chr7.21523_chr7_22934936_22935261_-_0.R 

fitVsDatCorrelation=0.90503009223622
cont.fitVsDatCorrelation=0.324060457833674

fstatistic=7881.64342557674,43,485
cont.fstatistic=1584.26948778309,43,485

residuals=-0.431872577207459,-0.0899723879283855,-0.00281272234205909,0.0809987353550367,0.74211702948271
cont.residuals=-0.79013498759995,-0.287545837510521,-0.0711826386484779,0.263632379957382,0.950652543282794

predictedValues:
Include	Exclude	Both
chr7.21523_chr7_22934936_22935261_-_0.R.tl.Lung	133.955954761097	77.4836891365517	47.7350690740803
chr7.21523_chr7_22934936_22935261_-_0.R.tl.cerebhem	90.3159841421896	75.3365502688586	52.9915433657873
chr7.21523_chr7_22934936_22935261_-_0.R.tl.cortex	109.258761827084	76.280135058638	48.3425766760254
chr7.21523_chr7_22934936_22935261_-_0.R.tl.heart	108.269242017643	72.3526528304525	49.3394737689278
chr7.21523_chr7_22934936_22935261_-_0.R.tl.kidney	151.261262018776	88.2104347512778	49.0227013631715
chr7.21523_chr7_22934936_22935261_-_0.R.tl.liver	131.459451918688	79.899751775449	51.0144271107419
chr7.21523_chr7_22934936_22935261_-_0.R.tl.stomach	110.671863814036	71.4090142622664	49.742746165154
chr7.21523_chr7_22934936_22935261_-_0.R.tl.testicle	101.226287686898	71.4380458017283	51.772877803221


diffExp=56.472265624545,14.9794338733309,32.9786267684464,35.9165891871907,63.0508272674983,51.5597001432392,39.2628495517692,29.7882418851698
diffExpScore=0.996923157719073
diffExp1.5=1,0,0,0,1,1,1,0
diffExp1.5Score=0.8
diffExp1.4=1,0,1,1,1,1,1,1
diffExp1.4Score=0.875
diffExp1.3=1,0,1,1,1,1,1,1
diffExp1.3Score=0.875
diffExp1.2=1,0,1,1,1,1,1,1
diffExp1.2Score=0.875

cont.predictedValues:
Include	Exclude	Both
Lung	59.5943676660434	70.9288331848902	76.1459189110025
cerebhem	63.5785003226743	69.6267511754866	65.5057150678877
cortex	75.3911447634815	78.2876629381134	76.1308060566352
heart	61.490227183501	64.7460348261102	71.4032666570024
kidney	74.1397244022086	74.9952102445228	70.7129541341146
liver	63.2678364155795	68.5411857165602	68.572353878774
stomach	63.1131350826004	81.8501223148604	70.0270774964079
testicle	68.0918798939912	58.3043104794505	76.0317044317927
cont.diffExp=-11.3344655188467,-6.04825085281223,-2.89651817463188,-3.25580764260925,-0.855485842314224,-5.27334930098063,-18.7369872322600,9.78756941454068
cont.diffExpScore=1.46891173175028

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

tran.correlation=0.825004453031542
cont.tran.correlation=0.264830493195128

tran.covariance=0.00935090744830756
cont.tran.covariance=0.00222876104434584

tran.mean=96.8018176294771
cont.tran.mean=68.4966829131296

weightedLogRatios:
wLogRatio
Lung	2.5312638268517
cerebhem	0.800228033269762
cortex	1.62193308646294
heart	1.80699318148200
kidney	2.56125421159501
liver	2.30526437438763
stomach	1.96617669627677
testicle	1.54854241164825

cont.weightedLogRatios:
wLogRatio
Lung	-0.726867792352994
cerebhem	-0.38146071369193
cortex	-0.163676942943072
heart	-0.213841233776688
kidney	-0.0494669929889367
liver	-0.335234212559747
stomach	-1.11130922915326
testicle	0.642960215847496

varWeightedLogRatios=0.346133786606199
cont.varWeightedLogRatios=0.260828205949165

