chr6.20128_chr6_121148984_121152832_-_0.R fitVsDatCorrelation=0.92377038986182 cont.fitVsDatCorrelation=0.25897644483791 fstatistic=7153.35010243671,46,554 cont.fstatistic=1114.29097009444,46,554 residuals=-1.46693250927040,-0.0748619065641222,0.00307637065857318,0.0792883474166713,0.690775763763455 cont.residuals=-0.738808812899974,-0.209403586325504,-0.0878699803020769,0.0497846065242997,2.37711122579572 predictedValues: Include Exclude Both chr6.20128_chr6_121148984_121152832_-_0.R.tl.Lung 44.6803504710975 47.5527055947629 68.0976148503683 chr6.20128_chr6_121148984_121152832_-_0.R.tl.cerebhem 46.7970376797364 50.5253522866986 52.0690137253038 chr6.20128_chr6_121148984_121152832_-_0.R.tl.cortex 44.3137674401736 45.7292238401204 61.7268250290744 chr6.20128_chr6_121148984_121152832_-_0.R.tl.heart 44.4605730696954 45.4398791760171 65.4096839469253 chr6.20128_chr6_121148984_121152832_-_0.R.tl.kidney 45.0143500612373 43.4491784131618 69.9665661040658 chr6.20128_chr6_121148984_121152832_-_0.R.tl.liver 47.6834582273879 45.0870548923099 69.6066611202572 chr6.20128_chr6_121148984_121152832_-_0.R.tl.stomach 45.9271524011976 46.0019333363846 62.572283222127 chr6.20128_chr6_121148984_121152832_-_0.R.tl.testicle 47.8121298066068 47.4843293628320 69.3103427708081 diffExp=-2.87235512366538,-3.72831460696224,-1.41545639994678,-0.979306106321673,1.56517164807557,2.59640333507799,-0.0747809351869364,0.327800443774876 diffExpScore=2.42966902429375 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 47.9694007710571 52.7959263479609 52.4685108904931 cerebhem 62.9982821194039 55.6170166017978 57.3212882893452 cortex 47.6472948915345 51.8802529394628 57.611343776394 heart 57.3691593918411 59.7853244196871 59.9268083428656 kidney 52.3781942912884 53.916702508673 59.6979907242856 liver 51.6494085273197 55.9777150448393 56.3753421560706 stomach 50.9632946270221 53.3627558997426 60.5712130886849 testicle 46.5858100661697 51.8723142327879 56.0689975216255 cont.diffExp=-4.82652557690384,7.3812655176061,-4.23295804792829,-2.41616502784602,-1.53850821738461,-4.32830651751961,-2.39946127272044,-5.28650416661813 cont.diffExpScore=1.73804957928037 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=0.331690224927409 cont.tran.correlation=0.71373077884459 tran.covariance=0.000468494248303514 cont.tran.covariance=0.00363350339417363 tran.mean=46.1224047537137 cont.tran.mean=53.2980532925367 weightedLogRatios: wLogRatio Lung -0.238670405815043 cerebhem -0.297740622688055 cortex -0.119700816369106 heart -0.0829115592473639 kidney 0.134100529094796 liver 0.214808272227202 stomach -0.00622766464641262 testicle 0.0265817498052459 cont.weightedLogRatios: wLogRatio Lung -0.375669256579584 cerebhem 0.508541945476351 cortex -0.332481460652462 heart -0.167906658610507 kidney -0.115017124990763 liver -0.320669725617081 stomach -0.181918239919697 testicle -0.418674850828533 varWeightedLogRatios=0.0306566024295265 cont.varWeightedLogRatios=0.0880842251889869 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 2.67567500789717 0.0853954769627899 31.3327485607120 9.30731371364506e-125 *** df.mm.trans1 1.11723483485815 0.0678345660262158 16.4699931068532 6.70605002975887e-50 *** df.mm.trans2 1.15959157361046 0.0678345660262158 17.0944054269076 6.29401869712965e-53 *** df.mm.exp2 0.375294796348471 0.090289471314793 4.15657319600434 3.74219203369803e-05 *** df.mm.exp3 0.0508840519260936 0.090289471314793 0.56356573125439 0.573277750645857 df.mm.exp4 -0.0101077238896218 0.0902894713147931 -0.111947979564321 0.910905202004525 df.mm.exp5 -0.109874546180273 0.090289471314793 -1.21691427118005 0.224154985925804 df.mm.exp6 -0.0101108615991146 0.0902894713147931 -0.111982731229683 0.910877660186269 df.mm.exp7 0.0789871851310607 0.090289471314793 0.87482165950084 0.382050045533176 df.mm.exp8 0.0486546587703259 0.0902894713147931 