chrX.25682_chrX_56697329_56704836_+_2.R 

fitVsDatCorrelation=0.923974502636827
cont.fitVsDatCorrelation=0.238268184736222

fstatistic=6432.88070128457,59,853
cont.fstatistic=985.363324339093,59,853

residuals=-1.12656899541968,-0.109303836271685,0.00052473707967109,0.110858426674249,1.10618118150912
cont.residuals=-0.956302684189859,-0.359932334822583,-0.117572647826453,0.199700823716422,2.57403110312805

predictedValues:
Include	Exclude	Both
chrX.25682_chrX_56697329_56704836_+_2.R.tl.Lung	70.182190545009	425.275779663825	303.780930143519
chrX.25682_chrX_56697329_56704836_+_2.R.tl.cerebhem	66.6150452912286	60.3929913771559	73.9660578661153
chrX.25682_chrX_56697329_56704836_+_2.R.tl.cortex	63.0730666289068	72.4104532570915	71.7973734794726
chrX.25682_chrX_56697329_56704836_+_2.R.tl.heart	73.0267146273933	198.494451112177	158.489594288478
chrX.25682_chrX_56697329_56704836_+_2.R.tl.kidney	66.714658192279	113.430163945221	101.114280094281
chrX.25682_chrX_56697329_56704836_+_2.R.tl.liver	69.3688705261502	104.282573944686	91.6755158801361
chrX.25682_chrX_56697329_56704836_+_2.R.tl.stomach	71.138738141155	137.728032040593	117.926323961513
chrX.25682_chrX_56697329_56704836_+_2.R.tl.testicle	66.0382469208034	115.164414697613	106.731813049183


diffExp=-355.093589118816,6.22205391407267,-9.33738662818472,-125.467736484784,-46.7155057529425,-34.9137034185359,-66.5892938994377,-49.1261677768098
diffExpScore=1.01677969198141
diffExp1.5=-1,0,0,-1,-1,-1,-1,-1
diffExp1.5Score=0.857142857142857
diffExp1.4=-1,0,0,-1,-1,-1,-1,-1
diffExp1.4Score=0.857142857142857
diffExp1.3=-1,0,0,-1,-1,-1,-1,-1
diffExp1.3Score=0.857142857142857
diffExp1.2=-1,0,0,-1,-1,-1,-1,-1
diffExp1.2Score=0.857142857142857

cont.predictedValues:
Include	Exclude	Both
Lung	75.8541387914129	95.6981557064681	80.9421849825509
cerebhem	74.989876828714	95.4652296959112	84.6101019303641
cortex	77.2432292523065	102.471549479247	71.7308891649605
heart	85.2258527836665	103.047166040466	84.9256333560196
kidney	79.6841800822857	123.242045985977	99.90753342294
liver	78.4290642461558	94.2373644374157	87.7730193105557
stomach	80.5513635075609	112.225646824114	93.782242648881
testicle	86.9153847509445	90.1700292896386	78.4053914358226
cont.diffExp=-19.8440169150552,-20.4753528671971,-25.2283202269404,-17.8213132567999,-43.5578659036911,-15.8083001912599,-31.6742833165531,-3.25464453869407
cont.diffExpScore=0.994402904581383

cont.diffExp1.5=0,0,0,0,-1,0,0,0
cont.diffExp1.5Score=0.5
cont.diffExp1.4=0,0,0,0,-1,0,0,0
cont.diffExp1.4Score=0.5
cont.diffExp1.3=0,0,-1,0,-1,0,-1,0
cont.diffExp1.3Score=0.75
cont.diffExp1.2=-1,-1,-1,-1,-1,-1,-1,0
cont.diffExp1.2Score=0.875

tran.correlation=0.511033390278702
cont.tran.correlation=-0.0231100870647598

tran.covariance=0.0188941011651374
cont.tran.covariance=-9.71243310383005e-05

tran.mean=110.833524431956
cont.tran.mean=90.9656423563928

weightedLogRatios:
wLogRatio
Lung	-9.28191517496764
cerebhem	0.406928559769013
cortex	-0.581677909686779
heart	-4.79048575239758
kidney	-2.37028308379169
liver	-1.81137086533056
stomach	-3.03565308905915
testicle	-2.48493963035071

