chr1.369_chr1_135274451_135275365_+_1.R fitVsDatCorrelation=0.904723619018172 cont.fitVsDatCorrelation=0.309433342918534 fstatistic=10490.7901798777,36,324 cont.fstatistic=2098.21495260054,36,324 residuals=-0.447373863037183,-0.0611118983673754,0.000453218123137809,0.069978767242903,0.420631028698747 cont.residuals=-0.514155106008028,-0.152703762710334,-0.0426502173936051,0.0648308163179381,1.28299201697121 predictedValues: Include Exclude Both chr1.369_chr1_135274451_135275365_+_1.R.tl.Lung 53.2300992784209 54.5496847554916 76.7322920611755 chr1.369_chr1_135274451_135275365_+_1.R.tl.cerebhem 58.6756331019061 69.7936569457049 58.2245020135026 chr1.369_chr1_135274451_135275365_+_1.R.tl.cortex 49.3973713890875 56.3628276436673 63.8971196805803 chr1.369_chr1_135274451_135275365_+_1.R.tl.heart 51.5699665445129 60.3628262101784 75.5308114543544 chr1.369_chr1_135274451_135275365_+_1.R.tl.kidney 50.1349487787468 56.3962903864992 70.9728867900844 chr1.369_chr1_135274451_135275365_+_1.R.tl.liver 48.0495415815867 60.3965686989682 67.7481512683427 chr1.369_chr1_135274451_135275365_+_1.R.tl.stomach 52.990684164824 61.6462715555523 63.1763628932207 chr1.369_chr1_135274451_135275365_+_1.R.tl.testicle 52.3253703462853 57.0648017841017 70.2328039046106 diffExp=-1.31958547707068,-11.1180238437988,-6.96545625457977,-8.7928596656655,-6.26134160775246,-12.3470271173815,-8.65558739072834,-4.73943143781636 diffExpScore=0.983659947239063 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,-1,0,0 diffExp1.2Score=0.5 cont.predictedValues: Include Exclude Both Lung 54.1965305157312 70.3119547747133 55.8540290885761 cerebhem 56.5045808896498 55.9025669779177 57.2191038034506 cortex 57.7882369088946 52.8623652338926 56.7050234488754 heart 57.9009570301531 53.8302218344486 52.3777029062311 kidney 52.7420487197337 56.5632960291388 56.1945757149832 liver 61.1106247486549 55.9817756102028 71.0862990129837 stomach 59.5965605276281 63.1272085399109 59.7580226720792 testicle 59.5190138416238 61.2514065950624 51.9822979920499 cont.diffExp=-16.1154242589821,0.602013911732165,4.92587167500193,4.07073519570453,-3.82124730940514,5.12884913845209,-3.53064801228280,-1.73239275343860 cont.diffExpScore=3.48032937388044 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=-1,0,0,0,0,0,0,0 cont.diffExp1.2Score=0.5 tran.correlation=0.679395836792821 cont.tran.correlation=-0.21072666065622 tran.covariance=0.00301109790287249 cont.tran.covariance=-0.000948145578048738 tran.mean=55.8091589478459 cont.tran.mean=58.0743342985848 weightedLogRatios: wLogRatio Lung -0.0976301079321177 cerebhem -0.721626345113222 cortex -0.523146228815362 heart -0.633145446811383 kidney -0.467628660275299 liver -0.911730204185391 stomach -0.612110495227469 testicle -0.346896946910609 cont.weightedLogRatios: wLogRatio Lung -1.07326230871681 cerebhem 0.0431559170794075 cortex 0.357464718604319 heart 0.293219952950655 kidney -0.27981612175655 liver 0.356674042699718 stomach -0.236913882879189 testicle -0.117651467706749 varWeightedLogRatios=0.0605063447716528 cont.varWeightedLogRatios=0.227002790414875 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 2.92596683609214 0.071088811670832 41.1593156127081 9.81819255988552e-131 *** df.mm.trans1 1.05909401443442 0.0602114808815098 