chr11.4086_chr11_107542110_107551316_+_2.R fitVsDatCorrelation=0.784178535905945 cont.fitVsDatCorrelation=0.296310981316139 fstatistic=11103.9017656312,39,393 cont.fstatistic=4681.43182702446,39,393 residuals=-0.351294891366901,-0.0713529238486013,-0.00729510828551841,0.0693275199933427,0.728405845010634 cont.residuals=-0.380127238416742,-0.125384616305247,-0.0264780585967388,0.090561001446665,1.02740064962589 predictedValues: Include Exclude Both chr11.4086_chr11_107542110_107551316_+_2.R.tl.Lung 49.6827451124052 44.5696124595764 57.1851737524088 chr11.4086_chr11_107542110_107551316_+_2.R.tl.cerebhem 52.9100246178212 44.9231876900383 60.4146746378152 chr11.4086_chr11_107542110_107551316_+_2.R.tl.cortex 49.4566843374344 43.7057401558922 51.7687556521517 chr11.4086_chr11_107542110_107551316_+_2.R.tl.heart 47.5795470318885 48.0010814342361 54.6905062362934 chr11.4086_chr11_107542110_107551316_+_2.R.tl.kidney 47.8078732933722 44.2378635795886 55.9176996732229 chr11.4086_chr11_107542110_107551316_+_2.R.tl.liver 49.4451331784632 49.9069736143501 57.3667064638178 chr11.4086_chr11_107542110_107551316_+_2.R.tl.stomach 47.7542886194456 45.8818530379958 57.858293490722 chr11.4086_chr11_107542110_107551316_+_2.R.tl.testicle 48.50196268934 45.5641085908095 56.4729718835308 diffExp=5.1131326528288,7.98683692778288,5.75094418154215,-0.421534402347667,3.57000971378358,-0.461840435886913,1.87243558144986,2.93785409853054 diffExpScore=1.02803693906488 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 48.1205725537455 49.985187018395 47.4437305227858 cerebhem 49.5510619881261 50.840278888477 50.0317187848536 cortex 52.3620878366499 47.2070677757412 52.3072301208493 heart 51.657283103164 51.8373100329502 51.9846085057886 kidney 52.5534397123077 46.5000239219462 52.6522000407597 liver 49.350536155265 49.5275027332395 49.8656010421922 stomach 47.0363019474861 52.8607219466818 54.0725691964047 testicle 48.3421565476122 47.6641742764992 49.1638083945184 cont.diffExp=-1.8646144646495,-1.2892169003509,5.1550200609087,-0.180026929786173,6.05341579036143,-0.176966577974511,-5.8244199991957,0.677982271113002 cont.diffExpScore=5.97595822501538 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=-0.183613436344425 cont.tran.correlation=-0.529002229273389 tran.covariance=-0.000291569120842793 cont.tran.covariance=-0.00102235288730607 tran.mean=47.4955424651661 cont.tran.mean=49.7122316523929 weightedLogRatios: wLogRatio Lung 0.41827795005274 cerebhem 0.636026676619696 cortex 0.474604283212200 heart -0.0341074423110544 kidney 0.297118237730477 liver -0.0363099787698675 stomach 0.15383968148479 testicle 0.24058584729822 cont.weightedLogRatios: wLogRatio Lung -0.147989128583144 cerebhem -0.100579447308291 cortex 0.404852329605139 heart -0.0137292913944661 kidney 0.477351652551023 liver -0.0139626769940672 stomach -0.456373974804098 testicle 0.0546771669114961 varWeightedLogRatios=0.0570304756454429 cont.varWeightedLogRatios=0.0900318111282967 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.46265061269083 0.0643090142908738 53.8439385344804 1.75712901145152e-183 *** df.mm.trans1 0.464515055872936 0.0525080902913307 8.84654256697714 3.09857715598664e-17 *** df.mm.trans2 0.335324185522113 0.0525080902913307 6.38614323357854 4.80801065818181e-10 *** df.mm.exp2 0.0158995610943547 0.0713444456923975 0.22285632665654 0.82376310820563 df.mm.exp3 0.0753745560501304 0.0713444456923975 