chr14.7131_chr14_43850147_43851831_+_0.R fitVsDatCorrelation=0.807949737282112 cont.fitVsDatCorrelation=0.290923086502981 fstatistic=10066.5357080006,43,485 cont.fstatistic=3811.45350145408,43,485 residuals=-0.372529911467506,-0.093044057215847,-0.0113796357385201,0.0875009602166092,0.747150055766524 cont.residuals=-0.527354413228206,-0.168403399254257,0.00300978880178070,0.150847922770043,1.00102266348273 predictedValues: Include Exclude Both chr14.7131_chr14_43850147_43851831_+_0.R.tl.Lung 71.3150796042696 72.04421061643 67.082974392728 chr14.7131_chr14_43850147_43851831_+_0.R.tl.cerebhem 56.1595773764443 70.1085757305023 69.8107026798448 chr14.7131_chr14_43850147_43851831_+_0.R.tl.cortex 57.8461500701691 68.532805423779 58.8626957349217 chr14.7131_chr14_43850147_43851831_+_0.R.tl.heart 63.5643590267273 72.5046876278535 63.0353926030775 chr14.7131_chr14_43850147_43851831_+_0.R.tl.kidney 65.9034588090396 71.0647315348815 63.3199334454479 chr14.7131_chr14_43850147_43851831_+_0.R.tl.liver 69.127593008694 73.8925091553487 59.0764722672273 chr14.7131_chr14_43850147_43851831_+_0.R.tl.stomach 67.3614841003489 74.7149253596652 69.1764116784294 chr14.7131_chr14_43850147_43851831_+_0.R.tl.testicle 65.6560451607672 70.5475042894759 63.8982519963018 diffExp=-0.729131012160323,-13.948998354058,-10.6866553536099,-8.9403286011262,-5.16127272584195,-4.76491614665476,-7.35344125931624,-4.89145912870868 diffExpScore=0.982601494965113 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=0,0,0,0,0,0,0,0 diffExp1.3Score=0 diffExp1.2=0,-1,0,0,0,0,0,0 diffExp1.2Score=0.5 cont.predictedValues: Include Exclude Both Lung 62.6803922032196 77.6167029971885 70.5194636382322 cerebhem 67.2812252918534 75.8342198486002 67.2196855107513 cortex 66.6782186153806 72.4050586224658 71.4420930043784 heart 60.5911892200966 65.378458088744 71.5931427451322 kidney 72.4304753610979 67.551026760048 67.6008857185327 liver 67.854606585315 64.3799501593028 68.2548270575462 stomach 61.6472496174316 64.479326215721 68.4464056895867 testicle 66.6186457848203 76.6071509687238 63.3032979982841 cont.diffExp=-14.9363107939689,-8.55299455674682,-5.72684000708523,-4.78726886864737,4.8794486010499,3.47465642601217,-2.83207659828941,-9.98850518390344 cont.diffExpScore=1.39797956527053 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=-1,0,0,0,0,0,0,0 cont.diffExp1.2Score=0.5 tran.correlation=0.700726795971828 cont.tran.correlation=0.076763926738235 tran.covariance=0.00167627349220314 cont.tran.covariance=0.000489414110194472 tran.mean=68.1464810558998 cont.tran.mean=68.1271185212506 weightedLogRatios: wLogRatio Lung -0.0434574683704058 cerebhem -0.918255291113426 cortex -0.702268395725224 heart -0.555062145438982 kidney -0.318633231435875 liver -0.284579657851276 stomach -0.441558011766361 testicle -0.303260679143951 cont.weightedLogRatios: wLogRatio Lung -0.90728269426825 cerebhem -0.510830399947599 cortex -0.349455542837843 heart -0.314984475873871 kidney 0.296254916114764 liver 0.220304479360428 stomach -0.186126948208239 testicle -0.59638187394121 varWeightedLogRatios=0.0750437929374049 cont.varWeightedLogRatios=0.163232368334252 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.25003858933657 0.0741944654738364 57.2824207600133 5.27634150399413e-218 *** df.mm.trans1 -0.0760222630846462 0.0593965496517298 -1.27991042460212 0.201188510695569 df.mm.trans2 0.0326334003421456 0.0593965496517298 0.549415757876353 0.582973039822378 df.mm.exp2 -0.306002465139095 0.0795360264819489 -3.84734413666672 0.000135357044050027 *** df.mm.exp3 -0.128565587892725 0.0795360264819489 -1.61644469279471 0.106648428026547 df.mm.exp4 -0.0464497088589572 0.0795360264819489 -0.584008416230087 0.559486165751385 df.mm.exp5 -0.0348755748063187 