chr5.18616_chr5_37430539_37431125_-_1.R fitVsDatCorrelation=0.961906323429564 cont.fitVsDatCorrelation=0.303676189444364 fstatistic=7166.69932153913,37,347 cont.fstatistic=581.417300243375,37,347 residuals=-0.592787929998588,-0.0923086487081016,0.00299548394311482,0.093358719853465,0.515739962958843 cont.residuals=-1.04155797804660,-0.426925760733256,-0.176609890284508,0.41181102581154,1.62020342300426 predictedValues: Include Exclude Both chr5.18616_chr5_37430539_37431125_-_1.R.tl.Lung 98.3253419447243 51.9042450115133 154.894701557706 chr5.18616_chr5_37430539_37431125_-_1.R.tl.cerebhem 96.5686782929402 66.5157964707077 112.435353523243 chr5.18616_chr5_37430539_37431125_-_1.R.tl.cortex 95.7461027412718 53.5565264283423 148.674258508713 chr5.18616_chr5_37430539_37431125_-_1.R.tl.heart 109.833415950292 52.3980911312856 154.287725023647 chr5.18616_chr5_37430539_37431125_-_1.R.tl.kidney 93.5547809617805 49.34639452887 111.515113419344 chr5.18616_chr5_37430539_37431125_-_1.R.tl.liver 100.175781810133 56.1514239615915 91.216920323224 chr5.18616_chr5_37430539_37431125_-_1.R.tl.stomach 113.397512168549 55.3811101052833 159.945016209976 chr5.18616_chr5_37430539_37431125_-_1.R.tl.testicle 96.891137962487 55.9226283495782 133.449779964059 diffExp=46.421096933211,30.0528818222325,42.1895763129295,57.4353248190067,44.2083864329104,44.0243578485418,58.0164020632659,40.9685096129088 diffExpScore=0.997255134198944 diffExp1.5=1,0,1,1,1,1,1,1 diffExp1.5Score=0.875 diffExp1.4=1,1,1,1,1,1,1,1 diffExp1.4Score=0.888888888888889 diffExp1.3=1,1,1,1,1,1,1,1 diffExp1.3Score=0.888888888888889 diffExp1.2=1,1,1,1,1,1,1,1 diffExp1.2Score=0.888888888888889 cont.predictedValues: Include Exclude Both Lung 70.8371126003416 89.292459690246 98.3742077695937 cerebhem 75.4040977191465 70.8733498558099 90.71136527383 cortex 75.1951885958277 70.4457882236855 72.0757492791953 heart 94.9512225900688 65.5347662607561 64.6298398747961 kidney 62.5673087791971 75.6849168610321 73.6404911839941 liver 81.7413467742426 69.8258167528951 86.7196132421557 stomach 74.2392174615054 75.648569607541 91.4899984852313 testicle 83.6163173149969 78.0475407766309 59.2726234617915 cont.diffExp=-18.4553470899044,4.53074786333663,4.74940037214216,29.4164563293127,-13.1176080818350,11.9155300213475,-1.40935214603564,5.56877653836601 cont.diffExpScore=3.68464309570962 cont.diffExp1.5=0,0,0,0,0,0,0,0 cont.diffExp1.5Score=0 cont.diffExp1.4=0,0,0,1,0,0,0,0 cont.diffExp1.4Score=0.5 cont.diffExp1.3=0,0,0,1,0,0,0,0 cont.diffExp1.3Score=0.5 cont.diffExp1.2=-1,0,0,1,-1,0,0,0 cont.diffExp1.2Score=1.5 tran.correlation=-0.0604599728737197 cont.tran.correlation=-0.529596265315113 tran.covariance=-0.000202631864001463 cont.tran.covariance=-0.00622565397730601 tran.mean=77.8543104887094 cont.tran.mean=75.8690637414952 weightedLogRatios: wLogRatio Lung 2.7272824532702 cerebhem 1.63436384511870 cortex 2.48141692362320 heart 3.20380869866694 kidney 2.69863215969674 liver 2.49928408645589 stomach 3.13364919539668 testicle 2.36269021374457 cont.weightedLogRatios: wLogRatio Lung -1.01322749810967 cerebhem 0.265955410650377 cortex 0.279730509600667 heart 1.61956772239720 kidney -0.805389715954014 liver 0.681395963024405 stomach -0.081179708386913 testicle 0.302683766365184 varWeightedLogRatios=0.241119578341717 cont.varWeightedLogRatios=0.687800571703065 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.37117856860211 