chr9.24412_chr9_21485436_21485735_+_1.R 

fitVsDatCorrelation=0.921685034144652
cont.fitVsDatCorrelation=0.275681622822548

fstatistic=5746.72036193811,38,370
cont.fstatistic=927.847719907287,38,370

residuals=-0.657174691865897,-0.11033949578543,0.000396195649625985,0.097881817296547,1.07586090810877
cont.residuals=-1.01262299205662,-0.38816414511839,-0.077287304302037,0.327399796497423,2.03056915070196

predictedValues:
Include	Exclude	Both
chr9.24412_chr9_21485436_21485735_+_1.R.tl.Lung	118.208968133217	156.303516624051	74.386383926023
chr9.24412_chr9_21485436_21485735_+_1.R.tl.cerebhem	103.095392877505	100.102050605420	74.2376587643477
chr9.24412_chr9_21485436_21485735_+_1.R.tl.cortex	87.1474128536627	123.986546001866	80.5177878464416
chr9.24412_chr9_21485436_21485735_+_1.R.tl.heart	87.0509720975882	118.68865540558	79.1954306625161
chr9.24412_chr9_21485436_21485735_+_1.R.tl.kidney	124.248365841310	150.583085231904	75.615832044139
chr9.24412_chr9_21485436_21485735_+_1.R.tl.liver	112.193593660316	140.069820704737	75.1077586148436
chr9.24412_chr9_21485436_21485735_+_1.R.tl.stomach	93.7608565973465	140.780427750533	94.3808229669406
chr9.24412_chr9_21485436_21485735_+_1.R.tl.testicle	95.9307561859642	137.552131403560	81.8874176629058


diffExp=-38.0945484908344,2.99334227208482,-36.8391331482029,-31.6376833079919,-26.3347193905943,-27.876227044421,-47.0195711531867,-41.6213752175954
diffExpScore=1.02015392736356
diffExp1.5=0,0,0,0,0,0,-1,0
diffExp1.5Score=0.5
diffExp1.4=0,0,-1,0,0,0,-1,-1
diffExp1.4Score=0.75
diffExp1.3=-1,0,-1,-1,0,0,-1,-1
diffExp1.3Score=0.833333333333333
diffExp1.2=-1,0,-1,-1,-1,-1,-1,-1
diffExp1.2Score=0.875

cont.predictedValues:
Include	Exclude	Both
Lung	95.2296779990648	104.871302888684	95.7396542307608
cerebhem	108.987096278636	96.0044505163592	99.4389084057455
cortex	88.0604336583256	110.189404186291	83.4558681137007
heart	83.8380850989732	77.925501922423	108.079766914849
kidney	86.0409598656199	96.842027544045	107.479485807299
liver	106.161374904801	94.6690351496062	99.5078959604125
stomach	87.3662991970463	91.1865465707363	111.037800233829
testicle	83.6450637479324	110.454856932138	87.963060926395
cont.diffExp=-9.64162488961883,12.9826457622767,-22.1289705279655,5.91258317655021,-10.8010676784250,11.4923397551945,-3.82024737369005,-26.8097931842059
cont.diffExpScore=2.36428888628687

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,-1
cont.diffExp1.3Score=0.5
cont.diffExp1.2=0,0,-1,0,0,0,0,-1
cont.diffExp1.2Score=0.666666666666667

tran.correlation=0.581833899542605
cont.tran.correlation=-0.0103550600280833

tran.covariance=0.0103410128674603
cont.tran.covariance=0.000452474074690235

tran.mean=118.10640949841
cont.tran.mean=95.0920072787926

weightedLogRatios:
wLogRatio
Lung	-1.37218181822823
cerebhem	0.136153318816026
cortex	-1.63730443378297
heart	-1.43271032841411
kidney	-0.945475992334325
liver	-1.07211267397987
stomach	-1.92820722156335
testicle	-1.70955862554987

cont.weightedLogRatios:
wLogRatio
Lung	-0.444069685888548
cerebhem	0.586968271692101
cortex	-1.02899945676804
heart	0.321228453674924
kidney	-0.533809199813899
liver	0.527916711504557
stomach	-0.192226479781873
testicle	-1.26934711758188

varWeightedLogRatios=0.416441268533884
cont.varWeightedLogRatios=0.485614100869158

