chr17.10806_chr17_64901542_64921094_+_1.R fitVsDatCorrelation=0.972663944919725 cont.fitVsDatCorrelation=0.290217653377521 fstatistic=14562.1803933469,60,876 cont.fstatistic=843.745995471461,60,876 residuals=-0.546540289702185,-0.0806730299654908,-0.00878362197570693,0.0719353866215877,1.30043329150689 cont.residuals=-0.9958054120621,-0.388722600873699,-0.176140803622176,0.250465557419212,2.28346567821062 predictedValues: Include Exclude Both chr17.10806_chr17_64901542_64921094_+_1.R.tl.Lung 60.6910691388145 187.96892169824 57.5744639555488 chr17.10806_chr17_64901542_64921094_+_1.R.tl.cerebhem 70.731094885279 124.838810503641 54.9354627702889 chr17.10806_chr17_64901542_64921094_+_1.R.tl.cortex 58.1280328016278 122.435212628966 55.7381736837226 chr17.10806_chr17_64901542_64921094_+_1.R.tl.heart 61.6880965729508 170.459980754504 56.0551093358631 chr17.10806_chr17_64901542_64921094_+_1.R.tl.kidney 59.5937223459442 184.379434291817 56.3261925161549 chr17.10806_chr17_64901542_64921094_+_1.R.tl.liver 59.7765659910565 195.613136457582 51.2495245967795 chr17.10806_chr17_64901542_64921094_+_1.R.tl.stomach 67.0414484163873 172.902373254759 54.1629183626815 chr17.10806_chr17_64901542_64921094_+_1.R.tl.testicle 64.3084657800233 184.54401346126 54.4094462429728 diffExp=-127.277852559426,-54.1077156183623,-64.3071798273384,-108.771884181554,-124.785711945873,-135.836570466526,-105.860924838372,-120.235547681237 diffExpScore=0.998812610156772 diffExp1.5=-1,-1,-1,-1,-1,-1,-1,-1 diffExp1.5Score=0.888888888888889 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 86.7937559304886 68.6371083554221 75.0950759962855 cerebhem 75.8862440764683 74.6012616932801 71.8724482956535 cortex 81.625272612709 79.0169370097637 79.428806842917 heart 67.368579418741 54.7667480576359 80.7690045715151 kidney 77.6189814990542 86.3400932473593 66.1218877101936 liver 70.1655131640951 67.4093344634778 70.6297005512301 stomach 66.7638494391265 87.7207223784932 71.9771268113403 testicle 85.4832127223382 88.4226838854704 68.46661717251 cont.diffExp=18.1566475750665,1.28498238318824,2.60833560294535,12.6018313611051,-8.72111174830505,2.7561787006173,-20.9568729393666,-2.93947116313215 cont.diffExpScore=12.0931167200048 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,-1,0 cont.diffExp1.3Score=0.5 cont.diffExp1.2=1,0,0,1,0,0,-1,0 cont.diffExp1.2Score=1.5 tran.correlation=-0.308030738680757 cont.tran.correlation=0.302482238440691 tran.covariance=-0.00336701043429404 cont.tran.covariance=0.00577355059301688 tran.mean=115.318773686428 cont.tran.mean=76.1637686221202 weightedLogRatios: wLogRatio Lung -5.28051384034806 cerebhem -2.58102544016360 cortex -3.30386786110016 heart -4.70627690561025 kidney -5.25448899248338 liver -5.55226065927656 stomach -4.43297781951521 testicle -4.94501498903161 cont.weightedLogRatios: wLogRatio Lung 1.02005528015768 cerebhem 0.0737888996365807 cortex 0.142439600847647 heart 0.850464819731571 kidney -0.469059147816326 liver 0.169543448047853 stomach -1.18416555551420 testicle -0.150962657926797 varWeightedLogRatios=1.09194084655813 cont.varWeightedLogRatios=0.49111234951987 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.06711576443807 0.0650578611473274 77.8862949853714 0 *** df.mm.trans1 -1.12197535385291 0.0547400957837822 -20.4964083052503 1.42858924947954e-76 *** df.mm.trans2 0.0765260902891062 0.0490565639150784 1.55995618489669 0.119131412809539 df.mm.exp2 -0.209244472011785 0.0624133119802414 -3.35256158298452 0.000834985143228693 *** df.mm.exp3 -0.439429263081003 0.0624133119802414 -7.04063362668714 3.86587324038501e-12 *** df.mm.exp4 -0.0547378217256928 0.0624133119802414 -0.877021583841305 0.380715362210627 df.mm.exp5 -0.0156077020312463 0.0624133119802414 -0.250070081782992 0.802591784587835 df.mm.exp6 0.141052224590966 0.0624133119802414 2.25997019090447 0.0240679526251078 * df.mm.exp7 0.0770476088744103 0.0624133119802414 1.23447396764975 0.217357384845910 df.mm.exp8 0.096047430809049 0.0624133119802414 1.53889335082002 0.124191451220409 df.mm.trans1:exp2 0.362333206641754 0.0547400957837822 6.61915551030333 6.2890025364123e-11 *** df.mm.trans2:exp2 -0.200008777846935 0.0405963415535157 -4.92676852625439 9.9943627490739e-07 *** df.mm.trans1:exp3 0.39628074677531 0.0547400957837822 7.23931409145828 9.8643304563443e-13 *** df.mm.trans2:exp3 0.0107346376140625 0.0405963415535157 0.264423768331728 0.791515597050046 df.mm.trans1:exp4 0.0710322536770628 0.0547400957837822 1.29762750064656 0.194756962108479 df.mm.trans2:exp4 -0.0430382651324385 0.0405963415535157 -1.06015132116533 0.289367974469445 df.mm.trans1:exp5 -0.00263861529539032 0.0547400957837822 -0.0482026064735543 0.961565760155767 df.mm.trans2:exp5 -0.00367315981656266 0.0405963415535157 -0.0904800697797006 0.927926414766704 df.mm.trans1:exp6 -0.156235069580283 0.0547400957837822 -2.85412488493619 0.0044173447070093 ** df.mm.trans2:exp6 -0.101189948490759 0.0405963415535157 -2.49258786921395 0.0128653298529799 * df.mm.trans1:exp7 0.0224668962380671 0.0547400957837822 0.410428515266196 0.68159199520071 df.mm.trans2:exp7 -0.160597129158546 0.0405963415535157 -3.9559507830734 8.23934320341375e-05 *** df.mm.trans1:exp8 -0.0381527036627625 0.0547400957837822 -0.696979117710384 0.486000776806761 df.mm.trans2:exp8 -0.11443607948167 0.0405963415535157 -2.81887665495217 0.00492783700722836 ** df.mm.trans1:probe2 -0.0850142677830554 0.0410550718378366 -2.0707372798872 0.0386757667447185 * df.mm.trans1:probe3 -0.167859398501464 0.0410550718378367 -4.08863974625331 4.73831381662441e-05 *** df.mm.trans1:probe4 0.024766020917293 0.0410550718378367 0.603239010642004 0.546505849701515 df.mm.trans1:probe5 0.134650710457547 0.0410550718378367 3.2797582473952 0.00107995385947452 ** df.mm.trans1:probe6 -0.145437063674304 0.0410550718378367 -3.54248713164515 0.000417304130615141 *** df.mm.trans1:probe7 -0.0995423751088261 0.0410550718378367 -2.42460603898121 0.0155263704860560 * df.mm.trans1:probe8 -0.00485864824641639 0.0410550718378366 -0.118344653386738 0.905821708381806 df.mm.trans1:probe9 -0.0103896493846258 0.0410550718378367 -0.253066160148588 0.800276462305223 df.mm.trans1:probe10 1.10890417834041 0.0410550718378366 27.010162903148 2.26436190669616e-117 *** df.mm.trans1:probe11 0.757171826121786 0.0410550718378367 18.4428328152131 1.99644162623243e-64 *** df.mm.trans1:probe12 0.450869812730512 0.0410550718378367 10.9820734088934 2.23428582330419e-26 *** df.mm.trans1:probe13 0.619985727181507 0.0410550718378367 15.1013187756774 5.74014347614805e-46 *** df.mm.trans1:probe14 0.799084657997223 0.0410550718378367 19.4637257280544 2.11401094599340e-70 *** df.mm.trans1:probe15 0.473415960932564 0.0410550718378367 11.5312418110607 9.67470696724924e-29 *** df.mm.trans2:probe2 0.548487962488644 0.0410550718378367 13.3598100779148 3.45999370255021e-37 *** df.mm.trans2:probe3 0.34205938632127 0.0410550718378367 8.33172056481522 3.05661278490009e-16 *** df.mm.trans2:probe4 -0.199101152168649 0.0410550718378367 -4.84961158891837 1.46351220189835e-06 *** df.mm.trans2:probe5 0.359601100331193 0.0410550718378367 8.75899332856074 1.00491437686366e-17 *** df.mm.trans2:probe6 1.17218752675081 0.0410550718378367 28.5515887386785 2.86196807653307e-127 *** df.mm.trans3:probe2 -0.0850142677830554 0.0410550718378367 -2.0707372798872 0.0386757667447185 * df.mm.trans3:probe3 -0.167859398501464 0.0410550718378367 -4.08863974625332 4.73831381662441e-05 *** df.mm.trans3:probe4 0.0247660209172929 0.0410550718378367 0.603239010642002 0.546505849701568 df.mm.trans3:probe5 0.134650710457547 0.0410550718378367 3.2797582473952 0.00107995385947452 ** df.mm.trans3:probe6 -0.145437063674304 0.0410550718378367 -3.54248713164515 0.000417304130615141 *** df.mm.trans3:probe7 -0.0995423751088263 0.0410550718378367 -2.42460603898121 0.0155263704860552 * df.mm.trans3:probe8 -0.00485864824641646 0.0410550718378367 -0.118344653386739 0.905821708381806 df.mm.trans3:probe9 -0.0103896493846258 0.0410550718378367 -0.253066160148589 0.800276462305223 df.mm.trans3:probe10 -0.0914867185874505 0.0410550718378367 -2.22839017183586 0.0261076200633068 * df.mm.trans3:probe11 0.428700190285534 0.0410550718378366 10.4420762428295 3.88337327494871e-24 *** df.mm.trans3:probe12 0.11271908394987 0.0410550718378367 2.74555807367964 0.0061645537387592 ** df.mm.trans3:probe13 0.208090021175126 0.0410550718378367 5.06855820389405 4.8909124350895e-07 *** df.mm.trans3:probe14 -0.0176160431824592 0.0410550718378367 -0.429083238534833 0.667968151290644 df.mm.trans3:probe15 -0.081213788158014 0.0410550718378367 -1.97816699673064 0.0482228236065487 * df.mm.trans3:probe16 -0.117313660603629 0.0410550718378366 -2.85747059625193 0.00437147511257291 ** df.mm.trans3:probe17 0.422007201625015 0.0410550718378367 10.2790515942074 1.77269655686123e-23 *** df.mm.trans3:probe18 0.0552258043961201 0.0410550718378367 1.34516399372668 0.178920400255278 cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.57682606826947 0.268101592748793 17.0712378891306 1.26063195795495e-56 *** df.mm.trans1 -0.109649312567924 0.225582375565945 -0.48607216008269 0.627037569746023 df.mm.trans2 -0.342988221144979 0.202160702618730 -1.69661173859217 0.0901253471943028 . df.mm.exp2 -0.00711316489497532 0.257203480955775 -0.0276557878164892 0.977942985330177 df.mm.exp3 0.0233270216478014 0.257203480955775 0.0906948131538407 0.92775582540808 df.mm.exp4 -0.551944352875258 0.257203480955775 -2.14594433490643 0.0321515972200053 * df.mm.exp5 0.244993233308368 0.257203480955775 0.952526895817922 0.341092577524593 df.mm.exp6 -0.16942333576281 0.257203480955775 -0.65871323021457 0.510253029268262 df.mm.exp7 0.0253585124511464 0.257203480955775 0.098593193050551 0.921483830263047 df.mm.exp8 0.330489251331414 0.257203480955775 1.28493304252068 0.199155325633749 df.mm.trans1:exp2 -0.127186087387192 0.225582375565945 -0.563812164261968 0.573026276400727 df.mm.trans2:exp2 0.0904372581369863 0.167296367238761 0.540581123366036 0.588933748500722 df.mm.trans1:exp3 -0.0847227770320609 0.225582375565945 -0.375573565175501 0.707324870257926 df.mm.trans2:exp3 0.117501873765842 0.167296367238761 0.702357592727324 0.482642766423727 df.mm.trans1:exp4 0.298588398572583 0.225582375565945 1.32363354106667 0.185970099789427 df.mm.trans2:exp4 0.326194248786671 0.167296367238761 1.94979875636592 0.0515188292915543 . df.mm.trans1:exp5 -0.356715911878093 0.225582375565945 -1.58131108861301 0.114167894014221 df.mm.trans2:exp5 -0.0155324897830137 0.167296367238761 -0.0928441545945 0.926048600910654 df.mm.trans1:exp6 -0.0432544221786436 0.225582375565945 -0.191745574405474 0.847985941062122 df.mm.trans2:exp6 0.151373511011900 0.167296367238761 0.904822462736827 0.365808224513765 df.mm.trans1:exp7 -0.287731437252216 0.225582375565945 -1.27550495259371 0.202468709100221 df.mm.trans2:exp7 0.219966319510337 