chr7.20865_chr7_14739800_14740450_-_1.R fitVsDatCorrelation=0.984169742056512 cont.fitVsDatCorrelation=0.247887548990147 fstatistic=9210.74431351856,45,531 cont.fstatistic=296.845063179269,45,531 residuals=-0.92554501978752,-0.131109544115821,-0.00411576833096481,0.133258292417516,0.594154119139553 cont.residuals=-2.12994509818481,-1.03890819752471,-0.202047192938505,0.909385904155137,3.14939968856262 predictedValues: Include Exclude Both chr7.20865_chr7_14739800_14740450_-_1.R.tl.Lung 809.940801971635 92.1359943635125 256.831476012008 chr7.20865_chr7_14739800_14740450_-_1.R.tl.cerebhem 1854.56919008600 95.5421360887182 373.423123733786 chr7.20865_chr7_14739800_14740450_-_1.R.tl.cortex 2200.48757736455 89.3537083875814 649.431562826432 chr7.20865_chr7_14739800_14740450_-_1.R.tl.heart 591.888392019547 87.3737173454401 259.318868515395 chr7.20865_chr7_14739800_14740450_-_1.R.tl.kidney 248.372315096895 92.7093146912308 127.719761976196 chr7.20865_chr7_14739800_14740450_-_1.R.tl.liver 3624.35407622309 120.499238319281 1328.48268402171 chr7.20865_chr7_14739800_14740450_-_1.R.tl.stomach 512.609813351149 105.830304493334 211.187482238009 chr7.20865_chr7_14739800_14740450_-_1.R.tl.testicle 3718.46155895241 116.337513375686 1045.30165220977 diffExp=717.804807608122,1759.02705399728,2111.13386897697,504.514674674106,155.663000405664,3503.85483790381,406.779508857814,3602.12404557672 diffExpScore=0.999921641772846 diffExp1.5=1,1,1,1,1,1,1,1 diffExp1.5Score=0.888888888888889 diffExp1.4=1,1,1,1,1,1,1,1 diffExp1.4Score=0.888888888888889 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 364.317037658337 383.555104502962 372.072835832824 cerebhem 488.17944691072 265.713841266432 404.678995066004 cortex 409.240711123883 343.992802043859 406.974600166453 heart 337.693062785181 386.190579583426 254.647997320972 kidney 329.666056716401 426.689700714842 372.612478215721 liver 793.882268450553 289.289023406673 375.85853041087 stomach 354.662055603705 430.712803682494 428.677217250396 testicle 367.848304778846 262.818795098009 364.452410903037 cont.diffExp=-19.2380668446243,222.465605644288,65.2479090800242,-48.4975167982447,-97.0236439984414,504.59324504388,-76.0507480787884,105.029509680836 cont.diffExpScore=1.73095168364223 cont.diffExp1.5=0,1,0,0,0,1,0,0 cont.diffExp1.5Score=0.666666666666667 cont.diffExp1.4=0,1,0,0,0,1,0,0 cont.diffExp1.4Score=0.666666666666667 cont.diffExp1.3=0,1,0,0,0,1,0,1 cont.diffExp1.3Score=0.75 cont.diffExp1.2=0,1,0,0,-1,1,-1,1 cont.diffExp1.2Score=2.5 tran.correlation=0.73523288598512 cont.tran.correlation=-0.544406924133779 tran.covariance=0.0694359176935306 cont.tran.covariance=-0.0349961553217586 tran.mean=897.529103258128 cont.tran.mean=389.653224645395 weightedLogRatios: wLogRatio Lung 12.1946781666261 cerebhem 17.9210532857187 cortex 19.5258103006836 heart 10.3820553939567 kidney 4.94917585321489 liver 22.1026242443793 stomach 8.59941176654506 testicle 22.4808323249116 cont.weightedLogRatios: wLogRatio Lung -0.304829430860294 cerebhem 3.58057213706879 cortex 1.02949813481917 heart -0.790297491617073 kidney -1.52904655283998 liver 6.2308713978832 stomach -1.15949895176015 testicle 1.92967615920009 varWeightedLogRatios=43.7403237118614 cont.varWeightedLogRatios=7.24743364638225 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.82145512165652 0.112985144081441 51.5240757445096 9.75486051868132e-209 *** df.mm.trans1 0.80993373603745 0.0899494322132636 9.00432294132947 3.87603770213345e-18 *** df.mm.trans2 -1.38739283967667 0.0899494322132635 -15.4241422712626 1.27539896359117e-44 *** df.mm.exp2 0.490456202835813 0.119932576284351 4.08943272987797 4.9948642757505e-05 *** df.mm.exp3 0.0411328123653641 0.119932576284351 0.34296613680541 0.731759666565072 df.mm.exp4 -0.376352558095546 0.119932576284351 -3.13803446699286 0.00179527962326328 ** df.mm.exp5 -0.477247375396401 0.119932576284351 -3.97929728670951 