chr11.3500_chr11_61920321_61921662_-_1.R 

fitVsDatCorrelation=0.93451660811566
cont.fitVsDatCorrelation=0.322765905756391

fstatistic=7904.8216728529,42,462
cont.fstatistic=1108.38072635013,42,462

residuals=-0.879816877378614,-0.102065531420319,0.00240336019085744,0.0914637602318232,0.58875589070583
cont.residuals=-1.00432740771971,-0.329574795246681,-0.09339619503908,0.253337325130005,1.70425558290438

predictedValues:
Include	Exclude	Both
chr11.3500_chr11_61920321_61921662_-_1.R.tl.Lung	127.466437855849	144.707376170022	77.8167845218114
chr11.3500_chr11_61920321_61921662_-_1.R.tl.cerebhem	87.6363647401276	86.8007490835798	79.256557673363
chr11.3500_chr11_61920321_61921662_-_1.R.tl.cortex	101.660136183465	106.253166625821	75.8857580309624
chr11.3500_chr11_61920321_61921662_-_1.R.tl.heart	107.922557861213	133.052227899317	72.5928500933498
chr11.3500_chr11_61920321_61921662_-_1.R.tl.kidney	133.977529021604	149.593024370462	73.4620592830574
chr11.3500_chr11_61920321_61921662_-_1.R.tl.liver	129.429186959881	139.281476634287	71.7341946829847
chr11.3500_chr11_61920321_61921662_-_1.R.tl.stomach	125.258995011596	116.571936917222	74.2001297212306
chr11.3500_chr11_61920321_61921662_-_1.R.tl.testicle	122.06534730936	142.641424029477	69.3864584665753


diffExp=-17.2409383141727,0.835615656547773,-4.59303044235666,-25.1296700381037,-15.6154953488578,-9.85228967440528,8.68705809437412,-20.5760767201170
diffExpScore=1.21359276201536
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,-1,0,0,0,0
diffExp1.2Score=0.5

cont.predictedValues:
Include	Exclude	Both
Lung	127.742355312610	89.6229448693144	106.442139469848
cerebhem	87.780318273285	83.7386672985141	86.5051564239463
cortex	107.017786255828	92.7850187028042	91.238759480589
heart	101.753480755374	109.895708409667	108.755845445758
kidney	104.951031108638	89.7601393274165	95.7925968373527
liver	95.8143574498925	79.2601573437475	105.546428637235
stomach	109.42754504987	88.2382496224652	127.550189432789
testicle	85.1837133215114	105.943832945908	110.480187375067
cont.diffExp=38.1194104432958,4.04165097477087,14.2327675530239,-8.14222765429288,15.1908917812214,16.554200106145,21.1892954274048,-20.7601196243964
cont.diffExpScore=1.69762466461825

cont.diffExp1.5=0,0,0,0,0,0,0,0
cont.diffExp1.5Score=0
cont.diffExp1.4=1,0,0,0,0,0,0,0
cont.diffExp1.4Score=0.5
cont.diffExp1.3=1,0,0,0,0,0,0,0
cont.diffExp1.3Score=0.5
cont.diffExp1.2=1,0,0,0,0,1,1,-1
cont.diffExp1.2Score=1.33333333333333

tran.correlation=0.865015367424168
cont.tran.correlation=-0.137312135984443

tran.covariance=0.0245895032186468
cont.tran.covariance=-0.00164983679745378

tran.mean=122.144871042080
cont.tran.mean=97.4322066279278

weightedLogRatios:
wLogRatio
Lung	-0.623047913330351
cerebhem	0.0428108238510199
cortex	-0.205203450342543
heart	-1.00185928124628
kidney	-0.546027569905104
liver	-0.359465081996852
stomach	0.344600748913194
testicle	-0.760574732836238

cont.weightedLogRatios:
wLogRatio
Lung	1.65606383613240
cerebhem	0.209817086199240
cortex	0.656699403189168
heart	-0.358801350077225
kidney	0.715364043685566
liver	0.847395909756057
stomach	0.987364022998525
testicle	-0.993191412644027

varWeightedLogRatios=0.193197598087118
cont.varWeightedLogRatios=0.686749114017879