0.167296367238761 1.31483022100777 0.188911068727998 df.mm.trans1:exp8 -0.345703919889263 0.225582375565945 -1.53249525377129 0.125761313424206 df.mm.trans2:exp8 -0.0771940361692395 0.167296367238761 -0.461420875081348 0.644611227404361 df.mm.trans1:probe2 0.215310616072581 0.169186781674459 1.27262079189420 0.203490303666344 df.mm.trans1:probe3 0.0227567118254378 0.169186781674459 0.134506440752713 0.89303301526533 df.mm.trans1:probe4 -0.0495637299120403 0.169186781674459 -0.292952732013122 0.769627660993712 df.mm.trans1:probe5 -0.0258333131185090 0.169186781674459 -0.152691084154649 0.878677054085076 df.mm.trans1:probe6 0.165389639440824 0.169186781674459 0.977556507688994 0.328563596479680 df.mm.trans1:probe7 0.0863621044737042 0.169186781674459 0.51045420699519 0.609861888129648 df.mm.trans1:probe8 -0.173812949883269 0.169186781674459 -1.02734355582052 0.304542305475061 df.mm.trans1:probe9 -0.0533601580278394 0.169186781674459 -0.315392003439799 0.752539155537265 df.mm.trans1:probe10 -0.173005485297955 0.169186781674459 -1.0225709336492 0.306793061017401 df.mm.trans1:probe11 0.0796159276011036 0.169186781674459 0.470580070222606 0.63805778719758 df.mm.trans1:probe12 0.00217494683481392 0.169186781674459 0.0128553000020939 0.989746164170041 df.mm.trans1:probe13 -0.193611793026793 0.169186781674459 -1.14436713737679 0.252783997441832 df.mm.trans1:probe14 -0.249441553254547 0.169186781674459 -1.47435603884534 0.140745026834687 df.mm.trans1:probe15 0.259609286493129 0.169186781674459 1.53445371986954 0.125279140304464 df.mm.trans2:probe2 -0.0271928956127879 0.169186781674459 -0.160727069477042 0.872345425139803 df.mm.trans2:probe3 -0.0525021889809489 0.169186781674459 -0.310320868222265 0.756390777268697 df.mm.trans2:probe4 0.0135945855913518 0.169186781674459 0.0803525278795707 0.935975234988 df.mm.trans2:probe5 0.121753868290902 0.169186781674459 0.719641730198372 0.471937557071414 df.mm.trans2:probe6 -0.175761861798586 0.169186781674459 -1.03886284767080 0.299155181133421 df.mm.trans3:probe2 0.109053910703431 0.169186781674459 0.644577014966023 0.519370084703819 df.mm.trans3:probe3 -0.0339107908353967 0.169186781674459 -0.200434043958861 0.84118765922939 df.mm.trans3:probe4 0.193509319184271 0.169186781674459 1.14376145269204 0.253035030126493 df.mm.trans3:probe5 0.157891709869487 0.169186781674459 0.933239040939347 0.350953712529436 df.mm.trans3:probe6 -0.0487067184867319 0.169186781674459 -0.287887256939795 0.773501136674186 df.mm.trans3:probe7 0.390285643610214 0.169186781674459 2.30683295555077 0.0212966200949547 * df.mm.trans3:probe8 0.44773700156738 0.169186781674459 2.64640651672714 0.0082811460176586 ** df.mm.trans3:probe9 0.327466236273054 0.169186781674459 1.93553085549644 0.0532466991120335 . df.mm.trans3:probe10 0.0968954117363241 0.169186781674459 0.572712659803209 0.566986225943814 df.mm.trans3:probe11 0.27500711933736 0.169186781674459 1.62546457007803 0.104423291689358 df.mm.trans3:probe12 0.180006096911678 0.169186781674459 1.06394893933284 0.287645018233982 df.mm.trans3:probe13 0.0113367420327067 0.169186781674459 0.0670072562436958 0.946591216492542 df.mm.trans3:probe14 0.170165430325222 0.169186781674459 1.0057844273712 0.314797015713834 df.mm.trans3:probe15 0.15144122253631 0.169186781674459 0.895112614812344 0.370972771417871 df.mm.trans3:probe16 0.341330496802017 0.169186781674459 2.01747733140754 0.0439502546435358 * df.mm.trans3:probe17 0.387320467089159 0.169186781674459 2.28930690244125 0.0222986480000864 * df.mm.trans3:probe18 0.345366911186720 0.169186781674459 2.04133507221184 0.0415167287654843 *