chr19.12240_chr19_5113040_5113527_+_1.R fitVsDatCorrelation=0.85248071980716 cont.fitVsDatCorrelation=0.247374673363676 fstatistic=9264.42664260182,36,324 cont.fstatistic=2690.39830890224,36,324 residuals=-0.453800710413429,-0.0790097973440696,-0.000505818290916253,0.076803161317245,0.54649146791237 cont.residuals=-0.450325338722724,-0.167119740895724,-0.0341509637437425,0.110539227913596,1.09753323699092 predictedValues: Include Exclude Both chr19.12240_chr19_5113040_5113527_+_1.R.tl.Lung 64.0445790180508 72.6978000538865 82.2841423239032 chr19.12240_chr19_5113040_5113527_+_1.R.tl.cerebhem 58.0862808428854 57.8050600455775 62.5874663342058 chr19.12240_chr19_5113040_5113527_+_1.R.tl.cortex 54.0265680643684 65.8203815642168 72.3835372296429 chr19.12240_chr19_5113040_5113527_+_1.R.tl.heart 57.4375124162803 114.235607822468 126.639240016669 chr19.12240_chr19_5113040_5113527_+_1.R.tl.kidney 61.5887656994585 62.4603356426567 66.7495104779502 chr19.12240_chr19_5113040_5113527_+_1.R.tl.liver 56.6244768367271 61.0492534619804 70.7957528218522 chr19.12240_chr19_5113040_5113527_+_1.R.tl.stomach 57.9508725568713 67.8433613167851 77.5250057293755 chr19.12240_chr19_5113040_5113527_+_1.R.tl.testicle 55.3612548339324 59.4791557574399 66.6893771806538 diffExp=-8.65322103583578,0.281220797307839,-11.7938134998484,-56.7980954061873,-0.871569943198232,-4.42477662525329,-9.89248875991385,-4.1179009235075 diffExpScore=0.995501639743409 diffExp1.5=0,0,0,-1,0,0,0,0 diffExp1.5Score=0.5 diffExp1.4=0,0,0,-1,0,0,0,0 diffExp1.4Score=0.5 diffExp1.3=0,0,0,-1,0,0,0,0 diffExp1.3Score=0.5 diffExp1.2=0,0,-1,-1,0,0,0,0 diffExp1.2Score=0.666666666666667 cont.predictedValues: Include Exclude Both Lung 64.9514631249098 74.289965699925 64.7569772749825 cerebhem 65.4581582342072 62.8577411768669 64.6730703319932 cortex 68.5567958435882 66.255026243951 74.6543475690447 heart 63.9142321433579 62.9410251991171 61.429566977455 kidney 69.0478392526896 64.4185408687267 61.6401264477049 liver 64.117259967778 67.0139885517674 65.8897580172864 stomach 64.0261346873721 63.6285318355415 68.315496491507 testicle 66.0768172087096 71.2894836984309 72.4693865131618 cont.diffExp=-9.33850257501521,2.60041705734028,2.30176959963724,0.973206944240737,4.62929838396293,-2.89672858398946,0.397602851830612,-5.21266648972124 cont.diffExpScore=3.75718059817907 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=0.0473395822536605 cont.tran.correlation=-0.008670244756375 tran.covariance=0.00104204043648890 cont.tran.covariance=9.65011610704852e-06 tran.mean=64.156954120849 cont.tran.mean=66.1776877335587 weightedLogRatios: wLogRatio Lung -0.535181180907003 cerebhem 0.0197015389980632 cortex -0.807230403797882 heart -3.02149278056362 kidney -0.0580007268289389 liver -0.306530843984120 stomach -0.652236079611323 testicle -0.290553372537424 cont.weightedLogRatios: wLogRatio Lung -0.569691589823477 cerebhem 0.168680389634017 cortex 0.143796631470528 heart 0.0636751166778286 kidney 0.291478969992677 liver -0.184829010540497 stomach 0.025890366331635 testicle -0.321095161893545 varWeightedLogRatios=0.954648539430071 cont.varWeightedLogRatios=0.083196890654972 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.78970178194074 0.0779875673585978 48.5936657636103 7.66239051702169e-151 *** df.mm.trans1 0.332999283092486 0.0660546548836792 5.04126898670337 7.70835961593138e-07 *** df.mm.trans2 0.473832333091523 0.0660546548836792 7.17333750249595 5.00556220990036e-12 *** df.mm.exp2 -0.0532713217242364 0.0919891158969077 -0.579104616941179 0.562920971860251 df.mm.exp3 -0.141285523616190 0.0919891158969078 -1.53589391786881 0.125540330148922 df.mm.exp4 -0.0880938509764256 0.0919891158969077 -0.957655154280996 0.338950709729328 df.mm.exp5 0.0183521371110981 0.0919891158969077 0.199503353545275 0.841994167163883 df.mm.exp6 -0.147388797417027 0.0919891158969077 -1.60224169979203 0.110076612533925 df.mm.exp7 -0.109515477944857 0.0919891158969077 -1.19052647562773 0.234711053740503 df.mm.exp8 -0.136251875718623 0.0919891158969077 -1.48117388008513 0.139532062291297 df.mm.trans1:exp2 -0.0443785604121477 0.079664911238393 -0.557065334314467 0.577867395617337 df.mm.trans2:exp2 -0.175963485862880 0.079664911238393 -2.20879535453593 0.0278884240500573 * df.mm.trans1:exp3 -0.0288179376607667 0.079664911238393 -0.361739405878838 0.717782572756464 df.mm.trans2:exp3 0.0419039407260028 0.079664911238393 0.526002478062235 0.599246326881538 df.mm.trans1:exp4 -0.0207879207777498 0.079664911238393 -0.260941993841467 0.794303017046262 df.mm.trans2:exp4 0.540045778421592 0.079664911238393 6.77896667461957 5.73580151716434e-11 *** df.mm.trans1:exp5 -0.0574520462530932 0.079664911238393 -0.721171283065527 0.471324189157157 df.mm.trans2:exp5 -0.170131535023739 0.079664911238393 -2.13558933762732 0.0334623775986187 * df.mm.trans1:exp6 0.0242507540507129 0.079664911238393 0.304409478071768 0.76101137168758 df.mm.trans2:exp6 -0.0272413538808394 0.079664911238393 -0.341949215248870 0.732610801694881 df.mm.trans1:exp7 0.00953171664114105 0.079664911238393 0.119647615154154 0.90483645303819 df.mm.trans2:exp7 0.0404058924382767 0.079664911238393 0.507198110311882 0.612360856394446 df.mm.trans1:exp8 -0.0094475344712735 0.079664911238393 -0.118590911913556 0.905672955737256 df.mm.trans2:exp8 -0.0644333199865676 0.079664911238393 -0.808804265076683 0.419221244619656 df.mm.trans1:probe2 -0.0359806406334034 0.0398324556191965 -0.90329958507663 0.367038002669244 df.mm.trans1:probe3 0.260020436570961 0.0398324556191965 6.52785354377321 2.57459171380336e-10 *** df.mm.trans1:probe4 0.0168039414801725 0.0398324556191965 0.421865567135011 0.673402915400747 df.mm.trans1:probe5 0.0235543608126225 0.0398324556191965 0.591335895476926 0.554707709055443 df.mm.trans1:probe6 0.0675068088335871 0.0398324556191965 1.69476894618200 0.091080094785739 . df.mm.trans2:probe2 0.162541250843645 0.0398324556191965 4.08062340915059 5.66108581662538e-05 *** df.mm.trans2:probe3 0.0548603004464728 0.0398324556191965 1.37727638413620 0.16937753179646 df.mm.trans2:probe4 -0.00354342919241225 0.0398324556191965 -0.0889583415666836 0.92916997878531 df.mm.trans2:probe5 0.0356319018374754 0.0398324556191965 0.894544443308268 0.371694691993129 df.mm.trans2:probe6 -0.0444969479521848 0.0398324556191965 -1.11710280625381 0.264778066845367 df.mm.trans3:probe2 -0.254948299510850 0.0398324556191965 -6.4005167531771 5.42701370908547e-10 *** df.mm.trans3:probe3 -0.304116671596806 0.0398324556191965 -7.6348963896226 2.55826444136582e-13 