chr15.8514_chr15_79965633_79969107_+_2.R 

fitVsDatCorrelation=0.918321780335045
cont.fitVsDatCorrelation=0.241413847339426

fstatistic=8729.458778558,39,393
cont.fstatistic=1444.02411767550,39,393

residuals=-0.396305573979215,-0.096139693140474,-0.00546456956701719,0.0838980102693536,0.678504692567524
cont.residuals=-0.643147010015624,-0.268468378026100,-0.101891789521485,0.274314863587932,1.02431729578653

predictedValues:
Include	Exclude	Both
chr15.8514_chr15_79965633_79969107_+_2.R.tl.Lung	115.918473222643	50.1602963093037	60.5630074511337
chr15.8514_chr15_79965633_79969107_+_2.R.tl.cerebhem	99.5456392336673	62.6350898030825	59.514012524051
chr15.8514_chr15_79965633_79969107_+_2.R.tl.cortex	94.939920071468	50.0781430786526	73.0248000813846
chr15.8514_chr15_79965633_79969107_+_2.R.tl.heart	97.808501387013	51.6146856619607	62.1072869883193
chr15.8514_chr15_79965633_79969107_+_2.R.tl.kidney	120.620825286722	46.4548905093295	62.20584430439
chr15.8514_chr15_79965633_79969107_+_2.R.tl.liver	114.625928616907	51.4398930002548	63.4997858464701
chr15.8514_chr15_79965633_79969107_+_2.R.tl.stomach	98.292209520051	50.6708800315207	65.3582966860262
chr15.8514_chr15_79965633_79969107_+_2.R.tl.testicle	90.1089816440259	51.5792162803188	66.1639134945979


diffExp=65.7581769133393,36.9105494305848,44.8617769928155,46.1938157250522,74.1659347773929,63.1860356166518,47.6213294885304,38.5297653637071
diffExpScore=0.997608956186228
diffExp1.5=1,1,1,1,1,1,1,1
diffExp1.5Score=0.888888888888889
diffExp1.4=1,1,1,1,1,1,1,1
diffExp1.4Score=0.888888888888889
diffExp1.3=1,1,1,1,1,1,1,1
diffExp1.3Score=0.888888888888889
diffExp1.2=1,1,1,1,1,1,1,1
diffExp1.2Score=0.888888888888889

cont.predictedValues:
Include	Exclude	Both
Lung	68.2057299063418	66.2452244693616	71.3927463261794
cerebhem	69.7321871863477	68.6763912284985	68.2899610318453
cortex	66.8481050255455	57.7302760288047	78.8480614733091
heart	70.2544170934045	67.0948018046692	67.6329550906426
kidney	74.6201825056618	68.7031559091602	70.6898648700962
liver	69.1713275054136	68.5425317161836	58.2056741379673
stomach	76.0358286987066	69.4688443765975	70.084082850046
testicle	72.7524197837888	70.8660426445572	69.882622292745
cont.diffExp=1.96050543698016,1.05579595784920,9.11782899674083,3.15961528873528,5.91702659650156,0.628795789230054,6.56698432210911,1.88637713923164
cont.diffExpScore=0.968043899529281

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=-0.362152693339764
cont.tran.correlation=0.668991720744148

tran.covariance=-0.00336956319555286
cont.tran.covariance=0.00192555096685979

tran.mean=77.9058483535575
cont.tran.mean=69.0592166176902

weightedLogRatios:
wLogRatio
Lung	3.63047930475264
cerebhem	2.02410301100833
cortex	2.70794430214869
heart	2.72519338148257
kidney	4.11778530309518
liver	3.47830506729115
stomach	2.82042685848493
testicle	2.35549686278277

cont.weightedLogRatios:
wLogRatio
Lung	0.122725580805210
cerebhem	0.0646423787644147
cortex	0.605496548997994
heart	0.194609535933692
kidney	0.352860930008515
liver	0.0386467294294989
stomach	0.387142227653766
testicle	0.112279456184745

varWeightedLogRatios=0.490583643952767
cont.varWeightedLogRatios=0.0387399175821618

