chr8.23226_chr8_84757413_84758079_+_1.R 

fitVsDatCorrelation=0.90674568137829
cont.fitVsDatCorrelation=0.252992239536560

fstatistic=6771.00594729107,53,715
cont.fstatistic=1275.36975430006,53,715

residuals=-0.994105808051906,-0.111594268987394,0.000426807389584791,0.113880453598657,0.638587204376316
cont.residuals=-0.867278121410603,-0.341147296172968,-0.108328827472963,0.308009846123699,1.21474065107147

predictedValues:
Include	Exclude	Both
chr8.23226_chr8_84757413_84758079_+_1.R.tl.Lung	104.172241695539	54.6707373033384	77.0686545297297
chr8.23226_chr8_84757413_84758079_+_1.R.tl.cerebhem	75.2599659687432	59.048170673212	85.9449912366322
chr8.23226_chr8_84757413_84758079_+_1.R.tl.cortex	82.027040844034	56.7151790594692	114.276396065829
chr8.23226_chr8_84757413_84758079_+_1.R.tl.heart	74.0861781614342	51.8771297107289	73.4383674653656
chr8.23226_chr8_84757413_84758079_+_1.R.tl.kidney	98.558410054752	52.2714984969395	64.2754715692188
chr8.23226_chr8_84757413_84758079_+_1.R.tl.liver	85.1385726364415	49.2069648924595	61.1016539341522
chr8.23226_chr8_84757413_84758079_+_1.R.tl.stomach	87.4673313092791	65.5691996518536	78.0691589968854
chr8.23226_chr8_84757413_84758079_+_1.R.tl.testicle	75.7844299421013	54.2487635610606	79.381426066037


diffExp=49.5015043922009,16.2117952955312,25.3118617845648,22.2090484507052,46.2869115578125,35.931607743982,21.8981316574255,21.5356663810406
diffExpScore=0.995831362388674
diffExp1.5=1,0,0,0,1,1,0,0
diffExp1.5Score=0.75
diffExp1.4=1,0,1,1,1,1,0,0
diffExp1.4Score=0.833333333333333
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	77.0697467711039	91.4206521643084	78.4834117536285
cerebhem	80.7734416140144	72.4407431153313	86.819443078177
cortex	69.0034914207265	86.7921752752885	87.9739564087287
heart	89.8883887194861	94.1554156543744	72.1201617036207
kidney	78.4261818747655	75.8951745119667	81.4909510262832
liver	89.9127015100133	78.870870592397	84.8186678651966
stomach	87.9265867164154	81.3886047039505	83.9777522108662
testicle	95.3480254209635	89.2882264834456	79.8986246987966
cont.diffExp=-14.3509053932045,8.33269849868317,-17.7886838545620,-4.26702693488822,2.53100736279885,11.0418309176162,6.53798201246494,6.05979893751783
cont.diffExpScore=24.4239216345297

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,-1,0,0,0,0,0
cont.diffExp1.2Score=0.5

tran.correlation=-0.0573602639957441
cont.tran.correlation=0.142734427593025

tran.covariance=-0.000557090070494572
cont.tran.covariance=0.00117920805285973

tran.mean=70.3813633725866
cont.tran.mean=83.6625266592844

weightedLogRatios:
wLogRatio
Lung	2.78755504065271
cerebhem	1.01881335623155
cortex	1.55814913962419
heart	1.47067945094791
kidney	2.71027752034776
liver	2.28626817981749
stomach	1.24691880302263
testicle	1.39098690212009

cont.weightedLogRatios:
wLogRatio
Lung	-0.756484982872701
cerebhem	0.472232349741072
cortex	-0.997446454408325
heart	-0.209710080308066
kidney	0.142561285247431
liver	0.580886463648462
stomach	0.34290059415991
testicle	0.297109945323252

varWeightedLogRatios=0.470015351789597
cont.varWeightedLogRatios=0.34224459728435

