chr12.5360_chr12_79847525_79849444_-_1.R fitVsDatCorrelation=0.770798944464504 cont.fitVsDatCorrelation=0.232470585266014 fstatistic=7434.30358700623,40,416 cont.fstatistic=3183.79692552323,40,416 residuals=-0.48619327282457,-0.0919410154696532,-0.0127535818254775,0.0675665437351336,1.33901615193267 cont.residuals=-0.460285359006597,-0.164723631188847,-0.0386992934924173,0.124413992699582,1.46397531755508 predictedValues: Include Exclude Both chr12.5360_chr12_79847525_79849444_-_1.R.tl.Lung 68.311888431854 50.3413764697562 59.5718097022613 chr12.5360_chr12_79847525_79849444_-_1.R.tl.cerebhem 68.7123194272599 50.4310564938323 66.2699336297544 chr12.5360_chr12_79847525_79849444_-_1.R.tl.cortex 84.1641084771129 47.4178582100461 69.6692372659996 chr12.5360_chr12_79847525_79849444_-_1.R.tl.heart 64.6345115862515 48.3743384923975 57.7592929272909 chr12.5360_chr12_79847525_79849444_-_1.R.tl.kidney 66.5659522249503 52.7523756081494 61.1745396842569 chr12.5360_chr12_79847525_79849444_-_1.R.tl.liver 58.6428763983776 49.589918437326 65.4941592701639 chr12.5360_chr12_79847525_79849444_-_1.R.tl.stomach 61.8694955044162 49.3950039460711 58.4810124744129 chr12.5360_chr12_79847525_79849444_-_1.R.tl.testicle 65.7346155083717 46.400534539648 60.7063630081037 diffExp=17.9705119620977,18.2812629334276,36.7462502670667,16.2601730938540,13.8135766168009,9.05295796105157,12.4744915583451,19.3340809687237 diffExpScore=0.993100274657321 diffExp1.5=0,0,1,0,0,0,0,0 diffExp1.5Score=0.5 diffExp1.4=0,0,1,0,0,0,0,1 diffExp1.4Score=0.666666666666667 diffExp1.3=1,1,1,1,0,0,0,1 diffExp1.3Score=0.833333333333333 diffExp1.2=1,1,1,1,1,0,1,1 diffExp1.2Score=0.875 cont.predictedValues: Include Exclude Both Lung 60.9714705142698 56.9926047597883 61.2693509494109 cerebhem 60.9626214640157 60.111349435004 58.7010790971037 cortex 60.4431024055463 61.5635330682875 58.6823080618639 heart 64.8051250911673 58.9329502378674 55.5673843421562 kidney 59.3412589049544 54.4630640491587 59.4045717751507 liver 61.6677412207482 61.6771653837752 55.4670383966424 stomach 58.3399211775278 54.5544341303827 58.9092275799742 testicle 59.9935938187279 54.4702414211123 60.2781595025817 cont.diffExp=3.97886575448148,0.851272029011696,-1.12043066274119,5.87217485329984,4.87819485579567,-0.00942416302700622,3.78548704714504,5.52335239761556 cont.diffExpScore=1.05087784700346 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=-0.264606879492012 cont.tran.correlation=0.528313964326488 tran.covariance=-0.00106249216205078 cont.tran.covariance=0.000924961932763214 tran.mean=58.3336393597388 cont.tran.mean=59.3306360676458 weightedLogRatios: wLogRatio Lung 1.24283819914712 cerebhem 1.26056722790535 cortex 2.37878227038664 heart 1.16602994102716 kidney 0.949386548544355 liver 0.668639494817032 stomach 0.903512708384624 testicle 1.39725330232838 cont.weightedLogRatios: wLogRatio Lung 0.27511178016629 cerebhem 0.0577006318169832 cortex -0.075505603231666 heart 0.391705169069412 kidney 0.346595105786401 liver -0.000629857664282849 stomach 0.27054711178416 testicle 0.390770682656908 varWeightedLogRatios=0.264473251410304 cont.varWeightedLogRatios=0.0344659672813414 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.02424127359492 0.08198961983012 49.0823262985366 3.83466449086998e-175 *** df.mm.trans1 0.213940897019166 0.066502363234065 3.21704202099058 0.00139646031744454 ** df.mm.trans2 -0.0947414144597423 0.066502363234065 -1.42463229654389 0.155013260457892 df.mm.exp2 -0.098929289351042 0.0899276083788342 -1.10009919238914 0.271925089747401 