chr2.13964_chr2_132520000_132522125_+_2.R 

fitVsDatCorrelation=0.748007571160906
cont.fitVsDatCorrelation=0.2776709102554

fstatistic=9299.25772959856,60,876
cont.fstatistic=4430.75336844182,60,876

residuals=-0.834483739580158,-0.100524640835299,-0.00924217835979393,0.0810764448870553,1.21230395208614
cont.residuals=-0.900561396994267,-0.154427133577690,-0.0232829072893329,0.120834615549689,1.35085942854358

predictedValues:
Include	Exclude	Both
chr2.13964_chr2_132520000_132522125_+_2.R.tl.Lung	66.842911178366	60.6553041682921	63.5344494699966
chr2.13964_chr2_132520000_132522125_+_2.R.tl.cerebhem	72.4479991843698	62.4922108723808	63.6529992150629
chr2.13964_chr2_132520000_132522125_+_2.R.tl.cortex	65.4746728078661	57.7895313418745	73.3471557104431
chr2.13964_chr2_132520000_132522125_+_2.R.tl.heart	63.8252523407085	64.4572009017324	69.4438838102074
chr2.13964_chr2_132520000_132522125_+_2.R.tl.kidney	64.2659252228067	64.7961099643069	62.92663932941
chr2.13964_chr2_132520000_132522125_+_2.R.tl.liver	58.6266064033737	65.9147193051479	58.9951842727656
chr2.13964_chr2_132520000_132522125_+_2.R.tl.stomach	62.6603910764637	57.3909059976635	64.9781739066502
chr2.13964_chr2_132520000_132522125_+_2.R.tl.testicle	58.808174830693	62.8416936673507	56.770404551607


diffExp=6.18760701007379,9.95578831198901,7.68514146599166,-0.631948561023897,-0.53018474150015,-7.28811290177416,5.26948507880024,-4.03351883665773
diffExpScore=2.3606892597746
diffExp1.5=0,0,0,0,0,0,0,0
diffExp1.5Score=0
diffExp1.4=0,0,0,0,0,0,0,0
diffExp1.4Score=0
diffExp1.3=0,0,0,0,0,0,0,0
diffExp1.3Score=0
diffExp1.2=0,0,0,0,0,0,0,0
diffExp1.2Score=0

cont.predictedValues:
Include	Exclude	Both
Lung	67.6663690807215	62.0824110379714	65.7724918026843
cerebhem	66.4421172384286	62.0819293135112	67.8313375473315
cortex	64.0668274260782	65.4239999727901	62.9122944194042
heart	69.506248948989	57.8318447641571	70.800432237197
kidney	65.7827433324062	63.3664286228511	69.1230781997378
liver	63.8557583854091	54.6790927472357	68.6859702386443
stomach	65.5058599840099	71.142219528987	62.8711754627751
testicle	65.8993484963628	63.9466649589933	68.2559914557824
cont.diffExp=5.58395804275008,4.36018792491731,-1.35717254671192,11.6744041848319,2.41631470955513,9.17666563817341,-5.6363595449771,1.95268353736949
cont.diffExpScore=1.44520948147391

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

tran.correlation=-0.249916633400969
cont.tran.correlation=-0.169758467131608

tran.covariance=-0.000910703665377597
cont.tran.covariance=-0.000316333072655900

tran.mean=63.0806005789623
cont.tran.mean=64.3299914899314

weightedLogRatios:
wLogRatio
Lung	0.403490217087072
cerebhem	0.622197805575758
cortex	0.514310250403394
heart	-0.0409971384262964
kidney	-0.0342372592639593
liver	-0.48389875688252
stomach	0.359615084113551
testicle	-0.272479562936346

cont.weightedLogRatios:
wLogRatio
Lung	0.359279267258228
cerebhem	0.28252741459024
cortex	-0.0874219516166557
heart	0.7629939611741
kidney	0.155967229971513
liver	0.632846253905924
stomach	-0.348606034828702
testicle	0.125523091258122

varWeightedLogRatios=0.158921487222804
cont.varWeightedLogRatios=0.131077934119252