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.87998715498754	0.091527573640694	53.3171257674185	1.63773920101544e-199	***
df.mm.trans1	0.050026361313042	0.0735334227221163	0.68032140299102	0.496641751872339	   
df.mm.trans2	-0.100701485603457	0.0735334227221163	-1.36946550120492	0.171519103920036	   
df.mm.exp2	-0.904088428085693	0.0987326040962403	-9.15693895001925	1.73621744473765e-18	***
df.mm.exp3	-0.50997872117203	0.0987326040962403	-5.16525139633635	3.57717348314477e-07	***
df.mm.exp4	-0.180920336347522	0.0987326040962403	-1.83242747422289	0.067531227346683	.  
df.mm.exp5	0.140611897106766	0.0987326040962403	1.42416882846221	0.155072666885037	   
df.mm.exp6	0.0584537047269971	0.0987326040962403	0.592040544884433	0.554113050091465	   
df.mm.exp7	-0.186083335997227	0.0987326040962403	-1.88472022692566	0.0600950647155461	.  
df.mm.exp8	0.0569892082725664	0.0987326040962403	0.577207588052836	0.564080390479963	   
df.mm.trans1:exp2	0.529431365049105	0.0780549770659474	6.78280085332415	3.61815447686799e-11	***
df.mm.trans2:exp2	0.392990071766842	0.0780549770659474	5.03478556447222	6.86913193209037e-07	***
df.mm.trans1:exp3	0.283760875343639	0.0780549770659474	3.63539758782959	0.00030874989962777	***
df.mm.trans2:exp3	0.201089724126505	0.0780549770659474	2.57625755186126	0.0102971065550578	*  
df.mm.trans1:exp4	0.0144811519793251	0.0780549770659474	0.185525030224405	0.852898671881418	   
df.mm.trans2:exp4	0.096948470515588	0.0780549770659474	1.24205366729757	0.214846889390976	   
df.mm.trans1:exp5	-0.09079290253025	0.0780549770659474	-1.16319171362437	0.245352152174364	   
df.mm.trans2:exp5	-0.107407069136303	0.0780549770659474	-1.37604382415686	0.169474707908288	   
df.mm.trans1:exp6	-0.0431728894335459	0.0780549770659474	-0.553108732542063	0.580456494082384	   
df.mm.trans2:exp6	-0.0966704153544583	0.0780549770659474	-1.23849136836954	0.216162829791464	   
df.mm.trans1:exp7	0.168613792399795	0.0780549770659474	2.16019270952236	0.0312713276895313	*  
df.mm.trans2:exp7	-0.0301217052370579	0.0780549770659474	-0.385903710042841	0.699745621154662	   
df.mm.trans1:exp8	-0.100285770700127	0.0780549770659474	-1.28480943137549	0.199502671990654	   
df.mm.trans2:exp8	-0.0713688593295124	0.0780549770659474	-0.914340917289797	0.361014676821726	   
df.mm.trans1:probe2	0.0812705784650377	0.0523608704104936	1.55212428341814	0.121317215823063	   
df.mm.trans1:probe3	-0.102817399831849	0.0523608704104936	-1.96363045583068	0.0501722588792832	.  
df.mm.trans1:probe4	-0.509381002287302	0.0523608704104936	-9.72827606366943	1.79640120640533e-20	***
df.mm.trans1:probe5	-0.232989169756907	0.0523608704104936	-4.44968099136514	1.07897850730581e-05	***
df.mm.trans1:probe6	-0.468489289444072	0.0523608704104937	-8.94731668460159	8.86844074449895e-18	***
df.mm.trans2:probe2	-0.103070051148206	0.0523608704104936	-1.96845564904036	0.0496130696975067	*  
df.mm.trans2:probe3	0.615647276687326	0.0523608704104936	11.7577739227945	4.20251434562552e-28	***
df.mm.trans2:probe4	0.978669456678934	0.0523608704104936	18.6908553850701	1.80534483727075e-58	***
df.mm.trans2:probe5	0.699187199862862	0.0523608704104936	13.3532386757791	1.26153668749184e-34	***
df.mm.trans2:probe6	0.740985196303918	0.0523608704104937	14.1515064683764	5.02219269247149e-38	***
df.mm.trans3:probe2	-0.490453182283684	0.0523608704104936	-9.36678818435745	3.30844347213286e-19	***
df.mm.trans3:probe3	-0.473806656182695	0.0523608704104936	-9.04886898304386	4.03757349162863e-18	***
df.mm.trans3:probe4	-0.585940588030232	0.0523608704104936	-11.1904287197029	6.91643304233543e-26	***
df.mm.trans3:probe5	-0.52816185040819	0.0523608704104936	-10.0869570400102	9.3090150511468e-22	***
df.mm.trans3:probe6	-0.658534571269114	0.0523608704104936	-12.5768453829434	2.11130680379317e-31	***
df.mm.trans3:probe7	-0.77373663903117	0.0523608704104936	-14.7770010881275	9.63571293454776e-41	***
df.mm.trans3:probe8	-0.321270989141079	0.0523608704104936	-6.13570757365968	1.82445757338192e-09	***
