chr1.778_chr1_173774477_173779838_+_2.R fitVsDatCorrelation=0.926744660230986 cont.fitVsDatCorrelation=0.227500881088951 fstatistic=9111.05223198174,69,1083 cont.fstatistic=1342.80452566097,69,1083 residuals=-0.90591437493794,-0.106409323734849,-0.00499641142816429,0.103023500034364,1.68576285025840 cont.residuals=-0.943618333967192,-0.378688020305256,-0.116296019102276,0.377627727486841,1.93660962719788 predictedValues: Include Exclude Both chr1.778_chr1_173774477_173779838_+_2.R.tl.Lung 88.012873833104 198.249155509106 70.4187201943397 chr1.778_chr1_173774477_173779838_+_2.R.tl.cerebhem 81.4120356233157 136.660023082780 65.979921565305 chr1.778_chr1_173774477_173779838_+_2.R.tl.cortex 76.1233552768058 166.688554237161 63.8131279877242 chr1.778_chr1_173774477_173779838_+_2.R.tl.heart 81.237170105296 188.984622751592 66.7416605265157 chr1.778_chr1_173774477_173779838_+_2.R.tl.kidney 90.5598803304185 211.909950260286 72.8606530961953 chr1.778_chr1_173774477_173779838_+_2.R.tl.liver 89.675830489479 214.402425539963 66.3370717194207 chr1.778_chr1_173774477_173779838_+_2.R.tl.stomach 95.93525931305 184.527458091108 87.386813266542 chr1.778_chr1_173774477_173779838_+_2.R.tl.testicle 86.8652474450121 175.553220983739 74.6243942516838 diffExp=-110.236281676002,-55.2479874594645,-90.5651989603554,-107.747452646296,-121.350069929867,-124.726595050484,-88.5921987780579,-88.6879735387269 diffExpScore=0.998731212038514 diffExp1.5=-1,-1,-1,-1,-1,-1,-1,-1 diffExp1.5Score=0.888888888888889 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 97.7053958783682 84.6989530738576 90.859085941914 cerebhem 91.1691410142698 83.5503602954184 85.074102213998 cortex 90.9394816767427 103.880893981415 95.8068804392085 heart 88.4294465590629 82.6672332096658 99.291070529959 kidney 89.9047352094937 82.5556867913767 85.3467899599208 liver 86.8540941881241 85.3839726423158 83.2796584657368 stomach 83.0872317784528 77.3584229968353 98.4313454511467 testicle 90.4805457049625 71.4880408405006 85.976834730505 cont.diffExp=13.0064428045106,7.61878071885141,-12.9414123046725,5.76221334939707,7.34904841811698,1.47012154580835,5.72880878161753,18.9925048644618 cont.diffExpScore=1.51853792980723 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=0,0,0,0,0,0,0,1 cont.diffExp1.2Score=0.5 tran.correlation=0.559115082737559 cont.tran.correlation=0.226129551204205 tran.covariance=0.00601641731802298 cont.tran.covariance=0.00116102915127960 tran.mean=135.424816429513 cont.tran.mean=86.8846022400539 weightedLogRatios: wLogRatio Lung -3.96560780765573 cerebhem -2.41298288391036 cortex -3.70272794361017 heart -4.06908517544723 kidney -4.19216370025799 liver -4.29901927186201 stomach -3.19915114775012 testicle -3.38856720620915 cont.weightedLogRatios: wLogRatio Lung 0.644345204102023 cerebhem 0.390003049581371 cortex -0.608935950157047 heart 0.299748488008622 kidney 0.380006322086687 liver 0.0760641475108808 stomach 0.313212030149829 testicle 1.03367611046113 varWeightedLogRatios=0.399272027365629 cont.varWeightedLogRatios=0.220827205862317 coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 5.39815069711147 0.0871425200370575 61.9462312406837 0 *** df.mm.trans1 -1.07344605100710 0.0743197573582206 -14.4436161952615 2.24158047703876e-43 *** df.mm.trans2 -0.0626680769284512 0.0647360789650856 -0.968054876512527 0.333233094903002 df.mm.exp2 -0.384879657364905 0.0811614422219072 -4.7421490652247 2.39679590921889e-06 *** df.mm.exp3 -0.220025248672067 0.0811614422219071 -2.71095784708318 0.00681500864602507 ** df.mm.exp4 -0.0743393589989732 0.0811614422219071 -0.915944282948036 0.359900020699522 df.mm.exp5 0.0610754008236004 0.0811614422219071 0.752517441183603 0.451903472908133 df.mm.exp6 0.156758576269090 0.0811614422219072 1.93144148228034 0.0536891581747082 . df.mm.exp7 -0.201421093205547 0.0811614422219071 -2.4817337850507 0.0132252850489216 * df.mm.exp8 -0.192715724537390 0.0811614422219071 -2.37447387899389 0.0177474692668810 * df.mm.trans1:exp2 0.306919679887459 0.0737895263964763 4.15939354642768 3.44336062926487e-05 *** df.mm.trans2:exp2 0.0128513148453519 0.0489775412328933 0.262391996859185 0.793069143886719 df.mm.trans1:exp3 0.0748972715731743 0.0737895263964763 1.01501222776178 0.310326700699161 df.mm.trans2:exp3 0.0466277744478844 0.0489775412328932 0.952023586201776 0.341297439368543 df.mm.trans1:exp4 -0.00577083599241334 0.0737895263964763 -0.0782067086513909 0.93767807222028 df.mm.trans2:exp4 0.0264804088671306 0.0489775412328932 0.540664316757216 0.588850153136698 df.mm.trans1:exp5 -0.0325472051456742 0.0737895263964763 -0.441081637667598 0.659241934439619 df.mm.trans2:exp5 0.00556141990910362 0.0489775412328932 0.113550410435234 0.90961524496139 df.mm.trans1:exp6 -0.138040389126224 0.0737895263964763 -1.87073146918606 0.0616518279921744 . df.mm.trans2:exp6 -0.0784284347624277 0.0489775412328933 -1.60131425114814 0.109598961088489 df.mm.trans1:exp7 0.287611577683374 0.0737895263964764 3.89772901018522 0.000103062237458718 *** df.mm.trans2:exp7 0.12969476917613 0.0489775412328932 2.64804573507311 0.00821351299659908 ** df.mm.trans1:exp8 0.179590665158655 0.0737895263964764 2.43382325282455 0.0151011403262500 * df.mm.trans2:exp8 0.0711333741610674 0.0489775412328932 1.45236719464582 0.146689178919313 df.mm.trans1:probe2 -0.0976196379784766 0.0560471686951282 -1.74174075606717 0.081837732263222 . df.mm.trans1:probe3 -0.24246951630945 0.0560471686951282 -4.32616886730491 1.65739237809172e-05 *** df.mm.trans1:probe4 -0.183190913813935 0.0560471686951282 -3.26851325551184 0.00111512979497091 ** df.mm.trans1:probe5 -0.286480369194924 0.0560471686951282 -5.11141554274134 3.77804101908907e-07 *** df.mm.trans1:probe6 -0.389222405125109 0.0560471686951282 -6.94455070946235 6.53503839411522e-12 *** df.mm.trans1:probe7 -0.0486196926889887 0.0560471686951282 -0.86747812281934 0.38587225897956 df.mm.trans1:probe8 -0.157604554120300 0.0560471686951282 -2.8119984967947 0.00501235942589618 ** df.mm.trans1:probe9 0.97547521391981 0.0560471686951282 17.4045404367518 5.1729880222928e-60 *** df.mm.trans1:probe10 -0.151493127555034 0.0560471686951282 -2.7029577243962 0.00698007770484763 ** df.mm.trans1:probe11 0.918696170220154 0.0560471686951282 16.3914822391378 4.13737249363902e-54 *** df.mm.trans1:probe12 1.12753004896596 0.0560471686951282 20.1175202105075 9.9557863237083e-77 *** df.mm.trans1:probe13 1.09751075421549 0.0560471686951282 19.5819125170348 2.46638541947756e-73 *** df.mm.trans1:probe14 1.05129160676116 0.0560471686951282 18.7572651971007 3.40079789697841e-68 *** df.mm.trans1:probe15 0.784043473567936 0.0560471686951282 13.9889934107606 5.3394242681638e-41 *** df.mm.trans1:probe16 0.869748446510872 0.0560471686951282 15.5181513493022 3.42764703295676e-49 *** df.mm.trans1:probe17 0.121093236398078 0.0560471686951282 2.16055938626929 0.0309481541515115 * df.mm.trans1:probe18 0.208383211216895 0.0560471686951282 3.71799710972748 0.000211090956741476 *** df.mm.trans1:probe19 0.096973812484598 0.0560471686951282 1.73021786367288 0.0838762353113415 . df.mm.trans1:probe20 0.059109061674737 0.0560471686951282 1.05463064506013 0.291829501206162 df.mm.trans1:probe21 0.269975533295144 0.0560471686951282 4.81693437118459 1.66511125410156e-06 *** df.mm.trans1:probe22 0.3935645992982 0.0560471686951282 7.02202463498231 3.85459340788199e-12 *** df.mm.trans2:probe2 -0.275060562642591 0.0560471686951282 -4.90766204692334 1.06314307904305e-06 *** df.mm.trans2:probe3 -0.12730678293657 0.0560471686951282 -2.27142219492054 0.0233169906701261 * df.mm.trans2:probe4 -0.283974127542299 0.0560471686951282 -5.06669889226684 4.75626828364237e-07 *** df.mm.trans2:probe5 -0.309136490369303 0.0560471686951282 -5.51564865035144 4.34480539248332e-08 *** df.mm.trans2:probe6 -0.199430541018939 0.0560471686951282 -3.55826254317597 0.000389481996731530 *** df.mm.trans3:probe2 0.0417655714273714 0.0560471686951282 0.745186106626681 0.456320905375912 df.mm.trans3:probe3 0.089183140540754 0.0560471686951282 1.59121580299392 0.111852848645175 df.mm.trans3:probe4 -0.148464331425487 0.0560471686951282 -2.64891759712372 0.00819249324019737 ** df.mm.trans3:probe5 -0.182223408582001 0.0560471686951282 -3.25125091640607 0.00118439753938677 ** df.mm.trans3:probe6 -0.289249116901104 0.0560471686951282 -5.16081585627441 2.92338680123149e-07 *** df.mm.trans3:probe7 -0.205133916264855 0.0560471686951282 -3.66002281722191 0.000264352510205402 *** df.mm.trans3:probe8 0.553822284957086 0.0560471686951282 9.88136060841242 4.17701864801879e-22 *** df.mm.trans3:probe9 -0.23236503405001 0.0560471686951282 -4.1458835380958 3.64944316366976e-05 *** df.mm.trans3:probe10 0.225911233866353 0.0560471686951282 4.03073409640386 5.9492937716141e-05 *** df.mm.trans3:probe11 0.0945290400242982 0.0560471686951282 1.68659795356469 0.091968687327666 . df.mm.trans3:probe12 -0.147586317003546 0.0560471686951282 -2.63325196329452 0.00857761983914469 ** df.mm.trans3:probe13 -0.0803387036579408 0.0560471686951282 -1.43341234764146 0.152028653542192 df.mm.trans3:probe14 0.00692134692196047 0.0560471686951282 0.123491464120329 0.90174084711938 df.mm.trans3:probe15 -0.259023351220994 0.0560471686951282 -4.62152428483883 4.26732282753084e-06 *** df.mm.trans3:probe16 -0.188924608800780 0.0560471686951282 -3.37081449784638 0.000775911893951048 *** df.mm.trans3:probe17 -0.191938173524804 0.0560471686951282 -3.42458286463788 0.000638808818540702 *** df.mm.trans3:probe18 0.515279952719385 0.0560471686951282 9.19368390439632 1.89054997627777e-19 *** df.mm.trans3:probe19 -0.0197054827502915 0.0560471686951282 -0.351587479065724 0.725216048514229 df.mm.trans3:probe20 0.265991283548562 0.0560471686951282 4.745846931099 2.35429442980573e-06 *** cont.coeff: Name Estimate Std-Error t-value Pr(>|t|) Signif df.mm.