chr2.14481_chr2_138026902_138070741_+_2.R fitVsDatCorrelation=0.671684534659504 cont.fitVsDatCorrelation=0.221079650667785 fstatistic=13180.2316879647,69,1083 cont.fstatistic=7598.92964330326,69,1083 residuals=-0.398598826435385,-0.0787349823076014,-0.00451566867682649,0.0687725095591772,1.02602358170304 cont.residuals=-0.368473837691104,-0.113409994022364,-0.0234193316535423,0.0712270232237722,1.37505307227575 predictedValues: Include Exclude Both chr2.14481_chr2_138026902_138070741_+_2.R.tl.Lung 47.570354418767 48.9807815352689 49.1761862652517 chr2.14481_chr2_138026902_138070741_+_2.R.tl.cerebhem 57.1545287027844 71.7961796439383 52.8182637923546 chr2.14481_chr2_138026902_138070741_+_2.R.tl.cortex 48.97416316998 50.7864045411366 50.6660922106192 chr2.14481_chr2_138026902_138070741_+_2.R.tl.heart 48.4896936593987 48.8127287980711 48.7519969725356 chr2.14481_chr2_138026902_138070741_+_2.R.tl.kidney 46.3414689498119 48.4531166355163 49.7259971272184 chr2.14481_chr2_138026902_138070741_+_2.R.tl.liver 50.1520189977391 53.6857403211668 50.9405870733776 chr2.14481_chr2_138026902_138070741_+_2.R.tl.stomach 49.0119396302521 51.7798046645687 50.5103228152191 chr2.14481_chr2_138026902_138070741_+_2.R.tl.testicle 50.0087209990646 58.3372803077269 49.3104297588081 diffExp=-1.41042711650186,-14.6416509411539,-1.81224137115662,-0.323035138672424,-2.11164768570442,-3.53372132342769,-2.7678650343166,-8.32855930866234 diffExpScore=0.972167444598523 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 49.4913254717766 51.6827933150186 52.7940040450494 cerebhem 49.1603604659268 52.374165993039 51.8809133493711 cortex 51.6809255365851 46.419722315555 50.9212850415133 heart 48.8345168715804 49.6921897666001 51.9300265260169 kidney 49.0079820773734 50.636393153804 53.0182889694311 liver 51.517258020987 53.2904091912466 50.6321210123464 stomach 49.9763374751128 47.4306646422297 49.6795793723454 testicle 48.7256959595297 50.0528805035886 51.2176373423797 cont.diffExp=-2.19146784324202,-3.21380552711224,5.26120322103008,-0.857672895019682,-1.62841107643057,-1.77315117025957,2.54567283288309,-1.32718454405885 cont.diffExpScore=4.49208868634153 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=0.966445785000544 cont.tran.correlation=-0.197170928375270 tran.covariance=0.0079980639166241 cont.tran.covariance=-0.000240667807548198 tran.mean=51.8959328109495 cont.tran.mean=49.9983512974971 weightedLogRatios: wLogRatio Lung -0.113273850665353 cerebhem -0.948735402493755 cortex -0.142053443100317 heart -0.0257936005416632 kidney -0.171924462339380 liver -0.268889099075054 stomach -0.215324462377512 testicle -0.614515051269553 cont.weightedLogRatios: wLogRatio Lung -0.169993751641379 cerebhem -0.24866476507184 cortex 0.417798337462261 heart -0.067850801051026 kidney -0.127752909491239 liver -0.133965115496580 stomach 0.203131879034314 testicle -0.104797172884161 varWeightedLogRatios=0.096865524365084 cont.varWeightedLogRatios=0.0499528883273159 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.83582640980888 0.0628608660064542 61.0208966802182 0 *** df.mm.trans1 -0.0179726471560009 0.0536110765093848 -0.335241303219397 0.737507991463258 df.mm.trans2 0.0664587813000998 