17.5895692802940 4.34269358870191e-49 *** df.mm.trans2 1.02301878887372 0.0602114808815098 16.9904273054988 9.66740485104493e-47 *** df.mm.exp2 0.619848091641516 0.0838517876277964 7.39218696675753 1.24131525853356e-12 *** df.mm.exp3 0.141019475953574 0.0838517876277964 1.68177065681099 0.0935768524558193 . df.mm.exp4 0.0853589349445188 0.0838517876277964 1.01797394378057 0.309449868411849 df.mm.exp5 0.0514104924372258 0.0838517876277964 0.61311146597647 0.540232773465354 df.mm.exp6 0.123954408785720 0.0838517876277964 1.47825600732487 0.140310730056572 df.mm.exp7 0.312185343449736 0.0838517876277964 3.72306127611105 0.00023204128541319 *** df.mm.exp8 0.116440039618656 0.0838517876277964 1.38864111204776 0.165895772737634 df.mm.trans1:exp2 -0.522447572252465 0.0726177782384093 -7.19448577092557 4.38005709239692e-12 *** df.mm.trans2:exp2 -0.373416893967223 0.0726177782384093 -5.14222416363757 4.7081161796275e-07 *** df.mm.trans1:exp3 -0.215746276189575 0.0726177782384094 -2.97098426064846 0.00319039489079564 ** df.mm.trans2:exp3 -0.108321552334571 0.0726177782384094 -1.49166712287648 0.136759414479392 df.mm.trans1:exp4 -0.117043487888108 0.0726177782384094 -1.61177456440275 0.107984655519926 df.mm.trans2:exp4 0.0159025871652461 0.0726177782384093 0.218990274158991 0.826795508482702 df.mm.trans1:exp5 -0.111316159395342 0.0726177782384093 -1.53290505569977 0.126275080675194 df.mm.trans2:exp5 -0.0181190426467003 0.0726177782384094 -0.249512489726885 0.803122491841639 df.mm.trans1:exp6 -0.226345826127493 0.0726177782384093 -3.11694782762954 0.00199098759351752 ** df.mm.trans2:exp6 -0.0221340483397187 0.0726177782384094 -0.304802059174147 0.76071260847677 df.mm.trans1:exp7 -0.316693228088992 0.0726177782384094 -4.36109773352285 1.74099615702188e-05 *** df.mm.trans2:exp7 -0.189884526536149 0.0726177782384093 -2.61484902378511 0.00934396094549645 ** df.mm.trans1:exp8 -0.133582705770908 0.0726177782384093 -1.83953170988441 0.0667517696777066 . df.mm.trans2:exp8 -0.0713644773913136 0.0726177782384094 -0.98274112927304 0.326468128044851 df.mm.trans1:probe2 -0.104169019425108 0.0363088891192047 -2.86896740583589 0.00438846564467697 ** df.mm.trans1:probe3 -0.0340803974063316 0.0363088891192047 -0.938624073417484 0.348622967470463 df.mm.trans1:probe4 0.0239548870797140 0.0363088891192047 0.659752684833414 0.509881244358076 df.mm.trans1:probe5 -0.0312821266906406 0.0363088891192047 -0.861555598353316 0.389569279280261 df.mm.trans1:probe6 0.0516451121056398 0.0363088891192047 1.42238204909231 0.155877370913586 df.mm.trans2:probe2 0.0209347323494646 0.0363088891192047 0.576573198941296 0.56462814444146 df.mm.trans2:probe3 0.154552023772927 0.0363088891192047 4.25658915825053 2.72157321573972e-05 *** df.mm.trans2:probe4 0.0499745743170445 0.0363088891192047 1.37637299100433 0.169656644848517 df.mm.trans2:probe5 0.203942006127479 0.0363088891192047 5.61686163016232 4.18883928269288e-08 *** df.mm.trans2:probe6 0.0217334380921375 0.0363088891192047 0.598570725223375 0.54987740990461 df.mm.trans3:probe2 -0.990190039824788 0.0363088891192047 -27.2712843561235 6.64170736516574e-86 *** df.mm.trans3:probe3 -1.01308096582548 0.0363088891192047 -27.9017339941044 3.66325017167679e-88 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.19592545483976 