chr11.3682_chr11_97803324_97805115_+_0.R 

fitVsDatCorrelation=0.96309722494705
cont.fitVsDatCorrelation=0.280890838391892

fstatistic=8723.60977361936,40,416
cont.fstatistic=676.522224201776,40,416

residuals=-0.74481005584783,-0.0996499792593081,0.00594595667613773,0.0895533858611793,1.0188423484175
cont.residuals=-1.33825100482015,-0.495206167109515,-0.185506151421708,0.55832486039876,1.53311814223483

predictedValues:
Include	Exclude	Both
chr11.3682_chr11_97803324_97805115_+_0.R.tl.Lung	298.546899623643	93.361241432565	78.7742853270904
chr11.3682_chr11_97803324_97805115_+_0.R.tl.cerebhem	345.140890663208	111.481426236082	81.8147524862914
chr11.3682_chr11_97803324_97805115_+_0.R.tl.cortex	293.132098570977	82.8426893734143	94.0977166867966
chr11.3682_chr11_97803324_97805115_+_0.R.tl.heart	281.068879671878	97.9439346332464	112.787440866613
chr11.3682_chr11_97803324_97805115_+_0.R.tl.kidney	265.607571228585	86.9676460562235	92.8513576902398
chr11.3682_chr11_97803324_97805115_+_0.R.tl.liver	278.739135126667	94.3626562166993	85.6866887332393
chr11.3682_chr11_97803324_97805115_+_0.R.tl.stomach	387.290801193036	110.239799922048	104.702477360972
chr11.3682_chr11_97803324_97805115_+_0.R.tl.testicle	341.66994661044	101.446920518263	111.574462975861


diffExp=205.185658191078,233.659464427126,210.289409197563,183.124945038631,178.639925172362,184.376478909967,277.051001270988,240.223026092177
diffExpScore=0.999416416180727
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	117.604631467221	132.924515919635	140.480857313499
cerebhem	194.926896605665	182.704693151167	130.289610597541
cortex	131.425159520127	178.247196424472	117.757420391035
heart	114.120223882519	140.999033582161	158.240298422868
kidney	121.760598790010	159.603808704897	127.771321968712
liver	149.305774447962	125.286738831518	148.561401516654
stomach	167.478484465302	119.277666307182	143.397441578632
testicle	129.330663880156	157.981222998809	148.756196351186
cont.diffExp=-15.3198844524134,12.2222034544978,-46.8220369043453,-26.8788096996415,-37.8432099148874,24.0190356164440,48.2008181581203,-28.6505591186535
cont.diffExpScore=3.32938010415700

cont.diffExp1.5=0,0,0,0,0,0,0,0
cont.diffExp1.5Score=0
cont.diffExp1.4=0,0,0,0,0,0,1,0
cont.diffExp1.4Score=0.5
cont.diffExp1.3=0,0,-1,0,-1,0,1,0
cont.diffExp1.3Score=1.5
cont.diffExp1.2=0,0,-1,-1,-1,0,1,-1
cont.diffExp1.2Score=1.25

tran.correlation=0.816731605447687
cont.tran.correlation=0.178893415718057

tran.covariance=0.0109813067614034
cont.tran.covariance=0.00307062755828722

tran.mean=204.365158567311
cont.tran.mean=145.186081811175

weightedLogRatios:
wLogRatio
Lung	5.94907615024307
cerebhem	5.96566304830859
cortex	6.38004591105456
heart	5.38856387811874
kidney	5.60896659140752
liver	5.51174019754058
stomach	6.69839222053179
testicle	6.34681983126366

cont.weightedLogRatios:
wLogRatio
Lung	-0.591271033967039
cerebhem	0.33932411971064
cortex	-1.53305600666348
heart	-1.02429773899078
kidney	-1.3362401803843
liver	0.862627447081463
stomach	1.6804257315782
testicle	-0.99299982784252

varWeightedLogRatios=0.216937388189205
cont.varWeightedLogRatios=1.33738038393816

