361221 1.14224603114351 0.253943394509031 df.mm.trans2:exp3 0.062203926607893 0.0914977656003113 0.679840936002938 0.496945678470078 df.mm.trans1:exp4 0.0240714993074112 0.100230780361221 0.240160749229528 0.810312164475717 df.mm.trans2:exp4 -0.000366766712624018 0.0914977656003113 -0.00400847725862686 0.996803436673837 df.mm.trans1:exp5 0.101742397573547 0.100230780361221 1.01508136728935 0.310598336344786 df.mm.trans2:exp5 0.0192131455124344 0.0914977656003113 0.209984860137055 0.833772059218576 df.mm.trans1:exp6 0.0730407594383847 0.100230780361221 0.728725838261992 0.466538609229029 df.mm.trans2:exp6 0.0688375827624877 0.0914977656003113 0.752341680814263 0.452228743606635 df.mm.trans1:exp7 -0.0368698028583107 0.100230780361221 -0.367849105089631 0.713154216438905 df.mm.trans2:exp7 0.0303434687885392 0.0914977656003113 0.331630708022841 0.740318511528635 df.mm.trans1:exp8 0.00451675243991153 0.100230780361221 0.0450635266295804 0.96407614427522 df.mm.trans2:exp8 0.00199081532080310 0.0914977656003113 0.0217580758146550 0.98265033076173 df.mm.trans1:probe2 -0.00789098808600272 0.0501153901806107 -0.157456383309886 0.874953970988014 df.mm.trans1:probe3 -0.0578759099946897 0.0501153901806107 -1.15485302590902 0.248747583637504 df.mm.trans1:probe4 -0.105751034630754 0.0501153901806107 -2.11015087879467 0.0353823756138338 * df.mm.trans1:probe5 -0.0556784929688097 0.0501153901806107 -1.11100587600236 0.267143678357828 df.mm.trans1:probe6 -0.0814897864753016 0.0501153901806107 -1.62604314127099 0.104622352875205 df.mm.trans1:probe7 -0.0863156534360067 0.0501153901806107 -1.72233825028467 0.0856775149147015 . df.mm.trans1:probe8 -0.00667126068362712 0.0501153901806107 -0.133118003463299 0.894158018194454 df.mm.trans1:probe9 -0.135211962482347 0.0501153901806107 -2.69801276603967 0.00723080958660986 ** df.mm.trans1:probe10 -0.144058686743707 0.0501153901806107 -2.87453986139855 0.00423288401410521 ** df.mm.trans1:probe11 -0.0421543979715725 0.0501153901806107 -0.841146757905155 0.400700868063754 df.mm.trans1:probe12 -0.0809739174906005 0.0501153901806107 -1.61574951723969 0.106831116044825 df.mm.trans2:probe2 -0.0083581512484441 0.0501153901806107 -0.166778133789285 0.867617592339104 df.mm.trans2:probe3 0.0165869892164419 0.0501153901806107 0.330975956820133 0.740812706253817 df.mm.trans2:probe4 -0.00166275582157608 0.0501153901806107 -0.0331785468612273 0.973546534840787 df.mm.trans2:probe5 -0.0201601220386793 0.0501153901806107 -0.402274071218927 0.687668383342966 df.mm.trans2:probe6 0.0164066088843155 0.0501153901806107 0.327376656655526 0.743531306260776 df.mm.trans3:probe2 0.00623129876379671 0.0501153901806107 0.124339025224382 0.901100928817124 df.mm.trans3:probe3 -0.0624587505443241 0.0501153901806107 -1.24629879801852 0.213286282818774