chrX.26016_chrX_33528543_33531705_-_1.R 

fitVsDatCorrelation=0.913760409833332
cont.fitVsDatCorrelation=0.316942463907516

fstatistic=9512.56761529999,42,462
cont.fstatistic=1736.30947087915,42,462

residuals=-0.446013372994542,-0.0805951151141592,0.0035749499373036,0.0693564783669272,0.74750945657162
cont.residuals=-0.674001761212175,-0.213280162000575,-0.0692408609420584,0.131666337558302,1.49483070946561

predictedValues:
Include	Exclude	Both
chrX.26016_chrX_33528543_33531705_-_1.R.tl.Lung	67.3115582970923	65.6888207528335	42.8384676408712
chrX.26016_chrX_33528543_33531705_-_1.R.tl.cerebhem	71.170512394154	66.3844775489091	45.8579226446465
chrX.26016_chrX_33528543_33531705_-_1.R.tl.cortex	115.773230919367	186.605589192097	53.7660344137829
chrX.26016_chrX_33528543_33531705_-_1.R.tl.heart	63.1522509102101	66.2630916073713	45.2189326182029
chrX.26016_chrX_33528543_33531705_-_1.R.tl.kidney	71.7973329677584	65.8355925631747	41.7386968543022
chrX.26016_chrX_33528543_33531705_-_1.R.tl.liver	69.6028255598573	65.9854059320975	46.4749474770545
chrX.26016_chrX_33528543_33531705_-_1.R.tl.stomach	65.2624316213792	63.1785093872041	43.4880233008870
chrX.26016_chrX_33528543_33531705_-_1.R.tl.testicle	65.2068945110282	58.5639742022651	45.6584453365017


diffExp=1.62273754425888,4.78603484524486,-70.83235827273,-3.11084069716119,5.96174040458375,3.61741962775976,2.08392223417503,6.64292030876308
diffExpScore=1.96418613342612
diffExp1.5=0,0,-1,0,0,0,0,0
diffExp1.5Score=0.5
diffExp1.4=0,0,-1,0,0,0,0,0
diffExp1.4Score=0.5
diffExp1.3=0,0,-1,0,0,0,0,0
diffExp1.3Score=0.5
diffExp1.2=0,0,-1,0,0,0,0,0
diffExp1.2Score=0.5

cont.predictedValues:
Include	Exclude	Both
Lung	55.8612946021881	54.2215190916595	54.0011970175288
cerebhem	53.1048787824096	51.2319747948134	53.5086861392372
cortex	49.4321948474986	52.108448034468	60.515832469406
heart	58.9762783274355	52.1756911773061	54.11413012873
kidney	50.45506691269	49.3644383328735	62.2718261309411
liver	50.7696921954905	50.0919022740361	54.6526635014267
stomach	48.8627241214241	48.9845306025937	55.2001250072495
testicle	51.8019259618675	52.7022497494532	53.1860344332775
cont.diffExp=1.63977551052854,1.87290398759625,-2.67625318696947,6.80058715012938,1.09062857981655,0.677789921454362,-0.121806481169550,-0.900323787585748
cont.diffExpScore=1.68171813293352

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=0.987060601819453
cont.tran.correlation=0.610737619001472

tran.covariance=0.0723061788971668
cont.tran.covariance=0.00139280704493305

tran.mean=76.7364061479249
cont.tran.mean=51.884050613013

weightedLogRatios:
wLogRatio
Lung	0.102423452563521
cerebhem	0.294491678804592
cortex	-2.38219622139681
heart	-0.200492948068624
kidney	0.366728502932728
liver	0.225020903450119
stomach	0.135072854721692
testicle	0.443088211170038

cont.weightedLogRatios:
wLogRatio
Lung	0.119413101043765
cerebhem	0.14197956285989
cortex	-0.207049818276030
heart	0.492019507945954
kidney	0.0854481974128001
liver	0.0526933817166003
stomach	-0.00968568998331821
testicle	-0.068165840822567

varWeightedLogRatios=0.86899583782146
cont.varWeightedLogRatios=0.0411693568129541

