chrX.25943_chrX_84485584_84488522_+_1.R fitVsDatCorrelation=0.881848053973365 cont.fitVsDatCorrelation=0.264602319038237 fstatistic=7202.01497026059,61,899 cont.fstatistic=1710.66718825603,61,899 residuals=-0.8328008606027,-0.103517473670831,0.00355049830045203,0.0966686401953973,0.720187100574104 cont.residuals=-0.722888707084154,-0.284814906887441,-0.104784438727314,0.230733680158135,1.67918826053103 predictedValues: Include Exclude Both chrX.25943_chrX_84485584_84488522_+_1.R.tl.Lung 65.4398156591467 73.9633994695091 72.018704337935 chrX.25943_chrX_84485584_84488522_+_1.R.tl.cerebhem 55.3055804924215 118.26535352267 85.1927058300912 chrX.25943_chrX_84485584_84488522_+_1.R.tl.cortex 68.6503365946706 139.313861846929 96.5112051689194 chrX.25943_chrX_84485584_84488522_+_1.R.tl.heart 65.2360846820004 69.6690486478515 74.8054658052335 chrX.25943_chrX_84485584_84488522_+_1.R.tl.kidney 59.5081441944464 71.5040061957275 64.0124793237155 chrX.25943_chrX_84485584_84488522_+_1.R.tl.liver 54.1626823241891 65.5368623594555 61.7544197868006 chrX.25943_chrX_84485584_84488522_+_1.R.tl.stomach 57.098448934356 63.9729374856993 68.3756955894411 chrX.25943_chrX_84485584_84488522_+_1.R.tl.testicle 61.8622448367824 71.4291352742839 70.5983190584487 diffExp=-8.52358381036241,-62.9597730302486,-70.6635252522581,-4.43296396585114,-11.9958620012811,-11.3741800352664,-6.87448855134332,-9.56689043750143 diffExpScore=0.994663572024671 diffExp1.5=0,-1,-1,0,0,0,0,0 diffExp1.5Score=0.666666666666667 diffExp1.4=0,-1,-1,0,0,0,0,0 diffExp1.4Score=0.666666666666667 diffExp1.3=0,-1,-1,0,0,0,0,0 diffExp1.3Score=0.666666666666667 diffExp1.2=0,-1,-1,0,-1,-1,0,0 diffExp1.2Score=0.8 cont.predictedValues: Include Exclude Both Lung 63.7585249986638 66.4091373966951 65.7558545938339 cerebhem 67.3561767935521 74.9453360157352 61.8303947345712 cortex 67.6948261531165 63.1627654360352 74.9794730059648 heart 66.9133615447185 60.0130400028491 74.2216870042283 kidney 65.485519646372 74.9265753110029 76.3893518522748 liver 75.5428167835836 65.0059100414614 65.5673856708561 stomach 75.0745381860092 69.2595543240325 76.8069110529635 testicle 76.2247736795715 70.3460401154306 73.1458393230224 cont.diffExp=-2.65061239803136,-7.58915922218303,4.53206071708121,6.90032154186937,-9.44105566463085,10.5369067421221,5.81498386197676,5.87873356414096 cont.diffExpScore=3.56048564132211 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=0.322063986854500 cont.tran.correlation=0.00274223088848857 tran.covariance=0.00749876650127956 cont.tran.covariance=0.000104079803278964 tran.mean=72.5573714075087 cont.tran.mean=68.8824310268018 weightedLogRatios: wLogRatio Lung -0.519431262447547 cerebhem -3.33885635623614 cortex -3.24331791472887 heart -0.276837827364324 kidney -0.767236923503325 liver -0.779124109384833 stomach -0.466285080099095 testicle -0.603483304442896 cont.weightedLogRatios: wLogRatio Lung -0.170074183209251 cerebhem -0.455176798780512 cortex 0.289677293695307 heart 0.451561733287306 kidney -0.572276334590015 liver 0.638379260508172 stomach 0.344907701956535 testicle 0.344600974716064 varWeightedLogRatios=1.61491228636623 cont.varWeightedLogRatios=0.200244396315557 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.53630580897124 0.090947075585743 49.8785230834005 3.65143482863445e-261 *** df.mm.trans1 -0.459420509199901 0.0767466228863875 -5.98619837487844 3.10106559052328e-09 *** df.mm.trans2 -0.209449978189929 0.0684260543890465 -3.06096822416604 0.00227178783154944 ** df.mm.exp2 0.133113480430761 0.0868712785359538 1.53230714079646 0.125798467794875 df.mm.exp3 0.388320927811827 0.0868712785359538 4.47007266793145 8.81805121269575e-06 *** df.mm.exp4 -0.100897415543975 0.0868712785359538 -1.16145885319526 0.245763627833887 df.mm.exp5 -0.0109867712238197 0.0868712785359538 -0.126471849027438 0.89938671079547 df.mm.exp6 -0.156336003366831 0.0868712785359538 -1.79962820855834 0.0722545678354846 . df.mm.exp7 -0.22955571610818 0.0868712785359538 -2.64248115115714 0.00837319815283911 ** df.mm.exp8 -0.0711658127645643 0.0868712785359538 -0.819209915681287 0.412883772185745 df.mm.trans1:exp2 -0.301370539276118 0.0767466228863875 -3.92682476364144 9.26577912667964e-05 *** df.mm.trans2:exp2 0.33624700894306 0.0559382332677949 6.01104091602848 2.67695812387272e-09 *** df.mm.trans1:exp3 -0.340425767901615 0.0767466228863875 -4.43571006903544 1.03132605758908e-05 *** df.mm.trans2:exp3 0.244838089684165 0.0559382332677949 4.37693640612574 1.34486249856927e-05 *** df.mm.trans1:exp4 0.0977793020788109 0.0767466228863875 1.27405348146145 0.202973721496634 df.mm.trans2:exp4 0.0410832002886783 0.0559382332677948 0.734438645782741 0.462872955848785 df.mm.trans1:exp5 -0.0840309237197869 0.0767466228863875 -1.09491363345307 0.273847728306818 df.mm.trans2:exp5 -0.0228301190213858 0.0559382332677949 -0.408130855904770 0.683274791021335 df.mm.trans1:exp6 -0.0328027186747797 0.0767466228863875 -0.427415792918204 0.66917885931681 df.mm.trans2:exp6 0.035378402733292 0.0559382332677949 0.632454774964448 0.527250569034602 df.mm.trans1:exp7 0.0932017930334646 0.0767466228863875 1.21440904535222 0.224910457647840 df.mm.trans2:exp7 0.084445489169896 0.0559382332677949 1.50962024069705 0.131491720792007 df.mm.trans1:exp8 0.0149449930048678 0.0767466228863875 0.194731604372895 0.845647065939916 df.mm.trans2:exp8 0.0363012868552796 0.0559382332677949 0.648953045790584 0.516534468866416 df.mm.trans1:probe2 -0.115017058358306 0.0575599671647906 -1.99821271664417 0.0459944189153888 * df.mm.trans1:probe3 -0.0614886023366009 0.0575599671647906 -1.0682529084939 0.28569320411521 df.mm.trans1:probe4 -0.0132984161677257 0.0575599671647906 -0.231035853958242 0.81733951704343 df.mm.trans1:probe5 -0.0305107783700296 0.0575599671647906 -0.530069419301077 0.596194689990426 df.mm.trans1:probe6 -0.123205681096504 0.0575599671647906 -2.14047518032409 0.0325848684591235 * df.mm.trans1:probe7 0.0951040040357459 0.0575599671647906 1.65225952550440 0.0988308427252442 . df.mm.trans1:probe8 0.123238714685801 0.0575599671647906 2.14104907900618 0.032538425233244 * df.mm.trans1:probe9 -0.0773290081465018 0.0575599671647906 -1.34345122062203 0.179464918666678 df.mm.trans1:probe10 0.0227146766935921 0.0575599671647906 0.394626296928929 0.693212303702828 df.mm.trans1:probe11 0.686302535530246 0.0575599671647906 11.9232614147504 1.56460065063297e-30 *** df.mm.trans1:probe12 0.64718406954434 0.0575599671647906 11.2436490398178 1.55173552829579e-27 *** df.mm.trans1:probe13 0.191011909616996 0.0575599671647906 3.31848538186517 0.000941425208069825 *** df.mm.trans1:probe14 0.624378435630342 0.0575599671647906 10.8474425262055 7.5463233842989e-26 *** df.mm.trans1:probe15 0.414288760685317 0.0575599671647906 7.19751558403837 1.29370516248266e-12 *** df.mm.trans1:probe16 0.327011402992943 0.0575599671647906 5.68122983907773 1.80581541252498e-08 *** df.mm.trans2:probe2 -0.0174672019128892 0.0575599671647906 -0.303460942965476 0.761608821246978 df.mm.trans2:probe3 -0.081972949651763 0.0575599671647906 -1.42413127889874 0.154755472349054 df.mm.trans2:probe4 -0.225812068474759 0.0575599671647906 -3.92307500503386 9.408757870974e-05 *** df.mm.trans2:probe5 -0.0548912054980219 0.0575599671647906 -0.953635107901847 0.340524713875082 df.mm.trans2:probe6 -0.178707655174564 0.0575599671647906 -3.10472128420322 0.00196423948079044 ** df.mm.trans3:probe2 0.101718642190580 0.0575599671647906 1.76717686268593 0.0775378431028803 . df.mm.trans3:probe3 0.0845062799882758 0.0575599671647906 1.46814329734309 0.142415084130068 df.mm.trans3:probe4 -0.00818862273819838 0.0575599671647906 -0.142262463679919 0.886904570009336 df.mm.trans3:probe5 0.210121062394051 0.0575599671647906 3.65047224214857 0.000276859271627967 *** df.mm.trans3:probe6 0.238255773044107 0.0575599671647906 4.13926179565036 3.81185744813069e-05 *** df.mm.trans3:probe7 0.0376880502118037 0.0575599671647906 0.654761496022143 0.512788806312409 df.mm.trans3:probe8 0.137731735051897 0.0575599671647906 2.3928390135731 0.0169229157597867 * df.mm.trans3:probe9 0.483661255768036 0.0575599671647906 8.40273682546316 1.69153523373214e-16 *** df.mm.trans3:probe10 0.844140345898523 0.0575599671647906 14.6654070090381 8.07612086620389e-44 *** df.mm.trans3:probe11 0.891739443088396 0.0575599671647906 15.4923549649603 3.68661635748390e-48 *** df.mm.trans3:probe12 0.299460381255882 0.0575599671647906 5.20258082146826 2.43523651188252e-07 *** df.mm.trans3:probe13 0.792091509334002 0.0575599671647906 13.7611529045229 3.06514329726299e-39 *** df.mm.trans3:probe14 1.07146196863618 0.0575599671647906 18.6147077806465 1.14376622431312e-65 *** df.mm.trans3:probe15 0.0555759249338354 0.0575599671647906 0.965530865831195 0.334538638683068 df.mm.trans3:probe16 0.0833646588730051 0.0575599671647906 1.44830970167751 0.147879122791616 df.mm.trans3:probe17 0.840830485404735 0.0575599671647906 14.6079041879487 1.59862532358765e-43 *** df.mm.trans3:probe18 1.20667093769495 0.0575599671647906 20.9637183120749 9.31325508717596e-80 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.14160229773432 0.186000510888725 22.2666178600555 8.03931424583952e-88 *** df.mm.trans1 0.0108380303763972 0.156958439553059 0.0690503193536999 0.944964921208698 df.mm.trans2 0.0487558030739757 0.139941619810120 0.34840101994053 0.727620606422925 df.mm.exp2 0.237369688804131 0.177664890104252 1.33605288397074 0.181870080620573 df.mm.exp3 -0.121478504560513 0.177664890104252 -0.68375076521439 0.494308755216002 df.mm.exp4 -0.174084690467989 0.177664890104252 -0.979848581032741 0.327424473531793 df.mm.exp5 -0.00249447917677844 0.177664890104252 -0.0140403609025661 0.98880089602651 df.mm.exp6 0.15111054340169 0.177664890104252 0.85053689174614 0.395253127853277 df.mm.exp7 0.0500590942047847 0.177664890104252 0.281761321414775 0.778191375790124 df.mm.exp8 0.129668921618303 0.177664890104252 0.72985113458385 0.465671310364041 df.mm.trans1:exp2 -0.182477978863601 0.156958439553059 -1.16258787602125 0.245305272232768 df.mm.trans2:exp2 -0.116445352544742 0.114402138815484 -1.01785992596304 0.309018369912161 df.mm.trans1:exp3 0.181385357846514 0.156958439553059 1.15562666373984 0.248140932629495 df.mm.trans2:exp3 0.0713588191896875 0.114402138815484 0.623754240336189 0.532947225346703 df.mm.trans1:exp4 0.222380461228945 0.156958439553059 1.41681111166864 0.156884587177299 df.mm.trans2:exp4 0.072811904046611 0.114402138815484 0.63645579357609 0.524641395264921 df.mm.trans1:exp5 0.0292206227089948 0.156958439553059 0.186167897643483 0.852355096353886 df.mm.trans2:exp5 0.123168458919537 0.114402138815484 1.07662723961998 0.281935656047043 df.mm.trans1:exp6 0.018486161256366 0.156958439553059 0.117777427636294 0.906270323444928 df.mm.trans2:exp6 -0.172467012335392 0.114402138815484 -1.50755059408075 0.132020897650742 df.mm.trans1:exp7 0.113319467709863 0.156958439553059 0.72197116658742 0.470499945668199 df.mm.trans2:exp7 -0.00803264848685911 0.114402138815484 -0.0702141460817855 0.94403883044295 