0.0466978231049203 1.42316658210771 0.154975866566963 df.mm.exp2 0.494504578603509 0.0585463737132262 8.44637416871807 9.5604693047174e-17 *** df.mm.exp3 0.0354363930914400 0.0585463737132262 0.605270503430591 0.545126083698243 df.mm.exp4 0.0243679470538852 0.0585463737132262 0.416216163502201 0.677334300183119 df.mm.exp5 -0.0481222775391256 0.0585463737132262 -0.82195146320829 0.411285437723235 df.mm.exp6 0.109317920204047 0.0585463737132262 1.86720224107324 0.062143344460338 . df.mm.exp7 0.0586581275142998 0.0585463737132262 1.00190880824867 0.316611438725536 df.mm.exp8 0.222074858768158 0.0585463737132262 3.79314455675654 0.000156976750383392 *** df.mm.trans1:exp2 -0.310955709993301 0.0532285906985028 -5.84189259780736 6.81972547441748e-09 *** df.mm.trans2:exp2 -0.112101319875466 0.0353302917503101 -3.17295200016235 0.00155144355913393 ** df.mm.trans1:exp3 -0.0063532771728141 0.0532285906985028 -0.119358357781823 0.905013587295147 df.mm.trans2:exp3 0.000764290922653086 0.0353302917503101 0.0216327373703722 0.982744903865759 df.mm.trans1:exp4 -0.00522643444476228 0.0532285906985027 -0.098188480592429 0.921800798588671 df.mm.trans2:exp4 -0.0278048397893656 0.0353302917503101 -0.786997174715423 0.431455704064882 df.mm.trans1:exp5 0.0219497345481269 0.0532285906985028 0.412367381140231 0.680151780137761 df.mm.trans2:exp5 0.0372909330406334 0.0353302917503101 1.05549462495752 0.291434566316883 df.mm.trans1:exp6 -0.0564689083137566 0.0532285906985028 -1.06087551018601 0.288983003821241 df.mm.trans2:exp6 -0.0175985049284100 0.0353302917503101 -0.498113773098279 0.618504986972649 df.mm.trans1:exp7 -0.0288039540464063 0.0532285906985028 -0.541136890314409 0.588524520723121 df.mm.trans2:exp7 -0.00308593321765289 0.0353302917503101 -0.0873452514760455 0.930413232690961 df.mm.trans1:exp8 -0.172087209452642 0.0532285906985028 -3.23298451441966 0.00126201362592654 ** df.mm.trans2:exp8 -0.0472615209924046 0.0353302917503101 -1.33770536984003 0.181273336160547 df.mm.trans1:probe2 0.19773027469556 0.0404300169410679 4.89067998620376 1.15693368449288e-06 *** df.mm.trans1:probe3 0.103041135715636 0.0404300169410679 2.54862954586025 0.0109517895833983 * df.mm.trans1:probe4 -0.035885698598801 0.0404300169410679 -0.887600384909785 0.374952820186856 df.mm.trans1:probe5 -0.0245443991886301 0.0404300169410679 -0.607083574177244 0.543922701708906 df.mm.trans1:probe6 -0.0325630955334748 0.0404300169410679 -0.805418795172403 0.42075484300036 df.mm.trans1:probe7 0.0631831535056054 0.0404300169410679 1.56277830894069 0.118396891666622 df.mm.trans1:probe8 0.0585894852495688 0.0404300169410679 1.44915806824842 0.147582929459578 df.mm.trans1:probe9 0.0968891305690624 0.0404300169410679 2.39646524784521 0.0167228534682560 * df.mm.trans1:probe10 -0.0185496901969791 0.0404300169410679 -0.458809854668568 0.646462779449551 df.mm.trans1:probe11 0.163861749163489 0.0404300169410679 4.05297255755145 5.41856351787508e-05 *** df.mm.trans1:probe12 0.175988869472107 0.0404300169410679 4.35292593937406 1.47047090310637e-05 *** df.mm.trans1:probe13 0.0787398266039434 0.0404300169410679 1.94755858546181 0.0517259428333767 . df.mm.trans1:probe14 0.311658401478603 0.0404300169410679 7.70858943573747 