(Intercept) 4.45149736454211 0.225869864882213 19.7082393743118 3.93907440002965e-74 *** df.mm.trans1 0.0922241768297932 0.192633785957092 0.478753902756891 0.632210353878206 df.mm.trans2 -0.0248807591984118 0.167793281656649 -0.148282213404257 0.882147655112333 df.mm.exp2 -0.0171068538841594 0.210367154639457 -0.0813190343971632 0.935203262048559 df.mm.exp3 0.0793545106140368 0.210367154639457 0.37721910889578 0.706084684659244 df.mm.exp4 -0.212777539518877 0.210367154639457 -1.01145799059531 0.312023196759745 df.mm.exp5 -0.0462493966658453 0.210367154639457 -0.219850844800895 0.82602875142034 df.mm.exp6 -0.0225665091162246 0.210367154639457 -0.107272017606079 0.914593051302205 df.mm.exp7 -0.332769025343951 0.210367154639457 -1.58184877251525 0.113976074715088 df.mm.exp8 -0.191163086164735 0.210367154639457 -0.908711659347981 0.363704517909229 df.mm.trans1:exp2 -0.0521334589414187 0.191259448886800 -0.272579782305420 0.785228216736591 df.mm.trans2:exp2 0.00345318007069801 0.126947793291177 0.0272015761847671 0.978303969924435 df.mm.trans1:exp3 -0.151117048426919 0.191259448886800 -0.790115465178193 0.429633304153331 df.mm.trans2:exp3 0.124787240869997 0.126947793291177 0.982980780010691 0.3258364402671 df.mm.trans1:exp4 0.113025772991239 0.191259448886800 0.590955237239732 0.554673721373359 df.mm.trans2:exp4 0.188497609156477 0.126947793291177 1.48484352716652 0.137876274710166 df.mm.trans1:exp5 -0.0369567778560209 0.191259448886800 -0.193228507512297 0.846816244932742 df.mm.trans2:exp5 0.0206192125343452 0.126947793291177 0.162422772383695 0.871003238110984 df.mm.trans1:exp6 -0.0951606449722606 0.191259448886800 -0.497547418055057 0.61890407462846 df.mm.trans2:exp6 0.0306216771416967 0.126947793291177 0.241214725737379 0.809434357696242 df.mm.trans1:exp7 0.170703279949194 0.191259448886800 0.892522073773344 0.372311433526444 df.mm.trans2:exp7 0.242115249849783 0.126947793291177 1.90720329651142 0.056758616264981 . df.mm.trans1:exp8 0.114341162600822 0.191259448886800 0.597832751617395 0.550076521253405 df.mm.trans2:exp8 0.0215900197244805 0.126947793291177 0.170070067109871 0.864986797215588 df.mm.trans1:probe2 0.0878063243443898 0.145271979910792 0.604427119381932 0.545686310211092 df.mm.trans1:probe3 0.16333501134271 0.145271979910792 1.12433940421966 0.261118206634807 df.mm.trans1:probe4 0.0946983972805932 0.145271979910792 0.651869667769004 0.514623566411104 df.mm.trans1:probe5 0.110919415839226 0.145271979910792 0.763529318643134 0.445314078967341 df.mm.trans1:probe6 0.00433300450273507 0.145271979910792 0.0298268427634556 0.976210646287436 df.mm.trans1:probe7 0.0992444458545925 0.145271979910792 0.683163029205882 0.494649948367690 df.mm.trans1:probe8 0.00265781332778593 0.145271979910792 0.0182954299199201 0.985406543150116 df.mm.trans1:probe9 0.134467265442401 0.145271979910792 0.925624236173928 0.354847501182599 df.mm.trans1:probe10 -0.0237544364171676 0.145271979910792 -0.163516986770296 0.870141907859432 df.mm.trans1:probe11 0.151026221370412 0.145271979910792 1.03961012621398 0.298753107307853 df.mm.trans1:probe12 0.055331981465065 0.145271979910792 