df.mm.trans1:exp8 0.0489147015740441 0.156958439553059 0.311641105208036 0.755385547549161 df.mm.trans2:exp8 -0.072077086390847 0.114402138815484 -0.63003268240551 0.528833297957815 df.mm.trans1:probe2 0.215286653761344 0.117718829664795 1.82882088085971 0.0677576056845159 . df.mm.trans1:probe3 0.159660870209157 0.117718829664795 1.35628998915291 0.175347444376276 df.mm.trans1:probe4 -0.0577876129726429 0.117718829664795 -0.49089523857138 0.623620348905601 df.mm.trans1:probe5 -0.091874254131226 0.117718829664795 -0.780455041838581 0.435328521808374 df.mm.trans1:probe6 0.137620509608984 0.117718829664795 1.16906114341146 0.242688879311381 df.mm.trans1:probe7 0.0107576774325169 0.117718829664795 0.0913845088602182 0.927207428164647 df.mm.trans1:probe8 0.00805440456042791 0.117718829664795 0.068420698569319 0.945465959909828 df.mm.trans1:probe9 0.0329921424547324 0.117718829664795 0.280262236285204 0.77934079811401 df.mm.trans1:probe10 -0.151620158222602 0.117718829664795 -1.28798560650273 0.198082394420470 df.mm.trans1:probe11 -0.0167590788525262 0.117718829664795 -0.142365319976828 0.88682335292472 df.mm.trans1:probe12 -0.0961848098940506 0.117718829664794 -0.81707242730783 0.414103511164931 df.mm.trans1:probe13 -0.0279843122471900 0.117718829664794 -0.237721631508533 0.812151171308511 df.mm.trans1:probe14 -0.0142321405268972 0.117718829664794 -0.120899439515525 0.903797701529682 df.mm.trans1:probe15 -0.071176370160121 0.117718829664794 -0.604630290351989 0.545577242393782 df.mm.trans1:probe16 0.0324733628517126 0.117718829664795 0.275855298121642 0.782722605483966 df.mm.trans2:probe2 0.0432303872464649 0.117718829664794 0.367234259545086 0.713530714391553 df.mm.trans2:probe3 0.0992186360920569 0.117718829664795 0.842844227848534 0.399539749102169 df.mm.trans2:probe4 0.0351158593476577 0.117718829664794 0.298302824175626 0.76554097956837 df.mm.trans2:probe5 0.0092270554072756 0.117718829664795 0.0783821537603604 0.937541511348757 df.mm.trans2:probe6 -0.055354555632922 0.117718829664794 -0.470226859972569 0.63830699634129 df.mm.trans3:probe2 0.00223610922561224 0.117718829664795 0.0189953402695183 0.98484903754818 df.mm.trans3:probe3 0.0396445883751874 0.117718829664795 0.336773551759525 0.73636621209923 df.mm.trans3:probe4 -0.122665321342404 0.117718829664795 -1.04201954514579 0.297682751760006 df.mm.trans3:probe5 -0.0832076788454973 0.117718829664794 -0.706834064545426 0.479852764725997 df.mm.trans3:probe6 -0.0525996416204929 0.117718829664795 -0.446824367607722 0.655109494369244 df.mm.trans3:probe7 0.0520333340409867 0.117718829664795 0.442013687947392 0.658585608482978 df.mm.trans3:probe8 0.0841225382600611 0.117718829664795 0.714605628509906 0.475038277884796 df.mm.trans3:probe9 0.0761275197018343 0.117718829664794 0.646689403204298 0.517998048375487 df.mm.trans3:probe10 -0.0679022349388456 0.117718829664795 -0.576817108462579 0.564207411070994 df.mm.trans3:probe11 -0.118524559594504 0.117718829664794 -1.00684452888296 0.314280407879847 df.mm.trans3:probe12 -0.0412038589187459 0.117718829664794 -0.350019270800384 0.726406220218703 df.mm.trans3:probe13 -0.0566907993272809 0.117718829664794 -0.481578006583216 0.630222954941258 df.mm.trans3:probe14 -0.0366321424189273 0.117718829664795 -0.311183372475225 0.755733364348994 df.mm.trans3:probe15 -0.0956232067110454 0.117718829664795 -0.81230171063825 0.416833568768634 df.mm.trans3:probe16 -0.0520593288780508 0.117718829664794 -0.442234509349866 0.658425884078263 df.mm.trans3:probe17 0.116509323537558 0.117718829664795 0.989725465920106 0.322574626605881 df.mm.trans3:probe18 0.0819817843578018 0.117718829664795 0.69642031433073 0.486345660571151