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.05485578515216	0.0975933106436557	41.5485012078106	7.77836832257098e-193	***
df.mm.trans1	0.387838697364308	0.0789680937914986	4.91133416982723	1.12190409163266e-06	***
df.mm.trans2	-0.055281899858198	0.0756598721693267	-0.73066340549026	0.465224122462837	   
df.mm.exp2	-0.357083215689101	0.0987101172393733	-3.61749358298471	0.000318405180233303	***
df.mm.exp3	-0.596206855119304	0.0987101172393733	-6.03997717552594	2.47777031311872e-09	***
df.mm.exp4	-0.345017155557156	0.0987101172393733	-3.49525626355488	0.000502824005466878	***
df.mm.exp5	0.0812448820091769	0.0987101172393733	0.823065398779306	0.410745226911635	   
df.mm.exp6	-0.0749012201509009	0.0987101172393733	-0.758799829699974	0.448222368023432	   
df.mm.exp7	-0.00590130901209979	0.0987101172393733	-0.0597842366835512	0.95234418585915	   
df.mm.exp8	-0.35546900650933	0.0987101172393733	-3.60114055631515	0.000338736681155197	***
df.mm.trans1:exp2	0.0319858493184003	0.0789680937914986	0.405047757678605	0.685563562300807	   
df.mm.trans2:exp2	0.434108179317643	0.0711808778227245	6.09866290773747	1.75049209057071e-09	***
df.mm.trans1:exp3	0.357210115059865	0.0789680937914987	4.52347394889656	7.12109603578826e-06	***
df.mm.trans2:exp3	0.63292013905561	0.0711808778227245	8.89171584300903	4.85958775900078e-18	***
df.mm.trans1:exp4	0.00420044157173314	0.0789680937914986	0.0531916293031419	0.957594082797972	   
df.mm.trans2:exp4	0.292566588680138	0.0711808778227245	4.11018517373126	4.41172613485977e-05	***
df.mm.trans1:exp5	-0.136641213457126	0.0789680937914986	-1.73033445403789	0.0840020217881947	.  
df.mm.trans2:exp5	-0.126122220551377	0.0711808778227245	-1.77185536915523	0.0768444125242562	.  
df.mm.trans1:exp6	-0.126864283842668	0.0789680937914986	-1.60652584799160	0.108599928236915	   
df.mm.trans2:exp6	-0.0303922027648595	0.0711808778227245	-0.426971452087892	0.669528657677228	   
df.mm.trans1:exp7	-0.168879023157956	0.0789680937914986	-2.13857287227740	0.0328085144795753	*  
df.mm.trans2:exp7	0.187678777952242	0.0711808778227245	2.63664601635926	0.00855478127385696	** 
df.mm.trans1:exp8	0.0373161689700099	0.0789680937914986	0.472547419829288	0.636680305033671	   
df.mm.trans2:exp8	0.347720607919168	0.0711808778227245	4.88502837496839	1.27700330548905e-06	***
df.mm.trans1:probe2	-0.198447631628723	0.059226070343624	-3.35068037567492	0.000848488081854617	***
df.mm.trans1:probe3	0.83582852497	0.059226070343624	14.1125102530120	4.4860356009797e-40	***
df.mm.trans1:probe4	0.93764959322853	0.059226070343624	15.8317036363949	1.28323763869454e-48	***
df.mm.trans1:probe5	0.780398723559026	0.059226070343624	13.1766081901302	1.18745177009257e-35	***
df.mm.trans1:probe6	0.832129008755621	0.059226070343624	14.0500459329429	8.96215704206608e-40	***
df.mm.trans1:probe7	0.83141995912325	0.059226070343624	14.0380740153691	1.02313083090896e-39	***
df.mm.trans1:probe8	0.861451026077754	0.059226070343624	14.5451322547604	3.55059734441092e-42	***
df.mm.trans2:probe2	-0.0529426930224911	0.059226070343624	-0.893908589837594	0.371671588831596	   
df.mm.trans2:probe3	0.120159069115635	0.059226070343624	2.02882055855612	0.0428466415733664	*  
df.mm.trans2:probe4	0.0322301246758825	0.059226070343624	0.544188133517662	0.586481673515483	   
df.mm.trans2:probe5	-0.0644021105821477	0.059226070343624	-1.08739462551699	0.277228866739811	   