2.86818957993678e-14 *** df.mm.trans1:probe15 0.0719041282711124 0.0404300169410679 1.77848375319560 0.0756049134138954 . df.mm.trans1:probe16 0.105201790737038 0.0404300169410679 2.60207139884171 0.00939273212730242 ** df.mm.trans1:probe17 0.0202075493206971 0.0404300169410679 0.499815504657153 0.617306523215083 df.mm.trans1:probe18 0.133686699405534 0.0404300169410679 3.30661992055061 0.00097529230167679 *** df.mm.trans1:probe19 0.114438863412217 0.0404300169410679 2.83054205935720 0.00473284230062085 ** df.mm.trans1:probe20 0.0289630476286097 0.0404300169410679 0.716374857592249 0.473914359189148 df.mm.trans1:probe21 0.0988581783660043 0.0404300169410679 2.44516786896486 0.0146369293977020 * df.mm.trans1:probe22 0.151552525652271 0.0404300169410679 3.74851501727488 0.000187283419433724 *** df.mm.trans2:probe2 -0.0208633564948295 0.0404300169410679 -0.516036303552396 0.605934390309074 df.mm.trans2:probe3 -0.0447792437470614 0.0404300169410679 -1.10757420191866 0.268291676428473 df.mm.trans2:probe4 -0.0862495344306638 0.0404300169410679 -2.13330443458344 0.0331240333989517 * df.mm.trans2:probe5 -0.0910812764373284 0.0404300169410679 -2.25281321474813 0.0244704454715117 * df.mm.trans2:probe6 -0.0393133598940783 0.0404300169410679 -0.972380495199463 0.331078415835648 df.mm.trans3:probe2 0.374991261728843 0.0404300169410679 9.2750706059669 9.34442803197643e-20 *** df.mm.trans3:probe3 -0.061754995761081 0.0404300169410679 -1.52745411536921 0.126940117996171 df.mm.trans3:probe4 -0.046880925961646 0.0404300169410679 -1.15955741571865 0.246484629062666 df.mm.trans3:probe5 0.0294654647665709 0.0404300169410679 0.72880169230502 0.466280542309287 df.mm.trans3:probe6 -0.0400539996265433 0.0404300169410679 -0.990699550903658 0.322053598491404 df.mm.trans3:probe7 -0.0255274619424845 0.0404300169410679 -0.631398744642976 0.527913074985214 df.mm.trans3:probe8 -0.131734420418455 0.0404300169410679 -3.25833206081698 0.00115551532701538 ** df.mm.trans3:probe9 0.271014324007676 0.0404300169410679 6.70329484162017 3.27245898841699e-11 *** df.mm.trans3:probe10 0.0176441942663030 0.0404300169410679 0.436413229606648 0.662623927618138 df.mm.trans3:probe11 -0.0270405217788769 0.0404300169410679 -0.66882291487268 0.503750981901961 df.mm.trans3:probe12 -0.0683710654649172 0.0404300169410679 -1.69109663160857 0.091106066544249 . df.mm.trans3:probe13 -0.166854637204606 0.0404300169410679 -4.12699894357746 3.95724258286362e-05 *** df.mm.trans3:probe14 0.0429993243947014 0.0404300169410679 1.06354950227645 0.287769907918875 df.mm.trans3:probe15 -0.139722502784860 0.0404300169410679 -3.45591007267013 0.000569700605988484 *** df.mm.trans3:probe16 0.0176398441729642 0.0404300169410679 0.436305633971824 0.662701956073791 df.mm.trans3:probe17 0.0766595652616816 0.0404300169410679 1.89610519761649 0.0582121038620827 . df.mm.trans3:probe18 -0.143311251078140 0.0404300169410679 -3.54467452455028 0.000409875083761899 *** df.mm.trans3:probe19 0.00289638937289945 0.0404300169410679 0.0716395785122058 0.94290196893085 df.mm.trans3:probe20 0.239880281476542 0.0404300169410679 5.93322238341376 3.9929987692916e-09 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.88334578661237 