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	5.483412074579	0.0842154925307254	65.111678502366	6.96076786954982e-242	***
df.mm.trans1	-0.542090999116422	0.0674189058658295	-8.04063774329472	6.89052837646888e-15	***
df.mm.trans2	-1.14588803587910	0.0674189058658295	-16.9965385994180	3.63111051990967e-51	***
df.mm.exp2	-0.526764646088571	0.090278507990278	-5.8348842688594	9.85156035707847e-09	***
df.mm.exp3	-0.232093268275606	0.090278507990278	-2.57085848495193	0.0104417895795601	*  
df.mm.exp4	-0.314463393241648	0.090278507990278	-3.48325864308161	0.000540207900073784	***
df.mm.exp5	0.224538160590818	0.090278507990278	2.48717181518992	0.0132114087701618	*  
df.mm.exp6	-0.0545494506069316	0.090278507990278	-0.604235180900486	0.545969830728008	   
df.mm.exp7	-0.313783067458718	0.090278507990278	-3.47572278767067	0.00055523282455095	***
df.mm.exp8	-0.442589526020452	0.090278507990278	-4.90249048054842	1.29287423403566e-06	***
df.mm.trans1:exp2	0.132568052282337	0.07082028829238	1.87189371123474	0.0618229277530776	.  
df.mm.trans2:exp2	0.498662607010241	0.07082028829238	7.04123943906474	6.55169462490378e-12	***
df.mm.trans1:exp3	0.0283012487198288	0.07082028829238	0.399620636998648	0.689611878119317	   
df.mm.trans2:exp3	0.21643836811573	0.07082028829238	3.05616333023341	0.00236549860983739	** 
df.mm.trans1:exp4	0.101573449581034	0.07082028829238	1.43424224936349	0.152147573653944	   
df.mm.trans2:exp4	0.245948060819048	0.07082028829238	3.47284749539083	0.000561067778418294	***
df.mm.trans1:exp5	-0.103040656929467	0.07082028829238	-1.45495958028392	0.146327348292310	   
df.mm.trans2:exp5	-0.0948803481930126	0.07082028829238	-1.33973400110010	0.180959228273891	   
df.mm.trans1:exp6	0.0357368541408644	0.07082028829238	0.504613225991478	0.614059701149754	   
df.mm.trans2:exp6	0.0852547452293484	0.07082028829238	1.20381810474106	0.229247100510064	   
df.mm.trans1:exp7	0.122841658673537	0.07082028829238	1.73455462601885	0.0834550572030138	.  
df.mm.trans2:exp7	0.232139727552435	0.07082028829238	3.2778704118522	0.00112099967499564	** 
df.mm.trans1:exp8	0.162436958788159	0.07082028829238	2.29365006419548	0.0222373712799388	*  
df.mm.trans2:exp8	0.361352656360720	0.07082028829238	5.10238894917914	4.82223581446151e-07	***
df.mm.trans1:probe2	-0.153295706327641	0.0484873367834444	-3.16156168799896	0.00166750272418151	** 
df.mm.trans1:probe3	-0.192322058686388	0.0484873367834444	-3.96643889816722	8.39608919767194e-05	***
df.mm.trans1:probe4	-0.117140591311305	0.0484873367834444	-2.41590070897236	0.0160648310004588	*  
df.mm.trans1:probe5	-0.0854405413411403	0.0484873367834444	-1.76212073108361	0.0786787996243153	.  
df.mm.trans1:probe6	-0.152761508040576	0.0484873367834444	-3.15054441374753	0.00173036263957214	** 
df.mm.trans2:probe2	0.0859079203298697	0.0484873367834444	1.7717599280314	0.0770622488379856	.  
df.mm.trans2:probe3	-0.0572203242456955	0.0484873367834444	-1.18010862302573	0.238535495425821	   
df.mm.trans2:probe4	0.0229056409860892	0.0484873367834444	0.472404600986668	0.636850512895087	   
df.mm.trans2:probe5	0.148741380223412	0.0484873367834444	3.06763353260100	0.0022782472946837	** 
df.mm.trans2:probe6	0.00035998678359817	0.0484873367834444	0.00742434638565434	0.99407933585061	   
df.mm.trans3:probe2	0.0265620664505046	0.0484873367834444	0.54781450606654	0.584071298622612	   
df.mm.trans3:probe3	0.0196790588123830	0.0484873367834444	0.405859758812373	0.685024641504286	   
df.mm.trans3:probe4	0.0678803955642814	0.0484873367834444	1.39996131087692	0.162164240643559	   
df.mm.trans3:probe5	0.0187442579224494	0.0484873367834444	0.386580479892422	0.699236357549873	   
df.mm.trans3:probe6	0.194854326119906	0.0484873367834444	4.0186642337188	6.78355544216177e-05	***
df.mm.trans3:probe7	0.0663537508033933	0.0484873367834444	1.36847587855246	0.17179672869168	   
df.mm.trans3:probe8	0.133066742685794	0.0484873367834444	2.74436072412268	0.00628770084615159	** 
df.mm.trans3:probe9	0.0357364126799649	0.0484873367834444	0.73702568651217	0.461463108255837	   
df.mm.trans3:probe10	0.139455877937611	0.0484873367834444	2.87612987614586	0.00420307537686796	** 