1.0564880744201 0.291394284777993 df.mm.exp4 0.0755210722873998 0.0713444456923975 1.05854172044464 0.290458721307792 df.mm.exp5 -0.0235248765726369 0.0713444456923975 -0.329736622722737 0.741774657469281 df.mm.exp6 0.105144951532246 0.0713444456923975 1.47376506344418 0.141345376881880 df.mm.exp7 -0.0222735673459387 0.0713444456923975 -0.312197636827560 0.755055902879527 df.mm.exp8 0.0105471101331276 0.0713444456923975 0.147833654473980 0.882549865194019 df.mm.trans1:exp2 0.0470355691144169 0.0582524959760264 0.807442982937148 0.419899731262028 df.mm.trans2:exp2 -0.00799776185257364 0.0582524959760264 -0.137294749668153 0.890868130448903 df.mm.trans1:exp3 -0.0799350254420553 0.0582524959760264 -1.37221631627514 0.170778803145935 df.mm.trans2:exp3 -0.0949474007177586 0.0582524959760264 -1.62992845417017 0.103917805638041 df.mm.trans1:exp4 -0.118775779579207 0.0582524959760264 -2.03898180823167 0.0421204698865437 * df.mm.trans2:exp4 -0.00134982357816116 0.0582524959760264 -0.0231719440608463 0.981524878549838 df.mm.trans1:exp5 -0.0149424762276731 0.0582524959760264 -0.256512205654203 0.797689583064489 df.mm.trans2:exp5 0.0160536491952429 0.0582524959760264 0.275587319071267 0.783009894197825 df.mm.trans1:exp6 -0.109939009331620 0.0582524959760264 -1.88728409812457 0.0598588051798442 . df.mm.trans2:exp6 0.00796350142666189 0.0582524959760264 0.136706613051211 0.891332705684353 df.mm.trans1:exp7 -0.0173152477250022 0.0582524959760264 -0.297244734923087 0.766436720815537 df.mm.trans2:exp7 0.0512909557634951 0.0582524959760264 0.880493700812472 0.379130035904733 df.mm.trans1:exp8 -0.034600537171493 0.0582524959760264 -0.593975186672391 0.552870446937157 df.mm.trans2:exp8 0.0115209123358418 0.0582524959760264 0.197775428207972 0.84332302750635 df.mm.trans1:probe2 -0.131397601980194 0.0356722228461988 -3.68347110149869 0.000262297430403847 *** df.mm.trans1:probe3 0.0519685114175727 0.0356722228461988 1.45683412109292 0.145960669893671 df.mm.trans1:probe4 -0.134655572390348 0.0356722228461988 -3.77480183870002 0.000184849499817110 *** df.mm.trans1:probe5 -0.013391579830135 0.0356722228461988 -0.375406373969824 0.707560795708046 df.mm.trans1:probe6 -0.0306194761687411 0.0356722228461988 -0.858356270669124 0.391218961465529 df.mm.trans2:probe2 0.03923017685816 0.0356722228461988 1.09974018236266 0.272118538481819 df.mm.trans2:probe3 -0.0312583805782262 0.0356722228461988 -0.876266688313682 0.381420351169112 df.mm.trans2:probe4 0.0434098486328894 0.0356722228461988 1.21690898882448 0.224369118688227 df.mm.trans2:probe5 -0.00623631783345376 0.0356722228461988 -0.174822798689662 0.861308902330416 df.mm.trans2:probe6 -0.0562154037373657 0.0356722228461988 -1.57588732218172 0.115856378224656 df.mm.trans3:probe2 0.055313029051034 0.0356722228461988 1.55059103800503 0.121804608999796 df.mm.trans3:probe3 -0.335081266842258 0.0356722228461988 -9.3933385728993 4.81990116341433e-19 *** df.mm.trans3:probe4 -0.415461535984255 0.0356722228461988 -11.6466399578048 3.91948984936835e-27 *** df.mm.trans3:probe5 -0.256776211307227 0.0356722228461988 -7.1982116846018 3.12162557525092e-12 *** df.mm.trans3:probe6 -0.345165151503300 0.0356722228461988 -9.67602027469618 5.27518401099947e-20 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.99437558863583 0.0989806650281145 40.3551096317778 7.63690898321992e-142 *** df.mm.trans1 -0.103594281528455 0.080817374573408 -1.28183180999475 