chr11.3270_chr11_101870206_101871551_-_0.R fitVsDatCorrelation=0.74729415730338 cont.fitVsDatCorrelation=0.299154089760607 fstatistic=9508.97235604825,36,324 cont.fstatistic=4606.75276753812,36,324 residuals=-0.277458163456251,-0.0686636282270132,-0.00322613763604083,0.0615571623247861,1.05133122367494 cont.residuals=-0.392311594196281,-0.119898753117077,-0.0195212148780397,0.0996541044744599,1.08212637515818 predictedValues: Include Exclude Both chr11.3270_chr11_101870206_101871551_-_0.R.tl.Lung 48.6454053526538 55.9815022145883 68.1333613634754 chr11.3270_chr11_101870206_101871551_-_0.R.tl.cerebhem 53.8866632941621 55.0537965925773 61.6628050588331 chr11.3270_chr11_101870206_101871551_-_0.R.tl.cortex 47.1113298355359 53.373047644534 65.84180030208 chr11.3270_chr11_101870206_101871551_-_0.R.tl.heart 48.0427737347589 56.0558447790585 64.7518453500958 chr11.3270_chr11_101870206_101871551_-_0.R.tl.kidney 49.1818560796234 56.8064042237047 65.9745400317797 chr11.3270_chr11_101870206_101871551_-_0.R.tl.liver 54.6024132610246 58.8656988840939 61.297973056572 chr11.3270_chr11_101870206_101871551_-_0.R.tl.stomach 50.5644764029005 54.5691780298145 68.7595140342586 chr11.3270_chr11_101870206_101871551_-_0.R.tl.testicle 50.703012846397 57.5836644600531 65.0837358256485 diffExp=-7.33609686193452,-1.16713329841522,-6.26171780899816,-8.01307104429964,-7.62454814408124,-4.26328562306929,-4.00470162691401,-6.88065161365616 diffExpScore=0.978518279428873 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=0,0,0,0,0,0,0,0 diffExp1.2Score=0 cont.predictedValues: Include Exclude Both Lung 53.4535489640566 55.0908077996206 56.2003170871098 cerebhem 52.6942264519854 56.0790785304783 61.7060267713678 cortex 53.1135722547952 50.2781429698588 56.8743092422891 heart 57.8551979338554 52.4425841059549 49.4070100329613 kidney 54.3419280116789 52.6136572015309 54.9208320802356 liver 55.5831256756208 57.312243636858 50.6039270934443 stomach 55.7730702206924 56.7779704672948 52.1748392826703 testicle 50.4974195588073 53.4500142677935 57.7843000413675 cont.diffExp=-1.63725883556401,-3.38485207849287,2.83542928493647,5.4126138279005,1.72827081014797,-1.72911796123719,-1.00490024660237,-2.95259470898618 cont.diffExpScore=11.9400366273414 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=0.504397655007772 cont.tran.correlation=0.136253100535412 tran.covariance=0.000828608425673493 cont.tran.covariance=0.000261340777335162 tran.mean=53.1891917272175 cont.tran.mean=54.2097867531801 weightedLogRatios: wLogRatio Lung -0.555505360992691 cerebhem -0.0856597632399595 cortex -0.488550869135287 heart -0.609193611201739 kidney -0.571825660918368 liver -0.303553836012327 stomach -0.301934548697116 testicle -0.507692468307641 cont.weightedLogRatios: wLogRatio Lung -0.120495268438748 cerebhem -0.248755875059785 cortex 0.216430845650247 heart 0.393764896855477 kidney 0.12860708602257 liver -0.12355544353487 stomach -0.0719687075435502 testicle -0.224476447620140 varWeightedLogRatios=0.0326240060553808 cont.varWeightedLogRatios=0.0521926377185768 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.81871964055607 0.0733291854592795 52.0763951847883 1.76694196301078e-159 *** df.mm.trans1 0.133094901273243 0.0621090540770664 2.14292269059669 