df.mm.trans2:probe6	0.00706874475352083	0.059226070343624	0.119351912299915	0.905030082885187	   
df.mm.trans3:probe2	-0.219225544114779	0.059226070343624	-3.70150413226563	0.000230806055305106	***
df.mm.trans3:probe3	-0.558103254218635	0.059226070343624	-9.42327003936904	5.92435974425383e-20	***
df.mm.trans3:probe4	-0.162028083842873	0.059226070343624	-2.73575611048988	0.00637806521884073	** 
df.mm.trans3:probe5	-0.360475715471596	0.059226070343624	-6.08643648616479	1.88235337521211e-09	***
df.mm.trans3:probe6	-0.118465536165256	0.059226070343624	-2.00022617536382	0.0458535957887714	*  
df.mm.trans3:probe7	-0.465685578104078	0.059226070343624	-7.86284782026252	1.38505213262104e-14	***
df.mm.trans3:probe8	0.27097705100664	0.059226070343624	4.5753001918658	5.60548330551792e-06	***
df.mm.trans3:probe9	0.389843640329367	0.059226070343624	6.58229793176437	8.96363519612057e-11	***
df.mm.trans3:probe10	-0.204701482061867	0.059226070343624	-3.45627324038567	0.000580073278450236	***
df.mm.trans3:probe11	-0.00212015999574712	0.059226070343624	-0.0357977489211449	0.971453619538025	   
df.mm.trans3:probe12	0.343992874509457	0.059226070343624	5.80813267727613	9.50563085112556e-09	***
df.mm.trans3:probe13	-0.0533423639103065	0.059226070343624	-0.90065681550066	0.368074071817202	   
df.mm.trans3:probe14	0.177228902459162	0.059226070343624	2.99241366902948	0.00286310460419303	** 
df.mm.trans3:probe15	0.0674156211146947	0.059226070343624	1.13827611258954	0.255386462199801	   
df.mm.trans3:probe16	0.156972438719589	0.059226070343624	2.65039429104194	0.00821761498288001	** 
df.mm.trans3:probe17	0.0502876683350101	0.059226070343624	0.849079941371187	0.396120997834921	   
df.mm.trans3:probe18	-0.081457412807635	0.059226070343624	-1.37536413162357	0.169449329782608	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.47016499092944	0.223911261039016	19.9640025704224	8.14253600721182e-71	***
df.mm.trans1	-0.130030506881548	0.181178867138382	-0.717691356256426	0.473182027134562	   
df.mm.trans2	0.0452087265688582	0.17358871500263	0.260435861675532	0.794602567218768	   
df.mm.exp2	-0.286708418720979	0.226473583922978	-1.26596847965494	0.205936691198628	   
df.mm.exp3	-0.276662179614146	0.226473583922978	-1.22160904959334	0.222258122778012	   
df.mm.exp4	0.267886976462854	0.226473583922978	1.18286191185088	0.237257048594276	   
df.mm.exp5	-0.206275987637043	0.226473583922978	-0.910816988294741	0.362698764225622	   
df.mm.exp6	-0.0711594099109814	0.226473583922978	-0.314206225195705	0.753456070300518	   
df.mm.exp7	-0.0521093462887096	0.226473583922978	-0.230090173812199	0.818087511642133	   
df.mm.exp8	0.171349686680823	0.226473583922978	0.756598998049583	0.449539364690963	   
df.mm.trans1:exp2	0.333645823236276	0.181178867138382	1.84152726256667	0.0659583646215514	.  
df.mm.trans2:exp2	0.0540059034458248	0.163312423874479	0.330690722509474	0.740974991597584	   
df.mm.trans1:exp3	0.166108469147096	0.181178867138382	0.916820332142957	0.359545925859212	   
df.mm.trans2:exp3	0.224707244024881	0.163312423874479	1.37593478006052	0.169272647170115	   
df.mm.trans1:exp4	-0.114029015147928	0.181178867138382	-0.629372602605102	0.529306189120267	   
df.mm.trans2:exp4	-0.238411608053364	0.163312423874479	-1.45984979217874	0.144770577449935	   
df.mm.trans1:exp5	0.223722997643398	0.181178867138382	1.23481839343063	0.217303735793292	   
df.mm.trans2:exp5	0.0201576865060314	0.163312423874479	0.123430208356497	0.901801124971112	   
