chr3.15091_chr3_95221879_95223753_+_0.R 

fitVsDatCorrelation=0.929413026849632
cont.fitVsDatCorrelation=0.246252500621493

fstatistic=3984.27976119761,58,830
cont.fstatistic=565.418254532511,58,830

residuals=-1.36545011648279,-0.191331390572412,0.0110431854858979,0.181623849798718,1.34359009023973
cont.residuals=-1.59826286318245,-0.598695172094035,-0.147634051847954,0.471257395893386,2.80959871157843

predictedValues:
Include	Exclude	Both
chr3.15091_chr3_95221879_95223753_+_0.R.tl.Lung	334.428917188176	140.158861172305	420.202090949481
chr3.15091_chr3_95221879_95223753_+_0.R.tl.cerebhem	116.854547282733	137.302475189343	68.5524987772148
chr3.15091_chr3_95221879_95223753_+_0.R.tl.cortex	102.032439341420	108.189910865082	87.9744521917302
chr3.15091_chr3_95221879_95223753_+_0.R.tl.heart	158.591991025036	107.041104885491	174.674855074642
chr3.15091_chr3_95221879_95223753_+_0.R.tl.kidney	245.890215145727	142.698581686740	269.188948368357
chr3.15091_chr3_95221879_95223753_+_0.R.tl.liver	497.920176197962	129.721242521147	519.919832483379
chr3.15091_chr3_95221879_95223753_+_0.R.tl.stomach	132.357563754208	111.424499231569	131.465170740522
chr3.15091_chr3_95221879_95223753_+_0.R.tl.testicle	93.3248473944082	104.083734491352	90.6584936510292


diffExp=194.270056015870,-20.4479279066109,-6.15747152366221,51.550886139545,103.191633458986,368.198933676815,20.9330645226394,-10.7588870969439
diffExpScore=1.10505933892714
diffExp1.5=1,0,0,0,1,1,0,0
diffExp1.5Score=0.75
diffExp1.4=1,0,0,1,1,1,0,0
diffExp1.4Score=0.8
diffExp1.3=1,0,0,1,1,1,0,0
diffExp1.3Score=0.8
diffExp1.2=1,0,0,1,1,1,0,0
diffExp1.2Score=0.8

cont.predictedValues:
Include	Exclude	Both
Lung	217.299798432921	186.23968679199	136.673309134595
cerebhem	179.018047052319	158.761507495037	146.290912492249
cortex	236.684154210006	161.764955740792	150.280749917147
heart	196.969080814552	212.721125532107	153.605195129999
kidney	211.844042447250	212.653858597348	171.543284387207
liver	226.232845621499	201.02238117853	153.569865538702
stomach	138.910433394784	156.623902313927	150.701817561464
testicle	155.294257088587	157.721752547469	154.762931593397
cont.diffExp=31.0601116409312,20.2565395572813,74.919198469214,-15.7520447175553,-0.8098161500981,25.2104644429685,-17.7134689191433,-2.42749545888236
cont.diffExpScore=1.62556996684269

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

tran.correlation=0.546088788495077
cont.tran.correlation=0.519068272664884

tran.covariance=0.0518200156919636
cont.tran.covariance=0.0146504600342514

tran.mean=166.376319210794
cont.tran.mean=188.110114328695

weightedLogRatios:
wLogRatio
Lung	4.67661865155139
cerebhem	-0.780732066718754
cortex	-0.272746474084963
heart	1.91441471256262
kidney	2.84743647977783
liver	7.4487815885185
stomach	0.82626866828648
testicle	-0.500881746218982

cont.weightedLogRatios:
wLogRatio
Lung	0.81813149740401
cerebhem	0.615721521134262
cortex	2.00811730976476
heart	-0.409412157047455
kidney	-0.0204420528764642
liver	0.633570253636919
stomach	-0.599350712036084
testicle	-0.078376614739901

varWeightedLogRatios=8.30081675186712
cont.varWeightedLogRatios=0.702100183506479

