chr3.15344_chr3_117239716_117241570_+_2.R 

fitVsDatCorrelation=0.813019135136798
cont.fitVsDatCorrelation=0.268680145069572

fstatistic=7872.23023772188,52,692
cont.fstatistic=2867.87879631629,52,692

residuals=-0.716425391189964,-0.102753336597896,-0.00724439408379177,0.0939879494345272,0.748494283055099
cont.residuals=-0.74195303520164,-0.200457975989027,-0.0305978359411362,0.158442128762184,1.19452092022991

predictedValues:
Include	Exclude	Both
chr3.15344_chr3_117239716_117241570_+_2.R.tl.Lung	60.3226117829266	73.13913949246	62.9528160768285
chr3.15344_chr3_117239716_117241570_+_2.R.tl.cerebhem	67.7533343525924	70.2019918060978	85.939538692172
chr3.15344_chr3_117239716_117241570_+_2.R.tl.cortex	58.9150294228639	66.7773410397164	57.2638533395269
chr3.15344_chr3_117239716_117241570_+_2.R.tl.heart	60.3994527469965	68.8426456298266	63.7584157760803
chr3.15344_chr3_117239716_117241570_+_2.R.tl.kidney	68.8758688531965	83.0477070511658	77.2852819302421
chr3.15344_chr3_117239716_117241570_+_2.R.tl.liver	64.3657078332384	90.8662177444535	65.5325787942961
chr3.15344_chr3_117239716_117241570_+_2.R.tl.stomach	72.1663639345155	82.744067875282	65.3829015667945
chr3.15344_chr3_117239716_117241570_+_2.R.tl.testicle	88.9657872021471	81.9275993468766	101.710081077036


diffExp=-12.8165277095334,-2.44865745350532,-7.86231161685253,-8.4431928828301,-14.1718381979693,-26.5005099112151,-10.5777039407665,7.03818785527048
diffExpScore=1.17030399555120
diffExp1.5=0,0,0,0,0,0,0,0
diffExp1.5Score=0
diffExp1.4=0,0,0,0,0,-1,0,0
diffExp1.4Score=0.5
diffExp1.3=0,0,0,0,0,-1,0,0
diffExp1.3Score=0.5
diffExp1.2=-1,0,0,0,-1,-1,0,0
diffExp1.2Score=0.75

cont.predictedValues:
Include	Exclude	Both
Lung	71.0495231694927	75.7566150645938	61.1831885856339
cerebhem	78.0583847050825	62.1929088599615	73.5202577713684
cortex	71.183739905503	75.9101976932162	66.2276250790836
heart	66.798739947618	64.918979510533	66.5915921133293
kidney	72.8583153235137	79.3236144567518	82.1513329219349
liver	70.7239609317733	77.7202066958616	65.4927070845481
stomach	74.9829473530569	71.7096877363714	72.7538294604562
testicle	75.9747173371172	72.871367693184	66.9562000537353
cont.diffExp=-4.70709189510109,15.8654758451210,-4.72645778771319,1.87976043708505,-6.4652991332381,-6.99624576408837,3.27325961668551,3.10334964393321
cont.diffExpScore=21.1145929252429

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

tran.correlation=0.456371346786753
cont.tran.correlation=-0.203346259224373

tran.covariance=0.00753341085264395
cont.tran.covariance=-0.000769622245525129

tran.mean=72.4569291321472
cont.tran.mean=72.6271191489769

weightedLogRatios:
wLogRatio
Lung	-0.80839400965927
cerebhem	-0.150306436432888
cortex	-0.518448737268899
heart	-0.545145991267482
kidney	-0.809408930990948
liver	-1.49542390520579
stomach	-0.594624775527082
testicle	0.366507391995849

cont.weightedLogRatios:
wLogRatio
Lung	-0.275547303943864
cerebhem	0.964270743548982
cortex	-0.276265783588770
heart	0.119526303781726
kidney	-0.368220394893231
liver	-0.406183946831017
stomach	0.191704216799665
testicle	0.179728923176087

varWeightedLogRatios=0.289660762170452
cont.varWeightedLogRatios=0.209128259718399