0.0827515331918735 46.9277805114278 3.18478929154652e-263 *** df.mm.trans1 -0.00930752241073688 0.0705748911693791 -0.131881498596986 0.895102518853207 df.mm.trans2 0.0645358038017233 0.0614741206119923 1.04980442435371 0.294042243538828 df.mm.exp2 0.0240254122599102 0.0770718333262612 0.311727530318445 0.755307603030807 df.mm.exp3 -0.02799251765721 0.0770718333262611 -0.36320036061309 0.716526096166764 df.mm.exp4 -0.036136714625027 0.0770718333262611 -0.468870572626095 0.63925651637781 df.mm.exp5 -0.0345078894210952 0.0770718333262612 -0.447736714332668 0.654432765124797 df.mm.exp6 0.112562361145047 0.0770718333262612 1.46048635781826 0.14444648577224 df.mm.exp7 -0.0153000699662079 0.0770718333262612 -0.198517010766300 0.842677835533211 df.mm.exp8 -0.0173220616749761 0.0770718333262612 -0.224752168560052 0.822214475123106 df.mm.trans1:exp2 -0.0307352063077293 0.0700713777868022 -0.438627115357196 0.661019230527931 df.mm.trans2:exp2 -0.0107368661318784 0.0465096330386887 -0.230852523023499 0.817472978052045 df.mm.trans1:exp3 0.0712838747374576 0.0700713777868022 1.01730374068489 0.309236162832407 df.mm.trans2:exp3 -0.0794079717413929 0.0465096330386886 -1.70734461988419 0.0880446367371681 . df.mm.trans1:exp4 0.0227766791750591 0.0700713777868021 0.325049683543529 0.745206249938666 df.mm.trans2:exp4 -0.00314042040157212 0.0465096330386886 -0.0675219346271726 0.94617866382462 df.mm.trans1:exp5 0.0246936625798819 0.0700713777868022 0.352407264703919 0.724601421292553 df.mm.trans2:exp5 0.0140535312526465 0.0465096330386886 0.302163881640524 0.762585153914341 df.mm.trans1:exp6 -0.0724429136309875 0.0700713777868022 -1.03384457276409 0.301439630292612 df.mm.trans2:exp6 -0.081930894518015 0.0465096330386887 -1.76158978613874 0.078420756692406 . df.mm.trans1:exp7 0.0250523016548654 0.0700713777868022 0.357525461124641 0.720768129520702 df.mm.trans2:exp7 -0.070555885350473 0.0465096330386886 -1.51701659937376 0.129554320852012 df.mm.trans1:exp8 0.00173117916095676 0.0700713777868022 0.0247059386533545 0.980294069464796 df.mm.trans2:exp8 -0.0147227899275186 0.0465096330386886 -0.316553560318818 0.751643382388958 df.mm.trans1:probe2 -0.000483316617465482 0.0532230320928649 -0.00908096736432038 0.99275620836892 df.mm.trans1:probe3 0.0744293894308697 0.0532230320928649 1.39844323978017 0.162266284950442 df.mm.trans1:probe4 0.0630115833853991 0.0532230320928649 1.18391570167320 0.236706216316205 df.mm.trans1:probe5 0.0891916818190476 0.0532230320928649 1.67580985734566 0.0940640872077059 . df.mm.trans1:probe6 0.0841240149322101 0.0532230320928649 1.58059418308653 0.114262849939502 df.mm.trans1:probe7 0.0542425526275694 0.0532230320928649 1.01915562670172 0.308356699933905 df.mm.trans1:probe8 0.0887329535199103 0.0532230320928649 1.66719087640642 0.0957655767550765 . df.mm.trans1:probe9 0.0364315210930583 0.0532230320928649 0.684506681796926 0.493801724727902 df.mm.trans1:probe10 -0.000676616790844427 0.0532230320928649 -0.0127128569011974 0.989859222393422 df.mm.trans1:probe11 0.0147217821436046 0.0532230320928649 0.276605476326820 0.782135838494975 df.mm.trans1:probe12 0.0339193435373887 0.0532230320928649 0.637305734070268 0.524060416293931 df.mm.trans1:probe13 