chr16.9761_chr16_24612205_24740709_+_2.R fitVsDatCorrelation=0.818834473528048 cont.fitVsDatCorrelation=0.213289007585281 fstatistic=10063.5731256966,69,1083 cont.fstatistic=3463.81589877387,69,1083 residuals=-0.510532368850029,-0.0913280611358,-0.00229076169770806,0.0764330755346858,2.31189206853897 cont.residuals=-0.629736400770451,-0.205215105340951,-0.0300960594175459,0.172317464968494,2.24859819700839 predictedValues: Include Exclude Both chr16.9761_chr16_24612205_24740709_+_2.R.tl.Lung 73.6604017522085 45.8074786118742 82.6561323028595 chr16.9761_chr16_24612205_24740709_+_2.R.tl.cerebhem 63.9339202486282 49.8885324768977 73.9477201239003 chr16.9761_chr16_24612205_24740709_+_2.R.tl.cortex 57.1744899302861 44.6257569922546 61.9484597356034 chr16.9761_chr16_24612205_24740709_+_2.R.tl.heart 65.165218838205 46.3253134558269 73.4321774587569 chr16.9761_chr16_24612205_24740709_+_2.R.tl.kidney 67.076683313774 45.007644145877 71.6204892634932 chr16.9761_chr16_24612205_24740709_+_2.R.tl.liver 63.5211053195756 47.8031360781511 68.6382700394723 chr16.9761_chr16_24612205_24740709_+_2.R.tl.stomach 82.2827050147778 46.7794666413687 97.6527665102897 chr16.9761_chr16_24612205_24740709_+_2.R.tl.testicle 72.8756404811995 56.3709081081835 86.1662233709818 diffExp=27.8529231403343,14.0453877717305,12.5487329380314,18.8399053823781,22.0690391678971,15.7179692414245,35.5032383734091,16.5047323730161 diffExpScore=0.993905483621365 diffExp1.5=1,0,0,0,0,0,1,0 diffExp1.5Score=0.666666666666667 diffExp1.4=1,0,0,1,1,0,1,0 diffExp1.4Score=0.8 diffExp1.3=1,0,0,1,1,1,1,0 diffExp1.3Score=0.833333333333333 diffExp1.2=1,1,1,1,1,1,1,1 diffExp1.2Score=0.888888888888889 cont.predictedValues: Include Exclude Both Lung 64.6655839802406 68.6372416509773 66.4840551433167 cerebhem 64.7413418412542 69.0827810633598 65.2950734154278 cortex 65.1384488824995 66.2878304934641 63.876149448459 heart 63.8709390517118 65.1936099466986 60.6163578416417 kidney 64.468693845164 70.9187153657437 65.4281577202865 liver 66.5142303567704 75.1447185478761 61.849171652492 stomach 64.2319937013581 66.5963234271778 65.1645699948771 testicle 67.4965532767283 68.3013269675268 67.0807386731693 cont.diffExp=-3.9716576707367,-4.34143922210554,-1.14938161096458,-1.32267089498682,-6.45002152057972,-8.63048819110567,-2.36432972581962,-0.804773690798498 cont.diffExpScore=0.966705246991788 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=0.232762342385091 cont.tran.correlation=0.465073783869384 tran.covariance=0.00218457527048924 cont.tran.covariance=0.000396672789827886 tran.mean=58.018650088068 cont.tran.mean=66.9556457749095 weightedLogRatios: wLogRatio Lung 1.92950238440065 cerebhem 1.00062505326205 cortex 0.971910241325405 heart 1.36710159250793 kidney 1.59854404624913 liver 1.13974829464803 stomach 2.33103859657626 testicle 1.06838394415141 cont.weightedLogRatios: wLogRatio Lung -0.250288105070719 cerebhem -0.272788410668639 cortex -0.0732058200989424 heart -0.0854132609264708 kidney -0.401810771586586 liver -0.519526395348804 stomach -0.151119194652883 testicle -0.0499945576046518 varWeightedLogRatios=0.243260065004777 cont.varWeightedLogRatios=0.0285057324004184 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.89511129077846 