df.mm.exp3 -0.00772005826396915 0.0899276083788342 -0.0858474766886626 0.931628966837897 df.mm.exp4 -0.0642949486280896 0.0899276083788341 -0.71496339986311 0.475032695562669 df.mm.exp5 -0.00565773476840867 0.0899276083788342 -0.0629143248708959 0.949864945527857 df.mm.exp6 -0.262435978848251 0.0899276083788342 -2.91830266121054 0.00371038962808192 ** df.mm.exp7 -0.0995542642740988 0.0899276083788342 -1.10704894824636 0.268912485901461 df.mm.exp8 -0.138840556870313 0.0899276083788342 -1.54391470398530 0.123369339623191 df.mm.trans1:exp2 0.104773981198845 0.0725019557438213 1.44511937814552 0.149177194148860 df.mm.trans2:exp2 0.100709142136437 0.0725019557438213 1.38905414486035 0.165559409129092 df.mm.trans1:exp3 0.216404810128511 0.0725019557438213 2.98481341514643 0.00300491381495053 ** df.mm.trans2:exp3 -0.0521083612962654 0.0725019557438213 -0.718716629940098 0.472719023874819 df.mm.trans1:exp4 0.0089596384556677 0.0725019557438213 0.123577886468687 0.901709186753284 df.mm.trans2:exp4 0.0244370925158322 0.0725019557438213 0.337054252745654 0.736245985698198 df.mm.trans1:exp5 -0.0202328596498737 0.0725019557438213 -0.279066398172273 0.780332549562818 df.mm.trans2:exp5 0.0524392085431668 0.0725019557438213 0.723279917143969 0.469914400931994 df.mm.trans1:exp6 0.109818273648212 0.0725019557438213 1.5146939488949 0.130609333994873 df.mm.trans2:exp6 0.247396201814648 0.0725019557438213 3.41226935572329 0.000707344052892865 *** df.mm.trans1:exp7 0.000497706271338834 0.0725019557438213 0.00686472890603712 0.994526072519065 df.mm.trans2:exp7 0.0805762158656583 0.0725019557438213 1.11136610094170 0.267052693989608 df.mm.trans1:exp8 0.100382402496444 0.0725019557438213 1.38454751277518 0.166933043515627 df.mm.trans2:exp8 0.0573242034942575 0.0725019557438213 0.790657340290338 0.42959448226117 df.mm.trans1:probe2 -0.00700747534818931 0.0460741887779205 -0.152091128114390 0.87918879526478 df.mm.trans1:probe3 0.0317450357336294 0.0460741887779205 0.688998256412973 0.491208455972467 df.mm.trans1:probe4 0.0666520191594312 0.0460741887779205 1.44662382403946 0.1487553539108 df.mm.trans1:probe5 -0.136846900581746 0.0460741887779205 -2.97014237714209 0.00314903400423547 ** df.mm.trans1:probe6 -0.137821322882519 0.0460741887779205 -2.99129136156523 0.00294322108959598 ** df.mm.trans2:probe2 0.00125995176828477 0.0460741887779205 0.0273461519715038 0.97819676003489 df.mm.trans2:probe3 -0.0143785833007425 0.0460741887779205 -0.312074584102780 0.75514019850982 df.mm.trans2:probe4 -0.000588373516614209 0.0460741887779205 -0.0127701329577433 0.989817306906037 df.mm.trans2:probe5 -0.0793268248563942 0.0460741887779205 -1.72171940430146 0.0858637383820743 . df.mm.trans2:probe6 -0.0457090125435319 0.0460741887779205 -0.9920741689854 0.321738033272878 df.mm.trans3:probe2 0.0545673607817079 0.0460741887779205 1.18433687557094 0.236955960068796 df.mm.trans3:probe3 -0.162215522122367 0.0460741887779205 -3.52074613628583 0.000477913727787466 *** df.mm.trans3:probe4 -0.214920518837474 0.0460741887779205 -4.66466202744014 4.17289630125634e-06 *** df.mm.trans3:probe5 -0.174276033121003 0.0460741887779205 -3.78250898699533 0.000178014819247780 *** df.mm.trans3:probe6 0.280853966114177 0.0460741887779205 6.09568987677471 2.48821911073072e-09 *** df.mm.trans3:probe7 -0.177817251676461 0.0460741887779205 -3.85936804082536 0.000131738875241760 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.0514116093531 0.125170427197833 32.3671629158044 1.06129093414660e-115 *** df.mm.trans1 0.0779796670864379 