chr1.476_chr1_53907594_53909573_-_1.R 

fitVsDatCorrelation=0.799197328130218
cont.fitVsDatCorrelation=0.298817417074591

fstatistic=7864.97653295433,40,416
cont.fstatistic=3113.81122300933,40,416

residuals=-0.52419058954742,-0.0837534320494001,-0.000318825254628599,0.0770963234198772,0.76834040745879
cont.residuals=-0.500282561905144,-0.163415864897411,-0.048238396941706,0.123212192813562,0.942007887101641

predictedValues:
Include	Exclude	Both
chr1.476_chr1_53907594_53909573_-_1.R.tl.Lung	55.086473438417	49.0566932955504	59.298970947222
chr1.476_chr1_53907594_53909573_-_1.R.tl.cerebhem	70.6288280334786	62.7521180832335	58.5370872539381
chr1.476_chr1_53907594_53909573_-_1.R.tl.cortex	61.0117233400289	47.4324063924204	62.3257342151162
chr1.476_chr1_53907594_53909573_-_1.R.tl.heart	77.8079287293337	47.6890220866483	86.3962126393007
chr1.476_chr1_53907594_53909573_-_1.R.tl.kidney	59.5653245007074	47.7451247379388	67.4689852153888
chr1.476_chr1_53907594_53909573_-_1.R.tl.liver	56.7548941756427	53.4917408356385	64.7823764235552
chr1.476_chr1_53907594_53909573_-_1.R.tl.stomach	61.0985619061857	51.3000586978725	67.207419945162
chr1.476_chr1_53907594_53909573_-_1.R.tl.testicle	61.052019506842	51.5938029119319	68.0324187263514


diffExp=6.02978014286663,7.87670995024504,13.5793169476084,30.1189066426854,11.8201997627686,3.2631533400042,9.79850320831319,9.45821659491005
diffExpScore=0.989240924244437
diffExp1.5=0,0,0,1,0,0,0,0
diffExp1.5Score=0.5
diffExp1.4=0,0,0,1,0,0,0,0
diffExp1.4Score=0.5
diffExp1.3=0,0,0,1,0,0,0,0
diffExp1.3Score=0.5
diffExp1.2=0,0,1,1,1,0,0,0
diffExp1.2Score=0.75

cont.predictedValues:
Include	Exclude	Both
Lung	70.4334841690718	62.2180015841195	57.3560964191035
cerebhem	60.888160329387	65.0244282105313	57.6834450054422
cortex	61.6568909858974	57.3410725224432	64.4118392910425
heart	68.3356535824657	62.3716480210394	59.9215068233215
kidney	60.3701411940776	61.0662575771195	59.8477673158934
liver	66.359689708562	59.0772259198461	59.4362387791184
stomach	65.5925325252661	54.1999121400474	57.0256660949345
testicle	56.6129433852447	61.306177042806	55.6117269743288
cont.diffExp=8.21548258495225,-4.13626788114435,4.31581846345428,5.96400556142624,-0.696116383041904,7.28246378871592,11.3926203852187,-4.69323365756129
cont.diffExpScore=1.63017556223772

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=0.212261750225076
cont.tran.correlation=-0.0842480781755707

tran.covariance=0.00220986991434403
cont.tran.covariance=-0.000406347627806044

tran.mean=57.1291700419919
cont.tran.mean=62.0533886811203

weightedLogRatios:
wLogRatio
Lung	0.458022880284506
cerebhem	0.496434243714986
cortex	1.00331181442641
heart	2.01175973691392
kidney	0.879582967712365
liver	0.237399414894402
stomach	0.703571393383635
testicle	0.677938541027403

cont.weightedLogRatios:
wLogRatio
Lung	0.519991737422165
cerebhem	-0.27222342743371
cortex	0.296461452394113
heart	0.381608862343865
kidney	-0.0470772068210595
liver	0.480898856424717
stomach	0.779932604298745
testicle	-0.324629432040827

varWeightedLogRatios=0.295038551259322
cont.varWeightedLogRatios=0.159058469693972

