chr17.10862_chr17_77937569_77941010_-_0.R fitVsDatCorrelation=0.92715566479628 cont.fitVsDatCorrelation=0.280784481429037 fstatistic=7290.70169497794,37,347 cont.fstatistic=1103.13462922725,37,347 residuals=-0.402520933885791,-0.0934300402328119,0.000181958705434511,0.0862373568956903,0.621386404207366 cont.residuals=-0.672929093280106,-0.263801165563200,-0.119018271204122,0.142192060927023,1.21433259646721 predictedValues: Include Exclude Both chr17.10862_chr17_77937569_77941010_-_0.R.tl.Lung 50.2216687472075 53.7090412454718 113.749502505282 chr17.10862_chr17_77937569_77941010_-_0.R.tl.cerebhem 64.6231080239958 57.0513637434629 103.076867344411 chr17.10862_chr17_77937569_77941010_-_0.R.tl.cortex 50.8631913392155 62.9438392363028 164.899326466849 chr17.10862_chr17_77937569_77941010_-_0.R.tl.heart 49.3187714091276 52.488779913755 113.383655145065 chr17.10862_chr17_77937569_77941010_-_0.R.tl.kidney 49.2063320796999 49.8860608413067 106.298280897044 chr17.10862_chr17_77937569_77941010_-_0.R.tl.liver 51.6464343727855 46.8116605418098 90.496613577717 chr17.10862_chr17_77937569_77941010_-_0.R.tl.stomach 50.6296531567783 52.748921538567 108.175221232301 chr17.10862_chr17_77937569_77941010_-_0.R.tl.testicle 54.6324041379757 56.6263924869771 133.002909033144 diffExp=-3.48737249826431,7.57174428053285,-12.0806478970873,-3.17000850462736,-0.679728761606832,4.83477383097568,-2.11926838178878,-1.99398834900138 diffExpScore=2.96404334426614 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,-1,0,0,0,0,0 diffExp1.2Score=0.5 cont.predictedValues: Include Exclude Both Lung 70.3016279835825 68.3820600682834 52.4112725180116 cerebhem 65.4351456057593 76.6854528840555 60.8254261459986 cortex 55.5884006676843 60.0256284893866 64.2809505014297 heart 64.7947641557296 62.2870828442198 68.1609858568618 kidney 64.2617854384279 62.9446943394841 61.0766002399117 liver 76.0615854829714 78.0897318600812 63.5299249532872 stomach 60.358232225348 63.035968266036 59.1235380087332 testicle 60.768346557278 69.5892732057534 59.0018645721002 cont.diffExp=1.91956791529917,-11.2503072782961,-4.43722782170234,2.50768131150984,1.31709109894386,-2.02814637710976,-2.67773604068805,-8.82092664847542 cont.diffExpScore=1.42863420536690 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=0.314129418541896 cont.tran.correlation=0.70697059876101 tran.covariance=0.00268169301983054 cont.tran.covariance=0.00671836186702705 tran.mean=53.3379764259024 cont.tran.mean=66.1631112546301 weightedLogRatios: wLogRatio Lung -0.265183284205918 cerebhem 0.511722683964245 cortex -0.86001944507927 heart -0.244783896034563 kidney -0.0535448314392347 liver 0.382862193704066 stomach -0.161769899696250 testicle -0.144056965676198 cont.weightedLogRatios: wLogRatio Lung 0.117353056712321 cerebhem -0.675920934707532 cortex -0.311517503316599 heart 0.163862333899741 kidney 0.0859950247577566 liver -0.114331789834613 stomach -0.178928423055405 testicle -0.565863611288008 varWeightedLogRatios=0.177285923054262 cont.varWeightedLogRatios=0.0990940775721997 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 2.78804508669736 0.0860031323459623 32.4179481682362 4.9981468729274e-107 *** df.mm.trans1 1.08982590124919 0.0716524116112935 15.2098984073471 2.17181545036804e-40 *** df.mm.trans2 1.17950103848824 