chr2.13460_chr2_130196007_130196937_+_1.R fitVsDatCorrelation=0.811508733304914 cont.fitVsDatCorrelation=0.277360770963618 fstatistic=5534.05563796839,37,347 cont.fstatistic=2041.19558757530,37,347 residuals=-0.499897598050126,-0.0887385175352565,-0.00488590564793282,0.0798266529817717,1.12478365373930 cont.residuals=-0.476430433769697,-0.174257410864274,-0.0540900638631631,0.107885027948147,1.35876946937883 predictedValues: Include Exclude Both chr2.13460_chr2_130196007_130196937_+_1.R.tl.Lung 51.9729548795988 49.4526316628935 66.3495057062334 chr2.13460_chr2_130196007_130196937_+_1.R.tl.cerebhem 64.0625155662058 59.2419159453412 84.2724990592336 chr2.13460_chr2_130196007_130196937_+_1.R.tl.cortex 52.4652913263187 47.8697579091437 98.0788820599305 chr2.13460_chr2_130196007_130196937_+_1.R.tl.heart 47.3453062592826 45.4310063545302 57.1964394785374 chr2.13460_chr2_130196007_130196937_+_1.R.tl.kidney 49.3483497931185 47.0714947613994 61.0138148376126 chr2.13460_chr2_130196007_130196937_+_1.R.tl.liver 49.2418479433092 51.4703597352799 56.5162630372106 chr2.13460_chr2_130196007_130196937_+_1.R.tl.stomach 55.0883820753863 46.0083086693342 59.3832225864487 chr2.13460_chr2_130196007_130196937_+_1.R.tl.testicle 53.5503204928232 52.9650936866647 57.8425189778594 diffExp=2.52032321670529,4.82059962086463,4.59553341717501,1.91429990475235,2.27685503171906,-2.22851179197066,9.08007340605216,0.585226806158495 diffExpScore=1.14073307870830 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=0,0,0,0,0,0,0,0 diffExp1.2Score=0 cont.predictedValues: Include Exclude Both Lung 55.0895976989432 51.0985254532764 51.6486188669176 cerebhem 52.3425487613068 53.144214859844 61.918872660953 cortex 55.2707168256804 60.480098295012 60.3165948722947 heart 55.5281976048735 56.6677868655341 55.2673261701705 kidney 57.9086349132315 55.5547416484656 59.8767533800233 liver 61.7174871722328 56.2612336427802 54.2808036647907 stomach 55.4627617952146 53.1253054951492 56.9422460707773 testicle 56.6713618337623 58.580893005956 52.6084006936779 cont.diffExp=3.99107224566686,-0.801666098537233,-5.20938146933165,-1.13958926066064,2.35389326476589,5.4562535294526,2.33745630006533,-1.90953117219370 cont.diffExpScore=3.81653620634146 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=0.772821692389314 cont.tran.correlation=0.273145588459650 tran.covariance=0.00613519236057445 cont.tran.covariance=0.000769227729981306 tran.mean=51.4115960662894 cont.tran.mean=55.9315066169539 weightedLogRatios: wLogRatio Lung 0.195147937606942 cerebhem 0.322366167424131 cortex 0.358817250914492 heart 0.158356979428451 kidney 0.183055780521427 liver -0.173458313376028 stomach 0.705856353695458 testicle 0.0436814626226844 cont.weightedLogRatios: wLogRatio Lung 0.298667063973569 cerebhem -0.0602728796300638 cortex -0.365443652757090 heart -0.0818093267720388 kidney 0.167572345079742 liver 0.377307533096322 stomach 0.171983348791262 testicle -0.134342533867840 varWeightedLogRatios=0.065334640927534 cont.varWeightedLogRatios=0.061955916671286 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.70671870668512 0.0945947670061205 39.1852406216645 1.80611682673692e-129 *** df.mm.trans1 0.139544900116277 0.0788104223289394 1.77064017667414 0.0774984485138243 . df.mm.trans2 0.242721236812383 0.0788104223289393 