chr2.13666_chr2_131437816_131438127_+_1.R fitVsDatCorrelation=0.815187686059341 cont.fitVsDatCorrelation=0.275024182352486 fstatistic=5993.65710010027,39,393 cont.fstatistic=2168.79620640831,39,393 residuals=-0.489916463338423,-0.0950909109319047,-0.00751525167130554,0.0835332272790795,1.37245772240720 cont.residuals=-0.644057214977533,-0.184237783135276,-0.0369540565138604,0.105162319960596,1.53287816658951 predictedValues: Include Exclude Both chr2.13666_chr2_131437816_131438127_+_1.R.tl.Lung 53.4655749168004 69.9764192866431 71.146086623591 chr2.13666_chr2_131437816_131438127_+_1.R.tl.cerebhem 68.9321600972277 87.9602712319669 74.3690271986972 chr2.13666_chr2_131437816_131438127_+_1.R.tl.cortex 56.4808729593452 64.7626071949849 98.1767992711381 chr2.13666_chr2_131437816_131438127_+_1.R.tl.heart 50.0190531175311 60.4089687889627 78.4840581428477 chr2.13666_chr2_131437816_131438127_+_1.R.tl.kidney 52.1562696424053 65.4559869481502 69.1852933548421 chr2.13666_chr2_131437816_131438127_+_1.R.tl.liver 51.2949740373914 67.7614576389826 65.2352686042737 chr2.13666_chr2_131437816_131438127_+_1.R.tl.stomach 54.0171604070642 82.4974769121395 81.0023808161502 chr2.13666_chr2_131437816_131438127_+_1.R.tl.testicle 55.2517417108903 67.9127571697052 83.3285163450826 diffExp=-16.5108443698427,-19.0281111347392,-8.28173423563966,-10.3899156714316,-13.2997173057449,-16.4664836015912,-28.4803165050754,-12.6610154588149 diffExpScore=0.992070926405867 diffExp1.5=0,0,0,0,0,0,-1,0 diffExp1.5Score=0.5 diffExp1.4=0,0,0,0,0,0,-1,0 diffExp1.4Score=0.5 diffExp1.3=-1,0,0,0,0,-1,-1,0 diffExp1.3Score=0.75 diffExp1.2=-1,-1,0,-1,-1,-1,-1,-1 diffExp1.2Score=0.875 cont.predictedValues: Include Exclude Both Lung 62.348960523326 69.5171331358773 68.6252012251384 cerebhem 66.5447664288968 65.5524361266671 65.158769098175 cortex 61.888307287885 66.2469477994642 65.7439563940508 heart 68.9698103890176 73.5984370171725 76.0168915589876 kidney 58.9178396142262 67.5485887904636 70.6152331234316 liver 62.7420072849084 68.4656074159679 66.5416594463533 stomach 66.4961275382285 64.3345299913734 61.3432351656455 testicle 69.0501452072312 65.7932625931165 61.2504992182779 cont.diffExp=-7.16817261255126,0.992330302229604,-4.35864051157918,-4.62862662815482,-8.63074917623737,-5.72360013105947,2.16159754685516,3.2568826141147 cont.diffExpScore=1.47100007998344 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=0.759806783631455 cont.tran.correlation=0.0798791770058569 tran.covariance=0.0094661348560333 cont.tran.covariance=0.000140897661389568 tran.mean=63.0221095037619 cont.tran.mean=66.1259316964889 weightedLogRatios: wLogRatio Lung -1.10705289507542 cerebhem -1.06158630386632 cortex -0.561304769439531 heart -0.75621222983055 kidney -0.923936452206626 liver -1.1349824245798 stomach -1.77899507963485 testicle -0.849036169870976 cont.weightedLogRatios: wLogRatio Lung -0.455672899734042 cerebhem 0.0629582150628107 cortex -0.283078276872935 heart -0.277107155726387 kidney -0.566566004309753 liver -0.36514951259011 stomach 0.138157841033169 testicle 0.203441054603200 varWeightedLogRatios=0.131003254681660 cont.varWeightedLogRatios=0.0836739555121192 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.16217898220037 0.094020538786741 44.2688271723383 8.47597730180253e-155 *** df.mm.trans1 -0.162795668902674 0.0767674484563567 -2.12063409916802 0.0345784039296602 * df.mm.trans2 0.0831705810086421 0.0767674484563567 1.08340947473232 0.279290949168234 