cont.weightedLogRatios:
wLogRatio
Lung	-1.03296044688453
cerebhem	-1.07138689650762
cortex	-1.26850210966737
heart	-0.862110873711029
kidney	-2.00426827712324
liver	-0.817854216196972
stomach	-1.51041481608710
testicle	-0.164815872054099

varWeightedLogRatios=8.88562318524916
cont.varWeightedLogRatios=0.290005937264469

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	5.35199259558553	0.101486416354909	52.7360487030009	1.08451440072874e-270	***
df.mm.trans1	-1.04862667427978	0.0873262737049337	-12.0081463434816	8.37997618120603e-31	***
df.mm.trans2	0.73702446148345	0.0771677972883174	9.55093299773414	1.31881361103530e-20	***
df.mm.exp2	-0.591328409393954	0.0989529157583568	-5.97585634402102	3.36006124673725e-09	***
df.mm.exp3	-0.434728998840543	0.0989529157583568	-4.39329145087702	1.25698844135277e-05	***
df.mm.exp4	-0.0716280839527911	0.0989529157583568	-0.723860266307938	0.469349991070706	   
df.mm.exp5	-0.272164937195442	0.0989529157583568	-2.75044888884396	0.00607739437314567	** 
df.mm.exp6	-0.219238471664314	0.0989529157583568	-2.21558374489635	0.0269833843402706	*  
df.mm.exp7	-0.167672686893801	0.0989529157583568	-1.69446939090969	0.090541139367658	.  
df.mm.exp8	-0.321250012314264	0.0989529157583568	-3.24649364652131	0.00121394041979537	** 
df.mm.trans1:exp2	0.539164283795781	0.0909059940331385	5.93100916534982	4.37173702991335e-09	***
df.mm.trans2:exp2	-1.36053638101094	0.0666667104808269	-20.4080323027522	1.07031804360312e-75	***
df.mm.trans1:exp3	0.327928258052774	0.0909059940331385	3.60733372469622	0.000327348879199173	***
df.mm.trans2:exp3	-1.33565818199666	0.0666667104808269	-20.0348595627917	1.77883187942245e-73	***
df.mm.trans1:exp4	0.111358829050866	0.0909059940331385	1.22498884958314	0.220917579606438	   
df.mm.trans2:exp4	-0.690348622216333	0.0666667104808269	-10.3552225276643	9.44066254329949e-24	***
df.mm.trans1:exp5	0.221495046069889	0.0909059940331385	2.43652850866078	0.0150326029163930	*  
df.mm.trans2:exp5	-1.04938556270278	0.0666667104808269	-15.7407730955104	3.34404152996881e-49	***
df.mm.trans1:exp6	0.207582104145898	0.0909059940331385	2.28348093383399	0.0226471597024337	*  
df.mm.trans2:exp6	-1.18639510837196	0.0666667104808269	-17.7959149298833	1.72006740369816e-60	***
df.mm.trans1:exp7	0.181210132667257	0.0909059940331385	1.99337936507464	0.046538028806854	*  
df.mm.trans2:exp7	-0.9597842066211	0.0666667104808269	-14.3967536375914	3.15471373606558e-42	***
df.mm.trans1:exp8	0.260389502390687	0.0909059940331385	2.86438210329415	0.00428079387510631	** 
df.mm.trans2:exp8	-0.985127039148587	0.0666667104808269	-14.7768958756696	3.65292461948931e-44	***
df.mm.trans1:probe2	-0.149732128684364	0.0633278922597267	-2.364394634678	0.0182826682612302	*  
df.mm.trans1:probe3	-0.220774175431046	0.0633278922597267	-3.48620753909801	0.000514929101887741	***
df.mm.trans1:probe4	-0.200892195824589	0.0633278922597267	-3.17225457308242	0.00156672444374089	** 
df.mm.trans1:probe5	-0.38502767515393	0.0633278922597267	-6.07990667958466	1.81242524304968e-09	***