0.0716524116112935 16.4614283310784 2.09977295832558e-45 *** df.mm.exp2 0.411019790904563 0.0987219710101834 4.16340746339197 3.95960316786659e-05 *** df.mm.exp3 -0.199982002235877 0.0987219710101833 -2.02570917283700 0.0435594855366879 * df.mm.exp4 -0.0379022990230701 0.0987219710101833 -0.383929723396228 0.701265679009787 df.mm.exp5 -0.0265144259882955 0.0987219710101833 -0.268576748589840 0.788415009067862 df.mm.exp6 0.119211805710433 0.0987219710101833 1.20755090777246 0.228042470989530 df.mm.exp7 0.0402991806954111 0.0987219710101833 0.408208834194104 0.683372132769002 df.mm.exp8 -0.0192978872934009 0.0987219710101833 -0.195477127289226 0.845133854552112 df.mm.trans1:exp2 -0.158894316644044 0.0834352938344417 -1.90440171469083 0.0576846459404311 . df.mm.trans2:exp2 -0.35064916370735 0.0834352938344417 -4.20264791543891 3.35951935427042e-05 *** df.mm.trans1:exp3 0.212674925873075 0.0834352938344417 2.54898036669086 0.0112337102640060 * df.mm.trans2:exp3 0.358643537183911 0.0834352938344417 4.2984631647077 2.23725140733641e-05 *** df.mm.trans1:exp4 0.0197604844922298 0.0834352938344417 0.236836038852334 0.812923743235823 df.mm.trans2:exp4 0.0149203766713230 0.0834352938344417 0.178825722132999 0.858178910499562 df.mm.trans1:exp5 0.00609016009714793 0.0834352938344417 0.0729926128052291 0.941854051449456 df.mm.trans2:exp5 -0.0473253053153615 0.0834352938344417 -0.567209668000544 0.57093848756742 df.mm.trans1:exp6 -0.0912372288516505 0.0834352938344417 -1.09350880974531 0.274928992430943 df.mm.trans2:exp6 -0.256660830125320 0.0834352938344417 -3.07616619214651 0.00226337450252519 ** df.mm.trans1:exp7 -0.0322083271996747 0.0834352938344417 -0.386027611571486 0.699712789708348 df.mm.trans2:exp7 -0.0583372064950791 0.0834352938344417 -0.699190999564716 0.484901065950132 df.mm.trans1:exp8 0.103478494468668 0.0834352938344417 1.24022448670221 0.215730340924803 df.mm.trans2:exp8 0.0721917089953848 0.0834352938344417 0.86524186201864 0.387503834944280 df.mm.trans1:probe2 0.0568848182180376 0.0456993925251954 1.24476092732907 0.214059662581424 df.mm.trans1:probe3 -0.0144480280128513 0.0456993925251954 -0.316153611995732 0.752076000860495 df.mm.trans1:probe4 0.117836303314154 0.0456993925251955 2.57850918366557 0.0103342736932906 * df.mm.trans1:probe5 0.125340010095546 0.0456993925251954 2.74270626303057 0.00640967703426264 ** df.mm.trans1:probe6 0.100142836070355 0.0456993925251955 2.19133845193114 0.029091635881494 * df.mm.trans2:probe2 -0.0367374895208302 0.0456993925251955 -0.803894482855013 0.42200827953176 df.mm.trans2:probe3 0.0334282981516654 0.0456993925251954 0.731482330607247 0.464978275768795 df.mm.trans2:probe4 0.0689572294391763 0.0456993925251955 1.50893098636176 0.132226373887519 df.mm.trans2:probe5 0.0493784392812302 0.0456993925251954 1.08050537551470 0.280667589130245 df.mm.trans2:probe6 0.0453258025961903 0.0456993925251955 0.991825057000503 0.321973974862884 df.mm.trans3:probe2 -0.584527193638169 0.0456993925251954 -12.7906994237593 5.90008209483194e-31 *** df.mm.trans3:probe3 -0.596203016894293 0.0456993925251954 -13.0461912938030 6.26998732239983e-32 *** df.mm.trans3:probe4 -0.112763158240497 0.0456993925251955 -2.46749796900095 0.0140881057996610 * cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.52431531639533 