chr11.4665_chr11_110495333_110497126_-_1.R fitVsDatCorrelation=0.826881826793853 cont.fitVsDatCorrelation=0.305627952781214 fstatistic=8762.69734387592,41,439 cont.fstatistic=3049.91406719712,41,439 residuals=-0.406233162913653,-0.0791252028473488,-0.00115757155586139,0.0739147060963672,1.35096441840049 cont.residuals=-0.472341698561968,-0.175270036093059,-0.0324374724645331,0.139498162538362,1.24029467622794 predictedValues: Include Exclude Both chr11.4665_chr11_110495333_110497126_-_1.R.tl.Lung 42.2603424659862 49.5015538461544 63.9157033813451 chr11.4665_chr11_110495333_110497126_-_1.R.tl.cerebhem 44.386292490672 51.5227124463374 74.264090998741 chr11.4665_chr11_110495333_110497126_-_1.R.tl.cortex 42.2828203649034 51.2647935564675 65.0682422095575 chr11.4665_chr11_110495333_110497126_-_1.R.tl.heart 46.6082473874191 47.507708003602 62.506092586894 chr11.4665_chr11_110495333_110497126_-_1.R.tl.kidney 43.7049088272342 45.286023376808 63.0533645629556 chr11.4665_chr11_110495333_110497126_-_1.R.tl.liver 50.2190086473427 50.9308108189529 70.1323016847554 chr11.4665_chr11_110495333_110497126_-_1.R.tl.stomach 44.1466220553647 48.0749574016279 62.604509207163 chr11.4665_chr11_110495333_110497126_-_1.R.tl.testicle 43.2323617959008 44.9968013288164 65.6989595572099 diffExp=-7.24121138016822,-7.13641995566541,-8.98197319156417,-0.899460616182914,-1.58111454957383,-0.711802171610181,-3.92833534626322,-1.76443953291563 diffExpScore=0.969920068668207 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 60.2852239132058 51.0575460202924 56.6730366320827 cerebhem 46.5273824247347 54.557284695722 53.2103037988265 cortex 50.8929666468239 57.858563238125 59.2956134816109 heart 54.9646637980465 50.7736428751056 54.3661884662645 kidney 53.1167059840242 51.1028837778817 53.5113321591403 liver 57.1864182640575 50.8830184132207 48.6596519786571 stomach 51.724257415165 54.7809505489801 59.13769959031 testicle 49.2989041937439 53.1099799577245 51.7326130390829 cont.diffExp=9.22767789291348,-8.02990227098733,-6.96559659130103,4.19102092294084,2.01382220614247,6.30339985083681,-3.05669313381514,-3.81107576398057 cont.diffExpScore=38.6741553340813 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=0.209496196179707 cont.tran.correlation=-0.639326400546304 tran.covariance=0.000624932839952737 cont.tran.covariance=-0.00255039625743885 tran.mean=46.6203728008494 cont.tran.mean=53.0075245104283 weightedLogRatios: wLogRatio Lung -0.604614740324708 cerebhem -0.576609972223239 cortex -0.739807124577974 heart -0.0736161976998456 kidney -0.134874955683666 liver -0.055220122097623 stomach -0.326500160338805 testicle -0.151471472704558 cont.weightedLogRatios: wLogRatio Lung 0.667196216616668 cerebhem -0.624047786307287 cortex -0.512319712075833 heart 0.314637852696242 kidney 0.152792098801840 liver 0.465738285107002 stomach -0.228206229052236 testicle -0.293021849071192 varWeightedLogRatios=0.0736146029481413 cont.varWeightedLogRatios=0.224834704898765 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.60794898596195 0.0739257570652914 48.8050326326101 1.89156021476371e-179 *** df.mm.trans1 0.100163650928045 0.0607665979865789 1.64833402307905 0.0999995865294324 . df.mm.trans2 0.251174360447936 0.0595388633887815 4.21866233501634 2.9870673830561e-05 *** df.mm.exp2 -0.0609622098738505 0.0800908108509048 -0.761163599496282 0.446968023018593 df.mm.exp3 0.0176604020871664 0.0800908108509048 0.220504723320165 0.825580604140539 df.mm.exp4 0.0791173509433888 0.0800908108509048 0.987845548107533 