chrX.26008_chrX_68739420_68747605_-_2.R fitVsDatCorrelation=0.907520902570644 cont.fitVsDatCorrelation=0.246185000322605 fstatistic=8736.9069044288,51,669 cont.fstatistic=1630.02347716964,51,669 residuals=-0.788406321123098,-0.094396574901977,0.00300586512181113,0.0893723365308723,0.768090784088477 cont.residuals=-0.763379295024006,-0.292208152453803,-0.0863615261388263,0.234275497108470,1.80174444668073 predictedValues: Include Exclude Both chrX.26008_chrX_68739420_68747605_-_2.R.tl.Lung 72.7219507441624 100.685448425009 67.3467569665919 chrX.26008_chrX_68739420_68747605_-_2.R.tl.cerebhem 82.9715817432201 168.767859798479 62.6065326341339 chrX.26008_chrX_68739420_68747605_-_2.R.tl.cortex 72.147591720125 108.696480605894 77.6994345774955 chrX.26008_chrX_68739420_68747605_-_2.R.tl.heart 72.8769309171069 120.017197539588 81.3739107033812 chrX.26008_chrX_68739420_68747605_-_2.R.tl.kidney 148.233974247390 225.462221576601 170.468325011608 chrX.26008_chrX_68739420_68747605_-_2.R.tl.liver 82.1143325276176 116.508888237369 81.4789049016644 chrX.26008_chrX_68739420_68747605_-_2.R.tl.stomach 75.392570629405 128.160598901718 76.0886313535899 chrX.26008_chrX_68739420_68747605_-_2.R.tl.testicle 73.0922292334004 157.05634488094 88.6338571947502 diffExp=-27.9634976808466,-85.796278055259,-36.5488888857687,-47.1402666224814,-77.2282473292104,-34.3945557097512,-52.7680282723132,-83.9641156475396 diffExpScore=0.997761881557471 diffExp1.5=0,-1,-1,-1,-1,0,-1,-1 diffExp1.5Score=0.857142857142857 diffExp1.4=0,-1,-1,-1,-1,-1,-1,-1 diffExp1.4Score=0.875 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 90.3091116432086 85.436143621095 86.351599633296 cerebhem 90.2333178343062 99.3920630702885 91.8686556173656 cortex 95.3176176508777 90.284204376449 85.5922598902436 heart 88.9552924862364 124.108163066082 98.0865927331685 kidney 90.0386106950123 83.8948493824875 89.2867073192586 liver 85.1425911023433 101.641307495971 82.4201486406281 stomach 81.9123800435589 104.975218824794 79.1657931574531 testicle 91.2922106026012 109.034690040341 93.4492209295568 cont.diffExp=4.87296802211355,-9.15874523598235,5.03341327442865,-35.152870579846,6.1437613125248,-16.4987163936276,-23.0628387812355,-17.7424794377394 cont.diffExpScore=1.35926878963190 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,-1,0,0,0,0 cont.diffExp1.3Score=0.5 cont.diffExp1.2=0,0,0,-1,0,0,-1,0 cont.diffExp1.2Score=0.666666666666667 tran.correlation=0.857096906486166 cont.tran.correlation=-0.315717720289596 tran.covariance=0.0527967790022768 cont.tran.covariance=-0.00200449717136512 tran.mean=112.806637608002 cont.tran.mean=94.4979857459783 weightedLogRatios: wLogRatio Lung -1.44762264348220 cerebhem -3.38931703251378 cortex -1.83759835675148 heart -2.26394142666823 kidney -2.18422847707459 liver -1.60339943190112 stomach -2.43427813715504 testicle -3.5751860586028 cont.weightedLogRatios: wLogRatio Lung 0.248252260840489 cerebhem -0.439935646144372 cortex 0.245766988951982 heart -1.55008737626425 kidney 0.315554068936135 liver -0.802877164861574 stomach -1.12369840422672 testicle -0.817471822401661 varWeightedLogRatios=0.608140531493468 cont.varWeightedLogRatios=0.495468508540598 