0.220305597744997 20.5365427057020 6.67258646234144e-62 *** df.mm.trans1 -0.315017787493498 0.183544795861585 -1.71629920649485 0.0869997624729364 . df.mm.trans2 -0.300770013105102 0.183544795861585 -1.63867360931289 0.102187588812573 df.mm.exp2 -0.106020132339025 0.252886171011465 -0.419240529899195 0.675299763694583 df.mm.exp3 -0.569300930884732 0.252886171011465 -2.25121416725837 0.0249972469641637 * df.mm.exp4 -0.437677254081923 0.252886171011465 -1.73072830487864 0.0843892112261505 . df.mm.exp5 -0.325690981064832 0.252886171011465 -1.28789557674178 0.198640515996164 df.mm.exp6 0.0191070932329819 0.252886171011465 0.0755561016110906 0.939815803088229 df.mm.exp7 -0.35441005891747 0.252886171011465 -1.40146081337679 0.161970086018406 df.mm.exp8 -0.246673348050125 0.252886171011465 -0.975432334095254 0.330025356270943 df.mm.trans1:exp2 0.0342846848312091 0.213727823392343 0.160412829209757 0.872649226031863 df.mm.trans2:exp2 0.220621649671704 0.213727823392343 1.03225516533103 0.302671505162922 df.mm.trans1:exp3 0.334480533082363 0.213727823392343 1.56498357477937 0.118498234393393 df.mm.trans2:exp3 0.438962032873944 0.213727823392343 2.05383663159352 0.0407403953377462 * df.mm.trans1:exp4 0.356107097900062 0.213727823392343 1.66617098442233 0.0965817552530427 . df.mm.trans2:exp4 0.344320809880131 0.213727823392343 1.61102473423901 0.108083532334617 df.mm.trans1:exp5 0.23586116275737 0.213727823392343 1.10355853072249 0.270549395150761 df.mm.trans2:exp5 0.242836943753975 0.213727823392343 1.13619714971876 0.256658142065067 df.mm.trans1:exp6 0.0596412980015256 0.213727823392343 0.279052568144304 0.780370719687755 df.mm.trans2:exp6 0.113640970182726 0.213727823392343 0.53170882657666 0.59526790083836 df.mm.trans1:exp7 0.201912448990812 0.213727823392343 0.944717659058167 0.345460369442677 df.mm.trans2:exp7 0.273005036727417 0.213727823392343 1.27734907132918 0.202333019164118 df.mm.trans1:exp8 0.100947429410838 0.213727823392343 0.472317678665205 0.636996953151404 df.mm.trans2:exp8 0.264173272381999 0.213727823392343 1.23602658834480 0.217284724795665 df.mm.trans1:probe2 0.0720532016941334 0.117063550038467 0.615505011341762 0.538624734541754 df.mm.trans1:probe3 -0.0560558675056233 0.117063550038467 -0.478849885273456 0.6323470207185 df.mm.trans1:probe4 0.151216125445824 0.117063550038467 1.29174388950391 0.197305554896818 df.mm.trans1:probe5 0.0811311080773056 0.117063550038467 0.693051834244273 0.488740614986576 df.mm.trans1:probe6 0.186629705366935 0.117063550038467 1.59425974443462 0.111788262549812 df.mm.trans2:probe2 -0.0316985530370579 0.117063550038467 -0.270780725739497 0.78672067930956 df.mm.trans2:probe3 -0.0278899659909555 0.117063550038467 -0.238246371153027 0.811830639031347 df.mm.trans2:probe4 0.071064204795044 0.117063550038467 0.607056635235242 0.544210328882068 df.mm.trans2:probe5 0.0269399708693205 0.117063550038467 0.230131162607559 0.818125455076475 df.mm.trans2:probe6 -0.0227635843015023 0.117063550038467 -0.194454928917005 0.845933476775255 df.mm.trans3:probe2 0.112597871812133 0.117063550038467 0.961852530314802 0.336793455716214 df.mm.trans3:probe3 0.0476825873732369 0.117063550038467 0.407322239566189 0.684022488856473 df.mm.trans3:probe4 0.0420962479501192 0.117063550038467 0.359601668805418 0.719363777685759