0.380885436400352 0.703362959495344 df.mm.trans1:probe13 0.149614293889580 0.145271979910792 1.02989092584444 0.303291157740496 df.mm.trans1:probe14 0.0371021450053109 0.145271979910792 0.255397806432421 0.798464359577808 df.mm.trans1:probe15 0.0488890680634716 0.145271979910792 0.33653474051564 0.73653285566489 df.mm.trans1:probe16 0.0808609095051388 0.145271979910792 0.556617384541697 0.577903868274993 df.mm.trans1:probe17 0.0970372932491764 0.145271979910792 0.667969785424311 0.504295201091716 df.mm.trans1:probe18 0.0269965826610333 0.145271979910792 0.185834754077223 0.852609148912565 df.mm.trans1:probe19 0.085337327156182 0.145271979910792 0.587431431777729 0.557036438181209 df.mm.trans1:probe20 0.125546767280501 0.145271979910792 0.864218738930912 0.387659106335157 df.mm.trans1:probe21 0.0563624978313756 0.145271979910792 0.387979139996485 0.698107716122495 df.mm.trans1:probe22 0.0180679695584402 0.145271979910792 0.124373396504511 0.901042716299429 df.mm.trans2:probe2 0.030211449326374 0.145271979910792 0.207964738588448 0.835295600768203 df.mm.trans2:probe3 -0.137278576328945 0.145271979910792 -0.944976288016755 0.344881754426912 df.mm.trans2:probe4 0.222506991392412 0.145271979910792 1.53165800816543 0.125898889154762 df.mm.trans2:probe5 0.0369926878322009 0.145271979910792 0.254644342666199 0.799046150877516 df.mm.trans2:probe6 0.172219979483385 0.145271979910792 1.18550032559026 0.236079734049135 df.mm.trans3:probe2 -0.0577028185653295 0.145271979910792 -0.397205425304753 0.69129424775915 df.mm.trans3:probe3 0.181887243913971 0.145271979910792 1.25204629293043 0.210823324033878 df.mm.trans3:probe4 -0.000205732235032874 0.145271979910792 -0.00141618662566043 0.99887030773614 df.mm.trans3:probe5 0.198062056418144 0.145271979910792 1.36338787796359 0.173043646778713 df.mm.trans3:probe6 -0.0369661244557768 0.145271979910792 -0.254461489947868 0.799187358495808 df.mm.trans3:probe7 -0.160212410259487 0.145271979910792 -1.10284454275264 0.270339684855816 df.mm.trans3:probe8 -0.0404734746389884 0.145271979910792 -0.278604825678306 0.780601294999548 df.mm.trans3:probe9 0.114989082181703 0.145271979910792 0.791543436334492 0.428800262447067 df.mm.trans3:probe10 -0.0487381876861448 0.145271979910792 -0.335496134327307 0.737315838119975 df.mm.trans3:probe11 -0.0647813242941989 0.145271979910792 -0.445931309905597 0.655735999346245 df.mm.trans3:probe12 0.0318079033200214 0.145271979910792 0.218954153027679 0.826727017017353 df.mm.trans3:probe13 -0.152603402147835 0.145271979910792 -1.05046687077264 0.29373785751396 df.mm.trans3:probe14 0.0659715636723904 0.145271979910792 0.454124489202268 0.649830222430213 df.mm.trans3:probe15 0.00218774507516431 0.145271979910792 0.0150596493316038 0.9879873662165 df.mm.trans3:probe16 0.0235986373591029 0.145271979910792 0.162444522154887 0.870986115897222 df.mm.trans3:probe17 -0.221177038130229 0.145271979910792 -1.52250308879970 0.128174991295527 df.mm.trans3:probe18 -0.212467337547983 0.145271979910792 -1.46254864619078 0.143881048438366 df.mm.trans3:probe19 0.0464401993011104 0.145271979910792 0.319677609747098 0.749274390792638 df.mm.trans3:probe20 0.139763779435029 0.145271979910792 0.962083531324176 0.336222400049004