fitVsDatCorrelation=0.93945274254595 cont.fitVsDatCorrelation=0.269841739161971 fstatistic=7767.54740101266,60,876 cont.fstatistic=971.013241184139,60,876 residuals=-1.24517870358426,-0.115015249048513,-0.00517324191664209,0.121394884281213,0.903792199663399 cont.residuals=-1.09867539906294,-0.40357961776378,-0.142289028981052,0.346392627993755,1.92735150450922 predictedValues: Include Exclude Both Lung 113.805930807758 141.170001033671 96.5662400627038 cerebhem 95.2717489263495 117.972503156413 101.176611609471 cortex 120.904419589309 144.862961874300 103.316116152498 heart 135.449598453803 181.781693419315 109.641529395409 kidney 113.314764472357 157.255072347122 96.7815003491639 liver 101.190573467883 180.857406599942 92.8192743861584 stomach 117.016326401961 156.312785789072 101.195354882101 testicle 112.976099866235 173.059295155618 94.1977235635067 diffExp=-27.364070225913,-22.7007542300634,-23.9585422849914,-46.3320949655122,-43.9403078747644,-79.6668331320589,-39.2964593871106,-60.0831952893831 diffExpScore=0.997095912631867 diffExp1.5=0,0,0,0,0,-1,0,-1 diffExp1.5Score=0.666666666666667 diffExp1.4=0,0,0,0,0,-1,0,-1 diffExp1.4Score=0.666666666666667 diffExp1.3=0,0,0,-1,-1,-1,-1,-1 diffExp1.3Score=0.833333333333333 diffExp1.2=-1,-1,0,-1,-1,-1,-1,-1 diffExp1.2Score=0.875 cont.predictedValues: Include Exclude Both Lung 121.751227293229 139.075936716024 133.914689034824 cerebhem 114.280533043706 140.891794410102 121.343130148931 cortex 108.449031556185 90.3924546642407 99.5684208652514 heart 103.769568798448 122.834182560386 102.145302429014 kidney 102.565474057702 137.782658932124 112.459798234028 liver 116.514865415309 126.190656224756 126.255182971986 stomach 112.330351358892 112.330483637582 97.2746961746635 testicle 120.755367880730 137.265787584655 135.96535182201 cont.diffExp=-17.3247094227945,-26.6112613663966,18.0565768919439,-19.0646137619379,-35.2171848744223,-9.67579080944708,-0.000132278689136456,-16.5104197039255 cont.diffExpScore=1.32709790380713 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,-1,0,0,0 cont.diffExp1.3Score=0.5 cont.diffExp1.2=0,-1,0,0,-1,0,0,0 cont.diffExp1.2Score=0.666666666666667 tran.correlation=0.459808439642903 cont.tran.correlation=0.339345228454729 tran.covariance=0.00764146241090297 cont.tran.covariance=0.00310042983381905 tran.mean=135.200073835069 cont.tran.mean=119.198773383379 weightedLogRatios: wLogRatio Lung -1.04335625342012 cerebhem -0.996694817137497 cortex -0.88322013122781 heart -1.48742260014071 kidney -1.60376855766652 liver -2.84971858850093 stomach -1.42082508583812 testicle -2.10687531620835 cont.weightedLogRatios: wLogRatio Lung -0.647706447449372 cerebhem -1.01388181923984 cortex 0.836879313345303 heart -0.797184368458616 kidney -1.41037800821164 liver -0.382753188029665 stomach -5.55990556790353e-06 testicle -0.622544014170977 varWeightedLogRatios=0.432899048569118 cont.varWeightedLogRatios=0.466975213972481 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.26572988966003 0.0987993272974237 53.2972241178138 3.81952973266632e-277 *** df.mm.trans1 -0.758503735432927 0.0851397750114183 -8.90892341835767 2.93345871904424e-18 *** df.mm.trans2 -0.0813488942957316 0.0750434761466137 -1.08402353506118 0.278652623322221 df.mm.exp2 -0.403913006455352 0.0961325863237868 -4.2016242556392 2.92159837070094e-05 *** df.mm.exp3 0.0187648574338765 0.0961325863237867 0.195197675954271 0.845283462408943 df.mm.exp4 0.299959580587275 0.0961325863237868 3.12026953666859 0.00186603758298857 ** df.mm.exp5 0.101352477113625 0.0961325863237868 