chr8.23161_chr8_84374288_84375456_-_1.R fitVsDatCorrelation=0.901082437718818 cont.fitVsDatCorrelation=0.293740694069103 fstatistic=7698.391351179,40,416 cont.fstatistic=1576.13341609564,40,416 residuals=-0.480545539606898,-0.107008688230545,0.00851360899505894,0.0958826432987922,0.530899523358497 cont.residuals=-0.888422232589342,-0.277780496733819,-0.0692259020832373,0.253961640730122,1.05755976892742 predictedValues: Include Exclude Both chr8.23161_chr8_84374288_84375456_-_1.R.tl.Lung 98.4850202531226 64.8548114056912 106.127906522010 chr8.23161_chr8_84374288_84375456_-_1.R.tl.cerebhem 128.064069906681 65.7417359322532 104.824811398636 chr8.23161_chr8_84374288_84375456_-_1.R.tl.cortex 186.69230344137 65.5572281683521 125.026099450620 chr8.23161_chr8_84374288_84375456_-_1.R.tl.heart 118.355611993831 62.7247773890507 99.1345815392762 chr8.23161_chr8_84374288_84375456_-_1.R.tl.kidney 84.938486011348 56.8530883654456 94.1514950400084 chr8.23161_chr8_84374288_84375456_-_1.R.tl.liver 81.4670580456188 52.4280612928489 86.7566010497748 chr8.23161_chr8_84374288_84375456_-_1.R.tl.stomach 121.337986888723 69.5904570382545 102.343794115748 chr8.23161_chr8_84374288_84375456_-_1.R.tl.testicle 109.811549471958 58.3163880926652 100.788512992189 diffExp=33.6302088474314,62.322333974428,121.135075273018,55.6308346047808,28.0853976459023,29.0389967527699,51.7475298504686,51.4951613792926 diffExpScore=0.99769630657623 diffExp1.5=1,1,1,1,0,1,1,1 diffExp1.5Score=0.875 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 88.5191367276985 88.9530979652546 90.1962738664168 cerebhem 81.457782119345 87.7681546623246 83.9419922444901 cortex 100.394210837651 100.106474524740 102.229569922924 heart 79.8757337266235 98.6951546500556 73.7751805779683 kidney 74.9885702159822 86.1695755420234 82.7957433785424 liver 77.2079811906365 86.9428115831124 94.6563739435197 stomach 83.7029405429228 92.644507773486 91.8984164844422 testicle 78.5647114803173 94.5915768266244 92.251287697727 cont.diffExp=-0.433961237556062,-6.31037254297955,0.287736312911221,-18.8194209234322,-11.1810053260412,-9.73483039247584,-8.9415672305632,-16.0268653463071 cont.diffExpScore=0.994116883487142 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,-1,0,0,0,-1 cont.diffExp1.2Score=0.666666666666667 tran.correlation=0.610668262725223 cont.tran.correlation=0.568076382089006 tran.covariance=0.0170214997721658 cont.tran.covariance=0.00304535291378884 tran.mean=89.0761646060759 cont.tran.mean=87.5364012730499 weightedLogRatios: wLogRatio Lung 1.83018906245650 cerebhem 3.01334257343518 cortex 4.92521109886433 heart 2.82942316376097 kidney 1.7026579649519 liver 1.84228413565762 stomach 2.51324085595302 testicle 2.77349669089671 cont.weightedLogRatios: wLogRatio Lung -0.0219370447975384 cerebhem -0.331090915073202 cortex 0.0132248398828592 heart -0.949128736843494 kidney -0.609687536509288 liver -0.523187854115457 stomach -0.454499352286799 testicle -0.827376076367687 varWeightedLogRatios=1.08429981974609 cont.varWeightedLogRatios=0.119004252664099 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.30494486026125 0.0889130656801684 48.41746066598 4.80336842161127e-173 *** df.mm.trans1 0.336375240951175 0.0721180193586488 4.66423293294223 4.18117716687998e-06 *** df.mm.trans2 -0.150194704451711 0.0721180193586488 -2.08262381284738 0.037895903583814 * df.mm.exp2 0.288563638059698 0.0975213614456888 2.95897876918385 0.00326290576800504 ** df.mm.exp3 0.486452261216982 0.0975213614456888 