0.0328638805858746 * df.mm.trans2 0.209965576722359 0.0621090540770665 3.38059530679422 0.000811730804674313 *** df.mm.exp2 0.185401227544921 0.0864943883788912 2.14350585072369 0.0328166848142354 * df.mm.exp3 -0.0455471849505052 0.0864943883788913 -0.526591213651738 0.598837802370909 df.mm.exp4 0.0397662570371668 0.0864943883788912 0.459755341155423 0.646000189086965 df.mm.exp5 0.0577932371173773 0.0864943883788912 0.668173256098561 0.50449870843742 df.mm.exp6 0.271478164603247 0.0864943883788912 3.13867951079125 0.00185315465605533 ** df.mm.exp7 0.0039916890780602 0.0864943883788912 0.0461496884696668 0.963219373807254 df.mm.exp8 0.115437875095482 0.0864943883788912 1.33462849161732 0.182935094180280 df.mm.trans1:exp2 -0.083075575759108 0.0749063376209173 -1.10905937197909 0.268227093897189 df.mm.trans2:exp2 -0.202111719066582 0.0749063376209173 -2.69819250928299 0.00733692955371543 ** df.mm.trans1:exp3 0.0135033443042642 0.0749063376209173 0.180269717264797 0.85705352674657 df.mm.trans2:exp3 -0.00216824082969416 0.0749063376209174 -0.0289460264452802 0.97692545841204 df.mm.trans1:exp4 -0.0522318847330047 0.0749063376209174 -0.69729593505609 0.486117646314164 df.mm.trans2:exp4 -0.0384391535778988 0.0749063376209173 -0.513162901815197 0.608187090544486 df.mm.trans1:exp5 -0.0468258217708399 0.0749063376209173 -0.625124966165265 0.532329059260932 df.mm.trans2:exp5 -0.0431654859004248 0.0749063376209174 -0.576259463102773 0.56483990011897 df.mm.trans1:exp6 -0.1559574451759 0.0749063376209173 -2.08203271083900 0.0381239145528329 * df.mm.trans2:exp6 -0.221240924055833 0.0749063376209174 -2.95356749619077 0.00337097643786294 ** df.mm.trans1:exp7 0.0347002320245616 0.0749063376209173 0.463248279473641 0.643497428379834 df.mm.trans2:exp7 -0.029543789240198 0.0749063376209173 -0.39440974126531 0.693538033520434 df.mm.trans1:exp8 -0.0740099025523285 0.0749063376209173 -0.988032587134009 0.323873957011606 df.mm.trans2:exp8 -0.087220269312324 0.0749063376209174 -1.16439105264663 0.245122223036828 df.mm.trans1:probe2 -0.161753421160164 0.0374531688104587 -4.31881804123860 2.08808082952628e-05 *** df.mm.trans1:probe3 -0.0843175068466703 0.0374531688104587 -2.25127831701987 0.0250376956659682 * df.mm.trans1:probe4 -0.135214720232346 0.0374531688104587 -3.61023444816205 0.000354334721613436 *** df.mm.trans1:probe5 -0.105955994297706 0.0374531688104587 -2.82902615887919 0.0049599832617554 ** df.mm.trans1:probe6 -0.118072982527204 0.0374531688104587 -3.15254987167421 0.00176984450801630 ** df.mm.trans2:probe2 -0.0205856889243568 0.0374531688104587 -0.549638110156604 0.582946264470367 df.mm.trans2:probe3 0.138716252400251 0.0374531688104587 3.70372539376469 0.000249687789687467 *** df.mm.trans2:probe4 0.00374998088141330 0.0374531688104587 0.100124528858720 0.920307386305192 df.mm.trans2:probe5 -0.0983520051217016 0.0374531688104587 -2.625999568139 0.00904960550955418 ** df.mm.trans2:probe6 -0.0565036275967026 0.0374531688104587 -1.50864744936947 0.132363390551307 df.mm.trans3:probe2 -0.0373674512954862 0.0374531688104587 -0.99771134145134 0.319163889729035 df.mm.trans3:probe3 0.216428038828451 0.0374531688104587 5.77863090633907 1.76892829918094e-08 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.96869050272011 