0.078550093507926 49.5876085798094 6.32992201822164e-281 *** df.mm.trans1 0.477506568684139 0.0684938853693653 6.97152112351491 5.44110698240937e-12 *** df.mm.trans2 -0.0731537613742567 0.0595088947573205 -1.22929121222265 0.219229651787605 df.mm.exp2 0.0550591475561369 0.0760485305361343 0.724000150535133 0.469222002064878 df.mm.exp3 0.00889256344601266 0.0760485305361343 0.116932745226252 0.906935029539346 df.mm.exp4 0.00702847339069952 0.0760485305361343 0.0924208967766964 0.926380729941632 df.mm.exp5 0.0320639274671987 0.0760485305361343 0.421624550022878 0.673382755464143 df.mm.exp6 0.080389498266727 0.0760485305361343 1.05708154648077 0.290710104433676 df.mm.exp7 -0.0350364020102777 0.0760485305361343 -0.460711098074803 0.645098387775175 df.mm.exp8 0.155205670653744 0.0760485305361344 2.04087665546671 0.0415051511568235 * df.mm.trans1:exp2 -0.196674458848467 0.0719495020844328 -2.73350687844469 0.00636848393436641 ** df.mm.trans2:exp2 0.0302846524498438 0.0504769473654234 0.599969967094102 0.548651760095648 df.mm.trans1:exp3 -0.262250109924302 0.0719495020844328 -3.64491903802963 0.000280170499643174 *** df.mm.trans2:exp3 -0.0350287263371165 0.0504769473654234 -0.693954927256775 0.48785929453053 df.mm.trans1:exp4 -0.129567965342267 0.0719495020844328 -1.80081809586699 0.072009673802362 . df.mm.trans2:exp4 0.00421269894959579 0.0504769473654235 0.0834578786846662 0.933502891501278 df.mm.trans1:exp5 -0.125692800622283 0.0719495020844328 -1.74695858874440 0.0809279820910812 . df.mm.trans2:exp5 -0.0496789484736586 0.0504769473654235 -0.984190825051527 0.325241512721072 df.mm.trans1:exp6 -0.228482645497946 0.0719495020844328 -3.17559731309637 0.00153749778074191 ** df.mm.trans2:exp6 -0.0377456188508263 0.0504769473654235 -0.747779349206088 0.454755596826367 df.mm.trans1:exp7 0.145731976835633 0.0719495020844328 2.02547582142566 0.0430633916702988 * df.mm.trans2:exp7 0.0560333954180621 0.0504769473654235 1.11007892399699 0.267211430364991 df.mm.trans1:exp8 -0.165916602402914 0.0719495020844328 -2.30601460185521 0.0212979810020645 * df.mm.trans2:exp8 0.052300174829038 0.0504769473654235 1.03612000247193 0.300377450747558 df.mm.trans1:probe2 -0.0701453802022302 0.049260456616136 -1.42396934622106 0.154743392661046 df.mm.trans1:probe3 -0.0346557063358297 0.049260456616136 -0.703519794911477 0.481883092057344 df.mm.trans1:probe4 0.308090642355857 0.049260456616136 6.25431966164391 5.73679848868471e-10 *** df.mm.trans1:probe5 -0.0513873222707884 0.049260456616136 -1.04317592244883 0.297099620307598 df.mm.trans1:probe6 -0.219756392594950 0.049260456616136 -4.46111156271673 9.00446236053102e-06 *** df.mm.trans1:probe7 -0.133432726089957 0.049260456616136 -2.70871882349237 0.00686084947655749 ** df.mm.trans1:probe8 -0.152699338357019 0.049260456616136 -3.09983603170662 0.00198625647803791 ** df.mm.trans1:probe9 0.238675333553592 0.049260456616136 4.84517095351914 1.44926036596033e-06 *** df.mm.trans1:probe10 0.000523646735703705 0.049260456616136 0.0106301640641345 0.991520473737592 df.mm.trans1:probe11 -0.208626297796376 0.049260456616136 -4.23516776188464 2.47776599975123e-05 *** df.mm.trans1:probe12 -0.214740964426528 0.049260456616136 -4.35929707472882 1.42902728666152e-05 *** df.mm.trans1:probe13 -0.0820309295584237 0.049260456616136 -1.66524906980974 0.0961522978519267 . df.mm.trans1:probe14 -0.155225678707795 0.049260456616136 -3.15112139372555 0.00167106414533670 ** df.mm.trans1:probe15 -0.0172142347823293 0.049260456616136 -0.34945341486523 0.726816875479809 df.mm.trans1:probe16 -0.076418125830747 0.049260456616136 -1.55130770358542 0.121120121436765 df.mm.trans1:probe17 -0.37366015155515 0.049260456616136 -7.58539764393398 7.11525977657431e-14 *** df.mm.trans1:probe18 -0.269514000494527 0.049260456616136 -5.47120386225254 5.55069923023554e-08 *** df.mm.trans1:probe19 -0.32371205072767 0.049260456616136 -6.57143828873143 7.72751128157436e-11 *** df.mm.trans1:probe20 -0.351173909649718 0.049260456616136 -7.12892112199149 1.84494771347027e-12 *** df.mm.trans1:probe21 -0.313333734771904 0.049260456616136 -6.36075579269533 2.95595443357086e-10 *** df.mm.trans1:probe22 -0.232223632415904 0.049260456616136 -4.71419975307 2.74275546751216e-06 *** df.mm.trans1:probe23 -0.0493092292817815 0.049260456616136 -1.00099009771723 0.317055191515139 df.mm.trans1:probe24 -0.0888772318524472 0.049260456616136 -1.80423077571177 0.0714728772862153 . df.mm.trans1:probe25 -0.0235464369884191 0.049260456616136 -0.477998756120057 0.632747555900728 df.mm.trans1:probe26 -0.0791277779660682 0.049260456616136 -1.60631434220504 0.108496368637580 df.mm.trans1:probe27 -0.158375348694792 0.049260456616136 -3.21506050845077 0.00134272206834089 ** df.mm.trans1:probe28 -0.194247975034827 0.049260456616136 -3.94328409394400 8.55366948891219e-05 *** df.mm.trans1:probe29 0.144577396538152 0.049260456616136 2.93495851377865 0.00340632671632904 ** df.mm.trans1:probe30 0.219819155883034 0.049260456616136 4.46238567368515 8.95203618599827e-06 *** df.mm.trans1:probe31 0.0256609822840848 0.049260456616136 0.520924572097433 0.602525806698208 df.mm.trans1:probe32 -0.136317342281614 0.049260456616136 -2.76727727767268 0.00574895086161381 ** df.mm.trans2:probe2 -0.0506200105134063 0.049260456616136 -1.02759929547273 0.304367806375717 df.mm.trans2:probe3 -0.0189155237548094 0.049260456616136 -0.383990020681483 0.701061219416499 df.mm.trans2:probe4 0.00951867551643392 0.049260456616136 0.193231572955333 0.846813844895972 df.mm.trans2:probe5 -0.0354241522073592 0.049260456616136 -0.71911944469787 0.472222460681445 df.mm.trans2:probe6 0.135278400634228 0.049260456616136 2.74618649373045 0.00612914360848291 ** df.mm.trans3:probe2 -0.0467928345038219 0.049260456616136 -0.94990663339678 0.342371621441562 df.mm.trans3:probe3 0.132101436097528 0.049260456616136 2.68169329259234 0.00743645357999573 ** df.mm.trans3:probe4 0.294430823462466 0.049260456616136 5.9770218079144 3.08091214857971e-09 *** df.mm.trans3:probe5 0.63185799223718 0.049260456616136 12.8268805374858 3.64537044960417e-35 *** df.mm.trans3:probe6 0.0333073074735928 0.049260456616136 0.676146949532791 0.499091713667721 df.mm.trans3:probe7 0.159258272395775 0.049260456616136 3.23298408776032 0.00126201549253905 ** df.mm.trans3:probe8 -0.116704601326223 0.049260456616136 -2.36913356763311 0.0180044459923189 * df.mm.trans3:probe9 0.0903801990300598 0.049260456616136 1.83474139783865 0.066818184225874 . df.mm.trans3:probe10 -0.0255894001849914 