chr7.21444_chr7_68261968_68267169_+_0.R fitVsDatCorrelation=0.955755977063428 cont.fitVsDatCorrelation=0.368608114525597 fstatistic=7609.74180618118,37,347 cont.fstatistic=753.571472480884,37,347 residuals=-0.81969817653384,-0.0963940427154032,-0.00542413398002381,0.0894543527072762,0.703386144282652 cont.residuals=-0.943011682705297,-0.254856955220448,-0.0727515278134929,0.108279340829502,2.20365895922911 predictedValues: Include Exclude Both chr7.21444_chr7_68261968_68267169_+_0.R.tl.Lung 61.0497136408154 64.0836191959797 123.062294273521 chr7.21444_chr7_68261968_68267169_+_0.R.tl.cerebhem 61.3521610142935 60.9416823175029 92.5614225122308 chr7.21444_chr7_68261968_68267169_+_0.R.tl.cortex 62.4383274270886 67.6920488122077 122.036135691520 chr7.21444_chr7_68261968_68267169_+_0.R.tl.heart 60.1880167639528 69.9267446245186 124.901930707319 chr7.21444_chr7_68261968_68267169_+_0.R.tl.kidney 69.070310454668 78.6755960338342 140.915766513705 chr7.21444_chr7_68261968_68267169_+_0.R.tl.liver 66.6825890321923 66.4583382313848 132.415253964229 chr7.21444_chr7_68261968_68267169_+_0.R.tl.stomach 59.3218717699304 58.0125065834834 113.107176132812 chr7.21444_chr7_68261968_68267169_+_0.R.tl.testicle 63.6007877046209 61.113643572633 126.891860586680 diffExp=-3.03390555516432,0.410478696790598,-5.25372138511916,-9.73872786056574,-9.60528557916622,0.224250800807511,1.30936518644701,2.48714413198792 diffExpScore=1.32489037883437 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 95.697329995261 65.8854932685194 65.3787416176748 cerebhem 77.1204170346416 66.3260572374607 69.3546112781265 cortex 115.388639589046 69.1710031075607 89.6660292296587 heart 93.9405029209458 113.420756457605 82.6432435766281 kidney 82.8065385810507 78.0605073133568 68.8834542295495 liver 78.8370940419252 72.969183328778 68.088609673133 stomach 85.8526778372641 61.260913269811 84.6570074831703 testicle 80.1310804423496 70.2328150445327 75.3989319144106 cont.diffExp=29.8118367267416,10.7943597971808,46.2176364814852,-19.4802535366595,4.74603126769391,5.8679107131472,24.5917645674531,9.89826539781694 cont.diffExpScore=1.33460843006213 cont.diffExp1.5=0,0,1,0,0,0,0,0 cont.diffExp1.5Score=0.5 cont.diffExp1.4=1,0,1,0,0,0,1,0 cont.diffExp1.4Score=0.75 cont.diffExp1.3=1,0,1,0,0,0,1,0 cont.diffExp1.3Score=0.75 cont.diffExp1.2=1,0,1,-1,0,0,1,0 cont.diffExp1.2Score=1.33333333333333 tran.correlation=0.687326503666082 cont.tran.correlation=0.112146330075534 tran.covariance=0.00338127964180896 cont.tran.covariance=0.00316648743267136 tran.mean=64.4129973236941 cont.tran.mean=81.6938130918818 weightedLogRatios: wLogRatio Lung -0.200594143171600 cerebhem 0.0276124717212847 cortex -0.337261402026346 heart -0.625764436511326 kidney -0.559924393496784 liver 0.0141423674986403 stomach 0.090880756106756 testicle 0.164855580966714 cont.weightedLogRatios: wLogRatio Lung 1.63289914492896 cerebhem 0.643849177834241 cortex 2.29889204670344 heart -0.873787117517743 kidney 0.258932616856132 liver 0.334810240064735 stomach 1.44577245317572 testicle 0.569285980929602 varWeightedLogRatios=0.0916107691142727 cont.varWeightedLogRatios=0.963536195245177 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.67240050419527 0.0873782995965913 42.0287476541662 3.40757543408169e-138 *** df.mm.trans1 0.443835639925851 0.0727981146477838 6.09680129867707 