chr17.9999_chr17_45449247_45449844_+_0.R fitVsDatCorrelation=0.889605303111375 cont.fitVsDatCorrelation=0.279783378977446 fstatistic=6998.55415486257,41,439 cont.fstatistic=1575.61694402103,41,439 residuals=-0.730064715320781,-0.0881554629054156,-2.25557275449816e-05,0.0733236884921558,1.08582814266420 cont.residuals=-0.546339274465129,-0.202494294248851,-0.0807753656540094,0.0725379814443817,1.89929821535828 predictedValues: Include Exclude Both chr17.9999_chr17_45449247_45449844_+_0.R.tl.Lung 54.211920329484 55.0073977756911 66.72106958121 chr17.9999_chr17_45449247_45449844_+_0.R.tl.cerebhem 74.4769910561654 60.9037781503882 77.6123415331914 chr17.9999_chr17_45449247_45449844_+_0.R.tl.cortex 51.735109945538 51.3374530569657 58.6586055224545 chr17.9999_chr17_45449247_45449844_+_0.R.tl.heart 55.3311666464792 54.7717234012106 62.6965978118752 chr17.9999_chr17_45449247_45449844_+_0.R.tl.kidney 53.3341817536586 52.7494595351511 66.4718768121654 chr17.9999_chr17_45449247_45449844_+_0.R.tl.liver 51.0075091898678 58.5714593788109 68.0980684451867 chr17.9999_chr17_45449247_45449844_+_0.R.tl.stomach 53.0207415015806 53.5301166644482 64.2494652464929 chr17.9999_chr17_45449247_45449844_+_0.R.tl.testicle 53.5843054933414 53.2574561520967 69.0314879479746 diffExp=-0.795477446207094,13.5732129057772,0.397656888572314,0.559443245268632,0.584722218507522,-7.56395018894312,-0.50937516286757,0.32684934124466 diffExpScore=3.2101445666474 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 55.707560549802 69.3040229594609 59.7647394379962 cerebhem 61.3822398291228 59.0153697124294 61.1159017728311 cortex 63.9189926963052 56.7979805944635 64.0016587384505 heart 58.4958639473475 59.7235292412261 62.2660388557556 kidney 53.2953699609193 53.5543809792795 58.4739584114108 liver 58.4265362922479 58.5935364082899 58.9191600579626 stomach 57.0132653140408 57.1364929203693 56.3076029812382 testicle 62.0219250226446 56.9563571122937 64.8472318967838 cont.diffExp=-13.5964624096589,2.36687011669337,7.12101210184161,-1.22766529387857,-0.259011018360184,-0.16700011604199,-0.123227606328498,5.06556791035091 cont.diffExpScore=16.4440619165876 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=-1,0,0,0,0,0,0,0 cont.diffExp1.2Score=0.5 tran.correlation=0.711362553345174 cont.tran.correlation=-0.144997276391241 tran.covariance=0.00479295322459153 cont.tran.covariance=-0.00047394949125751 tran.mean=55.4269231269298 cont.tran.mean=58.8339639712651 weightedLogRatios: wLogRatio Lung -0.0582701425591824 cerebhem 0.847009456370647 cortex 0.0304189976325556 heart 0.0407330015721103 kidney 0.0437766597069666 liver -0.55325221525333 stomach -0.038010354578773 testicle 0.0243402038781572 cont.weightedLogRatios: wLogRatio Lung -0.901787830460485 cerebhem 0.161122857263893 cortex 0.484104413073293 heart -0.0847279848181114 kidney -0.0192872456531227 liver -0.0116143643405868 stomach -0.00873199266507001 testicle 0.348043133482115 varWeightedLogRatios=0.145610266181039 cont.varWeightedLogRatios=0.171757116219369 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 2.89190984430614 0.085493967572498 33.8258935269769 2.36590107092533e-124 *** df.mm.trans1 1.09286494866779 0.0689807965522705 15.8430317318773 4.91699452662609e-45 *** df.mm.trans2 1.09222586947208 0.0689807965522705 15.8337671361107 5.40023867918197e-45 *** df.mm.exp2 0.268211280338456 0.0929177472181597 2.88654523348192 0.00408716664397108 ** df.mm.exp3 0.0129752251151941 0.0929177472181597 0.139642054436918 0.889006852622826 df.mm.exp4 0.078355512664183 0.0929177472181597 