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.5356578259312	0.0794947399160015	57.0560747883926	2.97982349407495e-192	***
df.mm.trans1	0.288922405325704	0.0662926779834506	4.35828532070814	1.67566807669853e-05	***
df.mm.trans2	-0.616907303748616	0.0650717138564026	-9.480421940476	2.44843918327159e-19	***
df.mm.exp2	0.0873034344062843	0.0885743838386034	0.985651049691353	0.324910800216799	   
df.mm.exp3	-0.388396854330824	0.0885743838386034	-4.38497946583004	1.49125475918592e-05	***
df.mm.exp4	-0.166472249481512	0.0885743838386034	-1.87946268737077	0.0609210235628548	.  
df.mm.exp5	-0.0637419219755647	0.0885743838386034	-0.7196428494689	0.47217265454421	   
df.mm.exp6	-0.0333751636432316	0.0885743838386034	-0.376803791308856	0.70652278770564	   
df.mm.exp7	-0.231014892528251	0.0885743838386034	-2.60814563439918	0.00945042536507208	** 
df.mm.exp8	-0.312423211904562	0.0885743838386034	-3.52724115443859	0.000469510313680264	***
df.mm.trans1:exp2	-0.239574336608898	0.0751383430232487	-3.18844316988426	0.00154499263521559	** 
df.mm.trans2:exp2	0.134798423051271	0.07265784274434	1.85524945360109	0.0643092120050354	.  
df.mm.trans1:exp3	0.188753998600455	0.0751383430232487	2.51208625324693	0.0124018284532732	*  
df.mm.trans2:exp3	0.386757697744847	0.07265784274434	5.3230000112407	1.71981407179457e-07	***
df.mm.trans1:exp4	-0.00340337797651135	0.0751383430232487	-0.0452948233827609	0.963895319589109	   
df.mm.trans2:exp4	0.195054683738431	0.07265784274434	2.68456475407296	0.0075697509317651	** 
df.mm.trans1:exp5	0.103506745045315	0.0751383430232487	1.37754894346404	0.169126561288118	   
df.mm.trans2:exp5	-0.0130001364428867	0.07265784274434	-0.178922686827216	0.858090611680187	   
df.mm.trans1:exp6	0.0221620685656009	0.0751383430232487	0.294950190194422	0.768187679166972	   
df.mm.trans2:exp6	0.0585653598920866	0.07265784274434	0.806043197541104	0.420705398907173	   
df.mm.trans1:exp7	0.0660725374873233	0.0751383430232487	0.879345149611294	0.379751511573946	   
df.mm.trans2:exp7	0.241142476175809	0.07265784274434	3.31887745448641	0.000988155320267934	***
df.mm.trans1:exp8	0.0605559298654099	0.0751383430232487	0.805925808700269	0.420773005209624	   
df.mm.trans2:exp8	0.34031821439718	0.07265784274434	4.6838469398913	3.88464249594962e-06	***
df.mm.trans1:probe2	-0.0254166506700384	0.0438713405322341	-0.579345202624108	0.562688200498162	   
df.mm.trans1:probe3	-0.177291250498253	0.0438713405322341	-4.04116328216571	6.39973843107516e-05	***
df.mm.trans1:probe4	-0.142166737086145	0.0438713405322341	-3.24053779441021	0.00129468250055626	** 
df.mm.trans1:probe5	-0.0852710977776844	0.0438713405322341	-1.94366291850672	0.0526495823297042	.  
df.mm.trans1:probe6	0.211161523407560	0.0438713405322341	4.81319970727612	2.12201662451711e-06	***
df.mm.trans1:probe7	-0.641333038836306	0.0438713405322341	-14.6184965185892	5.92566451303549e-39	***
df.mm.trans2:probe2	-0.0138047841017842	0.0438713405322341	-0.314665199064097	0.753182859578393	   
df.mm.trans2:probe3	-0.0318940667371852	0.0438713405322341	-0.726990931898953	0.467664328347252	   
df.mm.trans2:probe4	0.0464595030793864	0.0438713405322341	1.05899438028913	0.29025277978349	   
df.mm.trans2:probe5	-0.0633255100194381	0.0438713405322341	-1.44343685994528	0.149694070016053	   
df.mm.trans2:probe6	0.0237709532603985	0.0438713405322341	0.541833301011922	0.588240405107686	   
df.mm.trans3:probe2	-0.14415871357696	0.0438713405322341	-3.28594275506673	0.00110772855985345	** 
df.mm.trans3:probe3	-0.111614239937983	0.0438713405322341	-2.54412649770698	0.0113370459947235	*  
df.mm.trans3:probe4	0.0489423601422578	0.0438713405322341	1.11558843537725	0.265280019550755	   