3.07981139600181 0.00223659337625428 ** df.mm.exp2 0.150630709381537 0.108584206078998 1.38722485360301 0.166263537195023 df.mm.exp3 -0.413938743543891 0.108584206078998 -3.81214504844969 0.000162983335724981 *** df.mm.exp4 -0.0296315813677741 0.108584206078998 -0.272890344164937 0.78509983807551 df.mm.exp5 -0.0173308229280928 0.108584206078998 -0.159607216868024 0.873283355282923 df.mm.exp6 0.146419045513466 0.108584206078998 1.34843777746962 0.178397072632894 df.mm.exp7 0.0969466581197577 0.108584206078998 0.892824671474106 0.37256982009891 df.mm.exp8 0.235728291822947 0.108584206078998 2.17092614418942 0.0306141622823036 * df.mm.trans1:exp2 0.0585052181217881 0.091770403763983 0.637517279233652 0.524208377984187 df.mm.trans2:exp2 0.0299833462680569 0.091770403763983 0.32672130706942 0.744075664916217 df.mm.trans1:exp3 0.423367092098886 0.091770403763983 4.61332929500572 5.58311504043986e-06 *** df.mm.trans2:exp3 0.381407414363456 0.091770403763983 4.15610478672806 4.08201283702955e-05 *** df.mm.trans1:exp4 -0.0636242173595918 0.091770403763983 -0.693297781746955 0.48858647904549 df.mm.trans2:exp4 -0.0551888626604675 0.091770403763983 -0.601379752042972 0.547979744781727 df.mm.trans1:exp5 -0.0344883354081409 0.0917704037639829 -0.375811089344651 0.707286984565643 df.mm.trans2:exp5 -0.0320168413412395 0.091770403763983 -0.34887981340456 0.727391136180729 df.mm.trans1:exp6 -0.200398700403748 0.091770403763983 -2.18369640084768 0.0296538043632979 * df.mm.trans2:exp6 -0.106428217966593 0.091770403763983 -1.15972267312136 0.246959088046058 df.mm.trans1:exp7 -0.0387313006336501 0.091770403763983 -0.422045660093859 0.673253050432929 df.mm.trans2:exp7 -0.169139930010505 0.091770403763983 -1.84307710409014 0.0661704715483599 . df.mm.trans1:exp8 -0.205829994834478 0.091770403763983 -2.24287990890653 0.0255353165114679 * df.mm.trans2:exp8 -0.167110480250853 0.091770403763983 -1.82096267856281 0.0694735946656952 . df.mm.trans1:probe2 0.345382044709813 0.0502647202528905 6.87126165175368 2.95931208667100e-11 *** df.mm.trans1:probe3 0.0273396613905988 0.0502647202528905 0.54391352927159 0.586850270684504 df.mm.trans1:probe4 0.365457538607669 0.0502647202528905 7.27065696912246 2.39164338846695e-12 *** df.mm.trans1:probe5 0.196518307655550 0.0502647202528905 3.90966679346533 0.000111164965743598 *** df.mm.trans1:probe6 0.109901227762866 0.0502647202528905 2.18644861067433 0.0294502730792266 * df.mm.trans2:probe2 -0.152420440798772 0.0502647202528905 -3.03235430401121 0.00260917531920662 ** df.mm.trans2:probe3 -0.0951179911729584 0.0502647202528905 -1.89234100367819 0.0592777378110206 . df.mm.trans2:probe4 -0.0160153633471930 0.0502647202528905 -0.318620361689411 0.75020610215792 df.mm.trans2:probe5 -0.168221739804114 0.0502647202528905 -3.34671592635473 0.000907337083071363 *** df.mm.trans2:probe6 -0.0524711466937895 0.0502647202528905 -1.04389612495202 0.29726013366482 df.mm.trans3:probe2 -0.066471040707242 0.0502647202528905 -1.32241939023663 0.186899481915608 df.mm.trans3:probe3 0.506904188763498 0.0502647202528905 10.0846913344623 3.82163290845507e-21 *** df.mm.trans3:probe4 -0.0166272786815779 0.0502647202528905 -0.330794215066218 0.74099958301143 cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.09477131991764 0.155531669370059 26.3275726191485 