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.74602384470582	0.153215013280112	24.4494567765186	7.3129637133706e-100	***
df.mm.trans1	2.13773310332352	0.120057846470237	17.8058591435212	2.57686987697473e-60	***
df.mm.trans2	1.18542361068715	0.120057846470237	9.87377039934684	8.14555849922386e-22	***
df.mm.exp2	0.741051368963783	0.158051740317357	4.68866313952508	3.2138870434854e-06	***
df.mm.exp3	0.117667366187329	0.158051740317357	0.744486368521228	0.456793013011312	   
df.mm.exp4	-0.137843636071034	0.158051740317357	-0.872142475585864	0.383382871497459	   
df.mm.exp5	0.155741108619281	0.158051740317357	0.985380536187473	0.324724339356541	   
df.mm.exp6	0.107687914113388	0.158051740317357	0.681345956059441	0.495842664140399	   
df.mm.exp7	0.00564725623678707	0.158051740317357	0.0357304274248911	0.971505899614105	   
df.mm.exp8	-0.0402826156802134	0.158051740317357	-0.254869801492401	0.79888679733202	   
df.mm.trans1:exp2	-1.79254574549682	0.117594257872576	-15.2434802338666	1.92530842152154e-46	***
df.mm.trans2:exp2	-0.761641530710826	0.117594257872576	-6.47685987810845	1.60263741986080e-10	***
df.mm.trans1:exp3	-1.30480092302257	0.117594257872576	-11.0957877249112	9.01689017253482e-27	***
df.mm.trans2:exp3	-0.376555751319568	0.117594257872576	-3.20216104197537	0.00141596695037634	** 
df.mm.trans1:exp4	-0.608245906270714	0.117594257872576	-5.17241162344682	2.89894031503328e-07	***
df.mm.trans2:exp4	-0.131719947385933	0.117594257872576	-1.12012227271049	0.262985674143015	   
df.mm.trans1:exp5	-0.463280304511684	0.117594257872576	-3.93965073544399	8.84615110533293e-05	***
df.mm.trans2:exp5	-0.137783025269218	0.117594257872576	-1.17168157495002	0.241661148980941	   
df.mm.trans1:exp6	0.2903275089877	0.117594257872576	2.46889188502977	0.0137535977809600	*  
df.mm.trans2:exp6	-0.185076556192064	0.117594257872576	-1.57385708741503	0.115901572313017	   
df.mm.trans1:exp7	-0.93256453187837	0.117594257872576	-7.93035772961711	7.04499017404964e-15	***
df.mm.trans2:exp7	-0.235076533591455	0.117594257872576	-1.99904772430455	0.0459288384395907	*  
df.mm.trans1:exp8	-1.23605534704323	0.117594257872576	-10.5111879559851	2.39786466294919e-24	***
df.mm.trans2:exp8	-0.257298171746776	0.117594257872576	-2.18801645932050	0.0289465636855007	*  
df.mm.trans1:probe2	-0.395469350787177	0.0914546737436507	-4.32421148749254	1.71681241349073e-05	***
df.mm.trans1:probe3	-0.220084753025634	0.0914546737436507	-2.40648994760547	0.0163242181114199	*  
df.mm.trans1:probe4	-0.536775192050702	0.0914546737436507	-5.86930301184272	6.32270133529836e-09	***
df.mm.trans1:probe5	-0.465070869132917	0.0914546737436507	-5.08526081932696	4.54019670077975e-07	***
df.mm.trans1:probe6	-0.593910302091261	0.0914546737436507	-6.49403991922823	1.43791774322892e-10	***
df.mm.trans2:probe2	-0.0173114364402171	0.0914546737436507	-0.189289794950682	0.849911970725448	   
df.mm.trans2:probe3	-0.0812683484832547	0.0914546737436507	-0.888618866117783	0.374465399686537	   
df.mm.trans2:probe4	0.364597265758945	0.0914546737436507	3.98664443088954	7.29167628108278e-05	***
df.mm.trans2:probe5	0.0596256060972002	0.0914546737436507	0.651968933423042	0.514601709712654	   
df.mm.trans2:probe6	0.0255573565670967	0.0914546737436507	0.27945380504811	0.779966205723677	   
df.mm.trans3:probe2	-1.20238119312779	0.0914546737436507	-13.1472908262522	5.31902655488166e-36	***
df.mm.trans3:probe3	-0.76083192994996	0.0914546737436507	-8.31922414465757	3.61585216321578e-16	***
df.mm.trans3:probe4	-1.97353530868953	0.0914546737436507	-21.57938165327	2.4878482568081e-82	***
df.mm.trans3:probe5	-1.63467578738213	0.0914546737436507	-17.8741634567978	1.06505773950317e-60	***
df.mm.trans3:probe6	-0.886571912810146	0.0914546737436507	-9.69411268466416	4.0027176077746e-21	***