0.0905963438986495 37.2109780983376 3.57885957669735e-123 *** df.mm.trans1 1.61138764561062 0.075479187169502 21.3487678661929 3.58142015182255e-65 *** df.mm.trans2 0.595550612784258 0.0754791871695019 7.89026266865915 3.97800312895157e-14 *** df.mm.exp2 0.550378652908067 0.103994463829677 5.2923841581556 2.14510494298393e-07 *** df.mm.exp3 0.0457430277253463 0.103994463829677 0.439860219869634 0.660312179549969 df.mm.exp4 0.124078942113721 0.103994463829677 1.19313026428925 0.233633502297218 df.mm.exp5 0.228314899612042 0.103994463829677 2.19545244241057 0.0287928324057758 * df.mm.exp6 0.626801258327747 0.103994463829677 6.0272560215737 4.26254856409555e-09 *** df.mm.exp7 0.175371074102678 0.103994463829677 1.68635009638496 0.0926272033337514 . df.mm.exp8 0.20889509728123 0.103994463829677 2.00871363328879 0.0453417992206251 * df.mm.trans1:exp2 -0.568406001551594 0.0878913635738622 -6.46714282767859 3.39523902460723e-10 *** df.mm.trans2:exp2 -0.302339771498137 0.0878913635738622 -3.4399258266605 0.000652781849672278 *** df.mm.trans1:exp3 -0.0723248989445048 0.0878913635738622 -0.822889712977594 0.411135849206984 df.mm.trans2:exp3 -0.0144059418016370 0.0878913635738621 -0.163906227140629 0.869900390646336 df.mm.trans1:exp4 -0.0133959206471087 0.0878913635738622 -0.152414527462087 0.878948581858087 df.mm.trans2:exp4 -0.114609359198929 0.0878913635738622 -1.30398886237114 0.193101726023789 df.mm.trans1:exp5 -0.278049538256642 0.0878913635738621 -3.16355927306753 0.00169617271972129 ** df.mm.trans2:exp5 -0.278850774549999 0.0878913635738621 -3.17267548495432 0.00164527610650679 ** df.mm.trans1:exp6 -0.608156593402958 0.0878913635738622 -6.91941242772818 2.19696257247709e-11 *** df.mm.trans2:exp6 -0.548149796464148 0.0878913635738621 -6.23667416427661 1.29964041775677e-09 *** df.mm.trans1:exp7 -0.0327534176091504 0.0878913635738622 -0.372657975451992 0.70963053006881 df.mm.trans2:exp7 -0.110533090279114 0.0878913635738622 -1.25761037017277 0.209378392344710 df.mm.trans1:exp8 -0.223588834072830 0.0878913635738622 -2.54392269025307 0.0113945828772107 * df.mm.trans2:exp8 -0.13432657745708 0.0878913635738621 -1.52832510493701 0.127342855921805 df.mm.trans1:probe2 0.144173914569032 0.0481400824392922 2.99488300110091 0.0029427319475082 ** df.mm.trans1:probe3 -0.778513347904553 0.0481400824392922 -16.1718324617809 3.07378132747219e-44 *** df.mm.trans1:probe4 -1.08253997676768 0.0481400824392922 -22.4872896329754 1.00001660993332e-69 *** df.mm.trans1:probe5 -1.16094638842024 0.0481400824392922 -24.1160033301619 3.65348660415683e-76 *** df.mm.trans1:probe6 -1.06501838349866 0.0481400824392922 -22.123318647028 2.82858118025241e-68 *** df.mm.trans2:probe2 -0.0165606411580957 0.0481400824392922 -0.344009405862148 0.731047577881545 df.mm.trans2:probe3 -0.076589025288368 0.0481400824392922 -1.59096165622383 0.112528783380813 df.mm.trans2:probe4 -0.00612249988490483 0.0481400824392922 -0.127180918159534 0.898870874312088 df.mm.trans2:probe5 -0.0384340869873545 0.0481400824392922 -0.798380165547545 0.42519597281438 df.mm.trans2:probe6 -0.0355797709809654 0.0481400824392922 -0.739088285231622 0.460353035873646 df.mm.trans3:probe2 -0.332196945413155 0.0481400824392922 -6.90063100394723 2.46808847300684e-11 *** df.mm.trans3:probe3 -0.351615562487765 0.0481400824392922 -7.30400831637908 1.92973980781037e-12 *** df.mm.trans3:probe4 -1.45767263500296 0.0481400824392922 -30.2798117730932 