chr8.22859_chr8_105689933_105690296_-_0.R fitVsDatCorrelation=0.87361655130414 cont.fitVsDatCorrelation=0.269820506223800 fstatistic=10253.6503689428,47,577 cont.fstatistic=2609.50866845436,47,577 residuals=-0.513750767241154,-0.08441853456988,0.00282507361749836,0.0723710283827173,0.832667118407194 cont.residuals=-0.552822270707198,-0.188131715383886,-0.0790278520058537,0.133124760531902,1.02950354000960 predictedValues: Include Exclude Both chr8.22859_chr8_105689933_105690296_-_0.R.tl.Lung 45.4971931620212 48.9251036297995 64.7982906348866 chr8.22859_chr8_105689933_105690296_-_0.R.tl.cerebhem 51.2025659959638 64.0679426802503 65.0865541933812 chr8.22859_chr8_105689933_105690296_-_0.R.tl.cortex 47.6903766328333 43.2571838259283 64.6106395598469 chr8.22859_chr8_105689933_105690296_-_0.R.tl.heart 48.5049997711342 45.8312472532587 63.9313571178262 chr8.22859_chr8_105689933_105690296_-_0.R.tl.kidney 45.3127882131654 45.4418209870458 64.8961667835279 chr8.22859_chr8_105689933_105690296_-_0.R.tl.liver 45.2164246842537 48.5566330455748 66.0567588194783 chr8.22859_chr8_105689933_105690296_-_0.R.tl.stomach 45.5661017431149 46.2005710266984 65.5097339869691 chr8.22859_chr8_105689933_105690296_-_0.R.tl.testicle 47.5803733924039 51.3494451022469 69.6983066612181 diffExp=-3.42791046777832,-12.8653766842864,4.43319280690491,2.67375251787541,-0.129032773880432,-3.34020836132112,-0.634469283583471,-3.76907170984303 diffExpScore=1.73170164188582 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,-1,0,0,0,0,0,0 diffExp1.2Score=0.5 cont.predictedValues: Include Exclude Both Lung 55.2874510170392 56.2817052677943 54.5420754426626 cerebhem 57.810386783049 58.5898443449578 58.6202671233229 cortex 58.3648103555894 52.3363168880351 51.5120582752099 heart 50.9315855958398 57.7889752914186 53.2177143148858 kidney 58.0377366556818 53.600793424619 61.3104482433395 liver 54.327509777629 59.5948192727185 60.2490999775647 stomach 55.2983681481755 53.3770869860027 58.1227910879425 testicle 53.5617782249663 53.2696351397653 61.7692580202924 cont.diffExp=-0.994254250755134,-0.7794575619088,6.02849346755428,-6.85738969557875,4.43694323106284,-5.26730949508946,1.92128116217277,0.292143085201033 cont.diffExpScore=11.9741710088574 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=0.696504289568354 cont.tran.correlation=-0.344735899413538 tran.covariance=0.00351524963197712 cont.tran.covariance=-0.000819304445904603 tran.mean=48.1375481966058 cont.tran.mean=55.5286751983301 weightedLogRatios: wLogRatio Lung -0.279952411809734 cerebhem -0.907347483791488 cortex 0.372307817437948 heart 0.218486003816551 kidney -0.0108481937581669 liver -0.27418407936342 stomach -0.0529073931611777 testicle -0.297352688609146 cont.weightedLogRatios: wLogRatio Lung -0.0716767507933908 cerebhem -0.0544269982793106 cortex 0.437420756749262 heart -0.50445570110818 kidney 0.319814499447079 liver -0.373973470778374 stomach 0.141272711623479 testicle 0.0217572264164664 varWeightedLogRatios=0.152121219869143 cont.varWeightedLogRatios=0.102227646170593 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.34559944064927 0.0719885080961597 46.4740766148444 3.35084814950181e-197 *** df.mm.trans1 0.46138065302121 0.0570742865681057 8.08386194141301 3.70126373475979e-15 *** df.mm.trans2 0.533712762900787 0.0570742865681057 9.35119464461316 1.89029609691151e-19 *** df.mm.exp2 0.38335374265564 0.0758515715207696 5.0539986841363 5.81656539403651e-07 *** df.mm.exp3 -0.0731481896926416 0.0758515715207696 -0.964359580507995 0.335269668763361 df.mm.exp4 0.0121609880814561 0.0758515715207696 0.160326118993146 0.872680296677591 df.mm.exp5 -0.0794284600320037 0.0758515715207696 -1.04715641930049 0.295465886050501 df.mm.exp6 -0.0329851901853123 0.0758515715207696 -0.434864954330977 0.663823048298831 df.mm.exp7 -0.066704569747455 0.0758515715207696 -0.879409198914092 0.379545536435499 df.mm.exp8 0.0202364170464291 0.0758515715207696 0.266789687289314 