7.87259051792213e-05 *** df.mm.exp6 0.123475354813068 0.119932576284351 1.02953975173782 0.303694828067469 df.mm.exp7 -0.123201123817245 0.119932576284351 -1.02725320871241 0.304768957299328 df.mm.exp8 0.353693369889798 0.119932576284351 2.94910174406007 0.00332740959881189 ** df.mm.trans1:exp2 0.337990341681923 0.0928993741234087 3.63824132155004 0.000301310891107034 *** df.mm.trans2:exp2 -0.454154522258302 0.0928993741234087 -4.88867149583804 1.3469453223683e-06 *** df.mm.trans1:exp3 0.958340267490324 0.0928993741234087 10.3158958446507 7.27627105956294e-23 *** df.mm.trans2:exp3 -0.071795752754077 0.0928993741234087 -0.772833546313268 0.439964761430437 df.mm.trans1:exp4 0.062709487202011 0.0928993741234087 0.675025938481641 0.49995309746885 df.mm.trans2:exp4 0.323281393470386 0.0928993741234087 3.47990927302626 0.000542820119406771 *** df.mm.trans1:exp5 -0.704784894676747 0.0928993741234087 -7.5865408279339 1.48195497930696e-13 *** df.mm.trans2:exp5 0.483450639835402 0.0928993741234087 5.20402472457112 2.79107545917083e-07 *** df.mm.trans1:exp6 1.37499484971914 0.0928993741234087 14.8009054172161 9.5073000573299e-42 *** df.mm.trans2:exp6 0.144902391904978 0.0928993741234087 1.55977791316966 0.119408141630814 df.mm.trans1:exp7 -0.334245079179342 0.0928993741234087 -3.59792606067859 0.000350759943284485 *** df.mm.trans2:exp7 0.261772348920862 0.0928993741234087 2.81780530160645 0.00501550344461324 ** df.mm.trans1:exp8 1.17041077140663 0.0928993741234087 12.5986938281398 5.00373222194509e-32 *** df.mm.trans2:exp8 -0.120463490595720 0.0928993741234087 -1.29670938832909 0.195294394435853 df.mm.trans1:probe2 0.300465153434736 0.0656897774106484 4.57400169826166 5.96125112494905e-06 *** df.mm.trans1:probe3 0.385130609325447 0.0656897774106484 5.86286975700753 7.99917394248691e-09 *** df.mm.trans1:probe4 -0.086493101811908 0.0656897774106484 -1.31669043831906 0.188510399656229 df.mm.trans1:probe5 0.311629718937941 0.0656897774106484 4.74396064687267 2.69734628397136e-06 *** df.mm.trans1:probe6 0.269569079803839 0.0656897774106484 4.10366864418909 4.70598773208789e-05 *** df.mm.trans2:probe2 0.230644344492392 0.0656897774106484 3.51111472110125 0.000484200141407388 *** df.mm.trans2:probe3 0.463839002853166 0.0656897774106484 7.06105304564447 5.19989059868315e-12 *** df.mm.trans2:probe4 0.119157856066915 0.0656897774106484 1.81394823919131 0.0702499781000692 . df.mm.trans2:probe5 0.208583363791493 0.0656897774106484 3.17527889442478 0.00158379939205512 ** df.mm.trans2:probe6 0.583436690594286 0.0656897774106484 8.88169687266606 1.01705669531152e-17 *** df.mm.trans3:probe2 -0.88516140094361 0.0656897774106484 -13.4748728924772 8.3225428570577e-36 *** df.mm.trans3:probe3 0.865031224215056 0.0656897774106484 13.1684298274823 1.80480257305650e-34 *** df.mm.trans3:probe4 0.464116322142624 0.0656897774106484 7.06527469626333 5.05741595457859e-12 *** df.mm.trans3:probe5 0.358489816929655 0.0656897774106484 5.45731514187691 7.42742635448679e-08 *** df.mm.trans3:probe6 1.26860821266217 0.0656897774106484 19.312110082695 2.42977458940871e-63 *** df.mm.trans3:probe7 -0.276314959098006 0.0656897774106484 -4.20636162870016 3.04624009586901e-05 *** df.mm.trans3:probe8 0.107548056470186 0.0656897774106484 1.63721146134913 0.102178746988435 df.mm.trans3:probe9 0.486167170916161 0.0656897774106484 7.40095628391264 5.32625070716827e-13 *** df.mm.trans3:probe10 0.586199422310678 0.0656897774106484 8.92375412761948 7.31337182619242e-18 *** df.mm.trans3:probe11 -0.622960062680925 0.0656897774106484 -9.48336388455996 8.18576320145242e-20 *** df.mm.trans3:probe12 1.30136559420738 0.0656897774106484 19.8107779551774 8.26285861299285e-66 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.72308905612926 0.617613885864618 9.26645139805644 4.7773726639736e-19 *** df.mm.trans1 0.151443047579120 0.491693123128697 0.308003184212687 0.758200688438628 