chr8.23467_chr8_123162151_123163441_+_1.R 

fitVsDatCorrelation=0.7463972097812
cont.fitVsDatCorrelation=0.31118978060518

fstatistic=5015.69586373722,37,347
cont.fstatistic=2454.81281621381,37,347

residuals=-0.680619588732421,-0.108289548183211,-0.00932582177525435,0.0904531901181068,0.910825649376272
cont.residuals=-0.604026296469111,-0.196321139382078,-0.0315132492451971,0.155888223442334,1.08961959631899

predictedValues:
Include	Exclude	Both
chr8.23467_chr8_123162151_123163441_+_1.R.tl.Lung	81.2367450799254	124.665804936035	83.5400000545185
chr8.23467_chr8_123162151_123163441_+_1.R.tl.cerebhem	72.481442634901	82.7526222305953	99.3190181809336
chr8.23467_chr8_123162151_123163441_+_1.R.tl.cortex	77.2395676286202	95.9075566392679	83.893132214908
chr8.23467_chr8_123162151_123163441_+_1.R.tl.heart	76.1853538834614	141.324219654478	114.591319743498
chr8.23467_chr8_123162151_123163441_+_1.R.tl.kidney	80.6283169233048	131.508016159066	98.134147914139
chr8.23467_chr8_123162151_123163441_+_1.R.tl.liver	74.4538463386895	101.026817133932	86.7793818586726
chr8.23467_chr8_123162151_123163441_+_1.R.tl.stomach	88.341472053416	96.6114474204896	92.2780523221627
chr8.23467_chr8_123162151_123163441_+_1.R.tl.testicle	82.028883646611	104.925379414987	90.7056265202198


diffExp=-43.42905985611,-10.2711795956944,-18.6679890106476,-65.1388657710167,-50.879699235761,-26.5729707952422,-8.2699753670736,-22.8964957683756
diffExpScore=0.995953485074615
diffExp1.5=-1,0,0,-1,-1,0,0,0
diffExp1.5Score=0.75
diffExp1.4=-1,0,0,-1,-1,0,0,0
diffExp1.4Score=0.75
diffExp1.3=-1,0,0,-1,-1,-1,0,0
diffExp1.3Score=0.8
diffExp1.2=-1,0,-1,-1,-1,-1,0,-1
diffExp1.2Score=0.857142857142857

cont.predictedValues:
Include	Exclude	Both
Lung	89.3128362831533	99.5502889133387	85.6181973329365
cerebhem	103.820493052679	111.443532909143	99.7411056001489
cortex	87.9555074099464	93.7399739622088	86.4067879074775
heart	89.2491350374824	86.1095204285197	78.3128857873707
kidney	102.214502765856	92.6102031293446	93.9454307672253
liver	91.3123661050767	100.030722684517	88.713708277138
stomach	94.341473361045	100.835353503147	94.6696253422976
testicle	81.6835823740378	91.4069745432697	97.8137952730954
cont.diffExp=-10.2374526301854,-7.62303985646317,-5.78446655226236,3.13961460896273,9.60429963651104,-8.71835657944051,-6.49388014210216,-9.72339216923184
cont.diffExpScore=1.66476763621149

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=0.115090192103078
cont.tran.correlation=0.564588412975739

tran.covariance=0.00204350287324322
cont.tran.covariance=0.00345054584432316

tran.mean=94.4573432361112
cont.tran.mean=94.7260291539228

weightedLogRatios:
wLogRatio
Lung	-1.97496306602988
cerebhem	-0.576430425539315
cortex	-0.964418947919182
heart	-2.86830330635899
kidney	-2.26726020761941
liver	-1.36207063286638
stomach	-0.405016567380846
testicle	-1.11522583509768

cont.weightedLogRatios:
wLogRatio
Lung	-0.493365367217935
cerebhem	-0.33146448808497
cortex	-0.287174042782885
heart	0.160204788404777
kidney	0.451704723743628
liver	-0.415820830388741
stomach	-0.304895670205732
testicle	-0.501507995439092

varWeightedLogRatios=0.73789193454418
cont.varWeightedLogRatios=0.116004366535061