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.25962506613006 0.0852360004662042 49.9744831154881 5.05786378890846e-228 *** df.mm.trans1 0.145525039433145 0.0723500973293878 2.01140074173798 0.0446837178742512 * df.mm.trans2 0.38472806893275 0.0658181606857825 5.84531784121788 7.9021624005482e-09 *** df.mm.exp2 0.72136288245502 0.0855756626506659 8.42953311854263 2.12731036041536e-16 *** df.mm.exp3 -0.0743644682428226 0.0855756626506658 -0.86899085486946 0.385163776577321 df.mm.exp4 -0.0114373385859387 0.0855756626506658 -0.133651767706759 0.893718140243297 df.mm.exp5 0.589605232979455 0.0855756626506658 6.88987049257594 1.29122974680282e-11 *** df.mm.exp6 0.076946177813651 0.0855756626506658 0.89915959082617 0.368891176438356 df.mm.exp7 0.155304220725005 0.0855756626506658 1.81481762354541 0.069999644153901 . df.mm.exp8 0.175022953194985 0.0855756626506658 2.04524216084026 0.0412216784256368 * df.mm.trans1:exp2 -0.589507996846898 0.0760002655790052 -7.75665706370568 3.26240739746283e-14 *** df.mm.trans2:exp2 -0.204840007522167 0.060935776092957 -3.36157214457538 0.000819106105847549 *** df.mm.trans1:exp3 0.066435099188969 0.0760002655790052 0.874142987301895 0.382354072983868 df.mm.trans2:exp3 0.150922599652735 0.060935776092957 2.47674862501963 0.0135046378901873 * df.mm.trans1:exp4 0.0135662042710036 0.0760002655790052 0.178502064007934 0.858382740604342 df.mm.trans2:exp4 0.187071098867177 0.060935776092957 3.06997154810668 0.00222745719855872 ** df.mm.trans1:exp5 0.122543424619304 0.0760002655790052 1.61240784733726 0.107344827454866 df.mm.trans2:exp5 0.216546095054766 0.060935776092957 3.55367747715934 0.00040660888855299 *** df.mm.trans1:exp6 0.0445231225112675 0.0760002655790052 0.585828512204132 0.558188335593562 df.mm.trans2:exp6 0.0690201011024598 0.060935776092957 1.13266959950047 0.257758809754229 df.mm.trans1:exp7 -0.119238758256480 0.0760002655790052 -1.56892554714203 0.117138122106867 df.mm.trans2:exp7 0.0859786506000436 0.060935776092957 1.41097161819821 0.158717825364418 df.mm.trans1:exp8 -0.169944170250701 0.0760002655790052 -2.23609968933645 0.0256741776923692 * df.mm.trans2:exp8 0.269580387299218 0.060935776092957 4.42400843287817 1.13081099251921e-05 *** df.mm.trans1:probe2 -0.139561325060599 0.0520338247925057 -2.68212697446565 0.0074961422972595 ** df.mm.trans1:probe3 -0.29826570655553 0.0520338247925057 -5.73215034153108 1.50079406273596e-08 *** df.mm.trans1:probe4 -0.134993377609660 0.0520338247925057 -2.59433893525934 0.00968484762771455 ** df.mm.trans1:probe5 -0.369435262874589 0.0520338247925057 -7.09990596208868 3.19723055684784e-12 *** df.mm.trans1:probe6 -0.200656874702102 0.0520338247925057 -3.85627763291009 0.00012624456962899 *** df.mm.trans1:probe7 -0.263240697581876 0.0520338247925057 -5.05903032559293 5.44991610883127e-07 *** df.mm.trans1:probe8 -0.261662696661413 0.0520338247925057 -5.02870388069376 6.34934975202707e-07 *** df.mm.trans1:probe9 -0.0408799845214934 0.0520338247925057 -0.78564250628336 0.432355109425711 df.mm.trans1:probe10 -0.116324459286885 0.0520338247925057 -2.23555465604824 0.02571007958795 * df.mm.trans1:probe11 -0.222928552650608 0.0520338247925057 -4.28430071284547 2.10214033002838e-05 *** df.mm.trans1:probe12 -0.298046871809794 0.0520338247925057 -5.72794471669744 1.53668270012377e-08 *** df.mm.trans1:probe13 -0.198047923202209 0.0520338247925057 -3.80613810328111 0.000154104848785671 *** df.mm.trans1:probe14 -0.300120202819269 0.0520338247925057 -5.76779054809161 1.22769208887326e-08 *** df.mm.trans2:probe2 -0.228898228259423 0.0520338247925057 -4.39902753972433 1.26497906007486e-05 *** df.mm.trans2:probe3 -0.060747844378971 0.0520338247925057 -1.16746836545678 0.243437203654994 df.mm.trans2:probe4 -0.0914050682253212 0.0520338247925057 -1.75664711540648 0.0794354454289115 . df.mm.trans2:probe5 -0.238888561370593 0.0520338247925057 -4.59102444079797 5.26929752340971e-06 *** df.mm.trans2:probe6 0.102310102227903 0.0520338247925057 1.96622298352817 0.049685924937979 * df.mm.trans3:probe2 -0.723951079878547 0.0520338247925057 -13.9130860121360 7.80709976617775e-39 *** df.mm.trans3:probe3 -0.641691181568977 0.0520338247925057 -12.3321932248463 1.24446403475149e-31 *** df.mm.trans3:probe4 -0.90921103508298 0.0520338247925057 -17.4734615167850 1.32953134707495e-56 *** df.mm.trans3:probe5 -0.822838065796698 0.0520338247925057 -15.8135226283656 4.3184070726951e-48 *** df.mm.trans3:probe6 -0.112117922263187 0.0520338247925057 -2.15471229936061 0.0315406056679655 * df.mm.trans3:probe7 -0.824976706856085 0.0520338247925057 -15.8546236058147 2.68486890336163e-48 *** df.mm.trans3:probe8 -0.748090435545503 0.0520338247925057 -14.3770026233637 4.87498325734578e-41 *** df.mm.trans3:probe9 -0.589207904208332 0.0520338247925057 -11.3235555248515 2.56543526627302e-27 *** df.mm.trans3:probe10 -0.428149916225906 0.0520338247925057 -8.22829991708723 9.9211600756512e-16 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.65509275079697 0.196693616834975 23.6667199764931 1.97448233143971e-90 *** df.mm.trans1 -0.099271136288858 0.166957649869109 -0.594588725743831 0.552319448064946 df.mm.trans2 -0.143854269926882 0.151884321271563 -0.947130478791656 0.343914270546957 df.mm.exp2 0.0885308289073542 0.197477433335026 0.448308586010225 0.654075658765226 df.mm.exp3 0.118002054081277 0.197477433335026 0.597547031518703 0.550344415913121 df.mm.exp4 0.230856423518003 0.197477433335026 1.16902685850868 0.242809175797093 df.mm.exp5 -0.0546300836314821 0.197477433335026 -0.276639627672295 0.782142278884982 df.mm.exp6 0.161367217643353 0.197477433335026 0.817142571270859 0.414137856110885 df.mm.exp7 0.195249881361430 0.197477433335026 0.98871996695533 0.3231576258827 df.mm.exp8 0.175733090471339 0.197477433335026 0.88988948004607 0.373845119824464 df.mm.trans1:exp2 -0.0893704521867617 0.175380907543642 -0.509579140845322 0.610514388938962 df.mm.trans2:exp2 0.0627721945073279 0.140617557473525 0.446403675580458 0.65545013327529 df.mm.trans1:exp3 -0.0640257548001731 0.175380907543642 -0.365066846197275 0.715176888419112 df.mm.trans2:exp3 -0.0628087714805024 0.140617557473525 -0.44666379226739 0.655262378834093 df.mm.trans1:exp4 -0.245960871077425 0.175380907543642 -1.40243812466428 0.161248310682058 df.mm.trans2:exp4 0.142527805988122 0.140617557473525 1.01358470840283 0.31114738876077 df.mm.trans1:exp5 0.0516303102211581 0.175380907543641 0.294389571500595 