0.843278221976408 0.399532091236421 df.mm.exp5 -0.0544957012141252 0.0929177472181597 -0.586493999754168 0.557845039158407 df.mm.exp6 -0.0185761606480272 0.0929177472181596 -0.199920480254570 0.841635346262832 df.mm.exp7 -0.0116934997497010 0.0929177472181597 -0.125847861143750 0.89990996829674 df.mm.exp8 -0.0780164228385308 0.0929177472181597 -0.839628867188931 0.401573513529415 df.mm.trans1:exp2 0.0493781359186241 0.0741227202541868 0.666167347195208 0.505654048761491 df.mm.trans2:exp2 -0.166383750152743 0.0741227202541868 -2.24470647572254 0.0252842410740576 * df.mm.trans1:exp3 -0.0597393814354333 0.0741227202541868 -0.80595236157781 0.420706666107061 df.mm.trans2:exp3 -0.0820223414334564 0.0741227202541868 -1.10657489568893 0.269083762770205 df.mm.trans1:exp4 -0.0579199872760897 0.0741227202541868 -0.781406660163935 0.434984552494622 df.mm.trans2:exp4 -0.0826491294104545 0.0741227202541868 -1.11503098006965 0.265447172324288 df.mm.trans1:exp5 0.0381723189920676 0.0741227202541868 0.514988101639611 0.606820531881835 df.mm.trans2:exp5 0.0125815465386388 0.0741227202541868 0.169739406426171 0.865293271869468 df.mm.trans1:exp6 -0.0423517949915759 0.0741227202541868 -0.571373997693827 0.568038550930898 df.mm.trans2:exp6 0.08135601607058 0.0741227202541868 1.09758540689802 0.272987220167014 df.mm.trans1:exp7 -0.0105241307111761 0.0741227202541868 -0.141982521352239 0.887158946847725 df.mm.trans2:exp7 -0.0155297576256464 0.0741227202541868 -0.209514135104469 0.83414409306769 df.mm.trans1:exp8 0.0663718235362733 0.0741227202541868 0.895431566848417 0.371047134298334 df.mm.trans2:exp8 0.0456865580615225 0.0741227202541867 0.616363753311414 0.537973943719593 df.mm.trans1:probe2 0.098570849856757 0.0485247108972639 2.0313536759745 0.0428210231167356 * df.mm.trans1:probe3 0.00342339799912738 0.0485247108972639 0.0705495805297093 0.943788365589349 df.mm.trans1:probe4 -0.0391116156844883 0.0485247108972639 -0.806014398875968 0.420670933233078 df.mm.trans1:probe5 0.0694842984951713 0.0485247108972639 1.43193637242441 0.152873616397353 df.mm.trans1:probe6 -0.0186026007088036 0.0485247108972639 -0.383363452657942 0.701635874708259 df.mm.trans2:probe2 0.135701455023410 0.0485247108972639 2.79654329751117 0.00539211874705353 ** df.mm.trans2:probe3 0.0449136643855491 0.0485247108972639 0.925583348258167 0.355171071221855 df.mm.trans2:probe4 0.0319748836168732 0.0485247108972639 0.658940218821089 0.510279624806485 df.mm.trans2:probe5 0.00875333812231579 0.0485247108972639 0.180389289507531 0.85693020372649 df.mm.trans2:probe6 0.105304202757440 0.0485247108972639 2.17011499523179 0.0305336831358333 * df.mm.trans3:probe2 -1.26134144313022 0.0485247108972639 -25.9937961464772 7.24833561186356e-91 *** df.mm.trans3:probe3 -1.19269264207261 0.0485247108972639 -24.5790777527303 1.56289580321648e-84 *** df.mm.trans3:probe4 -0.823424288285622 0.0485247108972639 -16.9691745310749 5.01650744195355e-50 *** df.mm.trans3:probe5 -0.267206175270466 0.0485247108972639 -5.50660004623608 6.23780905727888e-08 *** df.mm.trans3:probe6 -1.02219048233435 0.0485247108972639 -21.0653595546096 1.37559443744662e-68 *** df.mm.trans3:probe7 -1.16016569122839 0.0485247108972639 -23.9087605011122 1.64639515097136e-81 *** df.mm.trans3:probe8 -1.28481826672299 0.0485247108972639 -26.4776078613470 5.13394382983811e-93 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.18998766872605 0.179711396706255 23.3150915608025 8.00042640547193e-79 *** df.mm.trans1 -0.171983996524451 0.145000116924113 -1.18609557131916 0.236226101837328 