chr10.2324_chr10_59867131_59869994_+_2.R 

fitVsDatCorrelation=0.914794685976301
cont.fitVsDatCorrelation=0.293456292166426

fstatistic=11950.0102517478,43,485
cont.fstatistic=2124.10549537735,43,485

residuals=-0.463169481997669,-0.0860658862365574,0.00254870423399316,0.0820199779949687,0.434428238896324
cont.residuals=-0.54653023954575,-0.232870576372207,-0.0560255062820256,0.198674985463889,1.00002543657187

predictedValues:
Include	Exclude	Both
chr10.2324_chr10_59867131_59869994_+_2.R.tl.Lung	64.9749916659293	48.6775485366887	92.2624403985055
chr10.2324_chr10_59867131_59869994_+_2.R.tl.cerebhem	60.4514590164555	50.0377601817105	69.3784838437008
chr10.2324_chr10_59867131_59869994_+_2.R.tl.cortex	75.1832276303375	47.7110921864065	92.5832672808468
chr10.2324_chr10_59867131_59869994_+_2.R.tl.heart	69.9311752697134	46.564140469506	89.4145195880543
chr10.2324_chr10_59867131_59869994_+_2.R.tl.kidney	70.7915306063958	48.7776332935852	101.287673323083
chr10.2324_chr10_59867131_59869994_+_2.R.tl.liver	63.5083678739634	48.3220153298668	81.8177687034454
chr10.2324_chr10_59867131_59869994_+_2.R.tl.stomach	65.6691752397893	49.1513869044469	80.4922152831864
chr10.2324_chr10_59867131_59869994_+_2.R.tl.testicle	77.5706086252699	49.4627845539894	97.916648118544


diffExp=16.2974431292406,10.4136988347450,27.4721354439310,23.3670348002074,22.0138973128105,15.1863525440966,16.5177883353425,28.1078240712805
diffExpScore=0.993764659848669
diffExp1.5=0,0,1,1,0,0,0,1
diffExp1.5Score=0.75
diffExp1.4=0,0,1,1,1,0,0,1
diffExp1.4Score=0.8
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	60.6156330913005	65.5212637224742	70.4690649261882
cerebhem	66.3310024062603	61.8989140986258	52.0619326134094
cortex	60.3523094281933	63.2393864714664	62.9591389247328
heart	62.8867409600671	59.053085268992	56.3064441410545
kidney	67.4935985384957	59.6592224714108	65.9699600397616
liver	63.0412418811457	57.8036888844322	59.2022900040089
stomach	67.0624206997003	56.1975802623418	67.0336891028553
testicle	71.5482208341693	62.3518756496157	60.6809265602453
cont.diffExp=-4.90563063117366,4.43208830763447,-2.88707704327309,3.83365569107507,7.83437606708494,5.23755299671343,10.8648404373585,9.19634518455368
cont.diffExpScore=1.42146886964372

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=-0.282961643906774
cont.tran.correlation=-0.279648115643854

tran.covariance=-0.000582414876569189
cont.tran.covariance=-0.000868179931305173

tran.mean=58.5490560865034
cont.tran.mean=62.8160115417932

weightedLogRatios:
wLogRatio
Lung	1.16368913897708
cerebhem	0.757633074719153
cortex	1.86114366252183
heart	1.64468683793972
kidney	1.51724843754337
liver	1.09710833314838
stomach	1.1704198872726
testicle	1.85666019166270

cont.weightedLogRatios:
wLogRatio
Lung	-0.322452204544655
cerebhem	0.287689331492314
cortex	-0.192686262662062
heart	0.258505899991095
kidney	0.512085687186082
liver	0.35565636013773
stomach	0.72772428713466
testicle	0.578044862689114

varWeightedLogRatios=0.157940106399675
cont.varWeightedLogRatios=0.133660083377995

