chr16.9287_chr16_20450957_20452194_-_1.R fitVsDatCorrelation=0.884066188531433 cont.fitVsDatCorrelation=0.25674619640633 fstatistic=10074.2451497154,38,370 cont.fstatistic=2348.31642543289,38,370 residuals=-0.347965202114131,-0.0810798619711514,-0.0110619594582540,0.0806474798610756,0.731596901197694 cont.residuals=-0.440280008612127,-0.161072224804568,-0.0405432790719833,0.0901588483322734,1.65237753053398 predictedValues: Include Exclude Both chr16.9287_chr16_20450957_20452194_-_1.R.tl.Lung 70.928265440252 63.776510534672 76.6498952337454 chr16.9287_chr16_20450957_20452194_-_1.R.tl.cerebhem 73.0657781665109 62.2152507436342 95.5538258557143 chr16.9287_chr16_20450957_20452194_-_1.R.tl.cortex 69.6514873109113 59.3795975585821 87.095027961021 chr16.9287_chr16_20450957_20452194_-_1.R.tl.heart 67.7826645317147 59.9991075784501 67.6703495584104 chr16.9287_chr16_20450957_20452194_-_1.R.tl.kidney 78.739549057558 67.0595730158322 70.9612980397704 chr16.9287_chr16_20450957_20452194_-_1.R.tl.liver 81.0767404833215 66.888797052481 76.5190463378801 chr16.9287_chr16_20450957_20452194_-_1.R.tl.stomach 66.2189742437654 62.425955700312 77.6172580415719 chr16.9287_chr16_20450957_20452194_-_1.R.tl.testicle 75.3342662577344 64.0076379543847 72.3756164991201 diffExp=7.15175490558002,10.8505274228767,10.2718897523291,7.78355695326459,11.6799760417257,14.1879434308405,3.79301854345335,11.3266283033497 diffExpScore=0.987186927854247 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 64.9497977183108 69.8088624238003 72.6752733976834 cerebhem 75.353706266861 66.1627934779805 68.5426800029288 cortex 66.0725441989271 73.5863484041438 67.1495565503161 heart 68.146535241073 68.5702735845856 71.0385320582737 kidney 69.9161166466131 68.2746862375907 67.6681559960831 liver 63.5327366208541 68.5868144460475 60.7612808844722 stomach 74.4897591105389 68.7072814945053 62.9964327116763 testicle 59.4402891182184 73.8996876327838 70.9325267654 cont.diffExp=-4.85906470548952,9.19091278888045,-7.51380420521672,-0.423738343512568,1.64143040902241,-5.05407782519342,5.78247761603357,-14.4593985145653 cont.diffExpScore=2.93046626773691 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,-1 cont.diffExp1.2Score=0.5 tran.correlation=0.842713169197601 cont.tran.correlation=-0.725600956051445 tran.covariance=0.00264671182749071 cont.tran.covariance=-0.00224413019904234 tran.mean=68.0343847268823 cont.tran.mean=68.7186395389271 weightedLogRatios: wLogRatio Lung 0.447299381969754 cerebhem 0.676956945868524 cortex 0.664336701413342 heart 0.506852354756956 kidney 0.688156173168164 liver 0.827016649817411 stomach 0.24558625091935 testicle 0.690910918675416 cont.weightedLogRatios: wLogRatio Lung -0.303713575033572 cerebhem 0.553748838364883 cortex -0.457170562472597 heart -0.0261884172200273 kidney 0.100621316741869 liver -0.320710355475594 stomach 0.345064513044694 testicle -0.913151452204065 varWeightedLogRatios=0.0335554168767034 cont.varWeightedLogRatios=0.220576091312174 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.42820696614695 0.0731745694305182 60.5156545588107 5.38855117425348e-194 *** df.mm.trans1 -0.0792847944017693 0.0602621711445787 -1.31566441925154 0.189101328750616 df.mm.trans2 -0.253069955303300 0.0602621711445788 -4.19948286788646 3.35537216181505e-05 *** df.mm.exp2 -0.215535176542929 0.0823767158208142 -2.61645750738304 