0.789726413835495 df.mm.trans1:exp2 -0.265214730064619 0.0581754997054826 -4.55887326120595 6.28251807952655e-06 *** df.mm.trans2:exp2 -0.113700249436302 0.0581754997054826 -1.95443528653673 0.0511323428124776 . df.mm.trans1:exp3 0.120227184186490 0.0581754997054826 2.06662916167714 0.0392146775974358 * df.mm.trans2:exp3 -0.0499791221168961 0.0581754997054826 -0.859109459650863 0.390636893809847 df.mm.trans1:exp4 0.0518552573061049 0.0581754997054826 0.891359035481013 0.373108125920696 df.mm.trans2:exp4 -0.0774855065689188 0.0581754997054826 -1.33192678982036 0.183410114026057 df.mm.trans1:exp5 0.0753671178857881 0.0581754997054826 1.29551302983798 0.195661352394294 df.mm.trans2:exp5 0.00557067676498773 0.0581754997054826 0.0957564059301538 0.923747288043807 df.mm.trans1:exp6 0.0267949536806378 0.0581754997054826 0.460588285726621 0.645267554499464 df.mm.trans2:exp6 0.0254253671526213 0.0581754997054825 0.437045960607798 0.662241532147681 df.mm.trans1:exp7 0.0682179916880536 0.0581754997054826 1.17262407772021 0.241430478047627 df.mm.trans2:exp7 0.0094060962282026 0.0581754997054826 0.161684837703528 0.871610644129729 df.mm.trans1:exp8 0.0245333001658762 0.0581754997054826 0.421711894011701 0.673392386987228 df.mm.trans2:exp8 0.0281270816659552 0.0581754997054826 0.483486722217264 0.628933604198818 df.mm.trans1:probe2 -0.0380285392754947 0.042152154181499 -0.902173092073803 0.367341367451566 df.mm.trans1:probe3 0.076302492366983 0.042152154181499 1.81016827843339 0.0707897919470058 . df.mm.trans1:probe4 0.0898644911869724 0.042152154181499 2.13190744178894 0.0334362128800598 * df.mm.trans1:probe5 0.0613994277659339 0.042152154181499 1.45661423379597 0.145766836483194 df.mm.trans1:probe6 0.0238729606917385 0.042152154181499 0.566352091732872 0.571374665784061 df.mm.trans2:probe2 0.0794100450461164 0.042152154181499 1.88389055288117 0.0600823404580572 . df.mm.trans2:probe3 0.0203306168019756 0.042152154181499 0.482315013236001 0.629765093852547 df.mm.trans2:probe4 -0.0428282514474476 0.042152154181499 -1.01603944754608 0.310036446694775 df.mm.trans2:probe5 0.125981579111865 0.042152154181499 2.98873406491664 0.00292058785080485 ** df.mm.trans2:probe6 0.0366745678024852 0.042152154181499 0.870052041577083 0.38463376666109 df.mm.trans3:probe2 -0.301552158427263 0.042152154181499 -7.15389674104999 2.56974897032373e-12 *** df.mm.trans3:probe3 -0.4678786496519 0.042152154181499 -11.0997565542512 4.43445601054656e-26 *** df.mm.trans3:probe4 -0.485622309262873 0.042152154181499 -11.5206996817263 8.73951581880106e-28 *** df.mm.trans3:probe5 -0.229669751613855 0.042152154181499 -5.44858871565475 7.52876137782097e-08 *** df.mm.trans3:probe6 0.221349152122628 0.042152154181499 5.25119430835114 2.1280511222437e-07 *** df.mm.trans3:probe7 -0.457844242421434 0.042152154181499 -10.8617044920183 3.92172306447874e-25 *** df.mm.trans3:probe8 -0.406224977810767 0.042152154181499 -9.63711074080913 1.76155653884046e-20 *** df.mm.trans3:probe9 -0.0467943326986507 0.042152154181499 -1.110129093217 0.267405824146935 df.mm.trans3:probe10 0.443337788526582 0.042152154181499 10.5175594731803 8.67853094530254e-24 *** df.mm.trans3:probe11 -0.200789171686586 0.042152154181499 -4.7634379686036 2.41067358223106e-06 *** df.mm.trans3:probe12 0.0381235818283793 0.042152154181499 0.904427841676287 0.366146040172452 df.mm.trans3:probe13 -0.316172216377509 0.042152154181499 -7.5007368547793 2.41025059139211e-13 *** df.mm.trans3:probe14 -0.162053569657968 0.042152154181499 -3.84449081677289 0.000134235277811002 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.88892355111398 0.142450408594280 27.3001923230015 5.50243364741993e-106 *** df.mm.trans1 0.108782082831015 0.112938240517411 0.963199730513288 0.335850787370919 df.mm.trans2 0.125162186529283 0.112938240517411 1.10823566894499 0.268221783701695 df.mm.exp2 0.0127062879532888 0.150094614285085 0.0846551890872966 0.932564885474434 df.mm.exp3 