0.768551554828924 df.mm.trans2:exp5 0.036425066589414 0.140617557473525 0.259036405153545 0.795686834266974 df.mm.trans1:exp6 -0.220278183740551 0.175380907543642 -1.25599865359197 0.209554905041267 df.mm.trans2:exp6 0.0123135660437848 0.140617557473525 0.0875677708034657 0.930246422998747 df.mm.trans1:exp7 -0.292838100908432 0.175380907543642 -1.66972622624594 0.0954413404707918 . df.mm.trans2:exp7 0.0107051910762786 0.140617557473525 0.076129832352508 0.939338566545267 df.mm.trans1:exp8 -0.164905982485914 0.175380907543642 -0.940273287415162 0.347416770635179 df.mm.trans2:exp8 0.0681637597031851 0.140617557473525 0.484745723989827 0.628015400811916 df.mm.trans1:probe2 -0.0936334478695781 0.120075099021726 -0.779790719578226 0.435789849639907 df.mm.trans1:probe3 -0.0462315371251174 0.120075099021726 -0.385021853005114 0.700343599379354 df.mm.trans1:probe4 -0.08849238026541 0.120075099021726 -0.736975284520888 0.461395749721797 df.mm.trans1:probe5 -0.0496492568800904 0.120075099021726 -0.41348503798533 0.679383789679348 df.mm.trans1:probe6 -0.196912643028753 0.120075099021726 -1.63991239343576 0.101493471311067 df.mm.trans1:probe7 -0.0806780433740526 0.120075099021726 -0.671896538344351 0.501881521241937 df.mm.trans1:probe8 -0.0434741249757173 0.120075099021726 -0.362057789915721 0.717423178719912 df.mm.trans1:probe9 -0.113654734547770 0.120075099021726 -0.946530425323287 0.344219859301624 df.mm.trans1:probe10 -0.0879225325288912 0.120075099021726 -0.732229523400044 0.464284926506208 df.mm.trans1:probe11 -0.167483204181828 0.120075099021726 -1.39482045441849 0.163532915847001 df.mm.trans1:probe12 -0.168804803116479 0.120075099021726 -1.40582689076889 0.160239788944917 df.mm.trans1:probe13 -0.0150128442645407 0.120075099021726 -0.125028789373094 0.90053831838616 df.mm.trans1:probe14 -0.110048568865729 0.120075099021726 -0.916497839787891 0.359736092786838 df.mm.trans2:probe2 -0.241859931078674 0.120075099021726 -2.01423886425373 0.0443842214228645 * df.mm.trans2:probe3 -0.112760953002783 0.120075099021726 -0.939086904124734 0.348025048575684 df.mm.trans2:probe4 -0.172769945474445 0.120075099021726 -1.43884907763587 0.150660962167228 df.mm.trans2:probe5 -0.276095493111057 0.120075099021726 -2.29935678055199 0.0217918550001824 * df.mm.trans2:probe6 -0.212021552496763 0.120075099021726 -1.76574122548424 0.0778953596929728 . df.mm.trans3:probe2 0.168642678219924 0.120075099021726 1.40447669495081 0.160641042936836 df.mm.trans3:probe3 -0.0657265182574418 0.120075099021726 -0.547378422278458 0.584301330488365 df.mm.trans3:probe4 0.0365698694335457 0.120075099021726 0.304558311685665 0.76079728981235 df.mm.trans3:probe5 0.122875821272663 0.120075099021726 1.02332475487220 0.30652420776778 df.mm.trans3:probe6 -0.0513711825449142 0.120075099021726 -0.427825443938376 0.668915893205338 df.mm.trans3:probe7 0.0202117787233408 0.120075099021726 0.16832614661999 0.866377580257389 df.mm.trans3:probe8 0.0664675761971068 0.120075099021726 0.553550042753499 0.580071771448325 df.mm.trans3:probe9 0.0855114110034172 0.120075099021726 0.712149410661284 0.476620533871691 df.mm.trans3:probe10 0.0814184142985035 0.120075099021726 0.678062437273295 0.49796655573237