0.049260456616136 -0.519471436986421 0.603538172644007 cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.22092165430963 0.133690971220253 31.5722267239406 1.21843677883447e-155 *** df.mm.trans1 -0.064990580547007 0.116575469852943 -0.557497907827357 0.577302494581671 df.mm.trans2 0.0116204880434523 0.101283163151769 0.114732673050894 0.908678282723616 df.mm.exp2 0.0256866482366909 0.129433352058619 0.198454631886979 0.842726623729767 df.mm.exp3 0.0124730223887520 0.129433352058619 0.0963663707257082 0.923247428959782 df.mm.exp4 0.028558889474225 0.129433352058619 0.220645521575389 0.825410041363165 df.mm.exp5 0.0456591447514746 0.129433352058619 0.352761819309107 0.724335652051323 df.mm.exp6 0.191030794433398 0.129433352058619 1.47590085086325 0.140261186608651 df.mm.exp7 -0.0168673628853639 0.129433352058619 -0.130316974853010 0.896339851282584 df.mm.exp8 0.0290065305061655 0.129433352058619 0.224103989001449 0.822718657920597 df.mm.trans1:exp2 -0.0245158010167711 0.122456872842689 -0.20019946980244 0.841362167836256 df.mm.trans2:exp2 -0.0192164058138389 0.0859109367812032 -0.223678224610435 0.823049876243885 df.mm.trans1:exp3 -0.00518716256428676 0.122456872842689 -0.0423590970753460 0.966220242818218 df.mm.trans2:exp3 -0.0473019628141973 0.0859109367812032 -0.55059302792455 0.582026238470535 df.mm.trans1:exp4 -0.0409235471427223 0.122456872842689 -0.334187426093215 0.738302833367986 df.mm.trans2:exp4 -0.0800327009318159 0.0859109367812032 -0.931577560789985 0.351762502536214 df.mm.trans1:exp5 -0.048708533201417 0.122456872842689 -0.397760714206619 0.6908849664374 df.mm.trans2:exp5 -0.0129600461944544 0.0859109367812032 -0.150854439260287 0.8801186337309 df.mm.trans1:exp6 -0.162844007018341 0.122456872842689 -1.32980700256436 0.183861871478600 df.mm.trans2:exp6 -0.100450228142858 0.0859109367812032 -1.16923679226875 0.242565518178698 df.mm.trans1:exp7 0.0101396660254728 0.122456872842689 0.0828019350004023 0.934024331522935 df.mm.trans2:exp7 -0.0133185335229359 0.0859109367812032 -0.155027217976395 0.876828746955385 df.mm.trans1:exp8 0.0138408758201326 0.122456872842689 0.113026533332375 0.910030466368969 df.mm.trans2:exp8 -0.033912604238578 0.0859109367812032 -0.394741409058851 0.693111464468173 df.mm.trans1:probe2 0.0620239570638651 0.083840489471853 0.739785245226745 0.45959064027891 df.mm.trans1:probe3 0.0126888460344252 0.083840489471853 0.151345085344297 0.879731691708477 df.mm.trans1:probe4 0.0501450637844602 0.083840489471853 0.598100799510419 0.549897728774662 df.mm.trans1:probe5 -0.00988659399392977 0.083840489471853 -0.117921472741985 0.906151745286795 df.mm.trans1:probe6 -0.0779542522167241 0.083840489471853 -0.929792427355698 0.352685763857844 df.mm.trans1:probe7 -0.0663808007058389 0.083840489471853 -0.791751111235155 0.428679188637188 df.mm.trans1:probe8 0.00409674842950447 0.083840489471853 0.0488636034368554 0.961037004015545 df.mm.trans1:probe9 0.094515150312845 0.083840489471853 1.12732107014446 0.259856457506919 df.mm.trans1:probe10 0.0332693559125294 0.083840489471853 0.396817291050032 0.691580379706857 df.mm.trans1:probe11 0.0742310019766837 0.083840489471853 0.885383690437597 0.37614626104695 df.mm.trans1:probe12 0.000446309393093114 0.083840489471853 