0.538874113025782 0.590190189038935 df.mm.trans1:exp2 -0.329008711066359 0.069572710161697 -4.72899086871411 2.86626676042963e-06 *** df.mm.trans2:exp2 -0.314658247928278 0.069572710161697 -4.52272517768774 7.47212432336179e-06 *** df.mm.trans1:exp3 -0.0591224639223411 0.069572710161697 -0.849793888795362 0.395806774596037 df.mm.trans2:exp3 -0.08998517443085 0.069572710161697 -1.29339757243482 0.196412620539945 df.mm.trans1:exp4 0.00517670370281402 0.069572710161697 0.0744071014451301 0.940713316829426 df.mm.trans2:exp4 -0.0353408480471844 0.069572710161697 -0.507969977956115 0.611676581827809 df.mm.trans1:exp5 0.117322057169032 0.069572710161697 1.68632294036496 0.0922966281487605 . df.mm.trans2:exp5 0.0196278015572396 0.069572710161697 0.282119260721937 0.777957424749911 df.mm.trans1:exp6 0.0751615934662761 0.069572710161697 1.08033154510712 0.280464643604511 df.mm.trans2:exp6 -0.0431326516739063 0.069572710161697 -0.619965092256142 0.535535679322026 df.mm.trans1:exp7 -0.0514645055795351 0.069572710161697 -0.739722593239852 0.459781669623195 df.mm.trans2:exp7 -0.112142447840993 0.069572710161697 -1.61187407505555 0.107558857831600 df.mm.trans1:exp8 0.0190908919829482 0.069572710161697 0.27440201680484 0.783877982881476 df.mm.trans2:exp8 -0.0500935976799722 0.069572710161697 -0.720017914546485 0.471817620653698 df.mm.trans1:probe2 0.0150418432168861 0.0498384387124638 0.301812087326171 0.762908577466837 df.mm.trans1:probe3 -0.00986243635139163 0.0498384387124638 -0.19788814830841 0.84320516561883 df.mm.trans1:probe4 0.00430218212742321 0.0498384387124637 0.0863225702603583 0.931241186011377 df.mm.trans1:probe5 0.0687803449258633 0.0498384387124637 1.38006620397325 0.168122916179418 df.mm.trans1:probe6 0.047593599465429 0.0498384387124638 0.95495767313286 0.340015600936381 df.mm.trans2:probe2 0.0988735806212561 0.0498384387124638 1.98388198297491 0.0477621006680594 * df.mm.trans2:probe3 0.0979270009558256 0.0498384387124638 1.96488901911238 0.0499263847477412 * df.mm.trans2:probe4 0.211692417496023 0.0498384387124637 4.24757321788017 2.53464927225654e-05 *** df.mm.trans2:probe5 0.0501012644979171 0.0498384387124638 1.00527355575823 0.315204013509469 df.mm.trans2:probe6 0.0462757477697316 0.0498384387124638 0.928515197611093 0.353544753967817 df.mm.trans3:probe2 -0.925373972966108 0.0498384387124638 -18.5674751631954 3.39536592802287e-60 *** df.mm.trans3:probe3 -1.04385262675660 0.0498384387124638 -20.9447296850323 3.48472727200477e-72 *** df.mm.trans3:probe4 -0.766370596587108 0.0498384387124637 -15.3770988093865 1.07263171460818e-44 *** df.mm.trans3:probe5 -1.00107154559546 0.0498384387124637 -20.0863343928371 7.91163954272039e-68 *** df.mm.trans3:probe6 0.744568352873742 0.0498384387124637 14.9396404082686 1.18774456031183e-42 *** df.mm.trans3:probe7 -1.04041565962982 0.0498384387124638 -20.8757675101413 7.81586770554692e-72 *** df.mm.trans3:probe8 -0.882038389648848 0.0498384387124638 -17.6979538772804 6.92610579920016e-56 *** df.mm.trans3:probe9 -0.981595859086046 0.0498384387124638 -19.6955579758273 7.45552227210445e-66 *** df.mm.trans3:probe10 -1.06932107179504 0.0498384387124638 -21.4557498071789 8.68708543937983e-75 *** df.mm.trans3:probe11 -0.836531111356801 0.0498384387124638 -16.7848578921795 2.01510577230184e-51 *** df.mm.trans3:probe12 -0.784133581752493 0.0498384387124638 -15.7335101582224 2.22750632765303e-46 *** df.mm.trans3:probe13 -0.924133902314877 0.0498384387124638 -18.5425933514199 4.51752171119969e-60 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 3.83070222598181 0.215387854493390 17.7851357263943 2.57501859569882e-56 *** df.mm.trans1 0.00687200265881088 0.171095029344977 0.0401648293648258 0.967976187062994 df.mm.trans2 0.149894988233038 0.171095029344977 0.876092010427763 0.381359717368612 df.mm.exp2 0.236140426557945 0.227731680898155 1.03692391689477 