df.mm.trans1:exp6	0.225287812196476	0.181178867138382	1.24345524262718	0.214107674977375	   
df.mm.trans2:exp6	-0.076500031012852	0.163312423874479	-0.468427503541614	0.639621671983717	   
df.mm.trans1:exp7	0.183900756650066	0.181178867138382	1.01502321741313	0.310438104804181	   
df.mm.trans2:exp7	-0.0641267884485217	0.163312423874479	-0.392663258110781	0.694685242595342	   
df.mm.trans1:exp8	0.0414731223195285	0.181178867138382	0.228907062808003	0.819006607998147	   
df.mm.trans2:exp8	-0.194951456375034	0.163312423874479	-1.19373316340509	0.232978271996993	   
df.mm.trans1:probe2	0.00235538313577386	0.135884150353787	0.0173337591591176	0.986175189393253	   
df.mm.trans1:probe3	-0.0928012097856074	0.135884150353787	-0.682943592346797	0.494863705398797	   
df.mm.trans1:probe4	-0.0330629250315097	0.135884150353787	-0.243317008977334	0.807829618573168	   
df.mm.trans1:probe5	0.062894189524237	0.135884150353787	0.462851549356465	0.643611611970119	   
df.mm.trans1:probe6	0.0339488299157396	0.135884150353787	0.249836569072631	0.802785499847053	   
df.mm.trans1:probe7	-0.0663173091095791	0.135884150353787	-0.488043005287342	0.625669004781971	   
df.mm.trans1:probe8	0.202814962230576	0.135884150353787	1.49255790099528	0.135994046854980	   
df.mm.trans2:probe2	-0.0558859428959333	0.135884150353787	-0.411276390590287	0.680993121763504	   
df.mm.trans2:probe3	0.0232053533394101	0.135884150353787	0.170773068669105	0.864450519431437	   
df.mm.trans2:probe4	-0.112717000280857	0.135884150353787	-0.829508077192137	0.407093816208714	   
df.mm.trans2:probe5	0.239013428802169	0.135884150353787	1.75895001867308	0.0790137114590888	.  
df.mm.trans2:probe6	-0.0912713006664227	0.135884150353787	-0.671684669836693	0.502001420455334	   
df.mm.trans3:probe2	0.0134644324722864	0.135884150353787	0.0990875862801554	0.921096501622329	   
df.mm.trans3:probe3	-0.0117717554435979	0.135884150353787	-0.0866308205405054	0.930989220970662	   
df.mm.trans3:probe4	0.0625528843982775	0.135884150353787	0.460339813255743	0.645412292352729	   
df.mm.trans3:probe5	0.013738632093382	0.135884150353787	0.101105478877501	0.919495073355454	   
df.mm.trans3:probe6	0.00562236378012745	0.135884150353787	0.0413761558319283	0.967007572392713	   
df.mm.trans3:probe7	0.145241026509374	0.135884150353787	1.06885921670207	0.285493828810074	   
df.mm.trans3:probe8	-0.085802547903311	0.135884150353787	-0.631438969739416	0.527955354566669	   
df.mm.trans3:probe9	-0.0894930100676058	0.135884150353787	-0.658597855854437	0.510366056784575	   
df.mm.trans3:probe10	0.145981686813410	0.135884150353787	1.07430989142835	0.283046223676595	   
df.mm.trans3:probe11	-0.0547854227138133	0.135884150353787	-0.403177431445643	0.686938231868962	   
df.mm.trans3:probe12	-0.0383256662915744	0.135884150353787	-0.282046627158429	0.777989375119908	   
df.mm.trans3:probe13	-0.0402158892132667	0.135884150353787	-0.295957174612058	0.767348721109829	   
df.mm.trans3:probe14	-0.144714546270454	0.135884150353787	-1.06498473805574	0.287242342550121	   
df.mm.trans3:probe15	-0.153901978001751	0.135884150353787	-1.13259697765379	0.257763202548506	   
df.mm.trans3:probe16	-0.0461133480032088	0.135884150353787	-0.33935781239496	0.734439846252123	   
df.mm.trans3:probe17	-0.094870285874567	0.135884150353787	-0.698170357819978	0.485297655451057	   
df.mm.trans3:probe18	-0.0308131974656733	0.135884150353787	-0.226760791346514	0.820674568197642