4.98816109625269 8.97127060151428e-07 *** df.mm.exp4 0.218561433406392 0.0975213614456888 2.24116470654598 0.0255421841489903 * df.mm.exp5 -0.159917817110804 0.0975213614456888 -1.63982346780366 0.101797800164709 df.mm.exp6 -0.20087632394005 0.0975213614456888 -2.05981869984374 0.0400374728103679 * df.mm.exp7 0.315459174971493 0.0975213614456888 3.2347700062327 0.0013145968858077 ** df.mm.exp8 0.0542139456373896 0.0975213614456888 0.555918670880966 0.578565317977955 df.mm.trans1:exp2 -0.0259374111899806 0.0786242351940128 -0.32989079163667 0.74164853465392 df.mm.trans2:exp2 -0.274980764995242 0.0786242351940128 -3.49740464014309 0.000520426783799665 *** df.mm.trans1:exp3 0.153105106313917 0.0786242351940128 1.94730169312446 0.0521710638691463 . df.mm.trans2:exp3 -0.475679888396999 0.0786242351940128 -6.05004153265483 3.23087580436685e-09 *** df.mm.trans1:exp4 -0.0347721379137335 0.0786242351940128 -0.442257248390778 0.65853289969211 df.mm.trans2:exp4 -0.251955991009563 0.0786242351940128 -3.20455887917812 0.00145690779627864 ** df.mm.trans1:exp5 0.0119406596596652 0.0786242351940128 0.151869962616495 0.87936312394446 df.mm.trans2:exp5 0.0282372597911937 0.0786242351940128 0.359141932783392 0.719671129629293 df.mm.trans1:exp6 0.0111706087540524 0.0786242351940128 0.142075897164378 0.887088837596838 df.mm.trans2:exp6 -0.0118328080677461 0.0786242351940129 -0.15049822791341 0.880444493432787 df.mm.trans1:exp7 -0.106783701224262 0.0786242351940128 -1.35815249535672 0.175151413987721 df.mm.trans2:exp7 -0.244982829401659 0.0786242351940128 -3.11586915659199 0.00196111838919338 ** df.mm.trans1:exp8 0.0546473063896257 0.0786242351940128 0.695044044050518 0.487415731998548 df.mm.trans2:exp8 -0.160481893272922 0.0786242351940128 -2.04112501542200 0.0418689931495996 * df.mm.trans1:probe2 -0.173122787635159 0.0499648294681662 -3.46489299529101 0.000585560901093082 *** df.mm.trans1:probe3 -0.169915674622025 0.0499648294681662 -3.40070558492114 0.000737096483207124 *** df.mm.trans1:probe4 -0.0140244058950024 0.0499648294681662 -0.280685555105070 0.779091127614962 df.mm.trans1:probe5 -0.213901611286394 0.0499648294681662 -4.28104355730216 2.31159515601638e-05 *** df.mm.trans1:probe6 -0.0974388827855835 0.0499648294681662 -1.95014941155086 0.0518296187436928 . df.mm.trans2:probe2 0.0667208207197164 0.0499648294681662 1.33535571780998 0.182490154665269 df.mm.trans2:probe3 0.0838156543554967 0.0499648294681662 1.67749305356676 0.0941972311502788 . df.mm.trans2:probe4 -0.0694334715660404 0.0499648294681662 -1.38964692374820 0.165379365481406 df.mm.trans2:probe5 0.0917091665985107 0.0499648294681662 1.83547442420355 0.0671491045358125 . df.mm.trans2:probe6 0.0534001154256598 0.0499648294681662 1.06875408150211 0.285800259785657 df.mm.trans3:probe2 0.479432619760436 0.0499648294681662 9.59540190297045 7.8970041515755e-20 *** df.mm.trans3:probe3 -0.125899744324907 0.0499648294681662 -2.51976731763132 0.0121167679666691 * df.mm.trans3:probe4 0.0463178354451881 0.0499648294681662 0.927008776737611 0.354459477862973 df.mm.trans3:probe5 -0.189816234107467 0.0499648294681662 -3.79899693700353 0.000166952338506394 *** df.mm.trans3:probe6 0.731990355934026 0.0499648294681662 14.6501121634048 1.75016962282897e-39 *** df.mm.trans3:probe7 0.272612613817899 0.0499648294681662 5.4560901482029 8.3735541880049e-08 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.44724228557991 0.195990092738704 22.6911586368247 9.13208798680847e-75 *** df.mm.trans1 -0.0258274652079721 