df.mm.trans3:probe9	-0.442689474490252	0.0523608704104937	-8.45458585809782	3.69827421260128e-16	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.50033238834876	0.243394655695500	18.4898570409818	1.54013866683281e-57	***
df.mm.trans1	0.348288863144868	0.195543718615563	1.78113040710656	0.0755480476385648	.  
df.mm.trans2	-0.0802658700273168	0.195543718615563	-0.410475317722267	0.681647601033695	   
df.mm.exp2	-0.235691076702439	0.262554629430710	-0.897683949483126	0.369821629117542	   
df.mm.exp3	0.0117752281307534	0.262554629430710	0.044848678373279	0.964247302223467	   
df.mm.exp4	-0.0450457848986437	0.262554629430710	-0.171567284859213	0.86385284961185	   
df.mm.exp5	-0.0895757482191535	0.262554629430710	-0.341169943997476	0.733130752583353	   
df.mm.exp6	-0.402028030787986	0.262554629430710	-1.53121669063574	0.126400267028600	   
df.mm.exp7	-0.351231958830035	0.262554629430710	-1.3377481082379	0.181636687533241	   
df.mm.exp8	-0.275142080410380	0.262554629430710	-1.04794221685202	0.2952131402332	   
df.mm.trans1:exp2	-0.139486999533745	0.207567659805631	-0.672007381421377	0.501914906240113	   
df.mm.trans2:exp2	0.167780554084513	0.207567659805631	0.808317414387313	0.419323899226145	   
df.mm.trans1:exp3	-0.188795567089081	0.207567659805631	-0.909561572674045	0.363528030095135	   
df.mm.trans2:exp3	0.0228985939084982	0.207567659805631	0.110318697671596	0.912204533993428	   
df.mm.trans1:exp4	-0.182416568761829	0.207567659805631	-0.878829432931152	0.37995060562883	   
df.mm.trans2:exp4	0.248966227259764	0.207567659805631	1.19944613478275	0.230969291816413	   
df.mm.trans1:exp5	-0.106945767097834	0.207567659805631	-0.515233284404608	0.606636446130516	   
df.mm.trans2:exp5	0.0911053738855481	0.207567659805631	0.438918923934781	0.660925477673573	   
df.mm.trans1:exp6	0.114425187236265	0.207567659805631	0.551266933121539	0.581717204224907	   
df.mm.trans2:exp6	0.279152235379425	0.207567659805631	1.34487345302648	0.179325933928926	   
df.mm.trans1:exp7	0.196479213735407	0.207567659805631	0.946579124702724	0.344348101003059	   
df.mm.trans2:exp7	0.335661128695974	0.207567659805631	1.61711669828668	0.106535634457766	   
df.mm.trans1:exp8	-0.130063048521720	0.207567659805631	-0.626605554273304	0.53122731536554	   
df.mm.trans2:exp8	0.442439787890313	0.207567659805631	2.13154490590981	0.0335713733771237	*  
df.mm.trans1:probe2	0.120738724982562	0.139240619176782	0.867122867568334	0.386324828422878	   
df.mm.trans1:probe3	-0.159605738960148	0.139240619176782	-1.14625846899970	0.252281561809344	   
df.mm.trans1:probe4	0.0650284180449965	0.139240619176782	0.467021896551862	0.640704382202414	   
df.mm.trans1:probe5	-0.164921913849994	0.139240619176782	-1.18443823953847	0.236848603065378	   
df.mm.trans1:probe6	0.159672531819424	0.139240619176782	1.14673816278209	0.252083397028406	   
df.mm.trans2:probe2	0.217159209124518	0.139240619176782	1.55959669246234	0.119539935612662	   
df.mm.trans2:probe3	0.191406656472824	0.139240619176782	1.37464669149317	0.16990736503217	   
df.mm.trans2:probe4	0.37430521698138	0.139240619176782	2.68818983421896	0.0074435668062018	** 
df.mm.trans2:probe5	0.122046511837198	0.139240619176782	0.876515147366916	0.381205563416476	   
df.mm.trans2:probe6	0.228255155689099	0.139240619176782	1.63928569866026	0.101834498031756	   
df.mm.trans3:probe2	0.0581259499271707	0.139240619176782	0.417449665699726	0.67654345746507	   
df.mm.trans3:probe3	-0.167527792299471	0.139240619176782	-1.20315316959899	0.229533229467525	   
df.mm.trans3:probe4	-0.245194532155379	0.139240619176782	-1.76094112195864	0.0789098874243414	.  
df.mm.trans3:probe5	-0.188707452348644	0.139240619176782	-1.35526151394844	0.175996469139922	   
df.mm.trans3:probe6	-0.0833883908223542	0.139240619176782	-0.598879775997569	0.549546584157851	   
df.mm.trans3:probe7	-0.0570167484537438	0.139240619176782	-0.409483588846688	0.682374588385884	   
df.mm.trans3:probe8	-0.0655380681655068	0.139240619176782	-0.470682108087286	0.638089902208531	   
df.mm.trans3:probe9	-0.157537483526053	0.139240619176782	-1.13140464655677	0.258471751458728