0.00924879403165517 ** df.mm.exp3 -0.217350782983332 0.0823767158208142 -2.63849779415961 0.0086791443542866 ** df.mm.exp4 0.0181823184321336 0.0823767158208142 0.220721574670247 0.825430976357808 df.mm.exp5 0.231786570947484 0.0823767158208142 2.81373891442414 0.00515840172054967 ** df.mm.exp6 0.183082201951908 0.0823767158208142 2.22249940565910 0.0268535245106807 * df.mm.exp7 -0.102647343411602 0.0823767158208142 -1.24607229590070 0.213526247038064 df.mm.exp8 0.121262328773381 0.0823767158208142 1.47204616699154 0.141858463602235 df.mm.trans1:exp2 0.245226262358983 0.0683031644598436 3.59026209544295 0.000374868658817242 *** df.mm.trans2:exp2 0.190750385918088 0.0683031644598435 2.79270202817958 0.00549852168936129 ** df.mm.trans1:exp3 0.199185816664335 0.0683031644598436 2.91620188082851 0.00375915148203086 ** df.mm.trans2:exp3 0.145916525785463 0.0683031644598436 2.13630696234067 0.033310071070692 * df.mm.trans1:exp4 -0.0635448619376935 0.0683031644598436 -0.93033554799723 0.352803965897802 df.mm.trans2:exp4 -0.0792375791336657 0.0683031644598436 -1.16008650199876 0.246761600267147 df.mm.trans1:exp5 -0.127310032814653 0.0683031644598436 -1.86389655327757 0.0631280752589707 . df.mm.trans2:exp5 -0.181590146246252 0.0683031644598436 -2.65859053064828 0.00818748065494911 ** df.mm.trans1:exp6 -0.0493551028038114 0.0683031644598436 -0.722588816991458 0.470389012968902 df.mm.trans2:exp6 -0.135435656070323 0.0683031644598436 -1.98286063524842 0.0481221097551347 * df.mm.trans1:exp7 0.0339453648974623 0.0683031644598436 0.496980852437946 0.61949771990793 df.mm.trans2:exp7 0.081243539916212 0.0683031644598436 1.18945499170798 0.235023403392444 df.mm.trans1:exp8 -0.0609962546795526 0.0683031644598436 -0.89302238281234 0.372425635596369 df.mm.trans2:exp8 -0.117644858617782 0.0683031644598436 -1.72239250623516 0.0858340825403157 . df.mm.trans1:probe2 -0.0774212236723039 0.0398804560611593 -1.94133245501439 0.0529769010982588 . df.mm.trans1:probe3 -0.282980921893706 0.0398804560611593 -7.09572933317854 6.60014980671372e-12 *** df.mm.trans1:probe4 -0.108896270151096 0.0398804560611593 -2.73056732310423 0.0066250316899578 ** df.mm.trans1:probe5 -0.213583829619466 0.0398804560611593 -5.3556014828898 1.50109673842163e-07 *** df.mm.trans1:probe6 -0.276902419615610 0.0398804560611593 -6.94331125980511 1.72810296359403e-11 *** df.mm.trans2:probe2 0.112611001448540 0.0398804560611593 2.82371398350720 0.00500389701417001 ** df.mm.trans2:probe3 -0.106738712598486 0.0398804560611593 -2.67646669924725 0.00777125143497036 ** df.mm.trans2:probe4 0.0539796610816998 0.0398804560611593 1.35353670476883 0.176710510798405 df.mm.trans2:probe5 -0.125358151446168 0.0398804560611593 -3.14334799115445 0.00180509779978554 ** df.mm.trans2:probe6 -0.151766477440034 0.0398804560611593 -3.80553515253912 0.000165532958679836 *** df.mm.trans3:probe2 0.0774070210508262 0.0398804560611593 1.94097632514827 0.0530202486795721 . df.mm.trans3:probe3 -0.0683589595671386 0.0398804560611593 -1.71409673606304 0.0873484328773766 . df.mm.trans3:probe4 0.961462990570002 0.0398804560611593 24.1086257663537 7.2213941023154e-78 *** df.mm.trans3:probe5 0.246469058253859 0.0398804560611593 6.18019658240324 1.69103228695954e-09 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.09346144671182 0.151321068995668 27.0514970180987 1.08473840255293e-89 *** df.mm.trans1 