df.mm.trans3:probe5	-0.313112701258927	0.0438713405322341	-7.13706710258534	4.63292844596279e-12	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.01342315876054	0.194888081582214	20.5934766568446	1.91790930102164e-64	***
df.mm.trans1	0.198205432110708	0.162522109623778	1.21955980370629	0.223363196003101	   
df.mm.trans2	0.128455954775625	0.159528812750897	0.805221029107815	0.421179034788052	   
df.mm.exp2	0.102609040612147	0.217147596958895	0.472531319937061	0.636809888470856	   
df.mm.exp3	-0.257013705409108	0.217147596958894	-1.18358991307539	0.237290860859707	   
df.mm.exp4	0.0964387047950235	0.217147596958894	0.444115919980819	0.657203216604721	   
df.mm.exp5	0.136208256495140	0.217147596958895	0.627261173518413	0.530852297677979	   
df.mm.exp6	0.252362359928462	0.217147596958895	1.16216971066105	0.245871811231950	   
df.mm.exp7	0.174691640162827	0.217147596958895	0.804483414089524	0.421604228203041	   
df.mm.exp8	0.153340844321015	0.217147596958895	0.706159526831153	0.48050734440078	   
df.mm.trans1:exp2	-0.0804756109090773	0.184208005970463	-0.436873579327388	0.662442970491017	   
df.mm.trans2:exp2	-0.0665669294721741	0.178126849641989	-0.373705197200561	0.708825174190275	   
df.mm.trans1:exp3	0.236908084349522	0.184208005970463	1.28609005402028	0.199168823910890	   
df.mm.trans2:exp3	0.119432077059110	0.178126849641989	0.670488908882362	0.502939988188006	   
df.mm.trans1:exp4	-0.0668440993256593	0.184208005970463	-0.362872932549834	0.716894889307037	   
df.mm.trans2:exp4	-0.0836955119841508	0.178126849641989	-0.469864661910137	0.638712321244048	   
df.mm.trans1:exp5	-0.0463258204465084	0.184208005970464	-0.251486466087345	0.801569473410413	   
df.mm.trans2:exp5	-0.0997764995664294	0.178126849641989	-0.560142952996513	0.57570108021132	   
df.mm.trans1:exp6	-0.238304503117961	0.184208005970463	-1.29367071676663	0.196538984682243	   
df.mm.trans2:exp6	-0.218271285160210	0.178126849641989	-1.22536992934477	0.221169726311355	   
df.mm.trans1:exp7	-0.0660155582609553	0.184208005970463	-0.358375076659482	0.720255064407685	   
df.mm.trans2:exp7	-0.127176649238627	0.178126849641989	-0.713966757365525	0.475671541159054	   
df.mm.trans1:exp8	-0.0888072547320043	0.184208005970463	-0.482103121762492	0.630001071410289	   
df.mm.trans2:exp8	-0.0859128514870011	0.178126849641989	-0.482312754420092	0.629852300791079	   
df.mm.trans1:probe2	0.08050793112827	0.107554303615579	0.748532865928097	0.454586540804039	   
df.mm.trans1:probe3	8.5362841728158e-05	0.107554303615579	0.000793672022955606	0.999367144120446	   
df.mm.trans1:probe4	-0.0380465473786986	0.107554303615579	-0.353742677881907	0.72372142961243	   
df.mm.trans1:probe5	0.0206381510022189	0.107554303615579	0.191885868890787	0.847930711911386	   
df.mm.trans1:probe6	0.0351449798104311	0.107554303615579	0.326764979447465	0.744019607587659	   
df.mm.trans1:probe7	0.0324699626483716	0.107554303615579	0.301893662613687	0.762892818775346	   
df.mm.trans2:probe2	0.198259982972191	0.107554303615579	1.84334774441767	0.0660310305317262	.  
df.mm.trans2:probe3	-0.0334391695780561	0.107554303615579	-0.310904988958643	0.756037686426852	   
df.mm.trans2:probe4	0.157053617709833	0.107554303615579	1.46022625250938	0.145026833852310	   
df.mm.trans2:probe5	0.0802125691146253	0.107554303615579	0.745786699538508	0.456242106446777	   
df.mm.trans2:probe6	0.16423991753906	0.107554303615579	1.52704180137772	0.127555004069916	   
df.mm.trans3:probe2	0.00795106116307	0.107554303615579	0.0739260159359937	0.941106866721528	   
df.mm.trans3:probe3	-0.128148670369769	0.107554303615579	-1.19147877920161	0.234184728883725	   
df.mm.trans3:probe4	-0.106644107561328	0.107554303615579	-0.991537334875	0.32203335424736	   
df.mm.trans3:probe5	-0.132599650894333	0.107554303615579	-1.23286234429327	0.218364087020912