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.97613075230583	0.0802349831417236	49.5560738796762	1.26222823362402e-176	***
df.mm.trans1	0.0260759647465192	0.0650791649482659	0.400680690467496	0.688860929944584	   
df.mm.trans2	-0.0869492235471712	0.0650791649482659	-1.33605315336008	0.182262294461932	   
df.mm.exp2	0.507681320788047	0.0880030930403294	5.76890315156754	1.55943956877047e-08	***
df.mm.exp3	0.0187084184127726	0.0880030930403294	0.212588191692297	0.831752312075412	   
df.mm.exp4	-0.0592881531971598	0.0880030930403294	-0.673705334083992	0.500872809600805	   
df.mm.exp5	-0.0780063286257154	0.0880030930403294	-0.886404397058717	0.375911775743378	   
df.mm.exp6	0.0279466834145048	0.0880030930403294	0.317564786066072	0.750974422101268	   
df.mm.exp7	0.0231076905827759	0.0880030930403294	0.262578163840063	0.79300571701764	   
df.mm.exp8	0.0158546309953681	0.0880030930403294	0.180159929016385	0.8571147430356	   
df.mm.trans1:exp2	-0.259147125431567	0.0709503618738634	-3.65251308925362	0.000292836083844957	***
df.mm.trans2:exp2	-0.261465624357962	0.0709503618738634	-3.68519084966471	0.000258745753156091	***
df.mm.trans1:exp3	0.0834534183121264	0.0709503618738634	1.17622258869505	0.240178587696255	   
df.mm.trans2:exp3	-0.0523793794755089	0.0709503618738634	-0.738253873442249	0.460776456428485	   
df.mm.trans1:exp4	0.404627295991776	0.0709503618738634	5.7029631041365	2.23642071648156e-08	***
df.mm.trans2:exp4	0.0310127443434264	0.0709503618738634	0.437104808549973	0.662262151402603	   
df.mm.trans1:exp5	0.156175734818998	0.0709503618738634	2.20119715663536	0.0282706222981992	*  
df.mm.trans2:exp5	0.0509066552842712	0.0709503618738634	0.717496767314222	0.473470322213346	   
df.mm.trans1:exp6	0.00189101532377654	0.0709503618738634	0.0266526522745355	0.978749558286478	   
df.mm.trans2:exp6	0.0586039463395411	0.0709503618738634	0.825985164723022	0.409285958604394	   
df.mm.trans1:exp7	0.080476443708961	0.0709503618738634	1.13426403450955	0.257336989685789	   
df.mm.trans2:exp7	0.0216075704747124	0.0709503618738634	0.304544894543691	0.760865087192052	   
df.mm.trans1:exp8	0.0869674536841996	0.0709503618738634	1.22575067113557	0.22098597336259	   
df.mm.trans2:exp8	0.0345703003471417	0.0709503618738634	0.487246286475625	0.626340454207857	   
df.mm.trans1:probe2	0.0346634618224356	0.0450881680818209	0.768792862897697	0.442452522577285	   
df.mm.trans1:probe3	0.00698490968358014	0.0450881680818209	0.154916688362781	0.876962131686455	   
df.mm.trans1:probe4	-0.06880918831223	0.0450881680818209	-1.52610299419047	0.127744116500763	   
df.mm.trans1:probe5	0.0894772840199655	0.0450881680818209	1.98449588498677	0.0478571651272576	*  
df.mm.trans1:probe6	0.024750744613086	0.0450881680818209	0.548941011934021	0.583340440609069	   
df.mm.trans2:probe2	-0.0072054792824803	0.0450881680818209	-0.159808650229582	0.873109373761669	   
df.mm.trans2:probe3	0.0704233371494468	0.0450881680818209	1.56190282607292	0.119071266310623	   
df.mm.trans2:probe4	-0.059972276946539	0.0450881680818209	-1.3301111909827	0.184210396062890	   
df.mm.trans2:probe5	0.0399409127473879	0.0450881680818209	0.885840220319168	0.376215401557286	   
df.mm.trans2:probe6	0.00614989171574007	0.0450881680818209	0.136397018938094	0.891573412068936	   
df.mm.trans3:probe2	-0.141621542045183	0.0450881680818208	-3.14099126378754	0.00180402419561679	** 
df.mm.trans3:probe3	0.161564711819243	0.0450881680818209	3.58330619079608	0.000379451171662574	***
df.mm.trans3:probe4	0.174388454750117	0.0450881680818209	3.86772100462491	0.000127460016883403	***
df.mm.trans3:probe5	0.434509086491596	0.0450881680818209	9.63687603592806	5.67886647602669e-20	***
df.mm.trans3:probe6	0.465107601908924	0.0450881680818209	10.3155133973263	2.28418925033987e-22	***
df.mm.trans3:probe7	0.0773929001643554	0.0450881680818209	1.71647914423828	0.086818794052763	.  

