chr9.24877_chr9_121407991_121426534_+_2.R fitVsDatCorrelation=0.886368840351924 cont.fitVsDatCorrelation=0.240274787720437 fstatistic=2734.74779109549,69,1083 cont.fstatistic=609.984411805318,69,1083 residuals=-1.75465950269951,-0.151396120470991,0.00514637837031829,0.146928692784280,1.41447606280180 cont.residuals=-1.07090749041737,-0.478273849763258,-0.233651197397972,0.237013613669861,2.89099271965913 predictedValues: Include Exclude Both chr9.24877_chr9_121407991_121426534_+_2.R.tl.Lung 52.2902004614464 51.1843835816621 59.6857736718686 chr9.24877_chr9_121407991_121426534_+_2.R.tl.cerebhem 161.663118063435 66.3310605157035 158.637858746410 chr9.24877_chr9_121407991_121426534_+_2.R.tl.cortex 307.630487568942 55.4814449847527 240.307090803087 chr9.24877_chr9_121407991_121426534_+_2.R.tl.heart 50.845321622425 46.4466296288120 59.400440219039 chr9.24877_chr9_121407991_121426534_+_2.R.tl.kidney 53.8471106777197 49.1360232930596 62.6238144736587 chr9.24877_chr9_121407991_121426534_+_2.R.tl.liver 56.6311364657992 53.5244547488322 63.8757906859305 chr9.24877_chr9_121407991_121426534_+_2.R.tl.stomach 54.6336412231732 51.7173128135857 66.0259490357948 chr9.24877_chr9_121407991_121426534_+_2.R.tl.testicle 54.0276820937398 54.0659368001241 60.8183751720866 diffExp=1.10581687978428,95.3320575477315,252.149042584189,4.39869199361298,4.71108738466005,3.10668171696693,2.91632840958754,-0.0382547063842509 diffExpScore=0.997467678757316 diffExp1.5=0,1,1,0,0,0,0,0 diffExp1.5Score=0.666666666666667 diffExp1.4=0,1,1,0,0,0,0,0 diffExp1.4Score=0.666666666666667 diffExp1.3=0,1,1,0,0,0,0,0 diffExp1.3Score=0.666666666666667 diffExp1.2=0,1,1,0,0,0,0,0 diffExp1.2Score=0.666666666666667 cont.predictedValues: Include Exclude Both Lung 103.027749696994 66.9444176084825 88.5595611329063 cerebhem 82.5853259480944 99.809719883637 85.193851755844 cortex 72.0579464327594 83.4653228507088 78.533200081077 heart 107.834601302536 80.7628146228405 86.9971053613785 kidney 73.5560702795473 110.207004977463 92.0844430230583 liver 88.7476773158531 83.7813752333642 80.6705683862379 stomach 87.2551712162607 74.636089830151 78.2966761340808 testicle 88.5510775375254 95.0331797408101 83.8239749564857 cont.diffExp=36.0833320885115,-17.2243939355427,-11.4073764179494,27.0717866796951,-36.6509346979156,4.96630208248897,12.6190813861097,-6.48210220328477 cont.diffExpScore=15.2876877014535 cont.diffExp1.5=1,0,0,0,0,0,0,0 cont.diffExp1.5Score=0.5 cont.diffExp1.4=1,0,0,0,-1,0,0,0 cont.diffExp1.4Score=2 cont.diffExp1.3=1,0,0,1,-1,0,0,0 cont.diffExp1.3Score=1.5 cont.diffExp1.2=1,-1,0,1,-1,0,0,0 cont.diffExp1.2Score=4 tran.correlation=0.499126413523192 cont.tran.correlation=-0.614194856004337 tran.covariance=0.0462305995002199 cont.tran.covariance=-0.0141049248669728 tran.mean=76.2159965339508 cont.tran.mean=87.3909715298142 weightedLogRatios: wLogRatio Lung 0.0843463966281106 cerebhem 4.13365062841709 cortex 8.3458205238895 heart 0.351399597544004 kidney 0.360765789120649 liver 0.226152244146406 stomach 0.217959935850483 testicle -0.00282404392448357 cont.weightedLogRatios: wLogRatio Lung 1.90537418238137 cerebhem -0.854070445552258 cortex -0.639418548318524 heart 1.31129233176034 kidney -1.81948874791603 liver 0.256663379579629 stomach 0.685887691210487 testicle -0.319244930539737 varWeightedLogRatios=9.08267918869191 cont.varWeightedLogRatios=1.48604142145989 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 2.88096980636566 0.155507430439943 18.5262517566856 8.94446927703709e-67 *** df.mm.trans1 0.913920107199855 0.132624974499041 6.89101061585096 9.38395496764596e-12 *** df.mm.trans2 1.06624665984784 0.115522724065551 9.22975690257115 1.38427080024722e-19 *** df.mm.exp2 0.410399173092993 0.14483408702619 2.83358138625738 0.00468840084658808 ** df.mm.exp3 0.459880572729797 0.14483408702619 3.1752233343152 0.00153946231084297 ** df.mm.exp4 -0.120359383303479 0.14483408702619 -0.831015583242606 0.406147995229959 df.mm.exp5 -0.0595542079044511 0.14483408702619 -0.411189169119297 0.681015180736153 df.mm.exp6 0.0566074045268113 0.14483408702619 0.390843106682304 0.695990081068484 df.mm.exp7 -0.0467551673486408 0.14483408702619 -0.322818808117913 0.746894781238686 df.mm.exp8 0.0686591694399739 0.14483408702619 0.474053938887732 0.635556999997255 df.mm.trans1:exp2 0.718306496971846 0.131678767591489 5.45499103697771 6.06683578339162e-08 *** df.mm.trans2:exp2 -0.151175378556328 0.0874013235232894 -1.72966921394554 0.083974313953539 . df.mm.trans1:exp3 1.31220979248301 0.131678767591489 9.96523446022758 1.93301117785510e-22 *** df.mm.trans2:exp3 -0.379266409825734 0.0874013235232894 -4.33936689442321 1.56252414352676e-05 *** df.mm.trans1:exp4 0.0923385162327869 0.131678767591489 0.701240738516412 0.483303435390581 df.mm.trans2:exp4 0.0232288094590616 0.0874013235232894 0.265771827275269 0.790465525413828 df.mm.trans1:exp5 0.0888939732169713 0.131678767591489 0.675082056453851 0.499767730091491 df.mm.trans2:exp5 0.0187121683052821 0.0874013235232894 0.214094793430628 0.830513436961459 df.mm.trans1:exp6 0.0231425618211481 0.131678767591489 0.175750139862668 0.860523097322585 df.mm.trans2:exp6 -0.0119032343037015 0.0874013235232894 -0.136190549797907 0.891695956279663 df.mm.trans1:exp7 0.090596018141428 0.131678767591489 0.688007791981214 0.491595203971384 df.mm.trans2:exp7 0.0571132861249768 0.0874013235232894 0.653460197427766 0.513598349387669 df.mm.trans1:exp8 -0.0359716047012652 0.131678767591489 -0.273176954487157 0.78476927701409 df.mm.trans2:exp8 -0.0138892932494183 0.0874013235232894 -0.158913992254559 0.873766265100226 df.mm.trans1:probe2 0.644349401590839 0.100017203811722 6.44238568000563 1.76576716333695e-10 *** df.mm.trans1:probe3 0.553670253341062 0.100017203811722 5.53575017337342 3.88693099286435e-08 *** df.mm.trans1:probe4 0.588250118431835 0.100017203811722 5.88148934396519 5.41217201820411e-09 *** df.mm.trans1:probe5 0.675294357510175 0.100017203811722 6.75178201123668 2.37690066531076e-11 *** df.mm.trans1:probe6 0.70815913188506 0.100017203811722 7.08037322477183 2.58128866436382e-12 *** df.mm.trans1:probe7 0.911007158894143 0.100017203811722 9.10850457896301 3.93076453491264e-19 *** df.mm.trans1:probe8 0.294121046792857 0.100017203811722 2.94070455465370 0.00334427529533089 ** df.mm.trans1:probe9 0.464855498081771 0.100017203811722 4.64775538973118 3.76844758275149e-06 *** df.mm.trans1:probe10 0.340233425872314 0.100017203811722 3.40174902822509 0.000694016871108046 *** df.mm.trans1:probe11 0.240872368470842 0.100017203811722 2.40830936369981 0.0161928603017636 * df.mm.trans1:probe12 0.232186943050209 0.100017203811722 2.32147004916566 0.0204463406546919 * df.mm.trans1:probe13 0.334691494024653 0.100017203811722 3.34633924234371 0.000846978475189373 *** df.mm.trans1:probe14 0.166664795736308 0.100017203811722 1.66636127970592 0.0959306425118088 . df.mm.trans1:probe15 0.399252677244254 0.100017203811722 3.99184002380062 6.99794980995888e-05 *** df.mm.trans1:probe16 0.139434251048041 0.100017203811722 1.39410267168157 0.163572549759204 df.mm.trans1:probe17 -0.0202543111816454 0.100017203811722 -0.202508272674502 0.839557427510124 df.mm.trans1:probe18 -0.0700723065473864 0.100017203811722 -0.700602535132804 0.483701581153157 df.mm.trans1:probe19 -0.00150436811779502 0.100017203811722 -0.0150410935365373 0.988002166502612 df.mm.trans1:probe20 0.066491126782834 0.100017203811722 0.664796897421777 0.506321937753091 df.mm.trans1:probe21 0.0780172976811524 0.100017203811722 0.780038780408388 0.435538488372386 df.mm.trans1:probe22 0.054880506959572 0.100017203811722 0.548710670445081 0.58331712046325 df.mm.trans2:probe2 -0.0984001798112056 0.100017203811722 -0.983832541413976 0.325417591716118 df.mm.trans2:probe3 -0.0368024500003016 0.100017203811722 -0.367961196651535 0.712974070502503 df.mm.trans2:probe4 -0.108125685496934 0.100017203811722 -1.08107086957236 0.279906259181693 df.mm.trans2:probe5 -0.107055678294897 0.100017203811722 -1.0703726380556 0.284690097869166 df.mm.trans2:probe6 0.0440522831612862 0.100017203811722 0.440447057930283 0.659701243429641 df.mm.trans3:probe2 -0.812379680100698 0.100017203811722 -8.12239943870028 1.23629039689117e-15 *** df.mm.trans3:probe3 -0.59275985778981 0.100017203811722 -5.92657898040878 4.15256976149067e-09 *** df.mm.trans3:probe4 -1.22980781390669 0.100017203811722 -12.2959627647835 1.27480269319082e-32 *** df.mm.trans3:probe5 -1.16749400306476 0.100017203811722 -11.6729318414312 9.72590736182484e-30 *** df.mm.trans3:probe6 -0.807348480156105 0.100017203811722 -8.07209609334716 1.82551783198272e-15 *** df.mm.trans3:probe7 -1.06734920288550 0.100017203811722 -10.6716560972324 2.3859611206321e-25 *** df.mm.trans3:probe8 -0.374926907942721 0.100017203811722 -3.74862417318231 0.000187202991055738 *** df.mm.trans3:probe9 -0.960132220706827 0.100017203811722 -9.59967069779553 5.34296171472078e-21 *** df.mm.trans3:probe10 -1.01206755646625 0.100017203811722 -10.1189347221846 4.64580130712619e-23 *** df.mm.trans3:probe11 -0.447733759854913 0.100017203811722 -4.47656745831202 8.38786887803603e-06 *** df.mm.trans3:probe12 -0.779863126910105 0.100017203811722 -7.79728983803793 1.47944410062623e-14 *** df.mm.trans3:probe13 -0.0371978676930717 0.100017203811722 -0.371914693427095 0.710029120634179 df.mm.trans3:probe14 -0.562283023260984 0.100017203811722 -5.62186305787412 2.40245147049812e-08 *** df.mm.trans3:probe15 -1.05304544423857 0.100017203811722 -10.5286431144475 9.53577822151948e-25 *** df.mm.trans3:probe16 -1.22711627763826 0.100017203811722 -12.2690520317711 1.70711482217195e-32 *** df.mm.trans3:probe17 -1.13588579627470 0.100017203811722 -11.3569041423409 2.54904484195356e-28 *** df.mm.trans3:probe18 -0.758655734571015 0.100017203811722 -7.58525239316983 7.12283274862717e-14 *** df.mm.trans3:probe19 -0.956765176159632 0.100017203811722 -9.56600604392725 7.21622956619492e-21 *** df.mm.trans3:probe20 -0.458045637692568 0.100017203811722 -4.57966849937957 5.19696564968138e-06 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.49187213850254 0.326044100316593 13.7768851947969 6.58726803943782e-40 *** df.mm.trans1 0.279824067001481 0.278067680545662 1.00631639913122 0.314488175300917 df.mm.trans2 -0.271436244471365 0.242210308070269 -1.12066347065880 0.262679579016637 df.mm.exp2 0.216982595402348 0.303665872852722 0.71454389445858 0.475044907795143 df.mm.exp3 -0.0168053298953676 0.303665872852721 -0.0553415164420474 0.955876594895311 df.mm.exp4 0.251054661104508 0.303665872852721 0.826746379980176 0.408562936029223 df.mm.exp5 0.122516701211646 0.303665872852721 0.403458907188649 0.68669030126447 df.mm.exp6 0.168448461542161 0.303665872852722 0.554716471626228 0.579203146060774 df.mm.exp7 0.0657701238508934 0.303665872852721 0.21658714307614 0.828570896408085 df.mm.exp8 0.253900839155491 0.303665872852721 0.836119109369375 0.403272334038458 df.mm.trans1:exp2 -0.43814894909549 0.276083819202103 -1.58701422764204 0.112801323958748 df.mm.trans2:exp2 0.182420289636868 0.183249673755208 0.995474021310138 0.31972813482378 df.mm.trans1:exp3 -0.340722429687623 0.276083819202103 -1.2341267614753 0.217423406252164 df.mm.trans2:exp3 0.237373893132781 0.183249673755208 1.29535779392368 0.195472873100455 df.mm.trans1:exp4 -0.205454443777208 0.276083819202103 -0.744174158308093 0.456932549932703 df.mm.trans2:exp4 -0.0634007037321383 0.183249673755208 -0.345979899624985 0.729425018818964 df.mm.trans1:exp5 -0.459467091355126 0.276083819202103 -1.66423042351055 0.0963556665592645 . df.mm.trans2:exp5 0.375981072366247 0.183249673755208 2.05174211043069 0.040434787407501 * df.mm.trans1:exp6 -0.317649571096064 0.276083819202103 -1.15055482792903 0.250169401113891 df.mm.trans2:exp6 0.0558995814995885 0.183249673755208 0.305046008290640 0.760389725158425 df.mm.trans1:exp7 -0.231931662048395 0.276083819202103 -0.8400769835722 0.401050639592366 df.mm.trans2:exp7 0.0429913571007206 0.183249673755208 0.234605367746248 0.814559388955554 df.mm.trans1:exp8 -0.405319672788375 0.276083819202103 -1.46810368662593 0.142366424586277 df.mm.trans2:exp8 0.0964625647380344 0.183249673755208 0.526399653332494 0.598718341069161 df.mm.trans1:probe2 -0.212076913371465 0.209700714240584 -1.01133138310704 0.312083741294753 df.mm.trans1:probe3 -0.350146838093238 0.209700714240584 -1.66974556744487 0.0952586968930507 . df.mm.trans1:probe4 -0.356756162572642 0.209700714240584 -1.70126345951948 0.0891805705250292 . df.mm.trans1:probe5 -0.158818104738197 0.209700714240584 -0.757356050566374 0.449001322725932 df.mm.trans1:probe6 -0.0668699384233815 0.209700714240584 -0.318882740411954 0.749876922896618 df.mm.trans1:probe7 -0.189955218742286 0.209700714240584 -0.905839636408464 0.365222218286297 df.mm.trans1:probe8 -0.305077553943042 0.209700714240584 -1.45482362827355 0.146007861157766 df.mm.trans1:probe9 -0.422659443279138 0.209700714240584 -2.01553649833654 0.0440951074001953 * df.mm.trans1:probe10 -0.256893581353178 0.209700714240584 -1.22504867130997 0.220823252038479 df.mm.trans1:probe11 -0.117836169494175 0.209700714240584 -0.561925456100186 0.574283080818357 df.mm.trans1:probe12 -0.289420148734769 0.209700714240584 -1.38015814482503 0.16782277971465 df.mm.trans1:probe13 -0.259866654745532 0.209700714240584 -1.23922636928834 0.215530162942633 df.mm.trans1:probe14 -0.271318317771449 0.209700714240584 -1.29383592590043 0.195997955788807 df.mm.trans1:probe15 -0.258022215133665 0.209700714240584 -1.23043078831693 0.218803011934835 df.mm.trans1:probe16 -0.481585950807786 0.209700714240584 -2.29653939211325 0.0218352528344712 * df.mm.trans1:probe17 -0.297231239816007 0.209700714240584 -1.41740690246291 0.156651617817667 df.mm.trans1:probe18 -0.199528920722839 0.209700714240584 -0.95149375835661 0.341566081178199 df.mm.trans1:probe19 -0.309224649088034 0.209700714240584 -1.47459988492585 0.140610771530031 df.mm.trans1:probe20 -0.303332002249039 0.209700714240584 -1.44649961421225 0.148326467686484 df.mm.trans1:probe21 -0.220096960664885 0.209700714240584 -1.04957659043723 0.294146979368995 df.mm.trans1:probe22 -0.414592255348931 0.209700714240584 -1.97706649140584 0.0482874132924463 * df.mm.trans2:probe2 0.192303395794843 0.209700714240584 0.917037390603347 0.359327210060290 df.mm.trans2:probe3 0.0347537307474699 0.209700714240584 0.165730149624564 0.868400249995883 df.mm.trans2:probe4 -0.149364488928874 0.209700714240584 -0.712274583659796 0.476448173773469 df.mm.trans2:probe5 -0.281802750630978 0.209700714240584 -1.34383305107713 0.179283842166798 df.mm.trans2:probe6 -0.226793265649382 0.209700714240584 -1.08150926653110 0.279711398600811 df.mm.trans3:probe2 -0.085052366007667 0.209700714240584 -0.405589300521355 0.685124504143562 df.mm.trans3:probe3 -0.0864081129853913 0.209700714240584 -0.412054452452925 0.680381055201614 df.mm.trans3:probe4 -0.140180702175623 0.209700714240584 -0.668479850835402 0.503969788309383 df.mm.trans3:probe5 0.0222719113075264 0.209700714240584 0.106208085118749 0.91543692516147 df.mm.trans3:probe6 -0.125091761607282 0.209700714240584 -0.596525205268341 0.550949087668998 df.mm.trans3:probe7 0.0936178037694142 0.209700714240584 0.446435311908423 0.655372078818993 df.mm.trans3:probe8 -0.0117455259705193 0.209700714240584 -0.056010901121891 0.955343454208968 df.mm.trans3:probe9 -0.0314726368331206 0.209700714240584 -0.150083593883294 0.880726609356131 df.mm.trans3:probe10 -0.0726185905141226 0.209700714240584 -0.346296343229471 0.729187281812884 df.mm.trans3:probe11 -0.109271078906424 0.209700714240584 -0.521081100282091 0.602416802802937 df.mm.trans3:probe12 -0.364909056236535 0.209700714240584 -1.74014217146578 0.0821181085502943 . df.mm.trans3:probe13 0.256226210473658 0.209700714240584 1.22186617914757 0.222024120143623 df.mm.trans3:probe14 -0.071982659413928 0.209700714240584 -0.343263777973327 0.731466649531301 df.mm.trans3:probe15 0.202598244828615 0.209700714240584 0.96613044720572 0.334194598806725 df.mm.trans3:probe16 0.149923829697203 0.209700714240584 0.714941912525862 0.474799021080195 df.mm.trans3:probe17 0.085835959827012 0.209700714240584 0.40932602512996 0.682381357636384 df.mm.trans3:probe18 -0.0490240711600289 0.209700714240584 -0.233781135832398 0.815199077784388 df.mm.trans3:probe19 -0.0540495383652154 0.209700714240584 -0.257746086182643 0.796651842266638 df.mm.trans3:probe20 0.0596395755715921 0.209700714240584 0.284403302046788 0.776155697410801