0.105299864188370 37.6894171071346 1.77236931556183e-120 *** df.mm.trans1 -0.00482266818972346 0.0891878849904179 -0.0540731310114776 0.956910225104211 df.mm.trans2 0.0355644960529331 0.0891878849904179 0.39875927158441 0.690333261245445 df.mm.exp2 -0.0899864077056977 0.124204943670226 -0.72449940434431 0.469282037312543 df.mm.exp3 -0.109714297876535 0.124204943670227 -0.883332777540922 0.377711446077591 df.mm.exp4 0.158696410221590 0.124204943670226 1.27769801693998 0.202270632041750 df.mm.exp5 -0.00649442774716547 0.124204943670226 -0.0522879972025 0.958331439681065 df.mm.exp6 0.183491244513681 0.124204943670226 1.47732641786678 0.140559505680879 df.mm.exp7 0.146965665620303 0.124204943670226 1.18325133668196 0.237577020713279 df.mm.exp8 -0.114921480403955 0.124204943670226 -0.925256894033789 0.355520918858733 df.mm.trans1:exp2 0.075679269163016 0.107564636494031 0.703570166085351 0.482205786510237 df.mm.trans2:exp2 0.107766344308984 0.107564636494031 1.00187522425146 0.317151504024854 df.mm.trans1:exp3 0.103333758385940 0.107564636494031 0.960666644298783 0.337436170442068 df.mm.trans2:exp3 0.0183018724943150 0.107564636494031 0.170147672049545 0.865000196538027 df.mm.trans1:exp4 -0.0795661417910715 0.107564636494031 -0.73970539374701 0.460014385742454 df.mm.trans2:exp4 -0.207960349805871 0.107564636494031 -1.93335241566508 0.0540637539754691 . df.mm.trans1:exp5 0.0229774785424127 0.107564636494031 0.213615545883314 0.830981233498184 df.mm.trans2:exp5 -0.0395127182443301 0.107564636494031 -0.367339299719779 0.713605763293047 df.mm.trans1:exp6 -0.144424617461498 0.107564636494031 -1.34267750228033 0.180316327793690 df.mm.trans2:exp6 -0.143959842231049 0.107564636494031 -1.33835660978632 0.181718641683498 df.mm.trans1:exp7 -0.104487558357965 0.107564636494031 -0.97139321773065 0.332077120990466 df.mm.trans2:exp7 -0.116800133658251 0.107564636494031 -1.08585997652427 0.278348174563039 df.mm.trans1:exp8 0.0580306844367078 0.107564636494031 0.539495937774381 0.589915252375888 df.mm.trans2:exp8 0.084685510163671 0.107564636494031 0.787298808641166 0.431682501461197 df.mm.trans1:probe2 0.026533184243143 0.0537823182470157 0.493344004274403 0.622103761828758 df.mm.trans1:probe3 0.0401927855466156 0.0537823182470157 0.747323411423342 0.455410371970339 df.mm.trans1:probe4 0.0487569253175204 0.0537823182470157 0.906560499932073 0.365312963102409 df.mm.trans1:probe5 0.00922173204794365 0.0537823182470157 0.171464011751768 0.86396596339897 df.mm.trans1:probe6 0.00980215994990115 0.0537823182470157 0.18225618138811 0.855495663570969 df.mm.trans2:probe2 0.0390450003963695 0.0537823182470157 0.725982100976766 0.468373832528618 df.mm.trans2:probe3 0.0245122250911585 0.0537823182470157 0.455767357936801 0.648862587946237 df.mm.trans2:probe4 0.0182057070013003 0.0537823182470157 0.338507293748174 0.735200187220693 df.mm.trans2:probe5 0.00434090528693036 0.0537823182470157 0.0807124986132637 0.93572042925133 df.mm.trans2:probe6 -0.0435529548965964 0.0537823182470157 -0.809800624371805 0.418649106424256 df.mm.trans3:probe2 0.090560396950515 0.0537823182470157 1.68383215715213 0.0931772312428369 . df.mm.trans3:probe3 -0.00209019169111260 0.0537823182470157 -0.0388639195787843 0.969022818231902