0.0795360264819489 -0.438487768988987 0.661227983241307 df.mm.exp6 0.121275194289152 0.0795360264819489 1.52478316623821 0.127964980187958 df.mm.exp7 -0.0513641447352057 0.0795360264819489 -0.645797219287325 0.518716109702221 df.mm.exp8 -0.0550335151027277 0.079536026481949 -0.69193191484387 0.489311195554876 df.mm.trans1:exp2 0.0670918992707697 0.0623931924715523 1.07530800417625 0.282771491398801 df.mm.trans2:exp2 0.278767620455561 0.0623931924715523 4.46791724245658 9.83958342085216e-06 *** df.mm.trans1:exp3 -0.080755311104656 0.0623931924715523 -1.29429682799892 0.196178835691431 df.mm.trans2:exp3 0.0785981629033509 0.0623931924715523 1.25972337349443 0.208375017422462 df.mm.trans1:exp4 -0.0686051707444919 0.0623931924715523 -1.09956179555601 0.272068584207291 df.mm.trans2:exp4 0.0528209586531421 0.0623931924715523 0.846582079883562 0.397645623656039 df.mm.trans1:exp5 -0.0440412995505079 0.0623931924715523 -0.705867063471518 0.480609719006805 df.mm.trans2:exp5 0.0211867813376173 0.0623931924715523 0.339568797465801 0.734328273090163 df.mm.trans1:exp6 -0.152429023479715 0.0623931924715523 -2.44303933556877 0.0149198343290617 * df.mm.trans2:exp6 -0.0959437029945437 0.0623931924715523 -1.53772710121042 0.124767470925754 df.mm.trans1:exp7 -0.00567025341418256 0.0623931924715523 -0.0908793602245608 0.927625971041614 df.mm.trans2:exp7 0.0877640540152117 0.0623931924715523 1.40662868076877 0.160177948784883 df.mm.trans1:exp8 -0.0276446069402990 0.0623931924715523 -0.443070883941439 0.657912022640464 df.mm.trans2:exp8 0.0340398508030717 0.0623931924715523 0.54556994849385 0.585612409144013 df.mm.trans1:probe2 0.309613404424175 0.0427176986892884 7.24789522666426 1.6799052599121e-12 *** df.mm.trans1:probe3 0.364057999417193 0.0427176986892884 8.52241601461743 1.98989282171191e-16 *** df.mm.trans1:probe4 0.273619897968910 0.0427176986892884 6.40530520988766 3.5528380457294e-10 *** df.mm.trans1:probe5 0.286001955384102 0.0427176986892884 6.69516299237855 5.97305678365406e-11 *** df.mm.trans1:probe6 0.256170326124372 0.0427176986892884 5.99681944450364 3.9352425223182e-09 *** df.mm.trans2:probe2 0.112324100668093 0.0427176986892884 2.62945112013392 0.00882388939770062 ** df.mm.trans2:probe3 -0.00591689985299708 0.0427176986892884 -0.138511671614950 0.889893536683926 df.mm.trans2:probe4 -0.236957861805288 0.0427176986892884 -5.54706524639415 4.78327044728672e-08 *** df.mm.trans2:probe5 -0.164333824050203 0.0427176986892884 -3.8469727792572 0.000135556170510700 *** df.mm.trans2:probe6 0.208612120775827 0.0427176986892884 4.88350560017731 1.41739062464443e-06 *** df.mm.trans3:probe2 -0.138652843624624 0.0427176986892884 -3.24579384842638 0.00125221752085532 ** df.mm.trans3:probe3 -0.00048516871715564 0.0427176986892884 -0.0113575574537516 0.990942845318585 df.mm.trans3:probe4 -0.0184324698638077 0.0427176986892884 -0.431494917314676 0.666300284713396 df.mm.trans3:probe5 0.282517164914513 0.0427176986892884 6.61358578722675 9.92863161323772e-11 *** df.mm.trans3:probe6 0.396110788712331 0.0427176986892884 9.27275581003283 5.97203162313948e-19 *** df.mm.trans3:probe7 -0.27360181814573 0.0427176986892884 -6.40488197025316 3.56193610239526e-10 *** df.mm.trans3:probe8 -0.255845910816603 0.0427176986892884 -5.98922504410935 4.11017467175392e-09 *** df.mm.trans3:probe9 -0.133610141697667 0.0427176986892884 -3.12774671382685 0.00186743454843454 ** df.mm.trans3:probe10 0.134805902786407 0.0427176986892884 3.15573888394437 0.00170045771980604 ** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.19843927195061 0.120466900899332 34.8513927112562 3.66036349500987e-134 *** df.mm.trans1 -0.0883602404654514 0.0964400540520158 -0.91621931710857 0.360007211176486 df.mm.trans2 