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.95108843709758	0.0792316452086845	49.8675551503568	4.16090997059788e-258	***
df.mm.trans1	0.144098794783399	0.068277432968188	2.11048934500126	0.0350991446743018	*  
df.mm.trans2	0.15601285483887	0.0601807546662306	2.59240442736445	0.00968957045971462	** 
df.mm.exp2	0.108494456478704	0.0770930651144031	1.40731797753407	0.159687832777430	   
df.mm.exp3	-0.212702767106846	0.077093065114403	-2.75903891992364	0.00591804400239265	** 
df.mm.exp4	-0.0743387048572871	0.0770930651144031	-0.964272269457329	0.335175551474292	   
df.mm.exp5	0.0363354597759934	0.0770930651144031	0.47131943349344	0.637529994685886	   
df.mm.exp6	0.026124510393862	0.0770930651144031	0.338869784916377	0.734789038283049	   
df.mm.exp7	-0.142406116046891	0.0770930651144031	-1.84719748573450	0.065055565543733	.  
df.mm.exp8	0.0199144207288028	0.0770930651144031	0.258316629378408	0.796223230681224	   
df.mm.trans1:exp2	-0.0279706618088752	0.0710762941171215	-0.393530109529689	0.69402375047111	   
df.mm.trans2:exp2	-0.0786596204824637	0.0517156002568869	-1.52100372212133	0.128619759526630	   
df.mm.trans1:exp3	0.192020903068363	0.0710762941171215	2.70161669869768	0.0070336724425517	** 
df.mm.trans2:exp3	0.164303320790785	0.0517156002568869	3.17705527876775	0.00153990144598239	** 
df.mm.trans1:exp4	0.0281423643986213	0.0710762941171215	0.395945859983182	0.692241383927602	   
df.mm.trans2:exp4	0.135133069562146	0.0517156002568869	2.61300398508187	0.00912886730668826	** 
df.mm.trans1:exp5	-0.0756511605364188	0.0710762941171215	-1.06436557330576	0.287456416847784	   
df.mm.trans2:exp5	0.0297030234275239	0.0517156002568869	0.57435325665718	0.565876229930458	   
df.mm.trans1:exp6	-0.157281139878651	0.0710762941171215	-2.21284947157597	0.0271651708857551	*  
df.mm.trans2:exp6	0.0570301774326121	0.0517156002568869	1.10276545470470	0.270431895749664	   
df.mm.trans1:exp7	0.0777903855846034	0.0710762941171215	1.09446316174586	0.274052734963018	   
df.mm.trans2:exp7	0.0870848877865295	0.0517156002568869	1.68391911442491	0.0925535575379703	.  
df.mm.trans1:exp8	-0.147978804967495	0.0710762941171215	-2.08197130710911	0.0376348553003209	*  
df.mm.trans2:exp8	0.0154972574160935	0.0517156002568869	0.299663106279614	0.764505229789076	   
df.mm.trans1:probe2	0.0119695293126821	0.0495139175798341	0.241740704386458	0.809037663840214	   
df.mm.trans1:probe3	-0.0658792592547272	0.0495139175798341	-1.33052003304942	0.183693233768846	   
df.mm.trans1:probe4	0.551888344993215	0.0495139175798341	11.1461256141442	4.48704491001986e-27	***
df.mm.trans1:probe5	0.278085061076581	0.0495139175798341	5.61630092444631	2.61968594908110e-08	***
df.mm.trans1:probe6	0.227678031057201	0.0495139175798341	4.59826332041092	4.88722366082111e-06	***
df.mm.trans1:probe7	0.348525060257422	0.0495139175798341	7.03893121960052	3.91083323965376e-12	***
df.mm.trans1:probe8	0.00193832900499756	0.0495139175798341	0.039147154976624	0.968781985145615	   
