chr1.1284_chr1_59096284_59099384_-_0.R fitVsDatCorrelation=0.687937851153249 cont.fitVsDatCorrelation=0.308031246596019 fstatistic=9266.11111821105,36,324 cont.fstatistic=5388.74129375432,36,324 residuals=-0.394391820735881,-0.0715961958744396,-0.00770055959972043,0.071063377542961,0.813207030668398 cont.residuals=-0.331679537375546,-0.0986010252763605,-0.0172217427503880,0.0713991983143338,1.09520775918148 predictedValues: Include Exclude Both chr1.1284_chr1_59096284_59099384_-_0.R.tl.Lung 49.7561183087197 58.1242765681836 48.786610787416 chr1.1284_chr1_59096284_59099384_-_0.R.tl.cerebhem 58.9796502219055 76.698001773752 53.2586131497331 chr1.1284_chr1_59096284_59099384_-_0.R.tl.cortex 53.8492014173105 57.0975381757081 63.3677453556411 chr1.1284_chr1_59096284_59099384_-_0.R.tl.heart 49.3581433982097 54.431210358838 54.1849078103376 chr1.1284_chr1_59096284_59099384_-_0.R.tl.kidney 49.2138654701716 57.0192104752945 54.6805775718898 chr1.1284_chr1_59096284_59099384_-_0.R.tl.liver 49.7967973388655 54.046408533242 47.6072982355456 chr1.1284_chr1_59096284_59099384_-_0.R.tl.stomach 50.7461591993935 58.427997079792 49.4528685877791 chr1.1284_chr1_59096284_59099384_-_0.R.tl.testicle 55.5377398939742 60.2018618697546 53.5119768085977 diffExp=-8.3681582594639,-17.7183515518466,-3.2483367583976,-5.07306696062824,-7.80534500512297,-4.24961119437655,-7.68183788039855,-4.66412197578043 diffExpScore=0.983280060704719 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,-1,0,0,0,0,0,0 diffExp1.3Score=0.5 diffExp1.2=0,-1,0,0,0,0,0,0 diffExp1.2Score=0.5 cont.predictedValues: Include Exclude Both Lung 53.4417896551644 55.302696698705 51.5748922118226 cerebhem 53.3297006715315 57.1069986747506 56.887971766039 cortex 57.1754659898341 58.8365064538573 56.1757219821546 heart 53.4916251900934 56.6324104160841 53.2483268224279 kidney 54.5280644171937 57.167217009193 54.5007113458894 liver 52.8907021545882 56.6000977888815 50.1246580627518 stomach 50.0809434163471 57.5889319118527 54.2535618644034 testicle 54.5721867641196 51.1375362165334 56.5380400124623 cont.diffExp=-1.86090704354059,-3.77729800321911,-1.66104046402316,-3.14078522599069,-2.63915259199932,-3.70939563429338,-7.5079884955056,3.43465054758613 cont.diffExpScore=1.26847147572054 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=0.849129802191725 cont.tran.correlation=0.00039122827651767 tran.covariance=0.00628263874832529 cont.tran.covariance=-3.60966396578248e-05 tran.mean=55.8302612551947 cont.tran.mean=54.9926795892956 weightedLogRatios: wLogRatio Lung -0.619446165108445 cerebhem -1.10551112217075 cortex -0.235200093032193 heart -0.386254337949321 kidney -0.584402834576391 liver -0.323384734966813 stomach -0.563458573759407 testicle -0.327189364719109 cont.weightedLogRatios: wLogRatio Lung -0.136767686237014 cerebhem -0.274465987543556 cortex -0.116281485267747 heart -0.228684851785473 kidney -0.190116652292096 liver -0.271276250508190 stomach -0.556452410005578 testicle 0.257878465041521 varWeightedLogRatios=0.0762218397862752 cont.varWeightedLogRatios=0.0511979447974157 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.0828700503953 0.074171297128996 55.0464965348323 1.70952759354871e-166 *** df.mm.trans1 -0.140809347707049 0.0628223138645 -2.24139066273104 0.0256775267737750 * df.mm.trans2 0.0136812352066596 0.0628223138645 0.217776684191676 0.827740199243485 df.mm.exp2 0.359647638945585 0.0874876891139623 4.11083710848854 5.00099459516325e-05 *** df.mm.exp3 -0.200267357162509 0.0874876891139623 -2.28909186184628 0.0227170029656416 * df.mm.exp4 -0.178622890117372 0.0874876891139623 -2.04169171601614 0.0419917353472968 * df.mm.exp5 -0.144205884043821 0.0874876891139623 -1.64829915505 0.100260607201973 df.mm.exp6 -0.0474532562150222 0.0874876891139623 -0.542399241488813 0.587916369217664 df.mm.exp7 0.0113500963050444 0.0874876891139623 0.129733639326782 0.896857670014759 df.mm.exp8 0.0525996245130774 0.0874876891139623 0.601223155460885 0.548111758344158 df.mm.trans1:exp2 -0.189588603151486 0.0757665612910866 -2.50227276942275 0.0128322662333032 * df.mm.trans2:exp2 -0.0823554010964921 0.0757665612910866 -1.08696237090782 0.277861407148360 df.mm.trans1:exp3 0.279321493769995 0.0757665612910867 3.68660645290306 0.000266359199143624 *** df.mm.trans2:exp3 0.182444940942932 0.0757665612910867 2.40798761134215 0.0165990293144165 * df.mm.trans1:exp4 0.170592218395799 0.0757665612910867 2.25155022860814 0.0250202979326551 * df.mm.trans2:exp4 0.112977181605256 0.0757665612910866 1.49112193664446 0.136902410229789 df.mm.trans1:exp5 0.133247849215289 0.0757665612910866 1.75866301630565 0.0795787739762948 . df.mm.trans2:exp5 0.125010703288976 0.0757665612910867 1.64994558494873 0.09992313089429 . df.mm.trans1:exp6 0.0482704905902317 0.0757665612910866 0.637094910573834 0.524512921901157 df.mm.trans2:exp6 -0.0252870667173149 0.0757665612910867 -0.333749694936857 0.738784345421937 df.mm.trans1:exp7 0.0083524008299446 0.0757665612910867 0.110238615658636 0.912288388587186 df.mm.trans2:exp7 -0.00613833698737022 0.0757665612910866 -0.0810164389510488 0.935478900413895 df.mm.trans1:exp8 0.0573297261121486 0.0757665612910866 0.756662637649532 0.449801853082052 df.mm.trans2:exp8 -0.0174797622988424 0.0757665612910867 -0.230705498586469 0.817689208292005 df.mm.trans1:probe2 -0.112806304522144 0.0378832806455433 -2.97773325329509 0.00312283337021155 ** df.mm.trans1:probe3 -0.0927888946733167 0.0378832806455433 -2.44933630594194 0.0148411265535861 * df.mm.trans1:probe4 -0.0745407180004998 0.0378832806455433 -1.96764157513029 0.0499619482764783 * df.mm.trans1:probe5 -0.0316104880990391 0.0378832806455433 -0.834417916304665 0.40466031596918 df.mm.trans1:probe6 -0.00259898479365271 0.0378832806455433 -0.0686050613718022 0.945346309389123 df.mm.trans2:probe2 -0.144347056157366 0.0378832806455433 -3.81031034529338 0.000166059881799383 *** df.mm.trans2:probe3 -0.0537230502309141 0.0378832806455433 -1.41812032420255 0.157116710190789 df.mm.trans2:probe4 -0.0368754869631947 0.0378832806455433 -0.97339740209466 0.331081979786657 df.mm.trans2:probe5 0.0278367436497144 0.0378832806455433 0.73480287808678 0.462991048645746 df.mm.trans2:probe6 -0.0986019614942388 0.0378832806455433 -2.60278306984056 0.00967212310534034 ** df.mm.trans3:probe2 -0.170416126879421 0.0378832806455433 -4.49845219251013 9.55115374427352e-06 *** df.mm.trans3:probe3 -0.0344419684972543 0.0378832806455433 -0.909160133714718 0.36394139406466 cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.13344455819159 