2.88299944438888e-09 *** df.mm.trans2 0.460522807719402 0.0727981146477838 6.32602657290689 7.75695958691749e-10 *** df.mm.exp2 0.239488717083425 0.100300509113943 2.38771187902309 0.0174881651885526 * df.mm.exp3 0.0856442331691538 0.100300509113943 0.853876355421694 0.393762570385971 df.mm.exp4 0.0582059832959269 0.100300509113943 0.580315930697861 0.562078232054088 df.mm.exp5 0.193109079636696 0.100300509113943 1.92530507913297 0.0550082330470949 . df.mm.exp6 0.0513896895350486 0.100300509113943 0.512357215222799 0.608726984624899 df.mm.exp7 -0.0438857477677487 0.100300509113943 -0.437542622220332 0.66199007303063 df.mm.exp8 -0.0371608422234796 0.100300509113943 -0.370495050840315 0.711239717873484 df.mm.trans1:exp2 -0.234546832167584 0.084769402029085 -2.7668808149326 0.00596277686211662 ** df.mm.trans2:exp2 -0.289760118281094 0.084769402029085 -3.41821590509362 0.00070527616290299 *** df.mm.trans1:exp3 -0.063153434740265 0.084769402029085 -0.745002715939846 0.456774361507313 df.mm.trans2:exp3 -0.0308642880340801 0.084769402029085 -0.364097036139176 0.71600730347937 df.mm.trans1:exp4 -0.0724212178504144 0.084769402029085 -0.854332059881302 0.393510447025079 df.mm.trans2:exp4 0.0290534249171223 0.084769402029085 0.342734810222607 0.732005494117667 df.mm.trans1:exp5 -0.0696726117404048 0.084769402029085 -0.821907552403161 0.411693888157718 df.mm.trans2:exp5 0.0120351586806114 0.084769402029085 0.141975269289762 0.887181933736875 df.mm.trans1:exp6 0.0368656853335307 0.084769402029085 0.434893775950924 0.663909872873153 df.mm.trans2:exp6 -0.0150032114661811 0.084769402029085 -0.176988525423754 0.859620661832302 df.mm.trans1:exp7 0.0151753083370475 0.084769402029085 0.179018702194463 0.85802749569911 df.mm.trans2:exp7 -0.0556444146843037 0.084769402029085 -0.656420988615818 0.51198834614043 df.mm.trans1:exp8 0.0780981878080619 0.084769402029085 0.921301624627078 0.357533050696845 df.mm.trans2:exp8 -0.0102927979686153 0.084769402029085 -0.121421146336313 0.903427749935536 df.mm.trans1:probe2 0.122910386581140 0.0464301136775540 2.64721269981640 0.00848594167363682 ** df.mm.trans1:probe3 -0.121206038500744 0.0464301136775541 -2.61050488358678 0.00943285276462948 ** df.mm.trans1:probe4 -0.0359218403499452 0.0464301136775541 -0.77367547707106 0.43964947810402 df.mm.trans1:probe5 0.125831900831374 0.0464301136775540 2.71013553197922 0.00705962932284579 ** df.mm.trans1:probe6 -0.137090749997268 0.0464301136775541 -2.95262576674547 0.00336548629723445 ** df.mm.trans2:probe2 -0.114663131144541 0.0464301136775540 -2.46958540616223 0.0140076207114001 * df.mm.trans2:probe3 0.277765918499351 0.0464301136775540 5.9824518291807 5.47383066766585e-09 *** df.mm.trans2:probe4 0.0619200240560839 0.0464301136775541 1.33361775691749 0.183203885294578 df.mm.trans2:probe5 -0.148257584876673 0.0464301136775540 -3.19313422117133 0.00153614928654485 ** df.mm.trans2:probe6 0.195889459351190 0.0464301136775541 4.21901744009492 3.13575190725609e-05 *** df.mm.trans3:probe2 -0.347669884610052 0.0464301136775541 -7.48802570298525 5.83377894122406e-13 *** df.mm.trans3:probe3 1.56710977625232 0.0464301136775540 33.7520124791319 1.20411107353114e-111 *** df.mm.trans3:probe4 -0.275712960306773 0.0464301136775540 -5.93823573686537 6.99648857523483e-09 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.73001299651668 