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.84751610230809	0.0721434279258708	67.1927608886153	1.33626876767802e-240	***
df.mm.trans1	-0.549650187448007	0.0579601640388832	-9.48324071476521	1.30449542773198e-19	***
df.mm.trans2	-0.578135402212853	0.0579601640388832	-9.97470265655227	2.3679024799995e-21	***
df.mm.exp2	-0.00183038473745219	0.0778225426963982	-0.0235199811524136	0.981245655174906	   
df.mm.exp3	1.35916443122214	0.0778225426963982	17.4649193425165	8.1230870531811e-53	***
df.mm.exp4	-0.109158560094574	0.0778225426963982	-1.40265990177710	0.161389896553591	   
df.mm.exp5	0.092755017693857	0.0778225426963982	1.19187852876657	0.233920751873388	   
df.mm.exp6	-0.0434988887595115	0.0778225426963982	-0.558949723979203	0.576466857863731	   
df.mm.exp7	-0.0849290650574288	0.0778225426963982	-1.09131701580035	0.275702216694095	   
df.mm.exp8	-0.210327895883736	0.0778225426963982	-2.70266029091684	0.00713206888307386	** 
df.mm.trans1:exp2	0.0575770007999476	0.06152412205658	0.935844330244933	0.349842250606132	   
df.mm.trans2:exp2	0.0123648869938172	0.06152412205658	0.200976244446787	0.84080559713491	   
df.mm.trans1:exp3	-0.816863024109167	0.06152412205658	-13.277117930394	2.63496804866443e-34	***
df.mm.trans2:exp3	-0.315095945502874	0.06152412205658	-5.12150250942385	4.45890444508624e-07	***
df.mm.trans1:exp4	0.0453750873195854	0.06152412205658	0.737517022637994	0.461182398205067	   
df.mm.trans2:exp4	0.117862859563308	0.06152412205658	1.91571786192929	0.0560179398864939	.  
df.mm.trans1:exp5	-0.0282396524288301	0.06152412205658	-0.459001306883498	0.646449097717704	   
df.mm.trans2:exp5	-0.090523160237654	0.06152412205658	-1.47134420145655	0.141878845358074	   
df.mm.trans1:exp6	0.076972087596826	0.06152412205658	1.25108794768399	0.211535555415515	   
df.mm.trans2:exp6	0.0480037290505176	0.06152412205658	0.78024240648849	0.435647759567726	   
df.mm.trans1:exp7	0.054013651242651	0.06152412205658	0.87792640410176	0.380439983808527	   
df.mm.trans2:exp7	0.0459645119980207	0.06152412205658	0.74709740605075	0.455384812292937	   
df.mm.trans1:exp8	0.178561138456606	0.06152412205658	2.90229478272594	0.00388150809920254	** 
df.mm.trans2:exp8	0.0955188736665271	0.06152412205658	1.55254346545058	0.121216969262363	   
df.mm.trans1:probe2	-0.48209647280261	0.0412716357523521	-11.6810604671790	8.44564834849496e-28	***
df.mm.trans1:probe3	-0.167722419301212	0.0412716357523521	-4.06386653312264	5.67185170954682e-05	***
df.mm.trans1:probe4	-0.00239774424335663	0.0412716357523521	-0.05809666129407	0.953696752762618	   
df.mm.trans1:probe5	-0.45299076110346	0.0412716357523521	-10.9758373479937	4.5955670441725e-25	***
df.mm.trans1:probe6	-0.222801853399502	0.0412716357523521	-5.39842556123559	1.07703715912699e-07	***
df.mm.trans2:probe2	-0.472739785310621	0.0412716357523521	-11.4543505895251	6.55010732103329e-27	***
df.mm.trans2:probe3	-0.182743531759676	0.0412716357523521	-4.42782381721474	1.18932179684935e-05	***
df.mm.trans2:probe4	-0.0976618038832859	0.0412716357523521	-2.36631774105828	0.0183776791165981	*  
df.mm.trans2:probe5	-0.334845724021276	0.0412716357523521	-8.1132166902833	4.49106400261332e-15	***
df.mm.trans2:probe6	-0.178788330803455	0.0412716357523521	-4.33199042258135	1.81404516259608e-05	***
df.mm.trans3:probe2	-0.0309357198438292	0.0412716357523521	-0.749563696226075	0.453899021665285	   
df.mm.trans3:probe3	0.0348066001120744	0.0412716357523521	0.843354024563727	0.399466900754269	   
df.mm.trans3:probe4	0.0325092738361961	0.0412716357523521	0.787690462070997	0.431281715005378	   
df.mm.trans3:probe5	0.0537652561857115	0.0412716357523521	1.30271687093593	0.193320402334404	   
df.mm.trans3:probe6	0.126559966549071	0.0412716357523521	3.06651200617504	0.00229276008605876	** 
df.mm.trans3:probe7	-0.0379123759127807	0.0412716357523521	-0.918606089186084	0.358780972918996	   
df.mm.trans3:probe8	0.0803589596049254	0.0412716357523521	1.94707474370811	0.052131338839179	.  
df.mm.trans3:probe9	0.0802017059151345	0.0412716357523521	1.94326453151457	0.0525911857053669	.  