0.0972275633701357 42.5130941773783 1.40502288049476e-134 *** df.mm.trans1 -0.131541209240724 0.0823507305217583 -1.59732899037208 0.111167183321334 df.mm.trans2 -0.0927901745857144 0.0823507305217584 -1.12676808083928 0.260674368156872 df.mm.exp2 -0.0680435574843391 0.114683377083736 -0.593316653333787 0.553383195813123 df.mm.exp3 0.0440230191263725 0.114683377083736 0.383865737527323 0.701329743985933 df.mm.exp4 -0.00723955719329484 0.114683377083736 -0.063126473752241 0.94970471933144 df.mm.exp5 -0.00189735729558065 0.114683377083736 -0.0165443095924468 0.986810335953551 df.mm.exp6 0.0413454888226758 0.114683377083736 0.360518584942675 0.718694281544496 df.mm.exp7 -0.0750774079559861 0.114683377083736 -0.654649434513672 0.513157939032872 df.mm.exp8 -0.149250262583557 0.114683377083736 -1.30141147199198 0.194042274670689 df.mm.trans1:exp2 0.0659439515976517 0.0993187179463057 0.663962976579124 0.507186204330773 df.mm.trans2:exp2 0.100148563135529 0.0993187179463057 1.00835537556648 0.314036339963193 df.mm.trans1:exp3 0.0235088532629826 0.0993187179463057 0.236701134983358 0.81303823287695 df.mm.trans2:exp3 0.0179178289498485 0.0993187179463058 0.180407372551218 0.85694555394985 df.mm.trans1:exp4 0.00817164261503383 0.0993187179463058 0.0822769643427298 0.934477276852982 df.mm.trans2:exp4 0.0309993284746755 0.0993187179463057 0.312119700250606 0.75515032258847 df.mm.trans1:exp5 0.0220198521377866 0.0993187179463057 0.221708984903441 0.824680107376658 df.mm.trans2:exp5 0.0350562899355657 0.0993187179463058 0.352967604299101 0.7243422489321 df.mm.trans1:exp6 -0.0517109458035468 0.0993187179463057 -0.52065659799901 0.602961632112506 df.mm.trans2:exp6 -0.0181564481308035 0.0993187179463058 -0.182809932571012 0.855061490701167 df.mm.trans1:exp7 0.0101249550323728 0.0993187179463057 0.101944077025305 0.918864124810581 df.mm.trans2:exp7 0.115586130651186 0.0993187179463057 1.16378999891717 0.245365425461846 df.mm.trans1:exp8 0.170181597897781 0.0993187179463057 1.71348967663664 0.0875790026107354 . df.mm.trans2:exp8 0.0709473818229896 0.0993187179463058 0.714340491802819 0.475530979839876 df.mm.trans1:probe2 -0.0235134408826122 0.0496593589731529 -0.473494651739749 0.636179186451954 df.mm.trans1:probe3 -0.0785573890100295 0.0496593589731529 -1.58192515236654 0.114642302302359 df.mm.trans1:probe4 -0.0256786020333977 0.0496593589731529 -0.517094915528012 0.605442712883857 df.mm.trans1:probe5 -0.0487914323345716 0.0496593589731529 -0.982522395445127 0.326575654847794 df.mm.trans1:probe6 -0.0332521167824169 0.0496593589731529 -0.66960422909192 0.503587013742217 df.mm.trans2:probe2 -0.092788315936898 0.0496593589731529 -1.86849604698002 0.0625952449869886 . df.mm.trans2:probe3 -0.0647454815782803 0.0496593589731529 -1.30379213338786 0.193230041694342 df.mm.trans2:probe4 0.0106796886369005 0.0496593589731529 0.215058930637308 0.829856677430397 df.mm.trans2:probe5 -0.0328461115614758 0.0496593589731529 -0.66142842438287 0.50880768947998 df.mm.trans2:probe6 -0.0707941819023899 0.0496593589731529 -1.42559596753279 0.154947680822925 df.mm.trans3:probe2 0.0543534360230336 0.0496593589731529 1.09452552644545 0.274537563968164 df.mm.trans3:probe3 0.047411947954712 0.0496593589731529 0.954743454911372 0.340419222521914