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.48706860086923	0.112144467806086	40.0115020263686	4.79024365806833e-132	***
df.mm.trans1	-0.248303345376021	0.0934317314728407	-2.65759117873353	0.00823416704960664	** 
df.mm.trans2	0.48046904990876	0.0934317314728407	5.14246115676905	4.54188493631288e-07	***
df.mm.exp2	-0.696829514544235	0.128729298546585	-5.4131384417671	1.15793014339805e-07	***
df.mm.exp3	-0.316925824837334	0.128729298546585	-2.46195565745776	0.0143037923821423	*  
df.mm.exp4	-0.254824845737423	0.128729298546585	-1.97954038913065	0.0485451011933612	*  
df.mm.exp5	-0.115096382506282	0.128729298546585	-0.894096245421788	0.371890105776801	   
df.mm.exp6	-0.335482345454674	0.128729298546585	-2.60610715076077	0.0095524243737265	** 
df.mm.exp7	-0.270578127011692	0.128729298546585	-2.10191564831508	0.0362810523288897	*  
df.mm.exp8	-0.244977246637981	0.128729298546585	-1.9030418824921	0.0578624583497479	.  
df.mm.trans1:exp2	0.582792409560398	0.108796114374864	5.3567391897136	1.54645333197410e-07	***
df.mm.trans2:exp2	0.287048620441848	0.108796114374864	2.63840875284207	0.00870491617509475	** 
df.mm.trans1:exp3	0.266470014193196	0.108796114374864	2.44926039614849	0.0148089057032939	*  
df.mm.trans2:exp3	0.0546740042503167	0.108796114374864	0.502536368734033	0.615609046141951	   
df.mm.trans1:exp4	0.190626413278607	0.108796114374864	1.75214357951968	0.0806324080120878	.  
df.mm.trans2:exp4	0.380244930200569	0.108796114374864	3.49502307490882	0.00053548096586093	***
df.mm.trans1:exp5	0.107578626486360	0.108796114374864	0.988809454312777	0.323445360036568	   
df.mm.trans2:exp5	0.168527595205942	0.108796114374864	1.54902218865345	0.122287909408287	   
df.mm.trans1:exp6	0.248294096207197	0.108796114374864	2.28219635998841	0.0230825275926350	*  
df.mm.trans2:exp6	0.125231746785551	0.108796114374864	1.15106819306117	0.250496720945832	   
df.mm.trans1:exp7	0.354420126115628	0.108796114374864	3.25765426598279	0.00123431902946432	** 
df.mm.trans2:exp7	0.0156387680821573	0.108796114374864	0.143743810815457	0.8857862146755	   
df.mm.trans1:exp8	0.254681001049609	0.108796114374864	2.34090162606441	0.0198029350942295	*  
df.mm.trans2:exp8	0.0725900754653188	0.108796114374864	0.667212022069143	0.50508015482266	   
df.mm.trans1:probe2	0.192149636497253	0.0595900860120251	3.22452356350816	0.00138166878807243	** 
df.mm.trans1:probe3	0.134087010024685	0.0595900860120251	2.25015634308074	0.0250649904660972	*  
df.mm.trans1:probe4	0.609587601967339	0.0595900860120251	10.2296815252847	1.21502152389266e-21	***
df.mm.trans1:probe5	0.289843571066133	0.0595900860120251	4.86395624613872	1.74813675957844e-06	***
df.mm.trans1:probe6	0.360356329748869	0.0595900860120251	6.04725305608974	3.81056867527821e-09	***
df.mm.trans2:probe2	-0.197851094198265	0.0595900860120251	-3.32020152074187	0.00099509506892135	***
df.mm.trans2:probe3	-0.236707255769245	0.0595900860120251	-3.97225900498748	8.65990692536514e-05	***
df.mm.trans2:probe4	-0.249260081239675	0.0595900860120251	-4.18291192245258	3.64958143425369e-05	***
df.mm.trans2:probe5	-0.409620931558176	0.0595900860120251	-6.87397785389193	2.91011676579972e-11	***
df.mm.trans2:probe6	-0.32557118056715	0.0595900860120251	-5.46351251282723	8.92438574448748e-08	***
df.mm.trans3:probe2	-0.251580899857332	0.0595900860120251	-4.22185831056803	3.09839563625197e-05	***
df.mm.trans3:probe3	-0.324366846698246	0.0595900860120251	-5.44330220689377	9.9095727530678e-08	***