df.mm.trans1:probe9	0.153903666523455	0.0495139175798341	3.10829104312554	0.00194248589630714	** 
df.mm.trans1:probe10	0.61538660178537	0.0495139175798341	12.4285581077915	8.85905965619092e-33	***
df.mm.trans1:probe11	0.472720292741656	0.0495139175798341	9.54722057650684	1.28651709426618e-20	***
df.mm.trans1:probe12	0.165483300202369	0.0495139175798341	3.34215728205209	0.000866507833746296	***
df.mm.trans1:probe13	0.358498784596087	0.0495139175798341	7.24036396469859	9.79254819949396e-13	***
df.mm.trans1:probe14	0.243538242208207	0.0495139175798341	4.91858156477997	1.04097346100142e-06	***
df.mm.trans1:probe15	0.230630302214277	0.0495139175798341	4.65788839758879	3.69017739532997e-06	***
df.mm.trans1:probe16	0.151973054144465	0.0495139175798341	3.06929973576479	0.00221172344188250	** 
df.mm.trans1:probe17	-0.00820077079113597	0.0495139175798341	-0.165625569374780	0.868489838972686	   
df.mm.trans1:probe18	0.0755377363858002	0.0495139175798341	1.52558593781246	0.127473957630121	   
df.mm.trans1:probe19	-0.0362715248647103	0.0495139175798341	-0.732552111357936	0.464027604342135	   
df.mm.trans1:probe20	-0.103144029002356	0.0495139175798341	-2.0831320574877	0.0375286774298388	*  
df.mm.trans1:probe21	-0.0861965623731981	0.0495139175798341	-1.74085522993042	0.0820600569047803	.  
df.mm.trans1:probe22	-0.0518493542712617	0.0495139175798341	-1.04716727751671	0.295311274050708	   
df.mm.trans2:probe2	-0.0688257019947199	0.0495139175798341	-1.39002739752411	0.164873661214273	   
df.mm.trans2:probe3	0.172007628903590	0.0495139175798341	3.47392485408273	0.000538048909097252	***
df.mm.trans2:probe4	-0.144242329737858	0.0495139175798341	-2.91316738380249	0.00366877799449716	** 
df.mm.trans2:probe5	-0.00200912902252028	0.0495139175798341	-0.0405770563252413	0.967642321434028	   
df.mm.trans2:probe6	0.0108680468734070	0.0495139175798341	0.219494788629557	0.826315772902095	   
df.mm.trans3:probe2	-0.101203644145478	0.0495139175798341	-2.04394338182393	0.0412577435539891	*  
df.mm.trans3:probe3	-0.0929674764784494	0.0495139175798341	-1.87760292504734	0.0607675639229368	.  
df.mm.trans3:probe4	-0.30878685250429	0.0495139175798341	-6.23636479594682	6.95944103482267e-10	***
df.mm.trans3:probe5	0.121165238545649	0.0495139175798341	2.44709456387262	0.0145967931343615	*  
df.mm.trans3:probe6	-0.212334971283092	0.0495139175798341	-4.28838964197757	1.99974068319048e-05	***
df.mm.trans3:probe7	0.0180861012515909	0.0495139175798341	0.36527308150137	0.714995744856672	   
df.mm.trans3:probe8	-0.154938808154363	0.0495139175798341	-3.12919711724581	0.00181087206436877	** 
df.mm.trans3:probe9	-0.240849269450622	0.0495139175798341	-4.86427415205607	1.36174281707711e-06	***
df.mm.trans3:probe10	-0.0350956819890259	0.0495139175798341	-0.708804386815872	0.478634456363603	   
df.mm.trans3:probe11	-0.0888706182681449	0.0495139175798341	-1.79486137659889	0.0730204340359665	.  

