chr15.8829_chr15_12910555_12912198_+_0.R fitVsDatCorrelation=0.88883779923246 cont.fitVsDatCorrelation=0.337578239332385 fstatistic=4865.60991793511,36,324 cont.fstatistic=1146.14867383324,36,324 residuals=-0.672808106569495,-0.113951582554770,-0.00742894548329821,0.107116413081242,0.99683754778151 cont.residuals=-0.774663784280839,-0.300507328292591,-0.0488213311571864,0.259441979749422,1.35164904622516 predictedValues: Include Exclude Both chr15.8829_chr15_12910555_12912198_+_0.R.tl.Lung 66.4309505096639 117.265372445967 76.2409366392155 chr15.8829_chr15_12910555_12912198_+_0.R.tl.cerebhem 57.6558310263364 87.0519482134334 78.3969599448925 chr15.8829_chr15_12910555_12912198_+_0.R.tl.cortex 92.9487642702532 128.036770730362 117.939127225645 chr15.8829_chr15_12910555_12912198_+_0.R.tl.heart 78.0324457926389 135.154062468519 85.4605826161628 chr15.8829_chr15_12910555_12912198_+_0.R.tl.kidney 65.5671831520902 128.118861822245 74.5694723429314 chr15.8829_chr15_12910555_12912198_+_0.R.tl.liver 60.1989842222664 128.570074587059 57.0717969054069 chr15.8829_chr15_12910555_12912198_+_0.R.tl.stomach 70.4624624230736 109.476080683343 116.171648288900 chr15.8829_chr15_12910555_12912198_+_0.R.tl.testicle 62.9068218259442 118.149758277719 71.9954728734068 diffExp=-50.8344219363031,-29.3961171870970,-35.0880064601084,-57.1216166758805,-62.5516786701553,-68.3710903647925,-39.0136182602695,-55.2429364517748 diffExpScore=0.99749134190599 diffExp1.5=-1,-1,0,-1,-1,-1,-1,-1 diffExp1.5Score=0.875 diffExp1.4=-1,-1,0,-1,-1,-1,-1,-1 diffExp1.4Score=0.875 diffExp1.3=-1,-1,-1,-1,-1,-1,-1,-1 diffExp1.3Score=0.888888888888889 diffExp1.2=-1,-1,-1,-1,-1,-1,-1,-1 diffExp1.2Score=0.888888888888889 cont.predictedValues: Include Exclude Both Lung 91.3342576743739 70.6139582758832 94.6737988371127 cerebhem 80.3988710591808 72.8801766210241 60.6495850878545 cortex 74.0773627570332 81.7611294907618 93.7146427449255 heart 76.6767198964298 92.1249320996456 78.5600435783473 kidney 79.1692264907772 81.8074435114045 97.7097294565584 liver 70.0682880507034 73.6924909201707 100.332527158922 stomach 71.4984449119353 93.1450681214461 91.34980046823 testicle 78.9739907762305 85.199636515179 84.7868181865962 cont.diffExp=20.7202993984907,7.51869443815676,-7.68376673372855,-15.4482122032158,-2.63821702062729,-3.62420286946727,-21.6466232095108,-6.22564573894863 cont.diffExpScore=2.84756194523330 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,-1,0 cont.diffExp1.3Score=0.5 cont.diffExp1.2=1,0,0,-1,0,0,-1,0 cont.diffExp1.2Score=1.5 tran.correlation=0.494109498802553 cont.tran.correlation=-0.479043835673127 tran.covariance=0.0111865663821682 cont.tran.covariance=-0.00411151766744947 tran.mean=94.1266482781822 cont.tran.mean=79.5888748232612 weightedLogRatios: wLogRatio Lung -2.54604965291846 cerebhem -1.75538346136724 cortex -1.50276109285665 heart -2.54418782375510 kidney -3.02654327401828 liver -3.39728004909199 stomach -1.97197440003554 testicle -2.80911604903649 cont.weightedLogRatios: wLogRatio Lung 1.12847780695458 cerebhem 0.425910848322674 cortex -0.429749756071628 heart -0.813367108729283 kidney -0.143840405424217 liver -0.215574946366392 stomach -1.16422977351295 testicle -0.334401381085596 varWeightedLogRatios=0.426398907683845 cont.varWeightedLogRatios=0.505209569161466 