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.25654888020693	0.0932499058584718	45.6466828681546	6.57593805507784e-211	***
df.mm.trans1	-0.399026225984131	0.0827072871931865	-4.82455947384771	1.72707884155500e-06	***
df.mm.trans2	-0.0206612199650633	0.0753730015490143	-0.274119638868667	0.784074487034689	   
df.mm.exp2	-0.236078826888078	0.101662560830670	-2.32218060374550	0.0205125042167471	*  
df.mm.exp3	-0.0198947236732462	0.101662560830670	-0.195693709765811	0.844907356162377	   
df.mm.exp4	-0.0719829152629363	0.101662560830670	-0.708057269802911	0.479148110562968	   
df.mm.exp5	0.0545323988495753	0.101662560830670	0.536405913878219	0.591850435116671	   
df.mm.exp6	0.241736714835488	0.101662560830670	2.37783420819123	0.0176852967488402	*  
df.mm.exp7	0.264780433528882	0.101662560830670	2.60450289039939	0.00939827772606328	** 
df.mm.exp8	0.0222762066786239	0.101662560830670	0.219119078809429	0.826621901207361	   
df.mm.trans1:exp2	0.352245479422354	0.0963080886467388	3.65748593261363	0.000274039015793658	***
df.mm.trans2:exp2	0.195091863382641	0.0813951908845625	2.39684754421582	0.0168010952049895	*  
df.mm.trans1:exp3	-0.00371607130038109	0.0963080886467388	-0.0385852460846956	0.969232194023158	   
df.mm.trans2:exp3	-0.0711051067607119	0.0813951908845625	-0.873578721150193	0.382650763602326	   
df.mm.trans1:exp4	0.0732559381315622	0.0963080886467388	0.760641594708284	0.44713026192902	   
df.mm.trans2:exp4	0.0114426700048340	0.0813951908845624	0.140581647152378	0.888241357802912	   
df.mm.trans1:exp5	0.0780664619214704	0.0963080886467388	0.810590917319736	0.417879311771911	   
df.mm.trans2:exp5	0.0725191801301769	0.0813951908845625	0.890951656259719	0.373264767031326	   
df.mm.trans1:exp6	-0.176862732159186	0.0963080886467388	-1.83642656234124	0.066723384493916	.  
df.mm.trans2:exp6	-0.0247120721441803	0.0813951908845624	-0.30360604693744	0.761519303408032	   
df.mm.trans1:exp7	-0.085513391216942	0.0963080886467388	-0.887914944824706	0.374895013666056	   
df.mm.trans2:exp7	-0.141391756590061	0.0813951908845624	-1.73710209477348	0.0828141047087342	.  
df.mm.trans1:exp8	0.366268654137792	0.0963080886467388	3.80309337755915	0.000155524081903790	***
df.mm.trans2:exp8	0.0911960683340037	0.0813951908845624	1.12041101375806	0.262927343828877	   
df.mm.trans1:probe2	0.0128925601371695	0.052750112622026	0.244408201164412	0.806987139952205	   
df.mm.trans1:probe3	0.637002368271776	0.052750112622026	12.0758484979195	1.33024026034723e-30	***
df.mm.trans1:probe4	0.0595806198946614	0.052750112622026	1.12948801306982	0.259083393432095	   
df.mm.trans1:probe5	0.211946220908984	0.052750112622026	4.01792925879907	6.5147135670542e-05	***
df.mm.trans1:probe6	0.112302380574229	0.052750112622026	2.12895053663519	0.0336108597483634	*  
df.mm.trans1:probe7	0.203206241092777	0.052750112622026	3.85224279138178	0.000127911699745684	***
df.mm.trans1:probe8	0.0774213529955464	0.052750112622026	1.46770024076155	0.142640016267643	   
df.mm.trans1:probe9	0.0311817794271109	0.052750112622026	0.591122518553463	0.554631359474975	   
df.mm.trans1:probe10	0.479212444049926	0.052750112622026	9.08457670002829	1.07749010290698e-18	***
df.mm.trans1:probe11	0.426706944634672	0.052750112622026	8.08921390731778	2.69307310248784e-15	***
df.mm.trans1:probe12	0.336561904163991	0.052750112622026	6.38030683603617	3.23474335185795e-10	***