df.mm.trans2 0.0199426316271044 0.145000116924113 0.137535279626992 0.890670765806264 df.mm.exp2 -0.0860566222006978 0.195316448698140 -0.440600997889828 0.659718756544882 df.mm.exp3 -0.129994671147816 0.19531644869814 -0.665559260442637 0.506042387072825 df.mm.exp4 -0.140937022111903 0.195316448698140 -0.721582964728795 0.470935050423388 df.mm.exp5 -0.280237420372436 0.195316448698140 -1.43478658474659 0.152059919842140 df.mm.exp6 -0.105974755392475 0.195316448698140 -0.542579778092619 0.587694498701261 df.mm.exp7 -0.110305571608596 0.195316448698140 -0.564753108833516 0.572530161494388 df.mm.exp8 -0.170463948378985 0.195316448698140 -0.872757770864635 0.383272229715422 df.mm.trans1:exp2 0.183061287212461 0.155808625599825 1.17491112258849 0.240667149907047 df.mm.trans2:exp2 -0.07464842009227 0.155808625599825 -0.47910325763347 0.632103729727994 df.mm.trans1:exp3 0.267495338960814 0.155808625599825 1.71681983542967 0.0867174456426258 . df.mm.trans2:exp3 -0.069007512545486 0.155808625599825 -0.442899180195088 0.658056816863761 df.mm.trans1:exp4 0.189777197393390 0.155808625599825 1.21801470658504 0.223872606822099 df.mm.trans2:exp4 -0.00783986636661698 0.155808625599825 -0.0503172808080131 0.959892438432219 df.mm.trans1:exp5 0.235971005543972 0.155808625599825 1.51449256827432 0.130620584828458 df.mm.trans2:exp5 0.0224320690501262 0.155808625599825 0.143971933285261 0.885588698475628 df.mm.trans1:exp6 0.153629055887228 0.155808625599825 0.986011238439426 0.324670714185654 df.mm.trans2:exp6 -0.0619038101819178 0.155808625599825 -0.397306695592771 0.691334407906085 df.mm.trans1:exp7 0.133473662472569 0.155808625599825 0.856651305142624 0.392104988845159 df.mm.trans2:exp7 -0.0827543663088187 0.155808625599825 -0.53112827348444 0.595598502357168 df.mm.trans1:exp8 0.277836025607338 0.155808625599825 1.7831877056725 0.075246554312514 . df.mm.trans2:exp8 -0.0257536976280019 0.155808625599825 -0.165290577006609 0.868791362309987 df.mm.trans1:probe2 -0.0338876806379688 0.102000688676890 -0.332229919989222 0.739874222894749 df.mm.trans1:probe3 0.039405272081025 0.102000688676890 0.386323588518602 0.699444200803239 df.mm.trans1:probe4 0.0579235239771463 0.102000688676890 0.567873851917135 0.570410941777379 df.mm.trans1:probe5 -0.0386433966640805 0.102000688676890 -0.378854272116651 0.704979242151782 df.mm.trans1:probe6 0.00477311625081432 0.102000688676890 0.0467949414139174 0.962697940446654 df.mm.trans2:probe2 0.00460967341358578 0.102000688676890 0.0451925714755508 0.96397436479355 df.mm.trans2:probe3 -0.00855189071232746 0.102000688676890 -0.0838414997316091 0.933220669945119 df.mm.trans2:probe4 0.245168029214105 0.102000688676890 2.40359190113635 0.0166486037333925 * df.mm.trans2:probe5 0.0724146966654834 0.102000688676890 0.70994321317646 0.478116277850503 df.mm.trans2:probe6 0.0863766687111754 0.102000688676890 0.846824367870617 0.397554416175585 df.mm.trans3:probe2 0.0643555030134218 0.102000688676890 0.630932044167682 0.528413290544582 df.mm.trans3:probe3 -0.0597223526452759 0.102000688676890 -0.585509308024963 0.558506165501506 df.mm.trans3:probe4 0.183312693623823 0.102000688676890 1.79717113679993 0.0729956262049758 . df.mm.trans3:probe5 0.225904400062895 0.102000688676890 2.21473406692868 0.0272911116475462 * df.mm.trans3:probe6 -0.0080115336117264 0.102000688676890 -0.078543916866137 0.937431185288488 df.mm.trans3:probe7 -0.0150362338997717 0.102000688676890 -0.147413062547080 0.882873673076215 df.mm.trans3:probe8 0.0289538571837025 0.102000688676890 0.283859428394843 0.776651937065596