df.mm.trans3:probe4	-0.59968723616578	0.0595900860120251	-10.0635403688588	4.51372695805245e-21	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.60039456190585	0.160144450967439	28.7265311667977	9.58634654110271e-94	***
df.mm.trans1	-0.129477933946169	0.133422304571704	-0.970436947269073	0.332504676348704	   
df.mm.trans2	0.0388986411863778	0.133422304571704	0.291545265323106	0.770808535083607	   
df.mm.exp2	0.110693218528111	0.183827907363324	0.602156767793328	0.547463046472761	   
df.mm.exp3	-0.0846207401374306	0.183827907363324	-0.460325863200863	0.645570664390996	   
df.mm.exp4	-0.0565707577442493	0.183827907363324	-0.307737593032818	0.758466638323047	   
df.mm.exp5	-0.0301515033534879	0.183827907363324	-0.164020271926913	0.869810679122635	   
df.mm.exp6	-0.00856114248658776	0.183827907363324	-0.0465715059774205	0.962881532985292	   
df.mm.exp7	-0.0328935913819959	0.183827907363324	-0.178936875547323	0.858091697367386	   
df.mm.exp8	-0.30780111545908	0.183827907363324	-1.67439819053551	0.094953371151321	.  
df.mm.trans1:exp2	0.0398249400457166	0.155362938045953	0.256334879776393	0.797844168480538	   
df.mm.trans2:exp2	0.00216188008502714	0.155362938045953	0.0139150309090300	0.988905766824204	   
df.mm.trans1:exp3	0.0693066082190774	0.155362938045953	0.446094860787056	0.655806952086976	   
df.mm.trans2:exp3	0.024482522166633	0.155362938045953	0.157582770218928	0.874877237127219	   
df.mm.trans1:exp4	0.0558572659755136	0.155362938045953	0.359527611141031	0.719419118718866	   
df.mm.trans2:exp4	-0.0884721955514895	0.155362938045953	-0.569454959234365	0.569415867789068	   
df.mm.trans1:exp5	0.165079855863126	0.155362938045953	1.06254334488898	0.288727996918265	   
df.mm.trans2:exp5	-0.0421121087814255	0.155362938045953	-0.27105633628639	0.786508872051949	   
df.mm.trans1:exp6	0.0307021447344051	0.155362938045953	0.197615629058998	0.843461514866722	   
df.mm.trans2:exp6	0.0133755754360979	0.155362938045953	0.0860924465276377	0.931442582265142	   
df.mm.trans1:exp7	0.0876692657560238	0.155362938045953	0.564286868275451	0.572923464193387	   
df.mm.trans2:exp7	0.0457196820267941	0.155362938045953	0.294276631234092	0.76872248367735	   
df.mm.trans1:exp8	0.218508926072935	0.155362938045953	1.40644177318728	0.160487884353090	   
df.mm.trans2:exp8	0.222459966221867	0.155362938045953	1.43187280711741	0.153080335695494	   
df.mm.trans1:probe2	0.0128801112909375	0.0850957857680462	0.151360154615013	0.879779575225842	   
df.mm.trans1:probe3	0.0709152385323817	0.0850957857680462	0.833357820159064	0.405216202863823	   
df.mm.trans1:probe4	0.00834076081696709	0.0850957857680462	0.0980161442977012	0.921976065978201	   
df.mm.trans1:probe5	0.0738035874286954	0.0850957857680462	0.867300146095001	0.386376932038006	   
df.mm.trans1:probe6	0.046346231581636	0.0850957857680462	0.544636037652515	0.586353694859661	   
df.mm.trans2:probe2	-0.118789361798744	0.0850957857680462	-1.39594882080929	0.163622379169964	   
df.mm.trans2:probe3	-0.0200663160834648	0.0850957857680462	-0.23580857621036	0.813720327882575	   
df.mm.trans2:probe4	-0.0893507802404138	0.0850957857680462	-1.05000241121183	0.294447721323696	   
df.mm.trans2:probe5	-0.0288559698838933	0.0850957857680462	-0.3390998699107	0.734739616120009	   
df.mm.trans2:probe6	-0.129240275923240	0.0850957857680462	-1.51876235417254	0.129732888346488	   
df.mm.trans3:probe2	0.0160141723975203	0.0850957857680462	0.188189958562363	0.85083774822425	   
df.mm.trans3:probe3	-0.164491784007987	0.0850957857680462	-1.93301915627595	0.0540471720605988	.  
df.mm.trans3:probe4	-0.0911920800949175	0.0850957857680462	-1.07164037880194	0.284626349814238