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.00464210639292	0.187307815655743	21.3800053797708	6.14152990337646e-72	***
df.mm.trans1	0.0925295704725184	0.149949701796513	0.617070720141107	0.537477652269734	   
df.mm.trans2	0.254969250146270	0.149949701796513	1.70036516973053	0.089703334849141	.  
df.mm.exp2	0.196700218577540	0.200792866302469	0.97961756410826	0.327763322124016	   
df.mm.exp3	0.334040253568512	0.200792866302469	1.66360618143337	0.0968371217806181	.  
df.mm.exp4	0.00442048823826306	0.200792866302469	0.0220151657758804	0.982444912195067	   
df.mm.exp5	0.3481603385732	0.200792866302469	1.73392782813678	0.0835663398678858	.  
df.mm.exp6	0.130335846561565	0.200792866302469	0.649105961589445	0.516577143045332	   
df.mm.exp7	0.284350113343425	0.200792866302469	1.41613653203738	0.15737742962902	   
df.mm.exp8	-0.0612030290575021	0.200792866302469	-0.304806790124244	0.76064406255402	   
df.mm.trans1:exp2	-0.131985917980698	0.157514883610234	-0.837926645124492	0.402484641864128	   
df.mm.trans2:exp2	-0.215228393957883	0.157514883610234	-1.36640036182524	0.172446479513188	   
df.mm.trans1:exp3	-0.0989114962648681	0.157514883610234	-0.627950159361587	0.530332148857336	   
df.mm.trans2:exp3	-0.235327249284872	0.157514883610234	-1.49400008361866	0.135825881864059	   
df.mm.trans1:exp4	0.0268966990036198	0.157514883610234	0.170756555743488	0.864486402498783	   
df.mm.trans2:exp4	-0.0956250525850593	0.157514883610234	-0.607085821944807	0.544078055155543	   
df.mm.trans1:exp5	-0.129769925477436	0.157514883610234	-0.82385818091037	0.410425088222741	   
df.mm.trans2:exp5	-0.292413115327123	0.157514883610234	-1.85641577878248	0.064000524871737	.  
df.mm.trans1:exp6	-0.0705198274008884	0.157514883610234	-0.447702628377569	0.654567723435123	   
df.mm.trans2:exp6	-0.164578055480424	0.157514883610234	-1.04484129822086	0.296616797274035	   
df.mm.trans1:exp7	-0.226982269860035	0.157514883610234	-1.44102109373801	0.150224011221973	   
df.mm.trans2:exp7	-0.141137339993657	0.157514883610234	-0.896025421590618	0.370683689696979	   
df.mm.trans1:exp8	0.194499929771767	0.157514883610234	1.23480350119200	0.217501531307282	   
df.mm.trans2:exp8	-0.134797968981028	0.157514883610234	-0.855779250134748	0.392542474845577	   
df.mm.trans1:probe2	-0.126034591048049	0.107843068620157	-1.16868513350604	0.243104620775149	   
df.mm.trans1:probe3	0.146434458819452	0.107843068620157	1.35784766413890	0.175143405132670	   
df.mm.trans1:probe4	0.0127757026529090	0.107843068620157	0.118465681813148	0.905747733679343	   
df.mm.trans1:probe5	-0.103982971950300	0.107843068620157	-0.964206353553857	0.335422984588426	   
df.mm.trans1:probe6	-0.0829623505915446	0.107843068620157	-0.76928774053855	0.442096990543098	   
df.mm.trans2:probe2	0.0227624529808054	0.107843068620157	0.211070152880932	0.832921185401208	   
df.mm.trans2:probe3	0.0370460413888829	0.107843068620157	0.343518056958911	0.73135762092791	   
df.mm.trans2:probe4	0.0641177305906591	0.107843068620157	0.594546607501437	0.552423826301686	   
df.mm.trans2:probe5	-0.0665518270275089	0.107843068620157	-0.617117334280578	0.537446933407741	   
df.mm.trans2:probe6	-0.0243237050475926	0.107843068620157	-0.225547226713894	0.821648598559649	   
df.mm.trans3:probe2	-0.140957945772715	0.107843068620157	-1.30706541993157	0.191809847542073	   
df.mm.trans3:probe3	-0.0352698317470563	0.107843068620157	-0.327047738888839	0.743772880429204	   
df.mm.trans3:probe4	-0.0507339305096471	0.107843068620157	-0.470442200493582	0.638250604831369	   
df.mm.trans3:probe5	0.149403182117610	0.107843068620157	1.38537584315071	0.166574364153604	   
df.mm.trans3:probe6	-0.146828488400627	0.107843068620157	-1.36150139530788	0.173987434783771	   
df.mm.trans3:probe7	0.00945213424706808	0.107843068620157	0.0876471187996348	0.930193326700663	   
df.mm.trans3:probe8	-0.0387680414750856	0.107843068620157	-0.359485704284191	0.71938823497234	   
df.mm.trans3:probe9	0.157865091972470	0.107843068620157	1.46384087537883	0.143885243422669	   
df.mm.trans3:probe10	-0.0990565891413017	0.107843068620157	-0.918525320252124	0.358800473295210