0.158885413249124 0.0964400540520157 1.64750439857103 0.100102091250967 df.mm.exp2 0.095522151669403 0.129139802530235 0.739680174491815 0.459851949435588 df.mm.exp3 -0.0206752958316999 0.129139802530235 -0.160100104124437 0.872868875474835 df.mm.exp4 -0.220599562231288 0.129139802530235 -1.70822285545651 0.088234855785688 . df.mm.exp5 0.0479467483650722 0.129139802530235 0.371277851023866 0.710592722999352 df.mm.exp6 -0.075021200177891 0.129139802530235 -0.580930113783676 0.561557402010654 df.mm.exp7 -0.172220347792765 0.129139802530235 -1.33359618350387 0.182962195643601 df.mm.exp8 0.155794931457392 0.129139802530235 1.20640521671013 0.228249419323835 df.mm.trans1:exp2 -0.0246895990405027 0.101305595858952 -0.243714069604586 0.807555329345108 df.mm.trans2:exp2 -0.11875516054009 0.101305595858952 -1.17224679972696 0.241673465733632 df.mm.trans1:exp3 0.0825049632322902 0.101305595858952 0.81441664236556 0.415806003421472 df.mm.trans2:exp3 -0.0488311855778732 0.101305595858952 -0.482018640370674 0.630010147054457 df.mm.trans1:exp4 0.186700377629475 0.101305595858952 1.84294239668081 0.0659474704904278 . df.mm.trans2:exp4 0.0490097305758937 0.101305595858952 0.483781080011908 0.628759596834124 df.mm.trans1:exp5 0.0966317181632206 0.101305595858952 0.953863578254463 0.340627857323425 df.mm.trans2:exp5 -0.186846132910136 0.101305595858952 -1.84438116498798 0.0657372561689877 . df.mm.trans1:exp6 0.154339803122298 0.101305595858952 1.52350718451116 0.128283612820957 df.mm.trans2:exp6 -0.111959196952503 0.101305595858952 -1.10516300707005 0.269636901083329 df.mm.trans1:exp7 0.155600288853067 0.101305595858952 1.53594959423278 0.125202825829719 df.mm.trans2:exp7 -0.0132176524079696 0.101305595858952 -0.130473073041025 0.89624625446609 df.mm.trans1:exp8 -0.0948591010543133 0.101305595858952 -0.9363658566935 0.349550858867139 df.mm.trans2:exp8 -0.168887153221509 0.101305595858952 -1.66710586705053 0.0961389145726316 . df.mm.trans1:probe2 0.0152600767141532 0.0693592000668126 0.220015177502817 0.825951909244827 df.mm.trans1:probe3 0.0767176725132713 0.0693592000668126 1.10609223346536 0.269234942237448 df.mm.trans1:probe4 0.150548925059040 0.0693592000668126 2.17056893554162 0.0304482194659378 * df.mm.trans1:probe5 0.140454435471310 0.0693592000668126 2.02502963321394 0.04341160762367 * df.mm.trans1:probe6 0.0645331816625496 0.0693592000668126 0.9304199241108 0.35261657951747 df.mm.trans2:probe2 -0.000232836468879684 0.0693592000668126 -0.00335696589140873 0.997322914079686 df.mm.trans2:probe3 0.0228247371818504 0.0693592000668126 0.329080167589357 0.742237149318813 df.mm.trans2:probe4 -0.0472025092167388 0.0693592000668126 -0.680551522671389 0.496480060710332 df.mm.trans2:probe5 0.0337048029992424 0.0693592000668126 0.485945670751322 0.62722515870894 df.mm.trans2:probe6 -0.0977667763078793 0.0693592000668126 -1.40957185512091 0.159307032922338 df.mm.trans3:probe2 -0.00892365232875071 0.0693592000668126 -0.128658524322004 0.897681188726702 df.mm.trans3:probe3 0.0142446067777448 0.0693592000668126 0.205374438632845 0.837365758863963 df.mm.trans3:probe4 0.0320332726025856 0.0693592000668125 0.461846050296551 0.644398811388023 df.mm.trans3:probe5 -0.0262197545004800 0.0693592000668126 -0.378028501989973 0.705574813276253 df.mm.trans3:probe6 -0.0156461321156878 0.0693592000668126 -0.225581207692940 0.82162218167473 df.mm.trans3:probe7 0.00185534282203497 0.0693592000668126 0.0267497724922973 0.97867031736349 df.mm.trans3:probe8 -0.0305301672153972 0.0693592000668126 -0.440174730763734 0.660006658021264 df.mm.trans3:probe9 -0.0823946097725951 0.0693592000668126 -1.18794060042829 0.23543822864279 df.mm.trans3:probe10 -0.0151758367114734 0.0693592000668126 -0.218800630584764 0.82689739720909