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.35562166859896	0.127388210018929	34.1917173335881	6.59176603597409e-123	***
df.mm.trans1	-0.0850873331058283	0.103325482322873	-0.823488370854596	0.410702163324109	   
df.mm.trans2	-0.215347286953151	0.103325482322873	-2.08416435241241	0.0377548295660421	*  
df.mm.exp2	-0.107202465282322	0.139721553611284	-0.767257896233869	0.443363429324881	   
df.mm.exp3	-0.330729301937758	0.139721553611284	-2.36706000892226	0.0183869822465032	*  
df.mm.exp4	-0.0715270378831554	0.139721553611284	-0.511925583665846	0.608974739449035	   
df.mm.exp5	-0.215384040526224	0.139721553611284	-1.54152337244574	0.123949765046163	   
df.mm.exp6	-0.147002839434542	0.139721553611284	-1.05211283180772	0.293358534641919	   
df.mm.exp7	-0.203394315412885	0.139721553611284	-1.45571180792008	0.146226535903469	   
df.mm.exp8	-0.202309859736721	0.139721553611284	-1.44795025898125	0.148384185968201	   
df.mm.trans1:exp2	-0.0384275680614732	0.112647117820689	-0.3411322793242	0.733176230244981	   
df.mm.trans2:exp2	0.151321110790878	0.112647117820689	1.34331986222453	0.179900762172196	   
df.mm.trans1:exp3	0.197645523737889	0.112647117820689	1.75455464428749	0.0800717199827448	.  
df.mm.trans2:exp3	0.249102094421387	0.112647117820689	2.21134902730408	0.0275547303066023	*  
df.mm.trans1:exp4	0.0412899051516276	0.112647117820689	0.36654204697321	0.714146997357419	   
df.mm.trans2:exp4	0.073993478960677	0.112647117820689	0.656860826909567	0.511633620385985	   
df.mm.trans1:exp5	0.0612098946530525	0.112647117820689	0.54337737029798	0.587161049360042	   
df.mm.trans2:exp5	0.19669913260256	0.112647117820689	1.74615326524080	0.0815224756930184	.  
df.mm.trans1:exp6	0.0874238513745087	0.112647117820689	0.776086002605675	0.438139207733308	   
df.mm.trans2:exp6	0.0952039689464235	0.112647117820689	0.845152284304059	0.398511633211923	   
df.mm.trans1:exp7	0.132187393936375	0.112647117820689	1.17346450130034	0.241281002171965	   
df.mm.trans2:exp7	0.0654292304163272	0.112647117820689	0.580833595054578	0.561667136188102	   
df.mm.trans1:exp8	-0.0161212769704413	0.112647117820689	-0.143113088752995	0.886270161268993	   
df.mm.trans2:exp8	0.187546092613029	0.112647117820689	1.66489916689714	0.0966857904365784	.  
df.mm.trans1:probe2	0.049229802935544	0.0715859940399106	0.687701604144763	0.492023956054109	   
df.mm.trans1:probe3	-0.0312310184438558	0.0715859940399106	-0.436272749477278	0.662865174351664	   
df.mm.trans1:probe4	-0.117751216100834	0.0715859940399106	-1.64489182108983	0.100747497692928	   
df.mm.trans1:probe5	-0.0290350220281226	0.0715859940399106	-0.405596407754498	0.685247690406726	   
df.mm.trans1:probe6	-0.0774648003940725	0.0715859940399106	-1.08212229826528	0.279825048505548	   
df.mm.trans2:probe2	-0.0293772551399212	0.0715859940399106	-0.410377134995748	0.681740590042497	   
df.mm.trans2:probe3	-0.0499216458682192	0.0715859940399106	-0.697366105447762	0.485963254111733	   
df.mm.trans2:probe4	-0.00250740677960413	0.0715859940399106	-0.0350264994323638	0.97207541070085	   
df.mm.trans2:probe5	0.0120889716321971	0.0715859940399106	0.168873419924256	0.865978286058336	   
df.mm.trans2:probe6	-0.0554727839293864	0.0715859940399106	-0.77491113552826	0.438832404419232	   
df.mm.trans3:probe2	-0.0442237818831741	0.0715859940399106	-0.617771429681041	0.537064049499512	   
df.mm.trans3:probe3	0.0576806007694434	0.0715859940399106	0.805752599276408	0.42084584530292	   
df.mm.trans3:probe4	-0.0192607309597660	0.0715859940399106	-0.269057253700044	0.788019015571684	   
df.mm.trans3:probe5	0.0309991857188523	0.0715859940399106	0.43303422875667	0.665214331456013	   
df.mm.trans3:probe6	0.0175342977995416	0.0715859940399106	0.244940341119883	0.806623402814591	   
df.mm.trans3:probe7	-0.0840849318175375	0.0715859940399106	-1.1746003243408	0.240826578593266