df.mm.trans2 0.124235401010289 0.491693123128697 0.252668575512641 0.800622111656073 df.mm.exp2 -0.158409285377553 0.655590830838263 -0.241628280821142 0.809161487055824 df.mm.exp3 -0.0822446641608667 0.655590830838263 -0.125451211780533 0.900213828300646 df.mm.exp4 0.310168033231180 0.655590830838263 0.473112219758455 0.636327540391747 df.mm.exp5 0.00518015874542611 0.655590830838263 0.00790151189088866 0.993698538867622 df.mm.exp6 0.486730479754472 0.655590830838263 0.74243027336444 0.458154971425566 df.mm.exp7 -0.0525154687852775 0.655590830838263 -0.08010403183664 0.936184696266984 df.mm.exp8 -0.347678682048616 0.655590830838263 -0.530328774739056 0.596105697298145 df.mm.trans1:exp2 0.451067871588587 0.507818473952575 0.888246282333382 0.374810460388296 df.mm.trans2:exp2 -0.208654068514319 0.507818473952575 -0.410883178176391 0.681323956295586 df.mm.trans1:exp3 0.198523711710271 0.507818473952575 0.390934402533789 0.696002526098003 df.mm.trans2:exp3 -0.0266179018649512 0.507818473952575 -0.0524161747361657 0.958216798823784 df.mm.trans1:exp4 -0.386055119717245 0.507818473952575 -0.760222677037343 0.447458898513737 df.mm.trans2:exp4 -0.303320355009104 0.507818473952575 -0.597300749317424 0.550561213270973 df.mm.trans1:exp5 -0.105124437124934 0.507818473952575 -0.207011840878304 0.83607996951517 df.mm.trans2:exp5 0.101393595204150 0.507818473952575 0.199665038601214 0.841818995149446 df.mm.trans1:exp6 0.292180222858611 0.507818473952575 0.575363516384986 0.565289197158851 df.mm.trans2:exp6 -0.768787509287113 0.507818473952575 -1.51390220860478 0.130645611714684 df.mm.trans1:exp7 0.0256563776875030 0.507818473952575 0.0505227340151849 0.959724832055348 df.mm.trans2:exp7 0.168473689126305 0.507818473952575 0.331759669582322 0.740201641804233 df.mm.trans1:exp8 0.357324848829231 0.507818473952575 0.703646809160002 0.481961175733057 df.mm.trans2:exp8 -0.0303398141496753 0.507818473952575 -0.0597453927060337 0.952380896230653 df.mm.trans1:probe2 0.0730530165004397 0.35908188654367 0.203443891875496 0.83886603446841 df.mm.trans1:probe3 -0.00696586328974071 0.35908188654367 -0.0193990940528646 0.984530020070814 df.mm.trans1:probe4 0.111921473299059 0.35908188654367 0.311687883720216 0.755400075993985 df.mm.trans1:probe5 -0.00278188272498277 0.35908188654367 -0.00774720984051767 0.993821592365501 df.mm.trans1:probe6 0.247635869793035 0.35908188654367 0.689636205759765 0.490724255620916 df.mm.trans2:probe2 0.478922180877491 0.35908188654367 1.33374085083305 0.182860594102295 df.mm.trans2:probe3 0.308006221871836 0.35908188654367 0.857760397876204 0.39141176334782 df.mm.trans2:probe4 0.602688314528522 0.35908188654367 1.67841469345524 0.0938545335206005 . df.mm.trans2:probe5 -0.216926397277361 0.35908188654367 -0.604114006878426 0.546025855860718 df.mm.trans2:probe6 0.66616883149314 0.35908188654367 1.85520032186899 0.0641216226327105 . df.mm.trans3:probe2 0.0119354665601107 0.35908188654367 0.0332388433039471 0.973496612922035 df.mm.trans3:probe3 -0.362790072486136 0.35908188654367 -1.01032685323718 0.312798871451497 df.mm.trans3:probe4 0.117675901390638 0.35908188654367 0.327713275997636 0.743257631093903 df.mm.trans3:probe5 -0.0255403949579161 0.35908188654367 -0.071126937656907 0.94332350926475 df.mm.trans3:probe6 -0.149240464107684 0.35908188654367 -0.41561679856423 0.677858332810625 df.mm.trans3:probe7 -0.110748218618204 0.35908188654367 -0.308420510107617 0.757883332872098 df.mm.trans3:probe8 0.308224178724771 0.35908188654367 0.858367381578537 0.391076919219196 df.mm.trans3:probe9 -0.0088829980955888 0.35908188654367 -0.0247380846221228 0.980273170787028 df.mm.trans3:probe10 0.0251959111245351 0.35908188654367 0.070167591484654 0.94408668595349 df.mm.trans3:probe11 -0.486578967370064 0.35908188654367 -1.35506408316391 0.175973309366990 df.mm.trans3:probe12 -0.275384834501036 0.35908188654367 -0.766913745362493 0.443473634197979