df.mm.trans1:probe13	0.585009825343319	0.052750112622026	11.0902099780361	2.02500550667002e-26	***
df.mm.trans1:probe14	0.335852133300199	0.052750112622026	6.36685149293809	3.51434916222458e-10	***
df.mm.trans1:probe15	0.529734094194322	0.052750112622026	10.0423310560503	3.03536227316193e-22	***
df.mm.trans1:probe16	0.473679593714388	0.052750112622026	8.9796887659459	2.54011093213927e-18	***
df.mm.trans1:probe17	0.319248119623134	0.052750112622026	6.05208413317833	2.34264410122865e-09	***
df.mm.trans1:probe18	0.240052584171506	0.052750112622026	4.55075017358865	6.31329000358878e-06	***
df.mm.trans1:probe19	0.179775773660638	0.052750112622026	3.40806426232295	0.00069215489511386	***
df.mm.trans1:probe20	0.538011213854653	0.052750112622026	10.1992429420900	7.51119731115225e-23	***
df.mm.trans1:probe21	0.265231029189677	0.052750112622026	5.02806564774856	6.31799279114456e-07	***
df.mm.trans2:probe2	0.0934282125784246	0.052750112622026	1.77114716792876	0.0769763395012592	.  
df.mm.trans2:probe3	0.286844606282465	0.052750112622026	5.43780083158898	7.48671455000919e-08	***
df.mm.trans2:probe4	-0.105080059710798	0.052750112622026	-1.99203479362661	0.0467597684299307	*  
df.mm.trans2:probe5	0.0257675765372763	0.052750112622026	0.488483820345759	0.625361940150063	   
df.mm.trans2:probe6	0.263799536303178	0.052750112622026	5.00092839978179	7.23962351307e-07	***
df.mm.trans3:probe2	0.734597548591613	0.052750112622026	13.9259901463202	4.84584874395877e-39	***
df.mm.trans3:probe3	0.425922174363079	0.052750112622026	8.07433677753388	3.01071220412698e-15	***
df.mm.trans3:probe4	0.0615765185185395	0.052750112622026	1.16732487302459	0.243481266974054	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.50555224041079	0.154268898931424	29.2058365076788	8.3086053117114e-123	***
df.mm.trans1	-0.257083862413346	0.136827614048886	-1.87888873309956	0.060679789340047	.  
df.mm.trans2	-0.171586645260172	0.124694066455902	-1.37606102789866	0.169247891981395	   
df.mm.exp2	-0.286893383871695	0.168186457428701	-1.70580549859858	0.0884930299213466	.  
df.mm.exp3	-0.075312676623628	0.168186457428701	-0.447792752014858	0.654442922134887	   
df.mm.exp4	-0.300784540405969	0.168186457428701	-1.78839928615227	0.0741489804696995	.  
df.mm.exp5	-0.223540985973119	0.168186457428701	-1.32912595574399	0.184244458095053	   
df.mm.exp6	-0.0470695408274368	0.168186457428701	-0.279865225459017	0.779664541213033	   
df.mm.exp7	-0.174225426905660	0.168186457428701	-1.03590639561166	0.300607667730113	   
df.mm.exp8	-0.0619727123148294	0.168186457428701	-0.368476233237157	0.712630858634838	   
df.mm.trans1:exp2	0.380973309094401	0.159328233706442	2.39112240330445	0.0170631546897018	*  
df.mm.trans2:exp2	0.0896086034888098	0.134656934615379	0.665458513107839	0.505979006462338	   
df.mm.trans1:exp3	0.0771999535228073	0.159328233706442	0.484534044763504	0.628160232668165	   
df.mm.trans2:exp3	0.077337940797451	0.134656934615379	0.574333145324832	0.565929026578197	   
df.mm.trans1:exp4	0.239091614386903	0.159328233706442	1.50062301467185	0.133909202096069	   
df.mm.trans2:exp4	0.146398795582126	0.134656934615379	1.08719833850581	0.277327698867306	   
df.mm.trans1:exp5	0.248680511858223	0.159328233706442	1.56080630578262	0.119026645315533	   
df.mm.trans2:exp5	0.269551088462197	0.134656934615379	2.00176165625718	0.0457002665496841	*  
