chr1.1142_chr1_120186722_120188951_-_0.R fitVsDatCorrelation=0.938073820950697 cont.fitVsDatCorrelation=0.276027349706542 fstatistic=10782.8340101384,53,715 cont.fstatistic=1389.12414282611,53,715 residuals=-0.915278995462884,-0.0913029770638197,-3.58235955073582e-05,0.0977079501276868,0.571967137963183 cont.residuals=-1.02362714281503,-0.338510409934202,-0.0529688578996644,0.258916221674960,1.4594504824217 predictedValues: Include Exclude Both chr1.1142_chr1_120186722_120188951_-_0.R.tl.Lung 83.397837974042 49.4250974312773 123.910005669892 chr1.1142_chr1_120186722_120188951_-_0.R.tl.cerebhem 66.8020159222173 53.3069593533642 81.323340894117 chr1.1142_chr1_120186722_120188951_-_0.R.tl.cortex 69.9389180257542 46.9915097162969 99.2811134876123 chr1.1142_chr1_120186722_120188951_-_0.R.tl.heart 74.9157537228589 51.0049558970798 113.740731086450 chr1.1142_chr1_120186722_120188951_-_0.R.tl.kidney 86.8008011339608 52.7200538971309 117.873309817437 chr1.1142_chr1_120186722_120188951_-_0.R.tl.liver 69.9889759045963 51.3595951350089 91.6724777764873 chr1.1142_chr1_120186722_120188951_-_0.R.tl.stomach 79.7318464513923 50.1346507734607 134.053518141434 chr1.1142_chr1_120186722_120188951_-_0.R.tl.testicle 73.7363073958373 50.8962876122396 92.799440318338 diffExp=33.9727405427646,13.4950565688531,22.9474083094573,23.9107978257791,34.0807472368299,18.6293807695874,29.5971956779316,22.8400197835977 diffExpScore=0.99501180572686 diffExp1.5=1,0,0,0,1,0,1,0 diffExp1.5Score=0.75 diffExp1.4=1,0,1,1,1,0,1,1 diffExp1.4Score=0.857142857142857 diffExp1.3=1,0,1,1,1,1,1,1 diffExp1.3Score=0.875 diffExp1.2=1,1,1,1,1,1,1,1 diffExp1.2Score=0.888888888888889 cont.predictedValues: Include Exclude Both Lung 102.264111693430 96.2753334402455 89.2178336344306 cerebhem 77.7326990779669 100.693144737507 85.7963918880308 cortex 114.706845806641 92.1783544602068 88.7163765102289 heart 83.2264185333454 106.524053063624 91.5982699559274 kidney 108.351676453427 118.052509653454 87.5851758877805 liver 82.9299309330097 103.255956317192 85.9677114504138 stomach 87.1950236152563 102.851924180694 93.199525617392 testicle 99.553583336183 106.559493274376 98.7115514881125 cont.diffExp=5.98877825318463,-22.9604456595397,22.5284913464338,-23.2976345302786,-9.70083320002672,-20.3260253841821,-15.6569005654377,-7.00590993819272 cont.diffExpScore=1.7844625914848 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,-1,1,-1,0,-1,0,0 cont.diffExp1.2Score=1.33333333333333 tran.correlation=0.0423469803266089 cont.tran.correlation=-0.0645860152247545 tran.covariance=0.000122868216928844 cont.tran.covariance=-0.00091958161432957 tran.mean=63.1969728966573 cont.tran.mean=98.8969411610348 weightedLogRatios: wLogRatio Lung 2.17742987215025 cerebhem 0.922727222713948 cortex 1.61002471449381 heart 1.58549148474638 kidney 2.10133694073158 liver 1.26691012898951 stomach 1.92388488601929 testicle 1.52550531263221 cont.weightedLogRatios: wLogRatio Lung 0.277436830094592 cerebhem -1.16012445977332 cortex 1.01303718507656 heart -1.12172524633929 kidney -0.405435278373936 liver -0.99251802163983 stomach -0.75151964427176 testicle -0.315194000736220 varWeightedLogRatios=0.178986099085635 cont.varWeightedLogRatios=0.57542025826244 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.15388193842208 0.0806766051675564 