1.05429886981566 0.292036804692771 df.mm.exp6 0.169829917322268 0.0961325863237868 1.76662174416342 0.0776398000383446 . df.mm.exp7 0.0828893652585733 0.0961325863237868 0.862240041887476 0.388791413717924 df.mm.exp8 0.221184274542671 0.0961325863237868 2.30082517282635 0.0216355907450111 * df.mm.trans1:exp2 0.226151693187049 0.0886298653406698 2.55164207141443 0.0108904807635147 * df.mm.trans2:exp2 0.22439973445021 0.0644876993618561 3.47972926109596 0.000526682995829511 *** df.mm.trans1:exp3 0.041740818866189 0.0886298653406698 0.470956586763935 0.637788988877241 df.mm.trans2:exp3 0.00705850236672385 0.0644876993618561 0.109455019121040 0.91286666488639 df.mm.trans1:exp4 -0.125854612990435 0.0886298653406698 -1.42000230403920 0.155962790366364 df.mm.trans2:exp4 -0.047117945395779 0.0644876993618561 -0.73065012183779 0.465188253959002 df.mm.trans1:exp5 -0.105677640881581 0.0886298653406698 -1.19234797971749 0.233447713706553 df.mm.trans2:exp5 0.00655182930788504 0.0644876993618561 0.101598124490705 0.919098917900482 df.mm.trans1:exp6 -0.287318948753339 0.0886298653406698 -3.24178478269104 0.00123270201787016 ** df.mm.trans2:exp6 0.0779141494007193 0.0644876993618561 1.20820172175044 0.227295735693093 df.mm.trans1:exp7 -0.0550705346941525 0.0886298653406698 -0.621354150573014 0.534528283963771 df.mm.trans2:exp7 0.0190048264780476 0.0644876993618561 0.294704674939742 0.768289316020428 df.mm.trans1:exp8 -0.228502620204709 0.0886298653406698 -2.57816729526109 0.0100948641320076 * df.mm.trans2:exp8 -0.0175148374230876 0.0644876993618562 -0.271599663135874 0.785993851314816 df.mm.trans1:probe2 0.210888160015918 0.0617422714858822 3.41562036738702 0.000665627280830038 *** df.mm.trans1:probe3 -0.48746493808114 0.0617422714858822 -7.89515718080768 8.65012358148243e-15 *** df.mm.trans1:probe4 0.185466710883391 0.0617422714858822 3.00388544865569 0.00274140313424829 ** df.mm.trans1:probe5 0.695340787197917 0.0617422714858822 11.2619890791823 1.42886067158753e-27 *** df.mm.trans1:probe6 -0.0682735563025384 0.0617422714858822 -1.10578303420777 0.269124030792887 df.mm.trans1:probe7 0.255982603569053 0.0617422714858822 4.14598616812447 3.71241512384235e-05 *** df.mm.trans1:probe8 -0.052035445950403 0.0617422714858822 -0.842784768006168 0.399578874999581 df.mm.trans1:probe9 0.129453431487815 0.0617422714858822 2.09667426177242 0.0363086763352477 * df.mm.trans1:probe10 -0.439208758809423 0.0617422714858822 -7.11358277302531 2.35011715713314e-12 *** df.mm.trans1:probe11 1.65480728482107 0.0617422714858822 26.8018530092378 4.89232055832553e-116 *** df.mm.trans1:probe12 1.38735265598904 0.0617422714858822 22.4700618004678 1.18419401478533e-88 *** df.mm.trans1:probe13 0.81329641524722 0.0617422714858821 13.1724407877217 2.77348642807209e-36 *** df.mm.trans1:probe14 1.17586122254635 0.0617422714858822 19.0446706000316 6.22009977529184e-68 *** df.mm.trans1:probe15 1.46908117273393 0.0617422714858822 23.7937662055380 6.36727670368124e-97 *** df.mm.trans1:probe16 0.72381409991031 0.0617422714858822 11.7231530763460 1.38043959761829e-29 *** df.mm.trans1:probe17 0.0149262374407491 0.0617422714858821 0.241750701448717 0.809029919504712 df.mm.trans1:probe18 -0.0117054663392675 0.0617422714858822 -0.189585936143345 0.84967752735094 df.mm.trans1:probe19 -0.0496477495656115 0.0617422714858822 -0.80411277996087 0.421550001224087 df.mm.trans1:probe20 0.0228958424976204 0.0617422714858822 0.370829286753011 0.710854341936055 df.mm.trans1:probe21 -0.118264407011033 0.0617422714858822 -1.91545280348286 0.0557600994656413 . df.mm.trans1:probe22 -0.0127063907277583 0.0617422714858821 -0.205797266960994 0.836997091741177 df.mm.trans2:probe2 -0.139825259244248 0.0617422714858822 -2.26466010853230 0.0237771641072463 * df.mm.trans2:probe3 -1.13670365517259 0.0617422714858822 -18.4104605777666 3.07255161402676e-64 *** df.mm.trans2:probe4 -0.577973885986079 0.0617422714858822 -9.36107260190835 6.46437902857722e-20 *** df.mm.trans2:probe5 -1.21860977445094 0.0617422714858822 -19.7370414972437 5.05424998205729e-72 *** df.mm.trans2:probe6 -0.911961977628411 0.0617422714858822 -14.7704636658361 2.99912154880973e-44 *** df.mm.trans3:probe2 -0.195765129253430 0.0617422714858822 -3.17068233063296 0.00157368779157976 ** df.mm.trans3:probe3 0.83323196174293 0.0617422714858822 13.4953240574159 7.5879695001877e-38 *** df.mm.trans3:probe4 0.370435154424578 0.0617422714858822 5.99970078051438 2.89026978125196e-09 *** df.mm.trans3:probe5 -0.313065858864687 0.0617422714858822 -5.07052706890242 4.84201216541724e-07 *** df.mm.trans3:probe6 -0.264347622841844 0.0617422714858822 -4.28146902405898 2.06164502258486e-05 *** df.mm.trans3:probe7 -0.071854996358715 0.0617422714858822 -1.16378932341589 0.244826278695828 df.mm.trans3:probe8 -0.175367961932165 0.0617422714858822 -2.84032248428475 0.00461123059824379 ** df.mm.trans3:probe9 1.23867793134699 0.0617422714858822 20.0620725726008 5.81185328178364e-74 *** df.mm.trans3:probe10 0.0470836449307779 0.0617422714858822 0.762583620551503 0.445917043761849 df.mm.trans3:probe11 0.118844199772926 0.0617422714858822 1.9248433352521 0.0545725174359384 . cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.73930412864004 0.277619807750405 17.0712031214319 1.26119543310061e-56 *** df.mm.trans1 0.0593258855751698 0.239237337106840 0.247979208816707 0.804208608731959 df.mm.trans2 0.220150135537212 0.210867381293276 1.04402176470824 0.296763334401444 df.mm.exp2 0.0482291178477318 0.270126435713646 0.178542754322862 0.858338029464109 df.mm.exp3 -0.250200934958942 0.270126435713645 -0.926236391110472 0.354578245564793 df.mm.exp4 -0.0131852257838703 0.270126435713645 -0.0488113121880733 0.961080793390569 df.mm.exp5 -0.0062139198429519 0.270126435713645 -0.0230037457331245 0.981652523823664 df.mm.exp6 -0.0822893330244861 0.270126435713645 -0.304632653990663 0.760718303221766 df.mm.exp7 0.0255534878079657 0.270126435713645 0.0945982489290843 0.924655574040802 df.mm.exp8 -0.036511224913768 0.270126435713645 -0.135163464535817 0.892513683486709 df.mm.trans1:exp2 -0.111552718479489 0.249044268315202 -0.447923251693961 0.654319338511071 df.mm.trans2:exp2 -0.0352570288834931 0.181206321832631 -0.194568426349152 0.845775935726936 df.mm.trans1:exp3 0.134501399978265 0.249044268315202 0.540070248908654 0.589285853320998 df.mm.trans2:exp3 -0.180658358498652 0.181206321832631 -0.99697602529295 0.319051454537182 df.mm.trans1:exp4 -0.146621860315175 0.249044268315202 -0.588738144053983 0.556188717646069 df.mm.trans2:exp4 -0.110999528894377 0.181206321832631 -0.612558810155092 0.540327077150846 df.mm.trans1:exp5 -0.165264556560574 0.249044268315202 -0.663595101700581 0.507124090146717 df.mm.trans2:exp5 -0.00312866305727788 0.181206321832631 -0.0172657500336419 0.986228540593622 df.mm.trans1:exp6 0.0383283556723525 0.249044268315202 0.153901777911397 0.87772262926803 df.mm.trans2:exp6 -0.0149368503016432 0.181206321832631 -0.082430072806397 0.934323553400339 df.mm.trans1:exp7 -0.106089234591688 0.249044268315202 -0.425985449532277 0.670223092658572 df.mm.trans2:exp7 -0.239128305925636 0.181206321832631 -1.31964659680308 0.187297810503886 