0.158685463667388 26.4417758115174 6.68836198691052e-83 *** df.mm.trans1 -0.225868255133616 0.134404930075695 -1.68050573000863 0.0938227411490376 . df.mm.trans2 0.03589945397548 0.134404930075695 0.267099234791922 0.789562685422941 df.mm.exp2 -0.211772880311779 0.187175161411732 -1.13141550788322 0.258716973830946 df.mm.exp3 -0.236202976753191 0.187175161411732 -1.26193547782556 0.207879672621978 df.mm.exp4 -0.136729084334818 0.187175161411732 -0.730487332312502 0.46562022459528 df.mm.exp5 -0.250863981752906 0.187175161411732 -1.34026320512195 0.181098871287264 df.mm.exp6 -0.348999741229499 0.187175161411732 -1.86456225600254 0.0631468229470124 . df.mm.exp7 -0.0803707832344757 0.187175161411732 -0.429388080278893 0.667926218749206 df.mm.exp8 0.0275623307841068 0.187175161411732 0.147254211382660 0.883022960717855 df.mm.trans1:exp2 0.253477699098652 0.162098444740013 1.56372690376642 0.118857880643257 df.mm.trans2:exp2 -0.0175586577420041 0.162098444740013 -0.108320951321687 0.913808153244124 df.mm.trans1:exp3 0.300371324261036 0.162098444740013 1.85301792835087 0.0647888590049445 . df.mm.trans2:exp3 -0.0490472078756146 0.162098444740013 -0.302576671566964 0.762406652532405 df.mm.trans1:exp4 0.202846104023533 0.162098444740013 1.25137600393930 0.211700084791465 df.mm.trans2:exp4 -0.130377700135372 0.162098444740013 -0.804311851014258 0.42180664972822 df.mm.trans1:exp5 0.223660113804649 0.162098444740013 1.37977951709144 0.168605969343891 df.mm.trans2:exp5 0.0332824385038732 0.162098444740013 0.205322380219344 0.837449196446918 df.mm.trans1:exp6 0.469068589657931 0.162098444740013 2.89372665117338 0.00406498748660062 ** df.mm.trans2:exp6 0.121084105413435 0.162098444740013 0.746978822700242 0.455618062822992 df.mm.trans1:exp7 0.175351752600731 0.162098444740013 1.08176085761942 0.280163272364254 df.mm.trans2:exp7 -0.0274191810646435 0.162098444740013 -0.169151413566124 0.865783100074575 df.mm.trans1:exp8 0.0661165973105443 0.162098444740013 0.407879282349609 0.683631694452304 df.mm.trans2:exp8 -0.165517354859098 0.162098444740013 -1.02109156645253 0.307972865943723 df.mm.trans1:probe2 0.0174512633488450 0.0810492223700065 0.215316851149741 0.829655765677215 df.mm.trans1:probe3 0.0335528543449303 0.0810492223700065 0.413981200112626 0.679161783437533 df.mm.trans1:probe4 0.101990827553779 0.0810492223700065 1.25838132151558 0.209159916121394 df.mm.trans1:probe5 0.0583154414869397 0.0810492223700065 0.719506489781206 0.472347559370489 df.mm.trans1:probe6 -0.0082731401433782 0.0810492223700065 -0.102075503027156 0.918759888343523 df.mm.trans2:probe2 -0.00630969869925798 0.0810492223700064 -0.0778502065134309 0.937995263074486 df.mm.trans2:probe3 0.136465976430350 0.0810492223700065 1.68374195877357 0.0931946873419824 . df.mm.trans2:probe4 0.0454120723287469 0.0810492223700064 0.560302381698758 0.575660408680891 df.mm.trans2:probe5 0.0146033421187257 0.0810492223700065 0.180178682678267 0.857124933100811 df.mm.trans2:probe6 -0.000119329034317924 0.0810492223700065 -0.00147230326002589 0.998826178461647 df.mm.trans3:probe2 0.0432277089500101 0.0810492223700065 0.533351310302111 0.594156081845647 df.mm.trans3:probe3 0.00712732248189893 0.0810492223700065 0.0879381969806105 0.929980123647718