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	6.02890296479363	0.0922886899840713	65.3265634806843	8.01341851084815e-221	***
df.mm.trans1	-0.332720731493599	0.0748560122175621	-4.44480973053409	1.12973965885903e-05	***
df.mm.trans2	-1.49272330831333	0.0748560122175621	-19.9412614176516	1.40110804560343e-62	***
df.mm.exp2	0.284536424950802	0.101223803548292	2.81096357750532	0.00517276993720381	** 
df.mm.exp3	-0.315583633132923	0.101223803548292	-3.11768202804555	0.00194937332583324	** 
df.mm.exp4	-0.371326719005752	0.101223803548292	-3.66837350493947	0.000275794317112945	***
df.mm.exp5	-0.352260529732448	0.101223803548292	-3.48001672911245	0.000554367887529305	***
df.mm.exp6	-0.142092448730853	0.101223803548292	-1.4037454012787	0.161140723446047	   
df.mm.exp7	0.141894340300237	0.101223803548292	1.40178826843374	0.161724154581205	   
df.mm.exp8	-0.130127991592252	0.101223803548292	-1.28554734193693	0.199316257190852	   
df.mm.trans1:exp2	-0.139510750707518	0.0816092394469466	-1.7094970085858	0.0881046674164446	.  
df.mm.trans2:exp2	-0.10715471392294	0.0816092394469467	-1.31302184224619	0.189899407082784	   
df.mm.trans1:exp3	0.297279950755399	0.0816092394469466	3.64272419115801	0.000303843032699743	***
df.mm.trans2:exp3	0.196050848651297	0.0816092394469466	2.40231191933541	0.0167292139193841	*  
df.mm.trans1:exp4	0.31099944353102	0.0816092394469466	3.81083619500214	0.000159412743528870	***
df.mm.trans2:exp4	0.419245653234217	0.0816092394469466	5.13723269663314	4.29448980157401e-07	***
df.mm.trans1:exp5	0.235353414902043	0.0816092394469466	2.88390648530726	0.00413173278703271	** 
df.mm.trans2:exp5	0.28132040965578	0.0816092394469466	3.44716372266481	0.000624213919218741	***
df.mm.trans1:exp6	0.0734417554633754	0.0816092394469466	0.899919616468417	0.368683666685295	   
df.mm.trans2:exp6	0.152761567536910	0.0816092394469467	1.87186608492068	0.0619265969291359	.  
df.mm.trans1:exp7	0.118354456664973	0.0816092394469466	1.45025805248331	0.147740103228933	   
df.mm.trans2:exp7	0.0242873668789714	0.0816092394469467	0.297605602546515	0.766152761222194	   
df.mm.trans1:exp8	0.265046156127893	0.0816092394469466	3.24774692086424	0.00125751521497410	** 
df.mm.trans2:exp8	0.213187417574903	0.0816092394469467	2.61229511535265	0.00931924436911886	** 
df.mm.trans1:probe2	-0.131555766251475	0.0518617665651257	-2.53666187954229	0.0115560808340236	*  
df.mm.trans1:probe3	0.0614082804246335	0.0518617665651257	1.18407614109172	0.237059032735057	   
df.mm.trans1:probe4	0.125386344622350	0.0518617665651257	2.41770292311381	0.0160477260207797	*  
df.mm.trans1:probe5	-0.0927519268267535	0.0518617665651257	-1.78844518746348	0.0744317957333127	.  
df.mm.trans1:probe6	0.0731955311863225	0.0518617665651257	1.41135823235807	0.158886467557989	   
df.mm.trans2:probe2	0.0801624171006037	0.0518617665651257	1.54569391692316	0.122938871440834	   
df.mm.trans2:probe3	-0.0559271862896855	0.0518617665651257	-1.07838953421409	0.281484847622629	   
df.mm.trans2:probe4	-0.0661631786857906	0.0518617665651257	-1.27576021928805	0.202752180212683	   
df.mm.trans2:probe5	-0.0540788560347592	0.0518617665651257	-1.04274997973410	0.297669694212059	   
df.mm.trans2:probe6	0.0998629766660292	0.0518617665651257	1.92556064476951	0.0548405698008875	.  
df.mm.trans3:probe2	0.48596163961749	0.0518617665651257	9.37032561371085	4.65472087949065e-19	***
df.mm.trans3:probe3	-0.0974670609292309	0.0518617665651257	-1.87936253206562	0.0608938073806405	.  
df.mm.trans3:probe4	-0.380016586681537	0.0518617665651257	-7.32749020811564	1.22921580019403e-12	***
df.mm.trans3:probe5	-0.0731665154230594	0.0518617665651257	-1.41079874961799	0.159051317671601	   
df.mm.trans3:probe6	0.286818073001262	0.0518617665651257	5.53043392073983	5.65457628231159e-08	***