0.158968956858112 -0.162468608453060 0.871015733748282 df.mm.trans2 0.0734933606103528 0.158968956858112 0.462312655646029 0.644098825820506 df.mm.exp2 -0.0246822728496804 0.21496526441342 -0.114819819457955 0.908643337653418 df.mm.exp3 0.118778051617814 0.21496526441342 0.552545323738353 0.580871547357236 df.mm.exp4 0.202145695633508 0.21496526441342 0.940364463929126 0.347576350592272 df.mm.exp5 -0.112063671366503 0.21496526441342 -0.521310601842087 0.6024278202759 df.mm.exp6 -0.207839706249487 0.21496526441342 -0.966852513668305 0.334179512486206 df.mm.exp7 -0.0339799058540738 0.21496526441342 -0.158071611926678 0.874477070539018 df.mm.exp8 -0.0803650621237878 0.21496526441342 -0.373851386376686 0.708705346653301 df.mm.trans1:exp2 -0.0584516147729536 0.173310536863214 -0.337265210938021 0.73608708166291 df.mm.trans2:exp2 0.0112717628653510 0.173310536863214 0.0650379548142956 0.948175022506773 df.mm.trans1:exp3 0.00710773014786971 0.173310536863214 0.0410115292267516 0.967306380124068 df.mm.trans2:exp3 -0.000652928491610151 0.173310536863214 -0.00376739062394964 0.99699587022179 df.mm.trans1:exp4 -0.304892359892102 0.173310536863214 -1.75922575401598 0.0792742603689143 . df.mm.trans2:exp4 -0.0982190837606503 0.173310536863214 -0.566723094500423 0.571207962865351 df.mm.trans1:exp5 -0.0538193866809647 0.173310536863214 -0.310537302896025 0.756307922427844 df.mm.trans2:exp5 0.0802715931151581 0.173310536863214 0.463166259640132 0.643487407493231 df.mm.trans1:exp6 0.0711237783850144 0.173310536863214 0.410383463534875 0.681735952030722 df.mm.trans2:exp6 0.184981028967388 0.173310536863214 1.06733861838640 0.286437960855875 df.mm.trans1:exp7 -0.0219647481829658 0.173310536863214 -0.126736369181648 0.899210292834118 df.mm.trans2:exp7 0.0746403358650583 0.173310536863214 0.43067396371848 0.666928501843404 df.mm.trans1:exp8 -0.0389310654599354 0.173310536863214 -0.224631843882994 0.822375982174782 df.mm.trans2:exp8 0.141824252659533 0.173310536863214 0.818324466743004 0.413640430081739 df.mm.trans1:probe2 0.0415281980493283 0.11013692404179 0.377059722800783 0.706321491540506 df.mm.trans1:probe3 0.222472799496651 0.11013692404179 2.01996561491254 0.0440274867225837 * df.mm.trans1:probe4 0.136531968112490 0.11013692404179 1.23965663014780 0.215801276167053 df.mm.trans1:probe5 0.193020404790379 0.11013692404179 1.75254944215747 0.0804160525504935 . df.mm.trans1:probe6 0.209897881764976 0.11013692404179 1.9057903023089 0.0573664312721384 . df.mm.trans2:probe2 -0.102161591524731 0.11013692404179 -0.92758711407236 0.354159641892553 df.mm.trans2:probe3 -0.103880526566415 0.11013692404179 -0.943194368920265 0.346128929034198 df.mm.trans2:probe4 -0.0621590755180013 0.11013692404179 -0.564379984812503 0.572799721390452 df.mm.trans2:probe5 0.0195136311525374 0.11013692404179 0.177176104401946 0.859456295949006 df.mm.trans2:probe6 -0.175455696305348 0.11013692404179 -1.59306878988897 0.111904258087173 df.mm.trans3:probe2 0.0106627593521833 0.11013692404179 0.0968136657615153 0.92292099504447 df.mm.trans3:probe3 -0.0959799963138451 0.11013692404179 -0.871460658166072 0.384005325154752 df.mm.trans3:probe4 0.105453296160577 0.11013692404179 0.957474498929749 0.338883916250958 df.mm.trans3:probe5 0.100095108430621 0.11013692404179 0.908824259452182 0.363969109338126 df.mm.trans3:probe6 0.0415740607332937 0.11013692404179 0.377476137952781 0.706012298444303 df.mm.trans3:probe7 -0.112245679526382 0.11013692404179 -1.01914667131790 0.308725667063974