0.200657344977320 df.mm.trans2 -0.0879145800389017 0.080817374573408 -1.08781781767790 0.277342219573660 df.mm.exp2 -0.00685665801877014 0.109809188627198 -0.0624415689114005 0.95024293661918 df.mm.exp3 -0.0703002706004482 0.109809188627198 -0.640203898046436 0.522413114370596 df.mm.exp4 0.0159015676604537 0.109809188627198 0.144810902067945 0.884934409166711 df.mm.exp5 -0.08831674878616 0.109809188627198 -0.804274668543408 0.42172460408905 df.mm.exp6 -0.0337467540993072 0.109809188627198 -0.30732176898126 0.758761253859997 df.mm.exp7 -0.0976388692928177 0.109809188627198 -0.889168479555039 0.374456467199747 df.mm.exp8 -0.078565815545664 0.109809188627198 -0.715475786023656 0.474739947214386 df.mm.trans1:exp2 0.0361505617289406 0.0896588270685545 0.403201368018113 0.687019358211434 df.mm.trans2:exp2 0.0238188880337575 0.0896588270685545 0.265661383407851 0.79063930997384 df.mm.trans1:exp3 0.154773296004134 0.0896588270685545 1.72624716455182 0.085088866420526 . df.mm.trans2:exp3 0.0131171910908670 0.0896588270685546 0.146301167656781 0.883758658477333 df.mm.trans1:exp4 0.0550198372455573 0.0896588270685545 0.613657785233888 0.53979650748449 df.mm.trans2:exp4 0.020481891338267 0.0896588270685546 0.228442552818656 0.819421029182738 df.mm.trans1:exp5 0.176437510465021 0.0896588270685545 1.96787663004016 0.0497849313891458 * df.mm.trans2:exp5 0.0160428739273033 0.0896588270685545 0.178932453745315 0.858082947742818 df.mm.trans1:exp6 0.058985594768943 0.0896588270685545 0.65788943149838 0.51099434614571 df.mm.trans2:exp6 0.0245481782494594 0.0896588270685545 0.27379544270292 0.78438566707702 df.mm.trans1:exp7 0.0748487652383368 0.0896588270685545 0.834817582223178 0.404327608512167 df.mm.trans2:exp7 0.153572734185685 0.0896588270685545 1.71285682856705 0.0875275952469413 . df.mm.trans1:exp8 0.0831600124064003 0.0896588270685545 0.92751617576722 0.354227866932557 df.mm.trans2:exp8 0.031019165962298 0.0896588270685545 0.345968902075646 0.729551217332044 df.mm.trans1:probe2 -0.0695506982933027 0.0549045943135988 -1.26675552679708 0.205992939006173 df.mm.trans1:probe3 -0.0124038911300513 0.0549045943135988 -0.225917180249142 0.821383278758029 df.mm.trans1:probe4 -0.0207999671585091 0.0549045943135988 -0.378838372608781 0.705012470937182 df.mm.trans1:probe5 -0.0486372371773595 0.0549045943135988 -0.885850041975687 0.376240048238027 df.mm.trans1:probe6 -0.0534664176183482 0.0549045943135988 -0.973805895240093 0.330751920896868 df.mm.trans2:probe2 9.9441772771557e-05 0.0549045943135988 0.00181117398306552 0.998555812016952 df.mm.trans2:probe3 0.0462020960628351 0.0549045943135988 0.841497813442394 0.400580850268916 df.mm.trans2:probe4 -0.0108292771228509 0.0549045943135988 -0.197238086506882 0.84374319506983 df.mm.trans2:probe5 0.0306891251218426 0.0549045943135988 0.558953681481652 0.576511689106234 df.mm.trans2:probe6 -0.00297306616788028 0.0549045943135988 -0.0541496791852974 0.956843427637593 df.mm.trans3:probe2 -0.00745063932601762 0.0549045943135988 -0.135701564125249 0.89212669088045 df.mm.trans3:probe3 0.103028659820111 0.0549045943135988 1.87650343487909 0.0613269831723785 . df.mm.trans3:probe4 0.0551586346137029 0.0549045943135988 1.00462694066462 0.315694668652116 df.mm.trans3:probe5 0.140096089678168 0.0549045943135988 2.55162780874003 0.0110998459803606 * df.mm.trans3:probe6 0.0492332223036889 0.0549045943135988 0.89670496466076 0.370425322277603