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.28278072272755 0.113170092091355 46.6800072802193 6.81116479521451e-146 *** df.mm.trans1 -1.02884290013654 0.095853885810743 -10.7334500989133 3.38172791794848e-23 *** df.mm.trans2 -0.174155291267174 0.095853885810743 -1.81688295465696 0.0701588305182586 . df.mm.exp2 -0.46749274948916 0.133488158049434 -3.50212900020716 0.000526339272138622 *** df.mm.exp3 -0.0125067392321049 0.133488158049434 -0.0936917507504545 0.925411933817768 df.mm.exp4 0.188780763169252 0.133488158049434 1.41421355967277 0.158259403666987 df.mm.exp5 0.0975985170805122 0.133488158049434 0.731139889160573 0.465222130915254 df.mm.exp6 0.283115459616295 0.133488158049434 2.12090318537057 0.0346891661029339 * df.mm.exp7 -0.430986652107192 0.133488158049434 -3.22865082869439 0.00137112940777915 ** df.mm.exp8 0.0103002980310090 0.133488158049434 0.0771626351095096 0.938541793425678 df.mm.trans1:exp2 0.325821066371065 0.115604135975202 2.81842049700502 0.00512270053246923 ** df.mm.trans2:exp2 0.169558288834863 0.115604135975202 1.46671472784706 0.143423595133959 df.mm.trans1:exp3 0.348392088732233 0.115604135975202 3.01366456998533 0.00278469229908608 ** df.mm.trans2:exp3 0.100384726214547 0.115604135975202 0.86834891647891 0.385846081666786 df.mm.trans1:exp4 -0.0278191212861094 0.115604135975202 -0.240641228373324 0.80998538924169 df.mm.trans2:exp4 -0.0468049389516156 0.115604135975202 -0.404872529488526 0.68583838301994 df.mm.trans1:exp5 -0.110686273143260 0.115604135975202 -0.957459456009457 0.33904928176306 df.mm.trans2:exp5 -0.00907958307788435 0.115604135975202 -0.0785402961692649 0.93744676054396 df.mm.trans1:exp6 -0.381623050842861 0.115604135975202 -3.30111935549366 0.00107039776739420 ** df.mm.trans2:exp6 -0.191080883405907 0.115604135975202 -1.65288968075412 0.0993219352519792 . df.mm.trans1:exp7 0.489903702210327 0.115604135975202 4.23776967906593 2.9468323639299e-05 *** df.mm.trans2:exp7 0.362253229240358 0.115604135975202 3.13356633985884 0.00188476859080256 ** df.mm.trans1:exp8 -0.0648087551176958 0.115604135975202 -0.560609311864047 0.575451354493604 df.mm.trans2:exp8 -0.00278684730699634 0.115604135975202 -0.0241068131644886 0.980782248742283 df.mm.trans1:probe2 -0.0196472327198066 0.0578020679876011 -0.339905359857039 0.734148044135645 df.mm.trans1:probe3 -0.360162227169614 0.0578020679876011 -6.23095746759218 1.44051370843066e-09 *** df.mm.trans1:probe4 0.118967288776801 0.0578020679876011 2.05818395290494 0.0403719303711121 * df.mm.trans1:probe5 -0.217936687800733 0.0578020679876011 -3.77039603232677 0.000193675245000755 *** df.mm.trans1:probe6 -0.0411939142733756 0.0578020679876011 -0.712671980563256 0.476561679569451 df.mm.trans2:probe2 -0.350416605944018 0.0578020679876011 -6.06235413617354 3.7299185775113e-09 *** df.mm.trans2:probe3 -1.15099987444505 0.0578020679876011 -19.9127801913929 3.50501749412801e-58 *** df.mm.trans2:probe4 -0.227737376772112 0.0578020679876011 -3.93995205882536 9.98504479208867e-05 *** df.mm.trans2:probe5 -0.8826728210266 0.0578020679876011 -15.2706097161773 4.88887965405347e-40 *** df.mm.trans2:probe6 -0.485846641833023 0.0578020679876011 -8.40535051336295 1.36747131893620e-15 *** df.mm.trans3:probe2 0.44592723016141 0.0578020679876011 7.71472796193147 1.51045853153162e-13 *** df.mm.trans3:probe3 0.31642080989111 