df.mm.trans3:probe7	0.919764282403316	0.0518617665651257	17.7349200253007	8.10546771820893e-53	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.77940194960417	0.329080034662633	14.5235245113060	5.97168494798137e-39	***
df.mm.trans1	0.0572510371517822	0.266919154443665	0.21448830553622	0.830271384695747	   
df.mm.trans2	0.098138398145286	0.266919154443665	0.367670871540989	0.713305649508514	   
df.mm.exp2	0.898697400469852	0.360940574474562	2.48987635091490	0.0131682773602349	*  
df.mm.exp3	0.58094353929124	0.360940574474562	1.60952683176987	0.108259737516760	   
df.mm.exp4	-0.0901478322023327	0.360940574474562	-0.24975810030104	0.802897707123185	   
df.mm.exp5	0.31247063873609	0.360940574474562	0.865712144418698	0.387147022507148	   
df.mm.exp6	0.123564447626450	0.360940574474562	0.342340142297188	0.732267824075119	   
df.mm.exp7	0.224650307714441	0.360940574474562	0.622402477309387	0.53401825071081	   
df.mm.exp8	0.210501292195209	0.360940574474562	0.583202075581682	0.560073296958144	   
df.mm.trans1:exp2	-0.393401219310048	0.290999594323287	-1.35189610908185	0.177143105781884	   
df.mm.trans2:exp2	-0.580607667298121	0.290999594323287	-1.99521813302974	0.0466709080939644	*  
df.mm.trans1:exp3	-0.469834396727085	0.290999594323287	-1.61455344231553	0.107165621861885	   
df.mm.trans2:exp3	-0.287553626082639	0.290999594323287	-0.988158168231603	0.323649581171052	   
df.mm.trans1:exp4	0.0600719024486834	0.290999594323287	0.206432942246464	0.836553735995706	   
df.mm.trans2:exp4	0.149119450901626	0.290999594323287	0.512438689986493	0.608615980173664	   
df.mm.trans1:exp5	-0.277742244759332	0.290999594323287	-0.95444203420701	0.34041420929491	   
df.mm.trans2:exp5	-0.129557507567508	0.290999594323287	-0.445215423302534	0.656395658986668	   
df.mm.trans1:exp6	0.115103515068599	0.290999594323287	0.395545276742635	0.692643277367199	   
df.mm.trans2:exp6	-0.182740844296572	0.290999594323287	-0.627976285401813	0.53036405248309	   
df.mm.trans1:exp7	0.128876166433029	0.290999594323287	0.442874041569466	0.658087043281714	   
df.mm.trans2:exp7	-0.332977619906634	0.290999594323287	-1.14425458455008	0.253176031370835	   
df.mm.trans1:exp8	-0.115457299468643	0.290999594323287	-0.396761032389535	0.691747146666109	   
df.mm.trans2:exp8	-0.0378065256383302	0.290999594323287	-0.129919513208424	0.896692901939007	   
df.mm.trans1:probe2	-0.0874839530489866	0.184927014803901	-0.473072866837524	0.63640931823886	   
df.mm.trans1:probe3	-0.273491224864045	0.184927014803901	-1.47891439849424	0.139919986313149	   
df.mm.trans1:probe4	0.00111111878487954	0.184927014803901	0.0060084178942584	0.995208885178866	   
df.mm.trans1:probe5	-0.288432959544411	0.184927014803901	-1.55971240789384	0.119588258973280	   
df.mm.trans1:probe6	-0.252922376276699	0.184927014803901	-1.36768755254554	0.172148297772707	   
df.mm.trans2:probe2	-0.0452145999881827	0.184927014803901	-0.244499701874975	0.806964381652385	   
df.mm.trans2:probe3	0.0469045115845067	0.184927014803901	0.253637964330117	0.799900570030856	   
df.mm.trans2:probe4	0.0437975053025998	0.184927014803901	0.236836707438572	0.81290005226628	   
df.mm.trans2:probe5	0.0609809623642754	0.184927014803901	0.329756917500348	0.741749622737678	   
df.mm.trans2:probe6	0.0526655291599231	0.184927014803901	0.284790890156154	0.775946071557871	   
df.mm.trans3:probe2	0.0819292485813105	0.184927014803901	0.443035587137929	0.657970288270503	   
df.mm.trans3:probe3	-0.0860137390248399	0.184927014803901	-0.465122627519025	0.642087016921101	   
df.mm.trans3:probe4	0.0322242232360769	0.184927014803901	0.174253736103662	0.861750824244866	   
df.mm.trans3:probe5	-0.0749152460886674	0.184927014803901	-0.405107096808482	0.685607030615558	   
df.mm.trans3:probe6	0.173277671888936	0.184927014803901	0.937005726679159	0.349299262546142	   
df.mm.trans3:probe7	-0.0545432246151125	0.184927014803900	-0.294944601106285	0.768183337471731