1.00146469012493e-84 *** df.mm.trans1 -0.0600836433490408 0.129579224480634 -0.463682689797395 0.64316581988264 df.mm.trans2 -0.140578122605023 0.129579224480634 -1.08488164803018 0.278727227080871 df.mm.exp2 -0.193259271809865 0.178532950322679 -1.08248517408450 0.279788643112685 df.mm.exp3 0.0166972267928129 0.178532950322679 0.093524622556422 0.925540765539604 df.mm.exp4 0.0436618914468034 0.178532950322679 0.244559289295838 0.80694223697149 df.mm.exp5 -0.0143060548189019 0.178532950322679 -0.0801311735063205 0.936179122968468 df.mm.exp6 0.160149308340723 0.178532950322679 0.89702941698589 0.370325139299383 df.mm.exp7 -0.0519254072675661 0.178532950322679 -0.29084495144295 0.771343661236868 df.mm.exp8 0.146548675776700 0.178532950322679 0.820849459507782 0.412295574674659 df.mm.trans1:exp2 0.142107955125226 0.150887882574447 0.941811580231509 0.346944319861211 df.mm.trans2:exp2 0.232512884446221 0.150887882574447 1.54096459224618 0.124236806352468 df.mm.trans1:exp3 -0.0134149003491621 0.150887882574447 -0.0889064126308708 0.929207576724424 df.mm.trans2:exp3 0.151861489632312 0.150887882574447 1.00645251985285 0.314899239240227 df.mm.trans1:exp4 -0.0357318436060644 0.150887882574447 -0.236810557590234 0.812943496334424 df.mm.trans2:exp4 0.0597883842622225 0.150887882574447 0.3962437754584 0.692168744339426 df.mm.trans1:exp5 0.0642116543788654 0.150887882574447 0.425558721371705 0.670693233022703 df.mm.trans2:exp5 0.0979192847768932 0.150887882574447 0.648953932590185 0.51679741939867 df.mm.trans1:exp6 -0.0465429038644438 0.150887882574447 -0.308460182953922 0.757917287474573 df.mm.trans2:exp6 -0.0638992186834869 0.150887882574447 -0.423488073351149 0.672201563464101 df.mm.trans1:exp7 0.0586763353386589 0.150887882574447 0.388873740803596 0.697608056402722 df.mm.trans2:exp7 0.0908231442994932 0.150887882574447 0.601924705614991 0.547617337344113 df.mm.trans1:exp8 -0.118240583780011 0.150887882574447 -0.783632070134407 0.433790575357063 df.mm.trans2:exp8 -0.00989573097406007 0.150887882574447 -0.0655833378083068 0.947747322411128 df.mm.trans1:probe2 -0.0683323066491897 0.0826446969402152 -0.826820221733295 0.408907150984035 df.mm.trans1:probe3 -0.0143732461060600 0.0826446969402151 -0.173916133015257 0.862032788799939 df.mm.trans1:probe4 -0.123409985175760 0.0826446969402152 -1.49325957677641 0.136277931587798 df.mm.trans1:probe5 -0.0307510012205261 0.0826446969402151 -0.372086804828763 0.710055347560491 df.mm.trans1:probe6 -0.0204011381041539 0.0826446969402152 -0.246853565437017 0.805167530243379 df.mm.trans2:probe2 -0.100648290599433 0.0826446969402151 -1.21784330181816 0.224110984703119 df.mm.trans2:probe3 0.0242848059229433 0.0826446969402152 0.293845906900848 0.769051333524498 df.mm.trans2:probe4 -0.109492295692024 0.0826446969402152 -1.32485567429971 0.186090808323669 df.mm.trans2:probe5 0.08128033141098 0.0826446969402151 0.983491190847707 0.326050977141094 df.mm.trans2:probe6 -0.0998001172381344 0.0826446969402151 -1.20758041269520 0.228031130620632 df.mm.trans3:probe2 0.0962288285889136 0.0826446969402151 1.16436785603467 0.245074869804984 df.mm.trans3:probe3 0.000783029538486797 0.0826446969402151 0.00947464952352886 0.992445881257196 df.mm.trans3:probe4 0.104403745915084 0.0826446969402152 1.26328427328628 0.207335163214538