chr11.3329_chr11_78826630_78827695_+_1.R fitVsDatCorrelation=0.86825022808346 cont.fitVsDatCorrelation=0.291865449461203 fstatistic=7822.76919251286,39,393 cont.fstatistic=2097.44180502534,39,393 residuals=-0.60889671403544,-0.0825002643476882,-0.00473082103640306,0.0788870732341448,1.00249674752709 cont.residuals=-0.634131699200724,-0.205478659605184,-0.0526090262611637,0.189273359473295,0.98560266841064 predictedValues: Include Exclude Both chr11.3329_chr11_78826630_78827695_+_1.R.tl.Lung 138.222797989852 71.4006475300013 85.2891837525378 chr11.3329_chr11_78826630_78827695_+_1.R.tl.cerebhem 92.1113205801192 66.3042368710816 80.4501152858498 chr11.3329_chr11_78826630_78827695_+_1.R.tl.cortex 97.4413186122549 62.3199289317139 72.2866503267433 chr11.3329_chr11_78826630_78827695_+_1.R.tl.heart 107.846959846220 65.5045542650431 78.0129749344965 chr11.3329_chr11_78826630_78827695_+_1.R.tl.kidney 154.942475756154 81.379045357524 97.030262455438 chr11.3329_chr11_78826630_78827695_+_1.R.tl.liver 135.076617941093 66.133396033036 78.5543310945416 chr11.3329_chr11_78826630_78827695_+_1.R.tl.stomach 103.765004253536 58.3567807125113 77.7833992127285 chr11.3329_chr11_78826630_78827695_+_1.R.tl.testicle 119.963983154488 69.6404596326454 90.7117077788804 diffExp=66.8221504598512,25.8070837090376,35.121389680541,42.342405581177,73.5634303986298,68.9432219080566,45.4082235410248,50.3235235218429 diffExpScore=0.997556991890578 diffExp1.5=1,0,1,1,1,1,1,1 diffExp1.5Score=0.875 diffExp1.4=1,0,1,1,1,1,1,1 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 83.5737693962245 92.9886214807744 80.2802261791682 cerebhem 86.1852950271933 96.5681151722144 72.4049193465074 cortex 83.220227157546 78.8864925172135 84.2679606461953 heart 73.5550175133776 82.1491466417573 81.672522387863 kidney 80.935968769548 81.8745995663091 90.2577357125895 liver 90.6783164636817 88.001769003801 82.5983512851681 stomach 71.0683716012285 80.2581513255456 79.8315334593345 testicle 81.8581500685817 94.6070353581212 90.9899193795445 cont.diffExp=-9.4148520845499,-10.3828201450211,4.33373464033258,-8.5941291283797,-0.938630796761174,2.67654745988064,-9.18977972431712,-12.7488852895395 cont.diffExpScore=1.28769123055390 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=0.80400960550644 cont.tran.correlation=0.529782718548489 tran.covariance=0.0140727489437672 cont.tran.covariance=0.00346791918123584 tran.mean=93.1505954667046 cont.tran.mean=84.1505654414449 weightedLogRatios: wLogRatio Lung 3.03764220908438 cerebhem 1.43287231597535 cortex 1.94689261105858 heart 2.20947548286816 kidney 3.04007767841872 liver 3.2485787881385 stomach 2.50616135836248 testicle 2.45561007487502 cont.weightedLogRatios: wLogRatio Lung -0.478132771572158 cerebhem -0.513391989601425 cortex 0.235033076627985 heart -0.481050157105264 kidney -0.0507274219654038 liver 0.134596468204457 stomach -0.525878230438935 testicle -0.648070844210372 varWeightedLogRatios=0.381476265389078 cont.varWeightedLogRatios=0.116976764243935 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.40818887706689 0.0867047495191002 50.8413772200081 6.47726669952788e-175 *** df.mm.trans1 0.672007398614632 0.0707941315325402 9.49241673097927 2.22968876639746e-19 *** df.mm.trans2 -0.167686404239398 0.0707941315325402 -2.36864836970733 0.0183361006952419 * df.mm.exp2 -0.421511810673881 0.0961902831438085 -4.38206227175465 1.51042044124299e-05 *** df.mm.exp3 -0.32023402752387 0.0961902831438085 -3.32917231405907 0.000953313572118311 *** df.mm.exp4 -0.245168459269260 0.0961902831438085 -2.54878612741708 0.0111891774634316 * df.mm.exp5 0.116022665984255 0.0961902831438085 1.20617865123441 0.22847423371926 df.mm.exp6 -0.0174006450278955 0.0961902831438085 -0.180898157892734 0.856540766798136 df.mm.exp7 -0.396349858959639 0.0961902831438085 -4.12047710023973 4.61326192941717e-05 *** df.mm.exp8 -0.228275314696355 0.0961902831438085 -2.37316397494198 0.0181166598665743 * df.mm.trans1:exp2 0.0156428010852585 0.0785390373053895 0.199172304906583 0.842230967106419 df.mm.trans2:exp2 0.347458672013037 0.0785390373053895 4.42402509546923 1.25611156985467e-05 *** df.mm.trans1:exp3 -0.0293824975257958 0.0785390373053895 -0.37411328854905 0.7085217917826 df.mm.trans2:exp3 0.184208350356797 0.0785390373053895 2.34543682577271 0.0195013443041835 * df.mm.trans1:exp4 -0.00298521849159550 0.0785390373053895 -0.0380093593455677 0.969699519533931 df.mm.trans2:exp4 0.158981191905278 0.0785390373053895 2.02423148232769 0.0436223095224438 * df.mm.trans1:exp5 -0.00183560357813784 0.0785390373053895 -0.0233718624663086 0.981365511449474 df.mm.trans2:exp5 0.0147882074916559 0.0785390373053895 0.188291173396406 0.85074559103009 df.mm.trans1:exp6 -0.00562405869504508 0.0785390373053895 -0.0716084496067429 0.94294994228445 df.mm.trans2:exp6 -0.0592324390617627 0.0785390373053895 -0.754178318120256 0.451193795402771 df.mm.trans1:exp7 0.109611765449602 0.0785390373053895 1.39563418664517 0.163612689492123 df.mm.trans2:exp7 0.194618480172312 0.0785390373053895 2.47798402997432 0.0136319576162195 * df.mm.trans1:exp8 0.086600010572328 0.0785390373053895 1.10263651737409 0.270859807659471 df.mm.trans2:exp8 0.203314091346653 0.0785390373053895 2.588701088302 0.00999132567127791 ** df.mm.trans1:probe2 -0.0866697277575773 0.0480951415719042 -1.80204746103101 0.0723040967988435 . df.mm.trans1:probe3 -0.275723789515264 0.0480951415719042 -5.73288237655035 1.96997672909813e-08 *** df.mm.trans1:probe4 -0.624677160429514 0.0480951415719042 -12.9883630656455 2.42116718249793e-32 *** df.mm.trans1:probe5 -0.501357278432436 0.0480951415719042 -10.4242811653415 1.25734469493114e-22 *** df.mm.trans1:probe6 -0.327525014335426 0.0480951415719042 -6.80993970764724 3.67124399924617e-11 *** df.mm.trans2:probe2 0.0418197070454086 0.0480951415719042 0.869520406398771 0.385093291073558 df.mm.trans2:probe3 0.00600551456001251 0.0480951415719042 0.124867385015054 0.900692384675334 df.mm.trans2:probe4 0.0678812393513403 0.0480951415719042 1.41139493788276 0.158919375057860 df.mm.trans2:probe5 0.149919087576897 0.0480951415719042 3.11713579952274 0.00196046917129687 ** df.mm.trans2:probe6 0.0680280377610805 0.0480951415719042 1.41444718817130 0.158022400434463 df.mm.trans3:probe2 -0.431715319688222 0.0480951415719042 -8.97627713690768 1.170474536839e-17 *** df.mm.trans3:probe3 -0.867865084783572 0.0480951415719042 -18.0447557990047 1.87015175492500e-53 *** df.mm.trans3:probe4 -0.578328572651297 0.0480951415719042 -12.0246776233452 1.41483239098241e-28 *** df.mm.trans3:probe5 -0.40362599190598 0.0480951415719042 -8.39224043664664 8.70874061175547e-16 *** df.mm.trans3:probe6 -0.517238395471406 0.0480951415719042 -10.7544832714155 8.0859334545881e-24 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.64675809808007 0.167154073182910 27.7992513708913 7.93994950309023e-95 *** df.mm.trans1 -0.216627062324723 0.136480729241989 -1.58723552788636 0.113263514564816 df.mm.trans2 -0.102575476749926 0.136480729241989 -0.751574799751058 0.452756640816719 df.mm.exp2 0.171790441629700 0.185440794388813 0.926389698641543 0.354812029357939 df.mm.exp3 -0.217184782756647 0.185440794388812 -1.17118125745987 0.242235529151700 df.mm.exp4 -0.268831003939350 0.185440794388813 -1.44968643401998 0.147943506563572 df.mm.exp5 -0.276505673968384 0.185440794388813 -1.49107252737840 0.136744646136323 df.mm.exp6 -0.00199804607521333 0.185440794388812 -0.0107745767688206 0.99140876519895 df.mm.exp7 -0.303711359909511 0.185440794388813 -1.6377807316373 0.102267817790046 df.mm.exp8 -0.128712511766091 0.185440794388812 -0.694089518923331 0.488036142594802 df.mm.trans1:exp2 -0.141020577497900 0.151411774582987 -0.931371274699701 0.352233328914324 df.mm.trans2:exp2 -0.134018961576388 0.151411774582987 -0.88512905912039 0.37662825418629 df.mm.trans1:exp3 0.212945508256903 0.151411774582987 1.40639992393848 0.16039561276026 df.mm.trans2:exp3 0.0527176624532162 0.151411774582987 0.348174127133833 0.727895840647523 df.mm.trans1:exp4 0.141134960086946 0.151411774582987 0.932126715215216 0.35184331949148 df.mm.trans2:exp4 0.144890324564087 0.151411774582987 0.956929043088879 0.33919135219792 df.mm.trans1:exp5 0.244434299352254 0.151411774582987 1.6143678391292 0.107250223432055 df.mm.trans2:exp5 0.149217341119838 0.151411774582987 0.98550685064492 0.324981500467647 df.mm.trans1:exp6 0.0835865982035428 0.151411774582987 0.552048203871556 0.581229116218422 df.mm.trans2:exp6 -0.0531221733315395 0.151411774582987 -0.350845721727037 0.725892084928151 df.mm.trans1:exp7 0.141624046228117 0.151411774582987 0.935356887654034 0.350178784277192 df.mm.trans2:exp7 0.156482554912601 0.151411774582987 1.03348999999227 0.302010195459252 df.mm.trans1:exp8 0.107970676198934 0.151411774582987 0.713092997531421 0.476211413675889 df.mm.trans2:exp8 0.145967218595980 0.151411774582987 0.96404139637091 0.335617986872109 df.mm.trans1:probe2 -0.11348079751416 0.0927203971944063 -1.22390327207319 0.221721958736914 df.mm.trans1:probe3 -0.0286297902064027 0.0927203971944063 -0.308775534539339 0.757655897712432 df.mm.trans1:probe4 0.0423249972124148 0.0927203971944063 0.456479895396395 0.648297097262696 df.mm.trans1:probe5 0.0503993008054206 0.0927203971944063 0.543562175426715 0.587050988235125 df.mm.trans1:probe6 -0.00342964751785616 0.0927203971944063 -0.0369891374674036 0.970512447902453 df.mm.trans2:probe2 -0.0994290001137529 0.0927203971944063 -1.07235304336845 0.284219537794695 df.mm.trans2:probe3 0.0323158367539084 0.0927203971944063 0.348529964622046 0.727628846411296 df.mm.trans2:probe4 0.0159997419175957 0.0927203971944063 0.172559031256619 0.863086887276687 df.mm.trans2:probe5 -0.0571193920083856 0.0927203971944063 -0.616039121236978 0.538225330744717 df.mm.trans2:probe6 -0.0322330105250701 0.0927203971944063 -0.347636674349953 0.728299168468245 df.mm.trans3:probe2 0.093653426599349 0.0927203971944063 1.01006282795561 0.313086657320663 df.mm.trans3:probe3 0.0121127315719610 0.0927203971944063 0.130637183817972 0.896129169574742 df.mm.trans3:probe4 0.125454151355947 0.0927203971944062 1.35303725126315 0.176821549649882 df.mm.trans3:probe5 -0.0136132368799701 0.0927203971944063 -0.14682030375072 0.883349144302223 df.mm.trans3:probe6 0.130199621137889 0.0927203971944063 1.40421768108802 0.161043814011707