df.mm.trans1:exp8 0.0282981286080808 0.249044268315202 0.113626901753327 0.909559596222892 df.mm.trans2:exp8 0.0234102353586977 0.181206321832631 0.129191052066717 0.897236132120316 df.mm.trans1:probe2 0.121416142253454 0.173491844619380 0.699837750413144 0.484214436702309 df.mm.trans1:probe3 -0.172876111584899 0.173491844619380 -0.99645093960565 0.319306254957202 df.mm.trans1:probe4 -0.0728997815905514 0.173491844619380 -0.420191402947409 0.674448679398367 df.mm.trans1:probe5 0.115523203174765 0.173491844619381 0.665871087071608 0.50566880080363 df.mm.trans1:probe6 -0.256486606768629 0.173491844619380 -1.47837846402134 0.139665967170573 df.mm.trans1:probe7 -0.0860285101399848 0.173491844619380 -0.495864865168277 0.620114135470148 df.mm.trans1:probe8 0.0703768634864843 0.173491844619380 0.405649404678833 0.68509927908711 df.mm.trans1:probe9 -0.0311745131466813 0.173491844619380 -0.179688637325139 0.857438569294331 df.mm.trans1:probe10 -0.07834035887213 0.173491844619381 -0.451550671122317 0.651704482878392 df.mm.trans1:probe11 -0.0590102764986558 0.173491844619381 -0.340132855397999 0.733838021642698 df.mm.trans1:probe12 -0.0239217049857898 0.173491844619380 -0.137883743401720 0.890363985267498 df.mm.trans1:probe13 -0.0223602588598383 0.173491844619380 -0.128883630863998 0.897479313435015 df.mm.trans1:probe14 -0.175397089673438 0.173491844619380 -1.01098175570291 0.312304320441926 df.mm.trans1:probe15 0.0562010524451495 0.173491844619380 0.323940601176082 0.746060330510232 df.mm.trans1:probe16 -0.0542842954047206 0.173491844619381 -0.312892490847703 0.754436817445016 df.mm.trans1:probe17 0.239484917422055 0.173491844619380 1.38038141186091 0.16782137014993 df.mm.trans1:probe18 0.104045910606752 0.173491844619380 0.599716435288449 0.548850317564869 df.mm.trans1:probe19 0.256417487583065 0.173491844619380 1.47798006382152 0.139772556988234 df.mm.trans1:probe20 0.0495527034232607 0.173491844619380 0.285619785367855 0.775236869384132 df.mm.trans1:probe21 -0.108377303962597 0.173491844619380 -0.624682412019791 0.532342185015909 df.mm.trans1:probe22 0.238682859510952 0.173491844619380 1.37575838238732 0.169248094213024 df.mm.trans2:probe2 -0.0302242741966147 0.173491844619380 -0.174211498315226 0.861739501015001 df.mm.trans2:probe3 -0.044238623937612 0.173491844619380 -0.254989645390341 0.798790947837356 df.mm.trans2:probe4 -0.0621733703826277 0.173491844619380 -0.358364801060409 0.720156670683662 df.mm.trans2:probe5 -0.156600537004711 0.173491844619380 -0.902639183693463 0.366965548827152 df.mm.trans2:probe6 -0.12214413392383 0.173491844619380 -0.704033865060338 0.481598785562129 df.mm.trans3:probe2 0.0304248779551029 0.173491844619380 0.175367770294052 0.86083119020381 df.mm.trans3:probe3 -0.289353385847353 0.173491844619380 -1.66782125397397 0.0957086080854843 . df.mm.trans3:probe4 -0.284520343780653 0.173491844619380 -1.63996379429163 0.101371710520836 df.mm.trans3:probe5 -0.266064887118272 0.173491844619380 -1.53358728591528 0.125492277469592 df.mm.trans3:probe6 0.105410408574235 0.173491844619380 0.607581346578524 0.543622641516712 df.mm.trans3:probe7 -0.121372918912156 0.173491844619380 -0.699588612815971 0.484369979099234 df.mm.trans3:probe8 -0.0654688521169424 0.173491844619380 -0.377359824956458 0.705997621324698 df.mm.trans3:probe9 -0.265700702758381 0.173491844619380 -1.5314881419429 0.126009826977203 df.mm.trans3:probe10 0.0542375581134803 0.173491844619380 0.312623098984686 0.754641432104186 df.mm.trans3:probe11 -0.234940971075379 0.173491844619380 -1.35419028825713 0.17602489149713