0.323772435672784 df.mm.exp5 -0.0418106436520437 0.0800908108509048 -0.522040458922028 0.601905461461966 df.mm.exp6 0.108190096755854 0.0800908108509048 1.35084281962456 0.177441626034189 df.mm.exp7 0.0351524159580021 0.0800908108509047 0.438906980520413 0.660944872268 df.mm.exp8 -0.100190448331851 0.0800908108509047 -1.25096059419805 0.211615125725105 df.mm.trans1:exp2 0.110043788017424 0.0662487313784475 1.66107011753623 0.0974133227983988 . df.mm.trans2:exp2 0.100980878785639 0.0636497222853597 1.58650933829551 0.113343807024056 df.mm.trans1:exp3 -0.0171286524176688 0.0662487313784475 -0.258550647858009 0.796103142186663 df.mm.trans2:exp3 0.0173397691255575 0.0636497222853597 0.272424898380836 0.785423417817168 df.mm.trans1:exp4 0.0188110411504511 0.0662487313784476 0.283945681057536 0.776585879162614 df.mm.trans2:exp4 -0.120229439221080 0.0636497222853597 -1.88892323334982 0.0595609946600825 . df.mm.trans1:exp5 0.0754219536468532 0.0662487313784476 1.13846638384671 0.255546682428135 df.mm.trans2:exp5 -0.0471949661072661 0.0636497222853597 -0.741479529096415 0.45879920555265 df.mm.trans1:exp6 0.0643544006416277 0.0662487313784476 0.971405780950001 0.331881160756994 df.mm.trans2:exp6 -0.0797260956372512 0.0636497222853597 -1.25257570299862 0.211026995437373 df.mm.trans1:exp7 0.008514881586777 0.0662487313784475 0.128528975719331 0.89778922900871 df.mm.trans2:exp7 -0.0643950704785002 0.0636497222853597 -1.01171015624858 0.312233940191812 df.mm.trans1:exp8 0.122930662839857 0.0662487313784475 1.85559270769447 0.0641816513039275 . df.mm.trans2:exp8 0.00477779408053304 0.0636497222853597 0.0750638637371086 0.940198092350448 df.mm.trans1:probe2 0.113722519287824 0.0421003340463469 2.70122605589376 0.00717582917761022 ** df.mm.trans1:probe3 0.0362393637566120 0.0421003340463469 0.860785658297087 0.389825978454311 df.mm.trans1:probe4 0.0130963724736853 0.0421003340463469 0.31107526271093 0.75589106169753 df.mm.trans1:probe5 0.062480043267584 0.0421003340463469 1.48407476289385 0.138506700420052 df.mm.trans1:probe6 0.011417459608779 0.0421003340463469 0.271196413696145 0.78636744436695 df.mm.trans1:probe7 0.22761846926639 0.0421003340463469 5.40657157294316 1.05685252712090e-07 *** df.mm.trans2:probe2 0.0619904355028104 0.0421003340463469 1.47244521705142 0.141617239947059 df.mm.trans2:probe3 0.0262094526994782 0.0421003340463469 0.622547380992871 0.533905227009871 df.mm.trans2:probe4 0.0481455430273869 0.0421003340463469 1.14359052292519 0.253416704106742 df.mm.trans2:probe5 0.123616409497011 0.0421003340463469 2.93623345983255 0.00349685690163609 ** df.mm.trans2:probe6 0.297487434818494 0.0421003340463469 7.0661537861196 6.29283500754984e-12 *** df.mm.trans3:probe2 0.210440029952618 0.0421003340463469 4.99853587197079 8.36161464599856e-07 *** df.mm.trans3:probe3 0.213249367293144 0.0421003340463469 5.06526544559918 6.01664692835738e-07 *** df.mm.trans3:probe4 0.145907796341996 0.0421003340463469 3.46571588200158 0.000580855656170105 *** df.mm.trans3:probe5 0.133998684487675 0.0421003340463469 3.18284136035976 0.00156202183561955 ** df.mm.trans3:probe6 0.0964571785777758 0.0421003340463469 2.29112620511726 0.0224290678686639 * df.mm.trans3:probe7 0.587893525543532 0.0421003340463469 13.9641059592624 6.26951884115852e-37 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.00716267062018 0.125162738621692 32.0156199420656 6.95263402006142e-117 *** df.mm.trans1 0.0847566128311246 0.102883137388856 0.823814426564183 0.410492336619712 df.mm.trans2 -0.0854893241195379 