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.86788984131882	0.105798983292467	46.0107431076362	3.71527006713137e-155	***
df.mm.trans1	0.0754654344217551	0.0871296747997544	0.866127810016431	0.386981356313138	   
df.mm.trans2	0.159156945120441	0.0871296747997544	1.82666749860163	0.0685553294619613	.  
df.mm.exp2	-0.580407473846268	0.119103847807266	-4.87312110004611	1.63233945576126e-06	***
df.mm.exp3	-0.61568477957419	0.119103847807266	-5.16931057148122	3.85363633225959e-07	***
df.mm.exp4	-0.643901844501985	0.119103847807266	-5.40622201848548	1.15651666409336e-07	***
df.mm.exp5	-0.00384897157586854	0.119103847807266	-0.0323160976469623	0.974237396990474	   
df.mm.exp6	-0.171537749968476	0.119103847807266	-1.44023684479160	0.150646002359164	   
df.mm.exp7	-0.57436981516946	0.119103847807266	-4.82242871027061	2.07544192708563e-06	***
df.mm.exp8	-0.432696522001222	0.119103847807266	-3.63293487126808	0.000319783007374222	***
df.mm.trans1:exp2	0.443608203285281	0.0987556935660737	4.49197597896955	9.44525017045128e-06	***
df.mm.trans2:exp2	0.134797909157735	0.0987556935660737	1.36496341922349	0.173093964563902	   
df.mm.trans1:exp3	0.310831890343071	0.0987556935660737	3.14748323989143	0.00178042232075105	** 
df.mm.trans2:exp3	0.384058102939209	0.0987556935660737	3.88897175515506	0.000119331716804400	***
df.mm.trans1:exp4	0.337941703146174	0.0987556935660737	3.42199716232127	0.000691092607696432	***
df.mm.trans2:exp4	0.3686058315134	0.0987556935660737	3.73250207864501	0.000219388859535609	***
df.mm.trans1:exp5	0.0536775096582269	0.0987556935660737	0.543538379610623	0.587086500135412	   
df.mm.trans2:exp5	-0.0334357715919622	0.0987556935660737	-0.338570571321962	0.73512530136971	   
df.mm.trans1:exp6	0.119309669300038	0.0987556935660737	1.20812952642788	0.227769045644462	   
df.mm.trans2:exp6	0.0618790312096676	0.0987556935660738	0.626586974129918	0.531316401700578	   
df.mm.trans1:exp7	0.342663302395009	0.0987556935660737	3.46980806899752	0.000582252042877087	***
df.mm.trans2:exp7	0.469771505408858	0.0987556935660738	4.7569055357254	2.82237130569930e-06	***
df.mm.trans1:exp8	0.223869188859659	0.0987556935660737	2.26689905944387	0.0239729487854241	*  
df.mm.trans2:exp8	0.304899768365315	0.0987556935660738	3.08741458193818	0.00217135871497891	** 
df.mm.trans1:probe2	-0.81289279783704	0.0576609023783455	-14.0978160990821	1.99888835113539e-36	***
df.mm.trans1:probe3	-0.591271142972022	0.0576609023783455	-10.2542818198085	6.9923567723564e-22	***
df.mm.trans1:probe4	-0.473128509866490	0.0576609023783455	-8.20536083119248	3.85156495434799e-15	***
df.mm.trans1:probe5	-0.118220124931339	0.0576609023783455	-2.05026491183974	0.0410427819360876	*  
df.mm.trans1:probe6	0.115598263338577	0.0576609023783455	2.00479455871280	0.0457131119730684	*  
df.mm.trans2:probe2	0.387609844865847	0.0576609023783455	6.72222994920408	6.79249535381299e-11	***
df.mm.trans2:probe3	-0.606734748476527	0.0576609023783455	-10.5224636356781	7.93316853619498e-23	***
df.mm.trans2:probe4	-0.117567552671122	0.0576609023783455	-2.03894749859610	0.0421655389593423	*  
df.mm.trans2:probe5	0.0891375532701547	0.0576609023783455	1.54589244346669	0.122985400260288	   
df.mm.trans2:probe6	0.519837352233481	0.0576609023783455	9.01542172931213	1.07102398947395e-17	***
df.mm.trans3:probe2	-1.08037467172117	0.0576609023783455	-18.736693793521	1.46155530919988e-55	***
df.mm.trans3:probe3	-1.16142924415411	0.0576609023783455	-20.142404926883	1.90321856434411e-61	***
df.mm.trans3:probe4	-0.83468179770108	0.0576609023783455	-14.4756977999454	6.06026490389267e-38	***