0.101526622917886 0.768071121103943 0.442880697319304 df.mm.trans2 -0.0124024551989950 0.101526622917886 -0.122159635005549 0.902831583081709 df.mm.exp2 0.0959536265301946 0.137289051723630 0.698916813289336 0.484994577481537 df.mm.exp3 0.111586037247731 0.137289051723630 0.812781761158633 0.416808090766582 df.mm.exp4 0.192140792341736 0.137289051723630 1.39953470381983 0.162397934431571 df.mm.exp5 -0.0415914547701868 0.137289051723630 -0.302948081059752 0.762080861217074 df.mm.exp6 0.189837948039934 0.137289051723630 1.38276101157787 0.167479947233879 df.mm.exp7 -0.0485599788855625 0.137289051723630 -0.353706127880584 0.723738319052942 df.mm.exp8 -0.0451253736621953 0.137289051723630 -0.328688799985558 0.742556316118599 df.mm.trans1:exp2 -0.0960987713395924 0.11068597210154 -0.868210935089718 0.385779446452297 df.mm.trans2:exp2 -0.0426764786660961 0.11068597210154 -0.385563571027284 0.700016998305625 df.mm.trans1:exp3 -0.120289629105727 0.11068597210154 -1.08676489732030 0.277770016689827 df.mm.trans2:exp3 -0.0344378560126552 0.11068597210154 -0.311131170091391 0.75585675255596 df.mm.trans1:exp4 -0.131162159479769 0.11068597210154 -1.18499351805344 0.236696519250551 df.mm.trans2:exp4 -0.158661949677212 0.11068597210154 -1.43344225708801 0.152482626584760 df.mm.trans1:exp5 0.0144902262415214 0.11068597210154 0.130912941960057 0.895907460795639 df.mm.trans2:exp5 -0.00380731554900377 0.11068597210154 -0.0343974532338303 0.972576712575425 df.mm.trans1:exp6 -0.178483044862028 0.11068597210154 -1.61251729982814 0.107607754176426 df.mm.trans2:exp6 -0.110845695014995 0.11068597210154 -1.00144302760704 0.317194819459901 df.mm.trans1:exp7 0.00444053395443948 0.11068597210154 0.0401183083107032 0.968018051929158 df.mm.trans2:exp7 0.00483745511658806 0.11068597210154 0.0437043197502057 0.965161065632357 df.mm.trans1:exp8 0.0289571022143236 0.11068597210154 0.261614924317231 0.793747816074746 df.mm.trans2:exp8 -0.000141621128234947 0.11068597210154 -0.00127948578800056 0.998979731651868 df.mm.trans1:probe2 -0.020602509097854 0.0703397076858661 -0.292900123922378 0.769744538025813 df.mm.trans1:probe3 -0.030579047066991 0.0703397076858661 -0.434733780861809 0.663981097752136 df.mm.trans1:probe4 -0.111244432418774 0.0703397076858661 -1.58153105946341 0.114516629956716 df.mm.trans1:probe5 -0.0594800480200891 0.0703397076858661 -0.845611248282752 0.398255757302490 df.mm.trans1:probe6 -0.02490179944673 0.0703397076858661 -0.354021935347532 0.723501809289117 df.mm.trans2:probe2 0.055660251688156 0.0703397076858661 0.791306269521793 0.429216219600172 df.mm.trans2:probe3 0.0174355398410954 0.0703397076858661 0.247876205556066 0.804352494227657 df.mm.trans2:probe4 -0.0280912013266014 0.0703397076858661 -0.399364772058130 0.689829394355503 df.mm.trans2:probe5 0.0679945325105704 0.0703397076858661 0.966659298816408 0.334276008728705 df.mm.trans2:probe6 -0.0621383880222465 0.0703397076858661 -0.88340412643956 0.37752818966493 df.mm.trans3:probe2 -0.0504463392479732 0.0703397076858661 -0.71718153099618 0.473664579486113 df.mm.trans3:probe3 0.00532643923254448 0.0703397076858661 0.0757245005386162 0.939674685724544 df.mm.trans3:probe4 0.0452365463050368 0.0703397076858661 0.643115358213616 0.520503575830919 df.mm.trans3:probe5 -0.0373866110879786 0.0703397076858661 -0.531515019296718 0.595345630062358 df.mm.trans3:probe6 -0.0213947068193646 0.0703397076858661 -0.304162577912783 0.761156119724712 df.mm.trans3:probe7 0.0467010567071327 0.0703397076858661 0.66393589401448 0.507099138828918