0.100804475895742 -0.848070716700674 0.396860740024194 df.mm.exp2 -0.129701631945297 0.135600711071211 -0.95649669474951 0.339347779151988 df.mm.exp3 -0.0895509574373826 0.135600711071211 -0.660401827762942 0.509342363895041 df.mm.exp4 -0.0564163713652804 0.135600711071211 -0.416047754614304 0.677578370731321 df.mm.exp5 -0.0683028530403609 0.135600711071211 -0.503705714378528 0.614720856804246 df.mm.exp6 0.0962536559217374 0.135600711071211 0.709831498384912 0.478185490880413 df.mm.exp7 -0.125341060582212 0.135600711071211 -0.924339257457053 0.355817501619487 df.mm.exp8 -0.0705635127537775 0.135600711071211 -0.520377158765199 0.603063058283243 df.mm.trans1:exp2 -0.129344390234257 0.112164866194280 -1.15316314834469 0.249470903411205 df.mm.trans2:exp2 0.195999526983698 0.107764517672909 1.81877607969819 0.0696267931083472 . df.mm.trans1:exp3 -0.0798113391869736 0.112164866194280 -0.711553821574865 0.477119034471088 df.mm.trans2:exp3 0.214599075030795 0.107764517672909 1.99137044052065 0.0470594345254576 * df.mm.trans1:exp4 -0.0359801570842892 0.112164866194280 -0.32077920925763 0.748530359793945 df.mm.trans2:exp4 0.0508404003126766 0.107764517672909 0.471773097588481 0.637323146999238 df.mm.trans1:exp5 -0.0582926853636103 0.112164866194280 -0.519705388518377 0.603530870883858 df.mm.trans2:exp5 0.0691904327158838 0.107764517672909 0.642052079942431 0.52117448832343 df.mm.trans1:exp6 -0.149024259472561 0.112164866194280 -1.32861799357418 0.184664235386128 df.mm.trans2:exp6 -0.0996777644414918 0.107764517672909 -0.92495903655448 0.355495370980151 df.mm.trans1:exp7 -0.0278191030965862 0.112164866194280 -0.248019759132069 0.80423508729982 df.mm.trans2:exp7 0.195730226432571 0.107764517672909 1.81627710733750 0.0700097828625556 . df.mm.trans1:exp8 -0.130621664558513 0.112164866194280 -1.16455062080014 0.244833391472889 df.mm.trans2:exp8 0.109975019863875 0.107764517672908 1.02051233781490 0.308047589450496 df.mm.trans1:probe2 0.0699334692956559 0.0712795284798353 0.98111576755786 0.327076033315452 df.mm.trans1:probe3 -0.0124041697466815 0.0712795284798352 -0.174021489917551 0.861928791520279 df.mm.trans1:probe4 0.0397331425819472 0.0712795284798353 0.557427124299617 0.577519743360572 df.mm.trans1:probe5 0.0376574119605617 0.0712795284798352 0.52830613169972 0.597553834751953 df.mm.trans1:probe6 -0.0139745460026161 0.0712795284798353 -0.196052727910083 0.844659614037876 df.mm.trans1:probe7 -0.0277645924715775 0.0712795284798352 -0.389517061401886 0.697082579787941 df.mm.trans2:probe2 -0.0652300267297347 0.0712795284798353 -0.915129885408657 0.360625827225364 df.mm.trans2:probe3 0.0739837118789832 0.0712795284798353 1.03793772850101 0.299870394077697 df.mm.trans2:probe4 0.0243789582695476 0.0712795284798353 0.3420190732104 0.732500209987433 df.mm.trans2:probe5 -0.00357075277001869 0.0712795284798353 -0.0500950672117429 0.960069414592977 df.mm.trans2:probe6 0.117078154208803 0.0712795284798353 1.64252144627926 0.101198040604248 df.mm.trans3:probe2 0.0356471720905198 0.0712795284798353 0.500103926762145 0.617252488717911 df.mm.trans3:probe3 0.0120292301056217 0.0712795284798353 0.168761359147103 0.866062080543869 df.mm.trans3:probe4 0.0661722147982578 0.0712795284798353 0.928348099510474 0.353737169391366 df.mm.trans3:probe5 0.0217279160913014 0.0712795284798353 0.304826877431549 0.760642469543741 df.mm.trans3:probe6 0.0421981764839774 0.0712795284798353 0.592009759098156 0.55414881389766 df.mm.trans3:probe7 0.0383054476401963 0.0712795284798353 0.53739760148712 0.591265285818417