0.0703509823669076 0.124618924697005 0.56452888305654 0.57273631633853 df.mm.trans2 0.160508650199324 0.124618924697006 1.28799578867800 0.198552357178601 df.mm.exp2 0.153480376261936 0.170350612178104 0.900967565067919 0.368191628332287 df.mm.exp3 0.148916107877615 0.170350612178104 0.874174186834862 0.382590441717747 df.mm.exp4 0.0529226020698033 0.170350612178104 0.31066869319185 0.756227433393955 df.mm.exp5 0.122845170848054 0.170350612178104 0.721131372980436 0.471284091140799 df.mm.exp6 0.139328467992910 0.170350612178104 0.817892382137375 0.413945027835598 df.mm.exp7 0.264064345650715 0.170350612178104 1.55012266920786 0.121966971352862 df.mm.exp8 -0.00742262332027343 0.170350612178104 -0.0435726248668421 0.965268577934318 df.mm.trans1:exp2 -0.00490189373863974 0.141247265850530 -0.0347043442513572 0.972334211209815 df.mm.trans2:exp2 -0.207123073903688 0.141247265850530 -1.46638642989996 0.143392406219229 df.mm.trans1:exp3 -0.131777443640112 0.141247265850530 -0.932955713136151 0.35145123535458 df.mm.trans2:exp3 -0.0962175535171743 0.141247265850530 -0.681199405438357 0.49617143399283 df.mm.trans1:exp4 -0.00487691409941346 0.141247265850530 -0.0345274938247251 0.97247513743819 df.mm.trans2:exp4 -0.0708244614539821 0.141247265850530 -0.501421822415521 0.616372484909628 df.mm.trans1:exp5 -0.0491636096844209 0.141247265850530 -0.348067690998329 0.727987289200019 df.mm.trans2:exp5 -0.145067069597727 0.141247265850530 -1.02704338186085 0.305070988189178 df.mm.trans1:exp6 -0.161387786291757 0.141247265850530 -1.14259051543369 0.253947457728746 df.mm.trans2:exp6 -0.156989131507745 0.141247265850530 -1.11144899380830 0.267096822883302 df.mm.trans1:exp7 -0.127017320007480 0.141247265850530 -0.899255070479681 0.369101668176163 df.mm.trans2:exp7 -0.279970132838958 0.141247265850530 -1.98212780370013 0.0482044111431486 * df.mm.trans1:exp8 -0.0812197409374826 0.141247265850530 -0.575018146003837 0.565628509272638 df.mm.trans2:exp8 0.0643702538440623 0.141247265850530 0.45572743271491 0.648853332795717 df.mm.trans1:probe2 0.0327357650133040 0.0824706354977544 0.396938435307623 0.691641717153417 df.mm.trans1:probe3 0.0245282147375257 0.0824706354977544 0.297417554617892 0.76631465622301 df.mm.trans1:probe4 0.00619818060787738 0.0824706354977544 0.0751562125169528 0.940131040800157 df.mm.trans1:probe5 0.0151944266431871 0.0824706354977544 0.184240445723263 0.853925765737286 df.mm.trans1:probe6 0.0291676087227617 0.0824706354977544 0.353672656294202 0.723785654558388 df.mm.trans2:probe2 0.0189741624919737 0.0824706354977544 0.230071738594646 0.818163168953134 df.mm.trans2:probe3 0.0227243408682741 0.0824706354977544 0.275544631505754 0.783051660168621 df.mm.trans2:probe4 -0.0662899903212969 0.0824706354977544 -0.80380113383632 0.422027937346439 df.mm.trans2:probe5 -0.00638941720595254 0.0824706354977544 -0.0774750572417563 0.938287511261095 df.mm.trans2:probe6 -0.059319486016574 0.0824706354977544 -0.719280088707321 0.472422402072321 df.mm.trans3:probe2 0.0326549701316863 0.0824706354977544 0.395958754708219 0.692363683215024 df.mm.trans3:probe3 -0.100613946200934 0.0824706354977544 -1.21999722196482 0.223242961828674 df.mm.trans3:probe4 0.00685486895568761 0.0824706354977544 0.0831189054663494 0.933801942483821 df.mm.trans3:probe5 -0.130495247477252 0.0824706354977544 -1.58232377730137 0.114430056615127