df.mm.exp2 0.438507545140574 0.104306422628414 4.20403206332493 3.24932539833349e-05 *** df.mm.exp3 -0.344600475003571 0.104306422628414 -3.30373208398865 0.00104156921279177 ** df.mm.exp4 -0.311814928198701 0.104306422628414 -2.98941254374646 0.0029708558010937 ** df.mm.exp5 -0.0636269410167052 0.104306422628414 -0.610000222549792 0.542214203075429 df.mm.exp6 0.0131251010933098 0.104306422628414 0.125832146885789 0.899929140754174 df.mm.exp7 0.0451299603439949 0.104306422628414 0.432667128320256 0.665493944473133 df.mm.exp8 -0.155128044944410 0.104306422628414 -1.48723387338329 0.137754907993408 df.mm.trans1:exp2 -0.184422698479377 0.0851658374449025 -2.16545394271134 0.030953942241424 * df.mm.trans2:exp2 -0.209780613838840 0.0851658374449025 -2.46320144476424 0.0141979951863066 * df.mm.trans1:exp3 0.399464536854181 0.0851658374449025 4.69043161951659 3.76812121899053e-06 *** df.mm.trans2:exp3 0.26717054438143 0.0851658374449025 3.13706237614671 0.00183504552430906 ** df.mm.trans1:exp4 0.24518093609766 0.0851658374449025 2.87886485301431 0.00420923938637723 ** df.mm.trans2:exp4 0.164794194036283 0.0851658374449025 1.93498002227590 0.0537099664121043 . df.mm.trans1:exp5 0.0388333511916846 0.0851658374449025 0.455973338098244 0.648661005374061 df.mm.trans2:exp5 -0.00315341515824359 0.0851658374449025 -0.0370267615848159 0.970482467880093 df.mm.trans1:exp6 -0.0545703129908197 0.0851658374449025 -0.64075355363145 0.522056254485687 df.mm.trans2:exp6 -0.0452898571526684 0.0851658374449025 -0.531784322346016 0.595175848511981 df.mm.trans1:exp7 -0.0348661662407661 0.0851658374449025 -0.409391456560532 0.682475440654817 df.mm.trans2:exp7 0.119479431682675 0.0851658374449025 1.40290326810878 0.161435197335814 df.mm.trans1:exp8 0.187989921730414 0.0851658374449025 2.20733955504204 0.0278675701962608 * df.mm.trans2:exp8 0.125193625631863 0.0851658374449024 1.46999817518212 0.142362350051414 df.mm.trans1:probe2 -0.00814284484679747 0.052153211314207 -0.156133143896726 0.876008242987275 df.mm.trans1:probe3 -0.133453134307128 0.052153211314207 -2.55886705620319 0.0108751392671673 * df.mm.trans1:probe4 -0.0145912497632585 0.052153211314207 -0.279776631113868 0.779796073684214 df.mm.trans1:probe5 -0.0230038040444335 0.052153211314207 -0.441081257793363 0.659396721780126 df.mm.trans1:probe6 -0.0649528790827914 0.052153211314207 -1.24542434580817 0.213717836107652 df.mm.trans2:probe2 0.147810559993911 0.052153211314207 2.83416028024426 0.00483168107877222 ** df.mm.trans2:probe3 -0.0627591260833032 0.052153211314207 -1.20336072318153 0.229561137610393 df.mm.trans2:probe4 -0.0352191465176607 0.052153211314207 -0.675301589876723 0.499881297719827 df.mm.trans2:probe5 -0.0275564572892793 0.052153211314207 -0.528375081704177 0.597537266650378 df.mm.trans2:probe6 0.0114292269459650 0.052153211314207 0.219147137021101 0.82664920181024 df.mm.trans3:probe2 0.0657892974522897 0.052153211314207 1.26146206138543 0.207890656562328 df.mm.trans3:probe3 -0.0196598963423508 0.052153211314207 -0.376964252956658 0.70640363107628 df.mm.trans3:probe4 0.546176610485259 0.052153211314207 10.4725403617950 8.44385718202618e-23 *** df.mm.trans3:probe5 -0.0213501392728561 0.052153211314207 -0.409373435208584 0.682488652813003 df.mm.trans3:probe6 0.522132689318975 0.052153211314207 10.0115156125916 3.63177290798424e-21 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.09921252844323 0.156069301271251 26.2653353033133 1.60622865186818e-88 *** df.mm.trans1 0.0308709552621340 0.127430050875756 0.242258047061703 0.808706589589469 df.mm.trans2 0.13999426841269 0.127430050875756 1.09859697497244 0.272616474569221 df.mm.exp2 0.0582379709682887 0.173143344079795 0.336356972182824 0.736781214291032 df.mm.exp3 -0.0127075013851386 0.173143344079795 -0.0733929534090679 0.941530764140227 df.mm.exp4 0.0556766842316801 0.173143344079795 0.321564103590496 0.747953898141017 df.mm.exp5 -0.113915200904578 0.173143344079795 -0.65792422752375 0.510972009610414 df.mm.exp6 0.0218741138479994 0.173143344079795 0.126335285738263 0.899531133564363 df.mm.exp7 0.099094905184957 0.173143344079795 0.572328700890102 0.567426555495866 df.mm.exp8 0.160718013363807 0.173143344079795 0.92823674059188 0.353854520332036 df.mm.trans1:exp2 0.00688992924346606 0.141370948451545 0.0487365283952068 0.96115402313275 df.mm.trans2:exp2 -0.116960839175768 0.141370948451545 -0.827332917101113 0.408550458236311 df.mm.trans1:exp3 0.0052917660809355 0.141370948451545 0.0374317788689749 0.970159740648727 df.mm.trans2:exp3 -0.0354763478916913 0.141370948451546 -0.250945107748575 0.80198769921522 df.mm.trans1:exp4 0.0452451936788367 0.141370948451545 0.320045908826482 0.749103611082056 df.mm.trans2:exp4 0.00137386296755769 0.141370948451546 0.00971814211198119 0.992251097698821 df.mm.trans1:exp5 0.0573121250532049 0.141370948451545 0.405402423064654 0.685402332924855 df.mm.trans2:exp5 0.085189131629294 0.141370948451545 0.60259291291727 0.547127076819985 df.mm.trans1:exp6 -0.0155899182428949 0.141370948451545 -0.110276675750239 0.912246245658636 df.mm.trans2:exp6 -0.0371158183140467 0.141370948451545 -0.262542047857648 0.793041141678352 df.mm.trans1:exp7 -0.0346981920749243 0.141370948451545 -0.24544075324512 0.806243296050096 df.mm.trans2:exp7 -0.176571646349379 0.141370948451545 -1.24899527295665 0.212410237969739 df.mm.trans1:exp8 -0.0586320309303087 0.141370948451545 -0.414738894889742 0.678559354774897 df.mm.trans2:exp8 -0.215773814607231 0.141370948451545 -1.52629530303524 0.127740696740929 df.mm.trans1:probe2 0.0233365176559713 0.0865716720398975 0.269562977196703 0.787637963311299 df.mm.trans1:probe3 0.057784884856657 0.0865716720398975 0.667480291128329 0.504857140886778 df.mm.trans1:probe4 -0.0313871940118233 0.0865716720398975 -0.36255732703601 0.71713048757339 df.mm.trans1:probe5 -0.00504599846408771 0.0865716720398975 -0.058286947048478 0.953549689365818 df.mm.trans1:probe6 -0.0127260103208387 0.0865716720398975 -0.146999705804155 0.883207632450163 df.mm.trans2:probe2 -0.00222297699646372 0.0865716720398975 -0.0256778798893850 0.97952730053157 df.mm.trans2:probe3 0.0424508485313277 0.0865716720398975 0.490354957124586 0.624156393436766 df.mm.trans2:probe4 0.101091726992122 0.0865716720398975 1.16772293534463 0.243626493435973 df.mm.trans2:probe5 -0.090350279210074 0.0865716720398975 -1.04364715479256 0.297290202899068 df.mm.trans2:probe6 -0.0225719760234102 0.0865716720398975 -0.260731663043399 0.794436011077461 df.mm.trans3:probe2 -0.109643503807134 0.0865716720398975 -1.26650555803755 0.206082268161553 df.mm.trans3:probe3 -0.0522393761303608 0.0865716720398975 -0.603423439786235 0.546575133698848 df.mm.trans3:probe4 -0.0955142996378535 0.0865716720398975 -1.10329738801666 0.270573159156063 df.mm.trans3:probe5 0.106971816294201 0.0865716720398975 1.23564456794714 0.217328808557000 df.mm.trans3:probe6 -0.0980821570200894 0.0865716720398975 -1.13295902353471 0.257922173451108