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.96510131022023	0.168426992381699	23.5419587689027	4.14964458571485e-81	***
df.mm.trans1	0.0354019243619066	0.135314558618558	0.261626869446487	0.793725723342658	   
df.mm.trans2	-0.0283479141517322	0.135314558618558	-0.209496409264009	0.834153083950087	   
df.mm.exp2	-0.0981547340999743	0.181685528158142	-0.540245197815309	0.589288272151585	   
df.mm.exp3	-0.275919392678622	0.181685528158142	-1.51866467008015	0.129530920906704	   
df.mm.exp4	0.0137132802159148	0.181685528158142	0.0754781096487691	0.939866985452218	   
df.mm.exp5	-0.338139008845865	0.181685528158142	-1.86112241450262	0.0633618458841438	.  
df.mm.exp6	-0.186782404529374	0.181685528158142	-1.02805328758378	0.304462690827921	   
df.mm.exp7	-0.257389237375372	0.181685528158142	-1.41667440431104	0.157252063368983	   
df.mm.exp8	-0.088653761184014	0.181685528158142	-0.487951693691576	0.625815542921628	   
df.mm.trans1:exp2	0.0475518011843805	0.143635021717596	0.331059936607056	0.740749313780076	   
df.mm.trans2:exp2	0.0414407180718495	0.143635021717596	0.288514023782632	0.773082695674397	   
df.mm.trans1:exp3	0.153649586073252	0.143635021717596	1.06972230195604	0.285302882667508	   
df.mm.trans2:exp3	0.236168617805664	0.143635021717596	1.64422725726320	0.100809515749377	   
df.mm.trans1:exp4	0.0405502845099730	0.143635021717596	0.282314744865634	0.777828608462928	   
df.mm.trans2:exp4	-0.0521744409123401	0.143635021717596	-0.363243172092955	0.716589381875863	   
df.mm.trans1:exp5	0.236350448862709	0.143635021717596	1.64549318151253	0.100548268060251	   
df.mm.trans2:exp5	0.244291441142443	0.143635021717596	1.70077908730887	0.0896573999206789	.  
df.mm.trans1:exp6	0.09121023466178	0.143635021717596	0.635013895434988	0.525733710438189	   
df.mm.trans2:exp6	0.107563907438694	0.143635021717596	0.74886964301908	0.454316869178891	   
df.mm.trans1:exp7	0.123532319177320	0.143635021717596	0.86004316844258	0.390211311942321	   
df.mm.trans2:exp7	0.155815922792756	0.143635021717596	1.08480453394653	0.278573984690936	   
df.mm.trans1:exp8	0.0132093544050167	0.143635021717596	0.0919647189596136	0.926765933215164	   
df.mm.trans2:exp8	0.0602340447021003	0.143635021717596	0.419354861939783	0.675151725008929	   
df.mm.trans1:probe2	0.0570630254830446	0.0963533017530612	0.592226985944794	0.553988319186691	   
df.mm.trans1:probe3	-0.0447924369710503	0.0963533017530612	-0.464877032297726	0.642238537252577	   
df.mm.trans1:probe4	0.186993394261220	0.0963533017530611	1.94070562045145	0.0529019212054867	.  
df.mm.trans1:probe5	0.112619967297594	0.0963533017530612	1.16882312539971	0.24307762871233	   
df.mm.trans1:probe6	0.0236435724613856	0.0963533017530612	0.245384143887258	0.806267968237346	   
df.mm.trans2:probe2	0.0171916743211301	0.0963533017530612	0.178423302661591	0.858468760798877	   
df.mm.trans2:probe3	0.226300300637141	0.0963533017530612	2.34865122958748	0.0192620602104829	*  
df.mm.trans2:probe4	0.0712317605432663	0.0963533017530612	0.739276799520814	0.460114373893586	   
df.mm.trans2:probe5	0.350187119634382	0.0963533017530612	3.63440705469396	0.00030990508010156	***
df.mm.trans2:probe6	0.179956116751565	0.0963533017530612	1.86766943610054	0.0624410770403093	.  
df.mm.trans3:probe2	0.189795879558242	0.0963533017530612	1.96979113434701	0.0494592308196552	*  
df.mm.trans3:probe3	-0.00997711901556498	0.0963533017530612	-0.103547245751213	0.917573586886726	   
df.mm.trans3:probe4	-0.0813851366475646	0.0963533017530612	-0.844653324451115	0.398741603763117	   
df.mm.trans3:probe5	0.0549882174021597	0.0963533017530612	0.570693649326996	0.56848478716385	   
df.mm.trans3:probe6	0.0623231518022249	0.0963533017530612	0.646819057243618	0.518070270875682	   
df.mm.trans3:probe7	0.0040359975608124	0.0963533017530612	0.0418874858191787	0.966606488602728	   
df.mm.trans3:probe8	-0.00422058279390733	0.0963533017530612	-0.0438031984075028	0.965080202829285	   
df.mm.trans3:probe9	-0.0639023719512273	0.0963533017530612	-0.663208948614956	0.50752750765342