39.0928935578265 1.07903334422993e-179 *** df.mm.trans1 1.21801420187780 0.0634616929067484 19.192904350465 1.54797457209687e-66 *** df.mm.trans2 0.728438102811881 0.0634616929067483 11.4783906550092 4.13710448002835e-28 *** df.mm.exp2 0.274841895055493 0.0838097094134573 3.27935625811109 0.00109084434548921 ** df.mm.exp3 -0.00489133834338657 0.0838097094134573 -0.0583624305300499 0.953476246615333 df.mm.exp4 0.00984024696449902 0.0838097094134573 0.117411777625362 0.90656672466173 df.mm.exp5 0.154476177299269 0.0838097094134573 1.84317757907015 0.065716809415003 . df.mm.exp6 0.164442133700923 0.0838097094134573 1.96208929552163 0.0501395948652246 . df.mm.exp7 -0.109382807473258 0.0838097094134573 -1.3051328806504 0.192267452921839 df.mm.exp8 0.195319508382019 0.0838097094134573 2.33051170024288 0.0200563843411407 * df.mm.trans1:exp2 -0.496731021947989 0.0630089283168201 -7.88350215147823 1.18977008339623e-14 *** df.mm.trans2:exp2 -0.199233343275824 0.0630089283168201 -3.16198590577581 0.00163318132419054 ** df.mm.trans1:exp3 -0.171108785632056 0.0630089283168201 -2.715627613466 0.00677475621682124 ** df.mm.trans2:exp3 -0.0456000609489988 0.0630089283168201 -0.723707927862439 0.469481767169471 df.mm.trans1:exp4 -0.117098433935413 0.0630089283168201 -1.85844192344649 0.0635170373005817 . df.mm.trans2:exp4 0.0216242151410586 0.0630089283168201 0.343192873116778 0.731554246986318 df.mm.trans1:exp5 -0.114482711477672 0.0630089283168201 -1.81692840262308 0.069646602901076 . df.mm.trans2:exp5 -0.0899386051277449 0.0630089283168201 -1.42739461740275 0.153902757071621 df.mm.trans1:exp6 -0.339726776587193 0.0630089283168201 -5.39172440576971 9.48965097736206e-08 *** df.mm.trans2:exp6 -0.126048697585811 0.0630089283168201 -2.00048946955606 0.0458251157766324 * df.mm.trans1:exp7 0.0644295070668258 0.0630089283168201 1.02254567389026 0.306868546091224 df.mm.trans2:exp7 0.123636868351372 0.0630089283168201 1.96221189050707 0.0501252956194663 . df.mm.trans1:exp8 -0.318446578284858 0.0630089283168201 -5.0539913436339 5.50097865825823e-07 *** df.mm.trans2:exp8 -0.165987862762134 0.0630089283168201 -2.63435464141713 0.00861216514263112 ** df.mm.trans1:probe2 0.219480330061679 0.0478587166381474 4.58600533986602 5.33355910847349e-06 *** df.mm.trans1:probe3 0.333413368636074 0.0478587166381474 6.9666174117656 7.3762132248014e-12 *** df.mm.trans1:probe4 -0.0554589486446445 0.0478587166381474 -1.15880559572797 0.246922311102826 df.mm.trans1:probe5 0.327496922777217 0.0478587166381474 6.84299425020884 1.66864164245549e-11 *** df.mm.trans1:probe6 0.519950701229836 0.0478587166381474 10.8642842465064 1.48971269576940e-25 *** df.mm.trans2:probe2 0.162347888669024 0.0478587166381474 3.3922323888564 0.000731421469559099 *** df.mm.trans2:probe3 0.0841647015683008 0.0478587166381474 1.75860757413655 0.0790719469409705 . df.mm.trans2:probe4 0.0544456822232205 0.0478587166381474 1.1376335607759 0.255654604210893 df.mm.trans2:probe5 0.0186163285717864 0.0478587166381474 0.388985118688862 0.697402967593942 df.mm.trans2:probe6 0.152021175989458 0.0478587166381474 3.17645742861991 0.00155493494527564 ** df.mm.trans3:probe2 -0.369050100794564 0.0478587166381474 -7.71124105948967 4.18437973805991e-14 *** df.mm.trans3:probe3 -0.325921684409955 0.0478587166381474 -6.81007990402668 2.06946787015988e-11 *** df.mm.trans3:probe4 -0.55402771549615 0.0478587166381474 -11.5763178458184 1.58570355650694e-28 *** df.mm.trans3:probe5 -0.0365611983720375 0.0478587166381474 -0.763940216961339 0.445154886050348 df.mm.trans3:probe6 -0.460272651868446 0.0478587166381474 -9.61732123634861 1.12957253759426e-20 *** df.mm.trans3:probe7 0.500820921337963 0.0478587166381474 10.4645706470693 6.08174236539277e-24 *** df.mm.trans3:probe8 -0.250084098783326 0.0478587166381474 -5.22546604569811 2.28181205625692e-07 *** df.mm.trans3:probe9 -0.736590103149774 0.0478587166381474 -15.3909288608598 2.21825846354023e-46 *** df.mm.trans3:probe10 0.435073113630245 0.0478587166381474 9.09078103618548 9.54625960959788e-19 *** df.mm.trans3:probe11 -0.635608797484618 0.0478587166381474 -13.2809411144549 3.89362049768401e-36 *** df.mm.trans3:probe12 -0.781077064894747 0.0478587166381474 -16.3204765978234 3.91113095553394e-51 *** df.mm.trans3:probe13 -0.517366055708499 0.0478587166381474 -10.8102785041276 2.47312645355248e-25 *** df.mm.trans3:probe14 -0.540570343436034 0.0478587166381474 -11.2951282735642 2.45277714170532e-27 *** df.mm.trans3:probe15 -0.437369130665062 0.0478587166381474 -9.1387559338865 6.42241199700029e-19 *** df.mm.trans3:probe16 0.409443291689926 0.0478587166381474 8.55525012895071 7.13496706984933e-17 *** df.mm.trans3:probe17 0.219666426436809 0.0478587166381474 4.5898937929672 5.2379574186571e-06 *** df.mm.trans3:probe18 -0.492401269011433 0.0478587166381474 -10.2886433987440 3.01538174445851e-23 *** df.mm.trans3:probe19 -0.726625146371489 0.0478587166381474 -15.1827127305856 2.46744905538076e-45 *** df.mm.trans3:probe20 -0.317052427153075 0.0478587166381474 -6.62475823474876 6.84220787534358e-11 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.79384539583438 0.223829016703091 21.4174438437238 5.30323051031998e-79 *** df.mm.trans1 -0.160473090295299 0.176067997558025 -0.911426792608428 0.362377717671412 df.mm.trans2 -0.182747073678540 0.176067997558025 -1.03793464010014 0.299651362143051 df.mm.exp2 -0.190313217248576 0.232521495038438 -0.818475802493508 0.413358246011159 df.mm.exp3 0.0769705502736936 0.232521495038438 0.331025526310889 0.740722191820236 df.mm.exp4 -0.131166738613486 0.232521495038438 -0.564105862951738 0.572858985595115 df.mm.exp5 0.280209972445669 0.232521495038438 1.20509276959254 0.228566188459129 df.mm.exp6 -0.102454805338348 0.232521495038438 -0.440625092838885 0.659617618256021 df.mm.exp7 -0.136995038488377 0.232521495038438 -0.589171502039974 0.55593233095703 df.mm.exp8 -0.0264924912104306 0.232521495038438 -0.113935665199689 0.909320777402834 df.mm.trans1:exp2 -0.0839695734227037 0.174811848358995 -0.480342575237022 0.631130743849177 df.mm.trans2:exp2 0.235178795453896 0.174811848358995 1.34532526062495 0.178946722824111 df.mm.trans1:exp3 0.0378503594606873 0.174811848358995 0.216520560911623 0.828643760600413 df.mm.trans2:exp3 -0.120457357625790 0.174811848358995 -0.689068611518927 0.491003631650552 df.mm.trans1:exp4 -0.0748272305844764 0.174811848358995 -0.428044387648201 0.668747704637604 df.mm.trans2:exp4 0.232325405515653 0.174811848358995 1.32900262594642 0.184271037510368 df.mm.trans1:exp5 -0.222386569080549 0.174811848358995 -1.27214814766934 0.203734064503872 df.mm.trans2:exp5 -0.0762925930082921 0.174811848358995 -0.436426899689413 