2.00754646776804e-99 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.17052675180182 0.315744346328733 13.2085555934539 1.49706629368416e-32 *** df.mm.trans1 0.144847773407620 0.263058370665814 0.550629782435751 0.582241793904437 df.mm.trans2 0.213605071345824 0.263058370665814 0.812006364994882 0.417344658851653 df.mm.exp2 -0.0874480016751392 0.362439173488522 -0.241276352203989 0.809483444046823 df.mm.exp3 0.133691615371184 0.362439173488522 0.368866350964179 0.712452303335312 df.mm.exp4 0.403746430598454 0.362439173488522 1.11397017798144 0.266062983628082 df.mm.exp5 0.000105337587232722 0.362439173488522 0.000290635215335127 0.999768273643435 df.mm.exp6 0.0233622399353627 0.362439173488522 0.064458374381826 0.948642367418084 df.mm.exp7 -0.0463600257971829 0.362439173488522 -0.127911189485844 0.898293352008476 df.mm.exp8 0.53788783922939 0.362439173488522 1.48407754617734 0.138696108817670 df.mm.trans1:exp2 0.149926568989283 0.306317009554111 0.489449048903692 0.624833070859046 df.mm.trans2:exp2 -0.143574565363890 0.306317009554111 -0.468712349904709 0.639569573417028 df.mm.trans1:exp3 -0.0739874205315843 0.306317009554111 -0.241538726952459 0.809280274327774 df.mm.trans2:exp3 -0.370765209079762 0.306317009554111 -1.21039706420308 0.226950393390221 df.mm.trans1:exp4 -0.110766169907826 0.306317009554111 -0.36160633086965 0.717866317051718 df.mm.trans2:exp4 -0.713082692523744 0.306317009554111 -2.3279239163432 0.0204904947282433 * df.mm.trans1:exp5 -0.124245472492932 0.306317009554111 -0.405610751664719 0.685278606015792 df.mm.trans2:exp5 -0.165443492218231 0.306317009554111 -0.540105469360185 0.589470755850619 df.mm.trans1:exp6 0.119814661752316 0.306317009554111 0.391145963218704 0.695929406083152 df.mm.trans2:exp6 -0.269275477389376 0.306317009554111 -0.879074517544243 0.379969203615888 df.mm.trans1:exp7 0.0932695209301401 0.306317009554111 0.304486913952012 0.76093948670194 df.mm.trans2:exp7 -0.119458488535269 0.306317009554111 -0.389983203052152 0.696788232402804 df.mm.trans1:exp8 -0.372032207621587 0.306317009554111 -1.21453329726329 0.225369995045365 df.mm.trans2:exp8 -0.672486747429644 0.306317009554111 -2.19539472655647 0.0287970059445167 * df.mm.trans1:probe2 0.0913807248611415 0.167776735880312 0.544656709296874 0.586339490237972 df.mm.trans1:probe3 -0.049743956438087 0.167776735880312 -0.296488998770206 0.767034042876276 df.mm.trans1:probe4 -0.316398737382876 0.167776735880312 -1.88583200002524 0.0601526358821196 . df.mm.trans1:probe5 -0.197864954790856 0.167776735880312 -1.17933486876279 0.239072809581249 df.mm.trans1:probe6 -0.0772878020353996 0.167776735880312 -0.460658634404086 0.645332098933144 df.mm.trans2:probe2 0.0895361650987865 0.167776735880312 0.533662576214735 0.593916676985289 df.mm.trans2:probe3 0.315029680105682 0.167776735880312 1.87767200531554 0.0612646129261934 . df.mm.trans2:probe4 0.237713808938795 0.167776735880312 1.41684607041332 0.157425085381095 df.mm.trans2:probe5 0.230772030216013 0.167776735880312 1.37547097340504 0.169872741990955 df.mm.trans2:probe6 0.204800547746248 0.167776735880312 1.22067309672986 0.223038640090252 df.mm.trans3:probe2 0.239907258933545 0.167776735880312 1.42991969461540 0.153639812855270 df.mm.trans3:probe3 -0.104576160874039 0.167776735880312 -0.623305491821232 0.533493255258586 df.mm.trans3:probe4 0.103865129867821 0.167776735880312 0.619067532353927 0.536278079535994