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.43043383767158	0.072185377413328	47.5225587313781	1.28351500160189e-184	***
df.mm.trans1	0.821286984693777	0.0638104350143368	12.8707316367496	8.09162352525493e-33	***
df.mm.trans2	0.498446171890731	0.0600557863103526	8.29971935285122	1.04346333470501e-15	***
df.mm.exp2	0.240458617078726	0.0826664537373791	2.90878108600899	0.00379493218440956	** 
df.mm.exp3	0.122400423012724	0.0826664537373791	1.48065409218562	0.139348085283417	   
df.mm.exp4	0.0604759632563362	0.0826664537373791	0.731565955985734	0.464786849610523	   
df.mm.exp5	-0.0055367072790919	0.0826664537373791	-0.0669764702460968	0.946628035703623	   
df.mm.exp6	0.0899812628895477	0.0826664537373791	1.08848582250071	0.276921274074962	   
df.mm.exp7	0.156790998476877	0.0826664537373791	1.89667018951826	0.0584653729082765	.  
df.mm.exp8	0.133709341591249	0.082666453737379	1.61745587897150	0.106430071031451	   
df.mm.trans1:exp2	-0.312620356649417	0.0769582802370588	-4.06220559615463	5.6684225162906e-05	***
df.mm.trans2:exp2	-0.212898601153545	0.0697104746397485	-3.05404033258657	0.00238198050095882	** 
df.mm.trans1:exp3	0.0235252939742991	0.0769582802370588	0.305688925244078	0.759972666844474	   
df.mm.trans2:exp3	-0.142454419670680	0.0697104746397485	-2.04351527380727	0.0415412514624607	*  
df.mm.trans1:exp4	0.0130331324301824	0.0769582802370588	0.169353218263659	0.865589428931432	   
df.mm.trans2:exp4	-0.104863144291717	0.0697104746397485	-1.50426668063345	0.133163615515580	   
df.mm.trans1:exp5	0.09127362435803	0.0769582802370588	1.18601434539435	0.236197333062400	   
df.mm.trans2:exp5	0.00759067280874649	0.0697104746397485	0.108888554381157	0.913335920111304	   
df.mm.trans1:exp6	-0.112812040391809	0.0769582802370588	-1.46588567265676	0.143327446862605	   
df.mm.trans2:exp6	-0.097311910261491	0.0697104746397485	-1.39594387736394	0.163370053705223	   
df.mm.trans1:exp7	-0.146163809777244	0.0769582802370588	-1.89926034374738	0.0581233127982177	.  
df.mm.trans2:exp7	-0.147103842604828	0.0697104746397485	-2.11021146197949	0.0353516262768269	*  
df.mm.trans1:exp8	0.0434768067614616	0.0769582802370588	0.564939947040626	0.572375818813685	   
df.mm.trans2:exp8	-0.117706690086939	0.0697104746397484	-1.68850794224579	0.0919565661640911	.  
df.mm.trans1:probe2	0.112196247213629	0.0384791401185294	2.91576804647985	0.00371243026950114	** 
df.mm.trans1:probe3	0.300794260485471	0.0384791401185294	7.81707334308714	3.39013829756156e-14	***
df.mm.trans1:probe4	0.177413437587775	0.0384791401185294	4.61063935008107	5.14123902706849e-06	***
df.mm.trans1:probe5	0.0334080845351482	0.0384791401185294	0.86821286630209	0.385707207377892	   
df.mm.trans1:probe6	0.176691858677737	0.0384791401185294	4.59188688035812	5.60444263969922e-06	***
df.mm.trans1:probe7	-0.330672649375891	0.0384791401185294	-8.5935561022752	1.16431215948977e-16	***
df.mm.trans1:probe8	-0.324934063694702	0.0384791401185294	-8.44442112515481	3.56803015203775e-16	***
df.mm.trans1:probe9	-0.292395141357993	0.0384791401185294	-7.59879613882515	1.55498495802983e-13	***
df.mm.trans1:probe10	-0.306997148399626	0.0384791401185294	-7.97827465618946	1.07826970821954e-14	***
df.mm.trans1:probe11	-0.209890631664685	0.0384791401185294	-5.45466013580727	7.83368439960368e-08	***
df.mm.trans1:probe12	-0.172657922716511	0.0384791401185294	-4.48705252208504	9.02843134976519e-06	***
df.mm.trans1:probe13	-0.406450252948170	0.0384791401185294	-10.5628725511059	1.29666078184544e-23	***
df.mm.trans2:probe2	-0.0867980138809855	0.0384791401185294	-2.25571604806180	0.0245331989557893	*  
df.mm.trans2:probe3	0.0193610398072198	0.0384791401185294	0.503156768773442	0.615082478204262	   
df.mm.trans2:probe4	-0.116057597123982	0.0384791401185294	-3.01611722004398	0.00269473575483093	** 
df.mm.trans2:probe5	-0.147392041035830	0.0384791401185294	-3.83044009252313	0.000144707036617617	***
df.mm.trans2:probe6	-0.0620723007975621	0.0384791401185294	-1.61314157765369	0.107364190284322	   
df.mm.trans3:probe2	-0.543252876203361	0.0384791401185294	-14.1181137242140	3.68457990291252e-38	***