0.276126447072751 17.1298803380122 4.20228561250192e-48 *** df.mm.trans1 0.0303137660108155 0.230051223748825 0.131769635982953 0.895242872288598 df.mm.trans2 -0.57115369390784 0.230051223748825 -2.48272399772773 0.0135103302679283 * df.mm.exp2 -0.268193268547167 0.316962258925688 -0.846136285929376 0.398059833671585 df.mm.exp3 -0.0801158611268101 0.316962258925688 -0.252761516145029 0.800602172704298 df.mm.exp4 0.290321443588977 0.316962258925688 0.915949566276418 0.3603294440161 df.mm.exp5 -0.0273362491902654 0.316962258925688 -0.086244492586969 0.931321804944806 df.mm.exp6 -0.132300641023505 0.316962258925687 -0.417401874506841 0.676642616437876 df.mm.exp7 -0.439744627915008 0.316962258925687 -1.38737220451886 0.166218661344908 df.mm.exp8 -0.25622518662575 0.316962258925688 -0.808377588846698 0.419427104546346 df.mm.trans1:exp2 0.0523709281080395 0.267882001719407 0.195499987949528 0.845115973460301 df.mm.trans2:exp2 0.274857823919812 0.267882001719407 1.02604065280844 0.30558713426382 df.mm.trans1:exp3 0.26723136825214 0.267882001719407 0.997571193797678 0.319182460926396 df.mm.trans2:exp3 0.128779320915334 0.267882001719407 0.480731516446647 0.631010280290928 df.mm.trans1:exp4 -0.308850207698078 0.267882001719407 -1.15293377575095 0.249731150782608 df.mm.trans2:exp4 0.252864683720532 0.267882001719407 0.943940548814457 0.34585679185052 df.mm.trans1:exp5 -0.117347122499843 0.267882001719407 -0.438055269658463 0.661618779503183 df.mm.trans2:exp5 0.196902225159931 0.267882001719407 0.73503342477699 0.462815604654628 df.mm.trans1:exp6 -0.0615061346353727 0.267882001719407 -0.229601594136949 0.818536645839156 df.mm.trans2:exp6 0.234419562082154 0.267882001719407 0.875085151587365 0.382132870299612 df.mm.trans1:exp7 0.331187008485707 0.267882001719407 1.23631676021523 0.217177021327712 df.mm.trans2:exp7 0.366968352522229 0.267882001719407 1.36988804834530 0.171607587995890 df.mm.trans1:exp8 0.0786985876096528 0.267882001719407 0.293780795665719 0.769101048348357 df.mm.trans2:exp8 0.32012255443342 0.267882001719407 1.19501329831309 0.232897940530508 df.mm.trans1:probe2 -0.387689774592105 0.146725015091357 -2.64228819026336 0.00860780809550861 ** df.mm.trans1:probe3 -0.366847374956018 0.146725015091357 -2.50023743209435 0.012871839167056 * df.mm.trans1:probe4 -0.341938610111474 0.146725015091357 -2.33047248213653 0.0203538447209533 * df.mm.trans1:probe5 -0.442426149624757 0.146725015091357 -3.01534233511093 0.00275605565718882 ** df.mm.trans1:probe6 -0.452461732653981 0.146725015091357 -3.08373955437838 0.00220806008181825 ** df.mm.trans2:probe2 0.054225338569928 0.146725015091357 0.369571190953125 0.711927452172054 df.mm.trans2:probe3 -0.027071866622276 0.146725015091357 -0.184507506136019 0.853723122144324 df.mm.trans2:probe4 0.190092346166595 0.146725015091357 1.29556876206989 0.19598527187264 df.mm.trans2:probe5 -0.067776104228023 0.146725015091357 -0.461926033443057 0.644423829567476 df.mm.trans2:probe6 0.141120107823709 0.146725015091357 0.961799920319262 0.336819849373689 df.mm.trans3:probe2 0.0236512917243714 0.146725015091357 0.161194679105299 0.872033879709324 df.mm.trans3:probe3 -0.197779376371576 0.146725015091357 -1.34795948903758 0.178550717230967 df.mm.trans3:probe4 0.138224425788106 0.146725015091357 0.942064485064405 0.346815015736355