df.mm.trans1:exp6	0.0424768229148927	0.159328233706442	0.266599471586153	0.78985698374785	   
df.mm.trans2:exp6	0.0726590566649408	0.134656934615379	0.539586445157666	0.589655842239752	   
df.mm.trans1:exp7	0.228109002639751	0.159328233706442	1.43169228286329	0.152683394242047	   
df.mm.trans2:exp7	0.119325512094682	0.134656934615379	0.886144574993572	0.375847461652916	   
df.mm.trans1:exp8	0.128996187314321	0.159328233706442	0.809625414865218	0.418433796865619	   
df.mm.trans2:exp8	0.0231427446060619	0.134656934615379	0.171864484158685	0.863594315364645	   
df.mm.trans1:probe2	-0.0490334931094068	0.0872676676484734	-0.561874683152078	0.574383337960703	   
df.mm.trans1:probe3	0.0886315563484751	0.0872676676484734	1.01562879743155	0.310161146558377	   
df.mm.trans1:probe4	-0.0595110595152898	0.0872676676484734	-0.681937092154322	0.49550690518401	   
df.mm.trans1:probe5	0.0354975265862235	0.0872676676484734	0.406766074340529	0.68430558176114	   
df.mm.trans1:probe6	-0.025384429997582	0.0872676676484734	-0.290880124123795	0.771230160593048	   
df.mm.trans1:probe7	0.134338907859922	0.0872676676484734	1.53938923177205	0.124166418390896	   
df.mm.trans1:probe8	0.0163823945926294	0.0872676676484734	0.187725821418994	0.851146618425199	   
df.mm.trans1:probe9	0.108022693681647	0.0872676676484734	1.23783179489543	0.216198244683513	   
df.mm.trans1:probe10	0.0263403135052039	0.0872676676484734	0.301833591007685	0.762869608488963	   
df.mm.trans1:probe11	-0.0339489088551898	0.0872676676484734	-0.389020467373333	0.697380679232732	   
df.mm.trans1:probe12	0.00816508901945329	0.0872676676484734	0.093563736025849	0.925482800042112	   
df.mm.trans1:probe13	0.00244145033649029	0.0872676676484734	0.0279765737102635	0.977688901330952	   
df.mm.trans1:probe14	-0.0702202268390679	0.0872676676484734	-0.804653415534434	0.421296066182254	   
df.mm.trans1:probe15	0.0287098365858418	0.0872676676484734	0.328985950460932	0.742265846608532	   
df.mm.trans1:probe16	-0.061213703395494	0.0872676676484734	-0.701447684405541	0.483259494518916	   
df.mm.trans1:probe17	0.0642731671548832	0.0872676676484734	0.73650607248706	0.461672373960571	   
df.mm.trans1:probe18	0.087250130141636	0.0872676676484734	0.999799037750064	0.317757243683820	   
df.mm.trans1:probe19	0.0564673451390209	0.0872676676484734	0.647059176217238	0.517808218247207	   
df.mm.trans1:probe20	0.0135581745583531	0.0872676676484734	0.155363090634751	0.87658038653294	   
df.mm.trans1:probe21	0.00195236936981913	0.0872676676484734	0.0223721960541395	0.982157508434011	   
df.mm.trans2:probe2	0.0333762672966195	0.0872676676484734	0.382458569089572	0.702238688759702	   
df.mm.trans2:probe3	0.00512425486860883	0.0872676676484734	0.0587188245851838	0.953193017268367	   
df.mm.trans2:probe4	0.0232832876509108	0.0872676676484734	0.266803138874975	0.789700223000238	   
df.mm.trans2:probe5	-0.0989515879099706	0.0872676676484734	-1.13388601501947	0.257235017251977	   
df.mm.trans2:probe6	-0.0272304917918954	0.0872676676484734	-0.312034141918215	0.755108570265783	   
df.mm.trans3:probe2	0.0682505551912566	0.0872676676484734	0.782082952717145	0.434433340641438	   
df.mm.trans3:probe3	-0.000333364894318273	0.0872676676484734	-0.00382002754629715	0.996953167356703	   
df.mm.trans3:probe4	0.0800457006306412	0.0872676676484734	0.91724349679055	0.359334617062875