df.mm.trans3:probe7	-1.61973367480246	0.0914546737436507	-17.7107807452532	8.7930995983598e-60	***
df.mm.trans3:probe8	-1.48479701649184	0.0914546737436507	-16.2353322767709	1.10418592586649e-51	***
df.mm.trans3:probe9	-0.0542379419351871	0.0914546737436507	-0.59305817532319	0.553303775427755	   
df.mm.trans3:probe10	-1.06005815778219	0.0914546737436507	-11.5910769170043	6.7071624664571e-29	***
df.mm.trans3:probe11	-0.810624986406398	0.0914546737436507	-8.86368026065674	4.65784921495807e-18	***
df.mm.trans3:probe12	-0.993258466388343	0.0914546737436507	-10.8606638209925	8.74780880137573e-26	***
df.mm.trans3:probe13	-0.89534852278491	0.0914546737436507	-9.79007945831823	1.71489238430184e-21	***
df.mm.trans3:probe14	-1.39742497811655	0.0914546737436507	-15.2799733563488	1.24400556667239e-46	***
df.mm.trans3:probe15	-1.65524507943672	0.0914546737436507	-18.0990758774823	5.74580300523964e-62	***
df.mm.trans3:probe16	-1.34569210906089	0.0914546737436507	-14.7143065955590	1.01434864790590e-43	***
df.mm.trans3:probe17	-1.30197908922035	0.0914546737436507	-14.2363318999948	2.60947486002019e-41	***
df.mm.trans3:probe18	-0.670638900295711	0.0914546737436507	-7.33301943841083	5.35073497757589e-13	***
df.mm.trans3:probe19	-1.08049275936297	0.0914546737436507	-11.8145165810947	6.99470812742052e-30	***
df.mm.trans3:probe20	-1.57700804088546	0.0914546737436507	-17.2436025009049	3.50389159961179e-57	***
df.mm.trans3:probe21	-1.04786516616672	0.0914546737436507	-11.4577541340742	2.54699756729202e-28	***
df.mm.trans3:probe22	-0.91884980140044	0.0914546737436507	-10.0470513292300	1.71704331240769e-22	***
df.mm.trans3:probe23	-0.74970354299555	0.0914546737436507	-8.19754215183124	9.2732275881618e-16	***
df.mm.trans3:probe24	-0.587788773872442	0.0914546737436507	-6.42710481391062	2.19098059253964e-10	***
df.mm.trans3:probe25	-0.00237671654505564	0.0914546737436507	-0.0259879178150876	0.97927322213924	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	6.06474355542428	0.402385575395466	15.0719705831001	1.48785499328773e-45	***
df.mm.trans1	-0.675212592443863	0.315305560456701	-2.14145475730227	0.0325279527594071	*  
df.mm.trans2	-0.79203541908809	0.315305560456701	-2.51196146982271	0.0121949533195642	*  
df.mm.exp2	-0.421426414132877	0.415088176467298	-1.01526961745700	0.310273180906446	   
df.mm.exp3	-0.150353219166181	0.415088176467298	-0.362219951543299	0.717279875709147	   
df.mm.exp4	-0.0820758074863073	0.415088176467298	-0.197731017502912	0.843303934895321	   
df.mm.exp5	-0.120038469099910	0.415088176467298	-0.289187878396164	0.772509823352611	   
df.mm.exp6	0.000106427499642737	0.415088176467298	0.000256397328751959	0.999795486162356	   
df.mm.exp7	-0.718345369347318	0.415088176467298	-1.73058499391854	0.083897484356677	.  
df.mm.exp8	-0.626459270963255	0.415088176467298	-1.50921974288663	0.131623195543580	   
df.mm.trans1:exp2	0.227635076749018	0.308835486185357	0.737075520565004	0.461284722097186	   
df.mm.trans2:exp2	0.261795054638636	0.308835486185357	0.847684499835982	0.396858073475467	   
df.mm.trans1:exp3	0.235801829168018	0.308835486185357	0.763519218858466	0.445370774048137	   
df.mm.trans2:exp3	0.00946312755121015	0.308835486185357	0.0306413219157418	0.975562953755453	   
df.mm.trans1:exp4	-0.0161553859374102	0.308835486185357	-0.0523106529529903	0.95829375201914	   
df.mm.trans2:exp4	0.215023362753248	0.308835486185357	0.696239170599052	0.486473979031869	   
df.mm.trans1:exp5	0.0946108645520151	0.308835486185357	0.306347129083578	0.759417187872089	   
df.mm.trans2:exp5	0.252669753134034	0.308835486185357	0.818137048481492	0.413513745500901	   
df.mm.trans1:exp6	0.0401803720846125	0.308835486185357	0.130102834298313	0.896516591389117	   