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.24670834923526	0.114685979755313	37.0290105058679	2.18614386752771e-181	***
df.mm.trans1	0.000251831346485617	0.098830010086375	0.00254812628538156	0.99796747172389	   
df.mm.trans2	-0.142871109636927	0.0871102549130747	-1.64011814429305	0.101339612113322	   
df.mm.exp2	-0.0490885015105993	0.111590434373769	-0.439898829913848	0.660118891422397	   
df.mm.exp3	0.0422239639004173	0.111590434373769	0.378383363568504	0.70523750216815	   
df.mm.exp4	-0.117759184871348	0.111590434373769	-1.05528028035912	0.291588110334224	   
df.mm.exp5	-0.0574472209330798	0.111590434373769	-0.514804169868734	0.606819735461472	   
df.mm.exp6	-0.228287088407635	0.111590434373769	-2.04575857858025	0.0410783184143848	*  
df.mm.exp7	0.148882458541028	0.111590434373769	1.33418656694489	0.182489445207428	   
df.mm.exp8	-0.0339375980386196	0.111590434373769	-0.304126408585762	0.761103814679076	   
df.mm.trans1:exp2	0.0308303601297664	0.102881297071759	0.299669240253283	0.764500552039317	   
df.mm.trans2:exp2	0.0490807420450593	0.0748571390695433	0.65565880095234	0.512215836728992	   
df.mm.trans1:exp3	-0.0968865393256387	0.102881297071759	-0.941731316412748	0.346589841314270	   
df.mm.trans2:exp3	0.0102024865889766	0.0748571390695433	0.136292766672506	0.891621156392103	   
df.mm.trans1:exp4	0.144586553793105	0.102881297071759	1.40537257896600	0.160265056032516	   
df.mm.trans2:exp4	0.0468360435936153	0.0748571390695433	0.625672369740233	0.531692828022765	   
df.mm.trans1:exp5	0.0292154729402639	0.102881297071759	0.283972634208590	0.776498457737255	   
df.mm.trans2:exp5	0.0779187124259062	0.0748571390695433	1.04089888278416	0.298209672142277	   
df.mm.trans1:exp6	0.170324560423297	0.102881297071759	1.65554445046019	0.0981722696470862	.  
df.mm.trans2:exp6	0.101305795368429	0.0748571390695433	1.35332176232804	0.176301971219568	   
df.mm.trans1:exp7	-0.181332147039038	0.102881297071759	-1.76253752820165	0.0783272062811935	.  
df.mm.trans2:exp7	-0.0126642057728014	0.0748571390695433	-0.169178329952420	0.865695431190815	   
df.mm.trans1:exp8	0.00747686070966334	0.102881297071759	0.0726746349674059	0.9420816231816	   
df.mm.trans2:exp8	0.0635242612280717	0.0748571390695433	0.84860658606064	0.396332065859769	   
df.mm.trans1:probe2	0.0569602681099065	0.0716702541542668	0.794754654940978	0.426971496327218	   
df.mm.trans1:probe3	-0.0273733368571030	0.0716702541542668	-0.381934418680631	0.702602640533113	   
df.mm.trans1:probe4	-0.0710881024833172	0.0716702541542668	-0.99187736003145	0.321531246259816	   
df.mm.trans1:probe5	-0.123206962593885	0.0716702541542668	-1.71908086622224	0.0859529249262268	.  
df.mm.trans1:probe6	-0.0604349483204243	0.0716702541542668	-0.843236137970725	0.399326575755899	   
df.mm.trans1:probe7	-0.0996176178720189	0.0716702541542668	-1.38994369487789	0.164899070790807	   
df.mm.trans1:probe8	0.00929194565100807	0.0716702541542668	0.129648565651904	0.896874240199749	   
df.mm.trans1:probe9	-0.0586108891071479	0.0716702541542668	-0.817785422959304	0.413702097148913	   
df.mm.trans1:probe10	-0.00904221685426266	0.0716702541542668	-0.126164152212991	0.89963093713702	   
df.mm.trans1:probe11	-0.140733396836210	0.0716702541542668	-1.96362352131873	0.0498897112515059	*  
df.mm.trans1:probe12	-0.0812219350721152	0.0716702541542668	-1.13327259726593	0.257409857903525	   
df.mm.trans1:probe13	-0.0316116842143325	0.0716702541542668	-0.441071188980157	0.659270295613734	   
df.mm.trans1:probe14	0.0466913217307326	0.0716702541542668	0.651474203373574	0.514911291951124	   
df.mm.trans1:probe15	-0.00274392388015557	0.0716702541542668	-0.038285393466715	0.969468859551844	   
df.mm.trans1:probe16	-0.0265226761073723	0.0716702541542668	-0.370065327943215	0.711423266904688	   
df.mm.trans1:probe17	-0.0464289543290253	0.0716702541542668	-0.647813446134698	0.517275361205041	   
df.mm.trans1:probe18	-0.0576450738673594	0.0716702541542668	-0.804309605813328	0.421436408997281	   
df.mm.trans1:probe19	-0.0857405884298168	0.0716702541542668	-1.19632041830442	0.23189523448222	   
df.mm.trans1:probe20	-0.0978328169401315	0.0716702541542668	-1.36504074241946	0.172590715411591	   
df.mm.trans1:probe21	-0.0708574794768687	0.0716702541542668	-0.988659525670879	0.323102746702983	   
df.mm.trans1:probe22	-0.0904702375564954	0.0716702541542668	-1.26231221898227	0.207172412621605	   
df.mm.trans2:probe2	0.09600489038986	0.0716702541542668	1.33953606726738	0.18074363363674	   
df.mm.trans2:probe3	0.0377645186918376	0.0716702541542668	0.526920395880713	0.598382271657622	   
df.mm.trans2:probe4	0.0443794598636542	0.0716702541542668	0.61921728040938	0.535934230617698	   
df.mm.trans2:probe5	0.171280513106284	0.0716702541542668	2.38984101741304	0.0170661758190827	*  
df.mm.trans2:probe6	0.0692036609655799	0.0716702541542668	0.96558414341077	0.334518798472126	   
df.mm.trans3:probe2	0.0335066588860194	0.0716702541542668	0.46751137248513	0.640250331265503	   
df.mm.trans3:probe3	0.113414072084018	0.0716702541542668	1.58244272219127	0.113909488281936	   
df.mm.trans3:probe4	0.0307618343510245	0.0716702541542668	0.429213412370649	0.667873460718298	   
df.mm.trans3:probe5	0.0669835834478903	0.0716702541542668	0.93460786819189	0.350247973340869	   
df.mm.trans3:probe6	0.0732583828266053	0.0716702541542668	1.02215882573711	0.30698792637128	   
df.mm.trans3:probe7	0.123911401847799	0.0716702541542668	1.72890975914618	0.0841775717867724	.  
df.mm.trans3:probe8	0.231904574972888	0.0716702541542668	3.23571581696536	0.00125889077979926	** 
df.mm.trans3:probe9	0.0360820610745688	0.0716702541542668	0.503445418191261	0.614777713981427	   
df.mm.trans3:probe10	0.132402904668527	0.0716702541542668	1.84738991414117	0.0650276615112293	.  
df.mm.trans3:probe11	0.0610133707666763	0.0716702541542668	0.851306744850491	0.394831627538551