0.00532331569036162 0.995753609029293 df.mm.trans1:probe13 -0.0529464348195152 0.083840489471853 -0.631513903998502 0.527837827779552 df.mm.trans1:probe14 -0.0186975188175883 0.083840489471853 -0.223012996886968 0.823567445387366 df.mm.trans1:probe15 0.0938392076524271 0.083840489471853 1.11925882403073 0.263277911461025 df.mm.trans1:probe16 0.0272936226451337 0.083840489471853 0.325542262659341 0.744833585686807 df.mm.trans1:probe17 -0.00134564576276203 0.083840489471853 -0.0160500704521029 0.987197402587171 df.mm.trans1:probe18 0.0218399512130374 0.083840489471853 0.260494080492809 0.794532200171685 df.mm.trans1:probe19 0.0844692309576771 0.083840489471853 1.00749925829137 0.313919957271796 df.mm.trans1:probe20 0.0751610133861561 0.083840489471853 0.89647631901516 0.370197645812160 df.mm.trans1:probe21 0.0363927915669879 0.083840489471853 0.434071792713063 0.664322766878569 df.mm.trans1:probe22 -0.110620493840152 0.083840489471853 -1.31941612622967 0.187308897885457 df.mm.trans1:probe23 -0.0353718803239152 0.083840489471853 -0.4218949644347 0.673185417465976 df.mm.trans1:probe24 0.0414068695308669 0.083840489471853 0.493876762787365 0.621493362382175 df.mm.trans1:probe25 0.0628653798957644 0.083840489471853 0.749821241404723 0.453525223714879 df.mm.trans1:probe26 -0.0534554593913556 0.083840489471853 -0.637585249419395 0.523878468977135 df.mm.trans1:probe27 0.0264068028343256 0.083840489471853 0.314964798042966 0.752849054667 df.mm.trans1:probe28 -0.0330455237821913 0.083840489471853 -0.394147553173403 0.693549699340414 df.mm.trans1:probe29 0.0170694969134531 0.083840489471853 0.203594910060534 0.838708318663848 df.mm.trans1:probe30 0.112805225645520 0.083840489471853 1.34547432101278 0.178753736445103 df.mm.trans1:probe31 -0.0135404607986351 0.083840489471853 -0.161502644890699 0.871727651422175 df.mm.trans1:probe32 0.100797303894881 0.083840489471853 1.20225089965298 0.229529133148012 df.mm.trans2:probe2 -0.0448963269373391 0.083840489471853 -0.535496956424756 0.59241620588006 df.mm.trans2:probe3 0.0165328833764994 0.083840489471853 0.197194499705894 0.843712336151495 df.mm.trans2:probe4 -0.100278645430496 0.083840489471853 -1.19606464683346 0.231933127886861 df.mm.trans2:probe5 0.111732005620566 0.083840489471853 1.33267358437926 0.182919254531553 df.mm.trans2:probe6 -0.0423998961229413 0.083840489471853 -0.505720999364821 0.613155436964675 df.mm.trans3:probe2 -0.0125664298067988 0.083840489471853 -0.149884976649828 0.88088327273438 df.mm.trans3:probe3 0.0801471008658972 0.083840489471853 0.955947435073172 0.339312124162244 df.mm.trans3:probe4 0.0629963481677761 0.083840489471853 0.751383353849875 0.452585220422441 df.mm.trans3:probe5 0.085414039595319 0.083840489471853 1.01876837949514 0.308540466972353 df.mm.trans3:probe6 -0.0106684877262737 0.083840489471853 -0.127247440866329 0.898768179764575 df.mm.trans3:probe7 0.000283324808508329 0.083840489471853 0.0033793315174221 0.99730431104056 df.mm.trans3:probe8 0.0429943380618838 0.083840489471853 0.512811152853752 0.608188004608182 df.mm.trans3:probe9 -0.00379515448422153 0.083840489471853 -0.0452663684113586 0.963903338965032 df.mm.trans3:probe10 0.0493007687660076 0.083840489471853 0.588030545582143 0.556634385311423