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.26343681556679 0.144547973830163 29.4949607566007 8.93224730254596e-94 *** df.mm.trans1 -0.111561322469127 0.122430623865765 -0.911220730129126 0.362856523157792 df.mm.trans2 0.0575974703067258 0.122430623865765 0.470449863670356 0.638350177490243 df.mm.exp2 -0.158034371123939 0.170499488157969 -0.926890589709687 0.354673262308946 df.mm.exp3 -0.202669603058299 0.170499488157969 -1.18868159223167 0.235435488157227 df.mm.exp4 -0.129125733607205 0.170499488157969 -0.757337954513795 0.449397833296086 df.mm.exp5 -0.0320866909612645 0.170499488157969 -0.188192300797619 0.850843719553197 df.mm.exp6 -0.133342745838027 0.170499488157969 -0.7820712383282 0.434743866123764 df.mm.exp7 -0.222758000778948 0.170499488157969 -1.30650246042124 0.192308390946370 df.mm.exp8 -0.136572141885631 0.170499488157969 -0.801012034470721 0.423711678788761 df.mm.trans1:exp2 0.165805234252006 0.147656888077045 1.12290890327779 0.262307572228800 df.mm.trans2:exp2 -0.00906742379995336 0.147656888077045 -0.0614087423759204 0.951071552863922 df.mm.trans1:exp3 0.256691871380228 0.147656888077045 1.73843479111039 0.083084195682726 . df.mm.trans2:exp3 0.0882050414215678 0.147656888077045 0.597364894860467 0.550681028719191 df.mm.trans1:exp4 0.113027525633981 0.147656888077045 0.76547411438744 0.444546518332163 df.mm.trans2:exp4 -0.036651977832926 0.147656888077045 -0.248223962391796 0.804118376967517 df.mm.trans1:exp5 0.0932460080189658 0.147656888077045 0.631504626931536 0.528155903593341 df.mm.trans2:exp5 -0.110487707134330 0.147656888077045 -0.748273301525079 0.454838130577276 df.mm.trans1:exp6 0.120416069981688 0.147656888077045 0.815512717014983 0.415377979477711 df.mm.trans2:exp6 0.0302682363328443 0.147656888077045 0.204990344351906 0.837708389169842 df.mm.trans1:exp7 0.208409085469512 0.147656888077045 1.41144167524896 0.159073981462735 df.mm.trans2:exp7 0.0678440928358643 0.147656888077045 0.459471235777801 0.64620393396226 df.mm.trans1:exp8 0.153749834405294 0.147656888077045 1.04126422009564 0.298529292229047 df.mm.trans2:exp8 0.0953450732585014 0.147656888077045 0.645720457069039 0.51891745019627 df.mm.trans1:probe2 0.0950359389108281 0.0738284440385225 1.28725371567143 0.198924672278160 df.mm.trans1:probe3 0.0367781502726136 0.0738284440385225 0.498156919756068 0.618711413038797 df.mm.trans1:probe4 -0.0269651707426322 0.0738284440385225 -0.365240946003985 0.71516986649946 df.mm.trans1:probe5 0.0884103618287826 0.0738284440385225 1.19751083718697 0.2319828601919 df.mm.trans1:probe6 0.00262371009906146 0.0738284440385225 0.0355379303089803 0.971672685756181 df.mm.trans2:probe2 -0.0565987855395727 0.0738284440385225 -0.766625739938937 0.443862276689256 df.mm.trans2:probe3 0.0131910487696860 0.0738284440385225 0.178671634509906 0.858307212490332 df.mm.trans2:probe4 -0.00628148587132869 0.0738284440385225 -0.0850821922787795 0.93224859656882 df.mm.trans2:probe5 -0.0116599429332972 0.0738284440385225 -0.157932936081020 0.8746080274884 df.mm.trans2:probe6 -0.056176384160958 0.0738284440385225 -0.760904349164476 0.447267609660334 df.mm.trans3:probe2 -0.0441350658024845 0.0738284440385225 -0.597805715361623 0.550387179068615 df.mm.trans3:probe3 -0.0723594686601393 0.0738284440385225 -0.980102853344482 0.327766613237658