0.662658776902736 df.mm.trans1:exp6 -0.107107946105555 0.174811848358996 -0.612704156560357 0.540266793117131 df.mm.trans2:exp6 0.172453580708057 0.174811848358995 0.98650968070485 0.324216776404504 df.mm.trans1:exp7 -0.0224164979294130 0.174811848358995 -0.128232142957371 0.898001322052344 df.mm.trans2:exp7 0.203073219914225 0.174811848358995 1.16166736877692 0.245758245760129 df.mm.trans1:exp8 -0.000370280658182211 0.174811848358996 -0.00211816682712375 0.998310539478574 df.mm.trans2:exp8 0.127983799573541 0.174811848358995 0.732123141394355 0.464333315483682 df.mm.trans1:probe2 0.194915324375599 0.132779130499361 1.46796656705428 0.142553061424960 df.mm.trans1:probe3 -0.0123907523023978 0.132779130499361 -0.0933185226910147 0.925676659383541 df.mm.trans1:probe4 -0.0884716229459454 0.132779130499361 -0.666306690013842 0.505430015807242 df.mm.trans1:probe5 -0.177868974488630 0.132779130499361 -1.3395853235346 0.180805818693089 df.mm.trans1:probe6 -0.0673351947861685 0.132779130499361 -0.507121823534554 0.612225709284529 df.mm.trans2:probe2 -0.232627698549611 0.132779130499361 -1.75198992247302 0.080204218984044 . df.mm.trans2:probe3 -0.135242699546642 0.132779130499361 -1.01855388748229 0.30875932348818 df.mm.trans2:probe4 -0.267054768591310 0.132779130499361 -2.01127065365589 0.0446716950232241 * df.mm.trans2:probe5 -0.266605169064419 0.132779130499361 -2.00788458292926 0.0450312796802817 * df.mm.trans2:probe6 -0.239510319449554 0.132779130499361 -1.80382503296108 0.0716795173484698 . df.mm.trans3:probe2 0.0504845394519629 0.132779130499361 0.380214415187828 0.703899178150271 df.mm.trans3:probe3 -0.0957216604687132 0.132779130499361 -0.72090892679233 0.471201187331056 df.mm.trans3:probe4 -0.00635287155885826 0.132779130499361 -0.0478454071431717 0.961852809153635 df.mm.trans3:probe5 -0.0185363140931374 0.132779130499361 -0.139602616943079 0.889013286289088 df.mm.trans3:probe6 -0.058933853599329 0.132779130499361 -0.443848768836549 0.65728621382711 df.mm.trans3:probe7 0.229239551031715 0.132779130499361 1.72647275343332 0.0846943503886206 . df.mm.trans3:probe8 0.0599031346824679 0.132779130499361 0.451148719359599 0.652019159638477 df.mm.trans3:probe9 0.104384124788115 0.132779130499361 0.786148579189686 0.432040903661609 df.mm.trans3:probe10 -0.0597888102390974 0.132779130499361 -0.450287707219058 0.652639498890904 df.mm.trans3:probe11 0.147447861340350 0.132779130499361 1.11047467162816 0.267167842263460 df.mm.trans3:probe12 0.0882527691745052 0.132779130499361 0.664658435724052 0.506483287357913 df.mm.trans3:probe13 0.080687674272881 0.132779130499361 0.607683406039996 0.543590423556483 df.mm.trans3:probe14 -0.0074646546992974 0.132779130499361 -0.0562185839839741 0.955183382560486 df.mm.trans3:probe15 -0.00141146608668764 0.132779130499361 -0.0106301802201847 0.99152146832212 df.mm.trans3:probe16 -0.0338022524613306 0.132779130499361 -0.254575040024782 0.799124538882395 df.mm.trans3:probe17 0.0107320065984848 0.132779130499361 0.0808260044942559 0.935602945331173 df.mm.trans3:probe18 0.32730623733722 0.132779130499361 2.46504278274962 0.0139336208874696 * df.mm.trans3:probe19 0.070691274609732 0.132779130499361 0.532397481018841 0.594616131653411 df.mm.trans3:probe20 -0.0780029624915285 0.132779130499361 -0.58746402539444 0.557077573621882