df.mm.trans3:probe3	-0.133336719274388	0.0384791401185294	-3.46516889056419	0.000576932288898556	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.03115506353107	0.170844176396263	23.5955076056033	1.51025004608384e-82	***
df.mm.trans1	0.0654827190172558	0.151022847093944	0.433594785671881	0.66477551199706	   
df.mm.trans2	0.14592338647831	0.142136561692726	1.02664215836155	0.305100743751235	   
df.mm.exp2	0.335972270446359	0.19565018166345	1.71720909017240	0.0865793637806116	.  
df.mm.exp3	0.0728868568833237	0.19565018166345	0.372536617465047	0.709656091035288	   
df.mm.exp4	0.157209405867034	0.19565018166345	0.80352292305795	0.422066178768167	   
df.mm.exp5	0.0797282753473736	0.19565018166345	0.407504223453874	0.683817498427188	   
df.mm.exp6	0.0881277763705661	0.19565018166345	0.450435443613133	0.652597776047229	   
df.mm.exp7	-0.00245151780570674	0.19565018166345	-0.0125301074850201	0.99000783475936	   
df.mm.exp8	0.265782229524607	0.19565018166345	1.35845633908889	0.174950434012170	   
df.mm.trans1:exp2	-0.245867706221406	0.182140406757028	-1.34988007657954	0.177684118356398	   
df.mm.trans2:exp2	-0.392844360685232	0.164986719648590	-2.38106655809608	0.017647630503064	*  
df.mm.trans1:exp3	-0.0772404744375616	0.182140406757028	-0.424071054923025	0.671702020048447	   
df.mm.trans2:exp3	-0.108334273121189	0.164986719648590	-0.656624201947483	0.511734009616843	   
df.mm.trans1:exp4	-0.120426891538470	0.182140406757028	-0.66117614253007	0.50881331536637	   
df.mm.trans2:exp4	-0.261147343114463	0.164986719648590	-1.58283856828409	0.114110105837741	   
df.mm.trans1:exp5	0.0277516499572148	0.182140406757028	0.152364049533693	0.87896317283435	   
df.mm.trans2:exp5	-0.173454255949627	0.164986719648590	-1.05132253262003	0.293634015409744	   
df.mm.trans1:exp6	-0.048891462733616	0.182140406757028	-0.268427328148204	0.788484540755116	   
df.mm.trans2:exp6	-0.213449908141132	0.164986719648590	-1.29373993613404	0.196371036591371	   
df.mm.trans1:exp7	0.103522524102521	0.182140406757028	0.568366602148958	0.570049117106107	   
df.mm.trans2:exp7	-0.151049508994155	0.16498671964859	-0.915525257523025	0.360370914404902	   
df.mm.trans1:exp8	-0.0999634214905609	0.182140406757028	-0.548826168066652	0.583377312421186	   
df.mm.trans2:exp8	-0.315363202201323	0.16498671964859	-1.91144598106456	0.0565363640074519	.  
df.mm.trans1:probe2	-0.0152643408941271	0.091070203378514	-0.16761070391689	0.866959414525048	   
df.mm.trans1:probe3	0.0480299608081113	0.0910702033785139	0.52739490004744	0.598160549024743	   
df.mm.trans1:probe4	-0.0150945361451815	0.0910702033785139	-0.165746156099425	0.868425788276752	   
df.mm.trans1:probe5	-0.144742912345784	0.0910702033785139	-1.58935532123708	0.112631818005337	   
df.mm.trans1:probe6	0.128276986680332	0.0910702033785139	1.40855056782048	0.159608834390199	   
df.mm.trans1:probe7	-0.120581680470579	0.091070203378514	-1.32405195110202	0.186109456990493	   
df.mm.trans1:probe8	0.0953945950170556	0.0910702033785139	1.04748415484007	0.295398060548800	   
df.mm.trans1:probe9	0.0700199131762205	0.0910702033785139	0.768856448966054	0.442352769185019	   
df.mm.trans1:probe10	0.027435340543421	0.091070203378514	0.301254850935073	0.763349279899956	   
df.mm.trans1:probe11	-0.0257075697323190	0.091070203378514	-0.282282994641737	0.777846943526702	   
df.mm.trans1:probe12	0.0462035648169104	0.0910702033785139	0.507340086030939	0.61214682593938	   
df.mm.trans1:probe13	0.0326714635312012	0.091070203378514	0.358750308214524	0.719938002302372	   
df.mm.trans2:probe2	0.0598356307500727	0.0910702033785139	0.65702752964522	0.511474865649479	   
df.mm.trans2:probe3	-0.0366816344502346	0.091070203378514	-0.402784149913174	0.687284501581823	   
df.mm.trans2:probe4	-0.00642853382319283	0.091070203378514	-0.0705887720100283	0.943754143072649	   
df.mm.trans2:probe5	0.0862152629654868	0.0910702033785139	0.946690133183862	0.344268119422318	   
df.mm.trans2:probe6	-0.0552742330452973	0.0910702033785139	-0.606940920243274	0.544174137577922	   
df.mm.trans3:probe2	0.056776433340902	0.0910702033785139	0.623435890495631	0.533291190807287	   
df.mm.trans3:probe3	-0.0189384859823735	0.0910702033785139	-0.20795480058016	0.835351554270017