df.mm.trans3:probe5	-0.889710824011965	0.0576609023783455	-15.4300537680467	7.9998962943792e-42	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.46954808712572	0.262152443741329	17.0494236991966	1.63292752795849e-48	***
df.mm.trans1	0.04199173618047	0.215892974207524	0.194502560051381	0.845889140470422	   
df.mm.trans2	0.101199148382858	0.215892974207524	0.468746835112764	0.639526656110376	   
df.mm.exp2	0.00868759656505246	0.295119705218312	0.0294375347068942	0.976531508990441	   
df.mm.exp3	0.108513123572213	0.295119705218312	0.367691894690467	0.71331322330355	   
df.mm.exp4	-0.545621866059974	0.295119705218312	-1.8488154345924	0.0652820391594586	.  
df.mm.exp5	-0.29678844648337	0.295119705218312	-1.00565445558379	0.315239034938168	   
df.mm.exp6	-0.0322826639489520	0.295119705218312	-0.109388371491735	0.912953758498961	   
df.mm.exp7	-0.374246675974605	0.295119705218312	-1.26811822239304	0.205553093958258	   
df.mm.exp8	0.00687937758447176	0.295119705218312	0.0233104650852873	0.98141519013502	   
df.mm.trans1:exp2	0.126250258988482	0.244700332612358	0.515938240216786	0.606205713239805	   
df.mm.trans2:exp2	-0.0970269582410746	0.244700332612358	-0.396513389275935	0.691954916162894	   
df.mm.trans1:exp3	-0.186781435581887	0.244700332612358	-0.763306831616683	0.445766838958232	   
df.mm.trans2:exp3	-0.0590462938504844	0.244700332612358	-0.241300423338707	0.809455947759122	   
df.mm.trans1:exp4	0.418217609523409	0.244700332612358	1.70910110770437	0.0882707537732405	.  
df.mm.trans2:exp4	0.248641221174156	0.244700332612358	1.01610495792844	0.310243375068983	   
df.mm.trans1:exp5	0.195320269956946	0.244700332612358	0.798201898100246	0.425265343537817	   
df.mm.trans2:exp5	0.217135603770624	0.244700332612358	0.887353120662077	0.37546524352472	   
df.mm.trans1:exp6	0.140951368236977	0.244700332612358	0.576016251110969	0.564954389231301	   
df.mm.trans2:exp6	-0.0700642792996418	0.244700332612358	-0.286326865810330	0.77478803455461	   
df.mm.trans1:exp7	0.288064654661960	0.244700332612358	1.17721398899076	0.239866814593836	   
df.mm.trans2:exp7	0.234420134886937	0.244700332612358	0.957988623817255	0.338694040348038	   
df.mm.trans1:exp8	-0.136588599579684	0.244700332612358	-0.558187224845586	0.577054142505908	   
df.mm.trans2:exp8	0.0449936137348808	0.244700332612358	0.183872303133144	0.85421435946906	   
df.mm.trans1:probe2	0.00173340413260144	0.142874212931021	0.0121323792239425	0.990326538370607	   
df.mm.trans1:probe3	0.164604125156873	0.142874212931021	1.15209121212337	0.250027440160007	   
df.mm.trans1:probe4	0.0498450570616778	0.142874212931021	0.34887371233144	0.727382564607904	   
df.mm.trans1:probe5	0.128442629229455	0.142874212931021	0.898990983708632	0.369242131900121	   
df.mm.trans1:probe6	0.147644733984364	0.142874212931021	1.03338965762595	0.302096548560921	   
df.mm.trans2:probe2	0.256316452803949	0.142874212931021	1.79400080354387	0.0736293833654508	.  
df.mm.trans2:probe3	0.112435816062999	0.142874212931021	0.7869566785805	0.431810997611610	   
df.mm.trans2:probe4	0.283744738275921	0.142874212931021	1.98597586264858	0.0477735727652699	*  
df.mm.trans2:probe5	0.137056070832707	0.142874212931021	0.959277871220033	0.338045199545227	   
df.mm.trans2:probe6	0.112300359191685	0.142874212931021	0.786008593768445	0.432365528493144	   
df.mm.trans3:probe2	-0.158959698903905	0.142874212931021	-1.11258494897642	0.266609057811615	   
df.mm.trans3:probe3	-0.120021026931353	0.142874212931021	-0.840046810891615	0.401424623158169	   
df.mm.trans3:probe4	-0.047995064870547	0.142874212931021	-0.335925314204313	0.737117597804252	   
df.mm.trans3:probe5	0.0714437943288897	0.142874212931021	0.50004680945037	0.617339377745646