df.mm.trans2:exp6	0.0762753407098746	0.308835486185357	0.246977255275955	0.804986900983901	   
df.mm.trans1:exp7	0.270896771056159	0.308835486185357	0.877155583389055	0.380655950015313	   
df.mm.trans2:exp7	0.545158291370598	0.308835486185357	1.76520612350682	0.077896809101008	.  
df.mm.trans1:exp8	0.290503061302128	0.308835486185357	0.940640160527973	0.347162967955672	   
df.mm.trans2:exp8	0.460257208877651	0.308835486185357	1.49029897620448	0.136525547423431	   
df.mm.trans1:probe2	0.00545048516423309	0.2401856105946	0.0226928047468786	0.981900769605769	   
df.mm.trans1:probe3	-0.0299858519953133	0.240185610594600	-0.124844498057484	0.900676888545934	   
df.mm.trans1:probe4	-0.0773768577269282	0.2401856105946	-0.322154426884171	0.747416830296027	   
df.mm.trans1:probe5	-0.16880693236083	0.2401856105946	-0.702818674036857	0.482365828874146	   
df.mm.trans1:probe6	0.0148760541038261	0.240185610594600	0.0619356591221228	0.95062898112703	   
df.mm.trans2:probe2	-0.265846202417052	0.240185610594600	-1.10683650764476	0.268685299426697	   
df.mm.trans2:probe3	-0.00264999767566487	0.240185610594600	-0.0110331242121648	0.991199670448128	   
df.mm.trans2:probe4	-0.183048360923397	0.240185610594600	-0.762112103511302	0.4462096074362	   
df.mm.trans2:probe5	-0.524521448132222	0.240185610594600	-2.18381711890951	0.0292549820910669	*  
df.mm.trans2:probe6	-0.439817250547237	0.240185610594600	-1.83115570270189	0.0674356325003858	.  
df.mm.trans3:probe2	0.293143180063481	0.240185610594600	1.22048602053129	0.222627312236385	   
df.mm.trans3:probe3	0.130636382866082	0.240185610594600	0.543897623769719	0.586657988321734	   
df.mm.trans3:probe4	0.617386099570453	0.240185610594600	2.57045415019684	0.0103298238715089	*  
df.mm.trans3:probe5	0.205951797181697	0.2401856105946	0.857469340781263	0.391433070950443	   
df.mm.trans3:probe6	0.381695721725682	0.240185610594600	1.58916981238285	0.112402877646008	   
df.mm.trans3:probe7	0.256923002955525	0.240185610594600	1.06968524184063	0.285071987426355	   
df.mm.trans3:probe8	0.388915052655745	0.240185610594600	1.61922711228600	0.105778286883651	   
df.mm.trans3:probe9	0.579061941324594	0.240185610594600	2.41089355807401	0.0161298405900181	*  
df.mm.trans3:probe10	0.649122259497304	0.2401856105946	2.70258596212465	0.00702078130389503	** 
df.mm.trans3:probe11	0.587288736307244	0.240185610594600	2.44514538091337	0.0146862624225519	*  
df.mm.trans3:probe12	0.421096817170337	0.240185610594600	1.75321417518674	0.0799343876502028	.  
df.mm.trans3:probe13	0.196467793712197	0.240185610594600	0.817983197352347	0.413601541290254	   
df.mm.trans3:probe14	0.290525177988913	0.240185610594600	1.20958610830055	0.226782158277823	   
df.mm.trans3:probe15	0.0921907211923566	0.240185610594600	0.383831158594932	0.701201894819087	   
df.mm.trans3:probe16	0.320816017552008	0.2401856105946	1.33570040585612	0.182013358440174	   
df.mm.trans3:probe17	0.0545902720797411	0.240185610594600	0.227283690911367	0.820259124570614	   
df.mm.trans3:probe18	0.254213295247958	0.2401856105946	1.05840351809016	0.290179442019397	   
df.mm.trans3:probe19	0.269573357510515	0.240185610594600	1.12235431940807	0.262036385513736	   
df.mm.trans3:probe20	0.183996291110804	0.240185610594600	0.76605876036997	0.443859140992921	   
df.mm.trans3:probe21	0.344392192567382	0.240185610594600	1.43385855511831	0.151989240058880	   
df.mm.trans3:probe22	0.339249744493716	0.240185610594600	1.41244824639525	0.158192852180718	   
df.mm.trans3:probe23	0.381006506726434	0.240185610594600	1.58630030243369	0.113052081753435	   
df.mm.trans3:probe24	0.422387174385112	0.240185610594600	1.75858650873987	0.0790162595941389	.  
df.mm.trans3:probe25	0.34181869863174	0.240185610594600	1.42314395015396	0.155070186058473