0.0386446914973969 0.150094614285085 0.257468875092322 0.796908632876182 df.mm.exp4 -0.0310530833710894 0.150094614285085 -0.206890057441422 0.836168710048336 df.mm.exp5 -0.117236029651816 0.150094614285085 -0.781080854967531 0.435075284436987 df.mm.exp6 -0.0598313228455845 0.150094614285085 -0.398624048774612 0.690317708285065 df.mm.exp7 -0.116375948598537 0.150094614285085 -0.77535059570822 0.438450165327451 df.mm.exp8 -0.211146663574821 0.150094614285085 -1.40675709505322 0.160037800713923 df.mm.trans1:exp2 0.0319162164834635 0.115117314171211 0.277249488604254 0.781687841178143 df.mm.trans2:exp2 0.0274855574179181 0.115117314171211 0.238761281183468 0.811375470295891 df.mm.trans1:exp3 0.0155224970928467 0.115117314171211 0.134840681478726 0.892784863008842 df.mm.trans2:exp3 -0.111323697342058 0.115117314171211 -0.967045645075506 0.333926366898258 df.mm.trans1:exp4 -0.0510096005971127 0.115117314171211 -0.443109717807066 0.657852459582951 df.mm.trans2:exp4 0.0574815704544366 0.115117314171211 0.499330364578744 0.617736999115571 df.mm.trans1:exp5 0.165783503397557 0.115117314171211 1.44012657514743 0.150373938842913 df.mm.trans2:exp5 0.0684303688179143 0.115117314171211 0.594440283032834 0.552450678099874 df.mm.trans1:exp6 0.0423160900070453 0.115117314171211 0.367591011931617 0.713313010152234 df.mm.trans2:exp6 0.117030436685093 0.115117314171211 1.01661889462637 0.309760845558269 df.mm.trans1:exp7 0.116573390390878 0.115117314171211 1.01264862918450 0.311652467938541 df.mm.trans2:exp7 0.0633879883240401 0.115117314171211 0.550638179672649 0.58209484903231 df.mm.trans1:exp8 0.179436427236205 0.115117314171211 1.55872666529845 0.119609378424061 df.mm.trans2:exp8 0.156143603718157 0.115117314171211 1.35638678544853 0.175506627540121 df.mm.trans1:probe2 -0.00771526821587115 0.0834104184832235 -0.0924976562421028 0.926334758992036 df.mm.trans1:probe3 0.112383842572868 0.0834104184832235 1.34735977371307 0.178393234660138 df.mm.trans1:probe4 0.0672401764355937 0.0834104184832235 0.80613642346271 0.42049630416306 df.mm.trans1:probe5 0.0331860444728291 0.0834104184832235 0.397864500338215 0.690877225153409 df.mm.trans1:probe6 0.0917116703539961 0.0834104184832235 1.09952296154038 0.271998562638423 df.mm.trans2:probe2 0.0681836466404719 0.0834104184832235 0.817447602833761 0.414010088359169 df.mm.trans2:probe3 0.0756167535095438 0.0834104184832235 0.906562452084481 0.365016647802008 df.mm.trans2:probe4 0.096336031581403 0.0834104184832235 1.15496401208896 0.248583242574761 df.mm.trans2:probe5 0.0309617440390228 0.0834104184832235 0.371197562631222 0.710626641060437 df.mm.trans2:probe6 0.0545777013486825 0.0834104184832235 0.654327149307611 0.513161772504142 df.mm.trans3:probe2 -0.108401763765799 0.0834104184832235 -1.29961898929451 0.194250568492678 df.mm.trans3:probe3 -0.0759965451426789 0.0834104184832235 -0.911115739791717 0.362614866689631 df.mm.trans3:probe4 -0.118395823965643 0.0834104184832235 -1.41943687753414 0.156311687748608 df.mm.trans3:probe5 -0.0913459856261153 0.0834104184832235 -1.09513880025057 0.273912746483063 df.mm.trans3:probe6 -0.261635504430428 0.0834104184832235 -3.13672451461266 0.00179551542829172 ** df.mm.trans3:probe7 -0.0802449947598129 0.0834104184832235 -0.962050019877944 0.336427467021052 df.mm.trans3:probe8 -0.169705691927582 0.0834104184832235 -2.03458626648318 0.0423492235813121 * df.mm.trans3:probe9 -0.140724831865960 0.0834104184832235 -1.68713734357135 0.0921174243347133 . df.mm.trans3:probe10 -0.102947383842321 0.0834104184832235 -1.23422691930298 0.217620799972671 df.mm.trans3:probe11 -0.219905853364256 0.0834104184832235 -2.63643148377784 0.00860387356369386 ** df.mm.trans3:probe12 -0.115318293974306 0.0834104184832235 -1.38254064745521 0.167340621462077 df.mm.trans3:probe13 -0.177568576008710 0.0834104184832235 -2.12885367604797 0.0336892680518855 * df.mm.trans3:probe14 -0.072344214033209 0.0834104184832235 -0.867328270841366 0.38612272123848