0.0424615332875085 0.0532230320928649 0.797803725526584 0.425159288941741 df.mm.trans1:probe14 0.08726613757891 0.0532230320928649 1.63963107976723 0.101372311397397 df.mm.trans1:probe15 0.0578085833439866 0.0532230320928649 1.08615727197054 0.277651111903586 df.mm.trans1:probe16 0.0624018483090025 0.0532230320928649 1.17245947581720 0.241270466433211 df.mm.trans1:probe17 0.0323640884034271 0.0532230320928649 0.608084265980139 0.543259083789888 df.mm.trans1:probe18 0.111397068020975 0.0532230320928649 2.09302370873209 0.0365792524033062 * df.mm.trans1:probe19 0.0884576176570205 0.0532230320928649 1.66201762993655 0.096798629524004 . df.mm.trans1:probe20 0.104723021105604 0.0532230320928649 1.96762598799108 0.0493659607578375 * df.mm.trans1:probe21 0.0215800774083774 0.0532230320928649 0.405465013168057 0.685215815780916 df.mm.trans1:probe22 0.0197793107178892 0.0532230320928649 0.371630663269573 0.710240550082525 df.mm.trans2:probe2 -0.0104695807305359 0.0532230320928649 -0.196711467175871 0.844090243478552 df.mm.trans2:probe3 -0.0295800402930682 0.0532230320928649 -0.555775180967823 0.578479346665373 df.mm.trans2:probe4 0.00902484772566621 0.0532230320928649 0.16956658369105 0.865382671351745 df.mm.trans2:probe5 -0.0314492193138160 0.0532230320928649 -0.590894920434872 0.554714122565286 df.mm.trans2:probe6 -0.00919974425544369 0.0532230320928649 -0.172852689778961 0.862799517773943 df.mm.trans3:probe2 0.0116702638179852 0.0532230320928649 0.219270931382162 0.82648032187085 df.mm.trans3:probe3 0.0239726360033806 0.0532230320928649 0.450418457211391 0.652498890769862 df.mm.trans3:probe4 0.0848461799049409 0.0532230320928649 1.59416283831592 0.111191344005720 df.mm.trans3:probe5 0.0143640417855002 0.0532230320928649 0.269883943485923 0.787300955603798 df.mm.trans3:probe6 0.0578391752334285 0.0532230320928649 1.08673205864163 0.277397051384775 df.mm.trans3:probe7 0.0453787437304405 0.0532230320928649 0.852614778715773 0.394061476827342 df.mm.trans3:probe8 0.0236541871125441 0.0532230320928649 0.44443516617527 0.65681678928731 df.mm.trans3:probe9 0.0287973163729448 0.0532230320928649 0.541068692266507 0.588571508253683 df.mm.trans3:probe10 0.0342327305884722 0.0532230320928649 0.643193918917322 0.520234437327837 df.mm.trans3:probe11 0.090359369008167 0.0532230320928649 1.69774936629889 0.089842358475953 . df.mm.trans3:probe12 0.0389084914290627 0.0532230320928649 0.731046126067643 0.464909109405414 df.mm.trans3:probe13 0.0102807840788889 0.0532230320928649 0.193164193669964 0.846866598696379 df.mm.trans3:probe14 0.037759424715909 0.0532230320928649 0.709456474595912 0.478193959174484 df.mm.trans3:probe15 -0.00830791525274647 0.0532230320928649 -0.156096241158351 0.87598625206788 df.mm.trans3:probe16 -0.0111948834258817 0.0532230320928649 -0.210339076630370 0.83344260391767 df.mm.trans3:probe17 -0.00755208270146923 0.0532230320928649 -0.141895010571592 0.887189326259027 df.mm.trans3:probe18 0.0458878772803945 0.0532230320928649 0.86218081676234 0.388778890319138 df.mm.trans3:probe19 0.0243082111344025 0.0532230320928649 0.456723530744903 0.647961361737286 df.mm.trans3:probe20 0.0112665793358208 0.0532230320928649 0.211686160911738 0.83239171442798