0.0578020679876011 5.47421261742718 8.81939508965268e-08 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.21289037465713 0.232478428509009 18.1216399374184 3.56271894081387e-51 *** df.mm.trans1 0.28411160620501 0.196906800444901 1.44287350951351 0.150022160666324 df.mm.trans2 0.00885408682955617 0.196906800444901 0.0449658762904624 0.964162208719043 df.mm.exp2 0.349387530701752 0.274216594105478 1.2741297872271 0.203530568082855 df.mm.exp3 -0.05265900477132 0.274216594105478 -0.192034347677240 0.84783559921295 df.mm.exp4 0.277564049490691 0.274216594105478 1.01220734068313 0.312194222319388 df.mm.exp5 -0.0273617202213197 0.274216594105478 -0.0997814166227848 0.920579571857765 df.mm.exp6 -0.280435210047934 0.274216594105478 -1.02267775209864 0.307223197478448 df.mm.exp7 0.0678212655493515 0.274216594105478 0.24732735730524 0.804811539359139 df.mm.exp8 0.152659164393709 0.274216594105478 0.556710161511921 0.578109792235504 df.mm.trans1:exp2 -0.476913334358982 0.23747853663459 -2.00823763325109 0.0454476583735989 * df.mm.trans2:exp2 -0.31779868855057 0.23747853663459 -1.33822067903159 0.181762888530611 df.mm.trans1:exp3 -0.156756943647596 0.23747853663459 -0.660088890006927 0.509665760602548 df.mm.trans2:exp3 0.199233111594753 0.23747853663459 0.838952077177884 0.402114746528999 df.mm.trans1:exp4 -0.452491846939495 0.23747853663459 -1.90540102424392 0.0576129718231024 . df.mm.trans2:exp4 -0.0116462702747919 0.23747853663459 -0.0490413594417255 0.960916552417897 df.mm.trans1:exp5 -0.115576549065593 0.23747853663459 -0.486682083793668 0.626812693720855 df.mm.trans2:exp5 0.17450212191461 0.23747853663459 0.734812182976847 0.462985388791072 df.mm.trans1:exp6 0.0153795819542847 0.237478536634590 0.0647619872188678 0.948403446346097 df.mm.trans2:exp6 0.323108282697372 0.23747853663459 1.36057888547015 0.174592538743059 df.mm.trans1:exp7 -0.312671503760426 0.23747853663459 -1.31663058140507 0.188893040242917 df.mm.trans2:exp7 0.209109050293026 0.237478536634590 0.880538735232244 0.379220206222889 df.mm.trans1:exp8 -0.298066535006724 0.23747853663459 -1.25513041822959 0.210335940620384 df.mm.trans2:exp8 0.0351101689312729 0.23747853663459 0.147845651353736 0.88255654445644 df.mm.trans1:probe2 0.0942739377892092 0.118739268317295 0.793957543491766 0.427801253285035 df.mm.trans1:probe3 0.0702720910393879 0.118739268317295 0.591818461030153 0.554384878790447 df.mm.trans1:probe4 -0.0531613872732627 0.118739268317295 -0.447715301152142 0.654657872820442 df.mm.trans1:probe5 0.0950665615229462 0.118739268317295 0.80063287293391 0.423930897365223 df.mm.trans1:probe6 -0.0487355871177648 0.118739268317295 -0.410442036643965 0.681753001115092 df.mm.trans2:probe2 0.209960982227407 0.118739268317295 1.76825228252501 0.0779597290400487 . df.mm.trans2:probe3 0.0558702502444269 0.118739268317295 0.47052884051071 0.638293826045385 df.mm.trans2:probe4 0.0741298669048581 0.118739268317295 0.624307930774581 0.532864719265897 df.mm.trans2:probe5 -0.133932838931345 0.118739268317295 -1.12795742157893 0.260172466733268 df.mm.trans2:probe6 0.113322094401244 0.118739268317295 0.95437757034535 0.340604045280434 df.mm.trans3:probe2 -0.0111579226355489 0.118739268317295 -0.0939699460311033 0.9251911145189 df.mm.trans3:probe3 0.144901579012002 0.118739268317295 1.22033410737209 0.223225680314839