0.300223692799375 df.mm.exp3 -0.117739557693772 0.227731680898155 -0.517010005939519 0.605355513209308 df.mm.exp4 0.170358967430084 0.227731680898155 0.7480688095666 0.454736088198359 df.mm.exp5 -0.0201518507447776 0.227731680898155 -0.0884894480438577 0.929519648596229 df.mm.exp6 0.0606163809225547 0.227731680898155 0.266174564221757 0.790203803718288 df.mm.exp7 -0.0723852025305106 0.227731680898155 -0.3178530200323 0.750716201303112 df.mm.exp8 -0.113285999636867 0.227731680898155 -0.497453842127174 0.619066420549724 df.mm.trans1:exp2 0.0364037078235404 0.175479045331031 0.207453304494944 0.83573209007307 df.mm.trans2:exp2 -0.184085253372277 0.175479045331031 -1.04904407831152 0.294615251068747 df.mm.trans1:exp3 0.111002092113153 0.175479045331031 0.632566081629596 0.527278030167852 df.mm.trans2:exp3 0.100243757366586 0.175479045331031 0.571257708733726 0.56805663109374 df.mm.trans1:exp4 0.00858457498455533 0.175479045331031 0.0489207983116219 0.961000045331934 df.mm.trans2:exp4 -0.0460327828688058 0.175479045331031 -0.262326380804999 0.793167339370534 df.mm.trans1:exp5 0.108078892290183 0.175479045331031 0.6159076833721 0.538208408447292 df.mm.trans2:exp5 0.0411581249891207 0.175479045331031 0.234547235605700 0.814646825260734 df.mm.trans1:exp6 0.0132990393328456 0.175479045331031 0.0757870508570281 0.939615877828131 df.mm.trans2:exp6 -0.00209675025171863 0.175479045331031 -0.0119487215568288 0.99047082794666 df.mm.trans1:exp7 0.132927539249015 0.175479045331031 0.75751232290018 0.449065058671988 df.mm.trans2:exp7 0.0830642148656593 0.175479045331031 0.473356888333666 0.636145043841233 df.mm.trans1:exp8 0.084018665687284 0.175479045331031 0.478796003983197 0.632272672059232 df.mm.trans2:exp8 0.0956371677865741 0.175479045331031 0.545006200633017 0.585968582002052 df.mm.trans1:probe2 0.27726860721828 0.125704484211212 2.20571771133007 0.0278135820180791 * df.mm.trans1:probe3 0.247518473922832 0.125704484211212 1.96905047163589 0.0494452545867071 * df.mm.trans1:probe4 0.0111537208145221 0.125704484211212 0.088729697150512 0.929328796106387 df.mm.trans1:probe5 0.107016529992183 0.125704484211212 0.851334227762082 0.394951545830553 df.mm.trans1:probe6 -0.0161645259658799 0.125704484211212 -0.128591482374804 0.897727573993186 df.mm.trans2:probe2 -0.073888049048452 0.125704484211212 -0.587791672764064 0.556911642484827 df.mm.trans2:probe3 -0.0973856344214655 0.125704484211212 -0.774718857744453 0.438836323681886 df.mm.trans2:probe4 -0.0708651406508466 0.125704484211212 -0.563743935592444 0.573156532263556 df.mm.trans2:probe5 -0.0777154970376589 0.125704484211212 -0.618239655691833 0.536671452903745 df.mm.trans2:probe6 0.0507539205426307 0.125704484211212 0.403755847383716 0.686548066298522 df.mm.trans3:probe2 0.0214809911469628 0.125704484211212 0.170884843780672 0.864376706865537 df.mm.trans3:probe3 -0.108649633532345 0.125704484211212 -0.864325837014607 0.387782995030888 df.mm.trans3:probe4 0.0822180883251919 0.125704484211212 0.654058515422944 0.513345511139844 df.mm.trans3:probe5 -0.0165755710904780 0.125704484211212 -0.131861414447454 0.895141782837695 df.mm.trans3:probe6 -0.0979601551362743 0.125704484211212 -0.779289265223661 0.436142096174707 df.mm.trans3:probe7 -0.0362284913909299 0.125704484211212 -0.288203651749272 0.77329864443346 df.mm.trans3:probe8 -0.125344027039923 0.125704484211212 -0.997132503477893 0.319135517715139 df.mm.trans3:probe9 -0.185481954903244 0.125704484211212 -1.47553968394312 0.1406356084532 df.mm.trans3:probe10 0.0089562066853975 0.125704484211212 0.071248108145045 0.943226006261486 df.mm.trans3:probe11 -0.0050889484664449 0.125704484211212 -0.0404834282434533 0.967722303493388 df.mm.trans3:probe12 -0.0316415176613200 0.125704484211212 -0.25171351571003 0.801355855282954 df.mm.trans3:probe13 0.139986755850186 0.125704484211212 1.11361783733170 0.265926097014417