df.mm.trans1:probe6	-0.281342248645234	0.0633278922597267	-4.44262770488816	1.00565366478085e-05	***
df.mm.trans1:probe7	-0.480519714266826	0.0633278922597267	-7.58780526432287	8.51733872468726e-14	***
df.mm.trans1:probe8	-0.261232677413773	0.0633278922597267	-4.12508087814417	4.06899286244066e-05	***
df.mm.trans1:probe9	-0.412989773613966	0.0633278922597267	-6.52145143122987	1.19152752849035e-10	***
df.mm.trans1:probe10	0.281010135652238	0.0633278922597267	4.43738336497496	1.02989205467072e-05	***
df.mm.trans1:probe11	0.179770174846713	0.0633278922597267	2.8387203242044	0.00463707010913992	** 
df.mm.trans1:probe12	0.0852776513528517	0.0633278922597267	1.34660492098967	0.178465194193248	   
df.mm.trans1:probe13	-0.125168649045615	0.0633278922597267	-1.97651689609787	0.048418011678052	*  
df.mm.trans1:probe14	0.176085507542100	0.0633278922597267	2.78053636808123	0.00554646422898256	** 
df.mm.trans1:probe15	-0.111109048757467	0.0633278922597267	-1.75450413384636	0.0797031965607539	.  
df.mm.trans1:probe16	0.210483891533514	0.0633278922597267	3.3237154123219	0.00092611946509923	***
df.mm.trans1:probe17	-0.0870986251079987	0.0633278922597267	-1.37535960853996	0.169381064110649	   
df.mm.trans1:probe18	0.114621190270741	0.0633278922597267	1.80996376447592	0.0706532276019859	.  
df.mm.trans1:probe19	-0.0443817379896978	0.0633278922597267	-0.700824493063419	0.483603673895017	   
df.mm.trans1:probe20	-0.167996793102772	0.0633278922597267	-2.65280885101571	0.00813087352288361	** 
df.mm.trans1:probe21	0.208334063029774	0.0633278922597267	3.28976783524286	0.00104381038518264	** 
df.mm.trans2:probe2	-0.289950778097547	0.0633278922597267	-4.5785635326117	5.37810796506118e-06	***
df.mm.trans2:probe3	-0.257531285105272	0.0633278922597267	-4.06663282032281	5.21129898481976e-05	***
df.mm.trans2:probe4	0.0193238779562011	0.0633278922597267	0.305140077565634	0.760333908471136	   
df.mm.trans2:probe5	0.0344290638694953	0.0633278922597267	0.543663504989104	0.586815105953209	   
df.mm.trans2:probe6	-0.123017368011632	0.0633278922597267	-1.94254638236025	0.052399775088247	.  
df.mm.trans3:probe2	1.15981072245195	0.0633278922597267	18.3143742996406	1.92930630236713e-63	***
df.mm.trans3:probe3	0.78891904931723	0.0633278922597267	12.4576868290774	7.55320179921178e-33	***
df.mm.trans3:probe4	1.01850293566132	0.0633278922597267	16.0830070182050	4.9373292414608e-51	***
df.mm.trans3:probe5	0.493004011404458	0.0633278922597267	7.78494268185179	2.01740439501301e-14	***
df.mm.trans3:probe6	0.349078114445648	0.0633278922597267	5.51223326704091	4.69544475136388e-08	***
df.mm.trans3:probe7	0.100758930943494	0.0633278922597267	1.59106717984946	0.111964967503055	   
df.mm.trans3:probe8	0.598675224396278	0.0633278922597267	9.45357887391753	3.0719561572847e-20	***
df.mm.trans3:probe9	1.07504263393696	0.0633278922597267	16.9758157989513	6.64021359320624e-56	***
df.mm.trans3:probe10	1.27765743531131	0.0633278922597267	20.1752717439458	2.60773670550010e-74	***
df.mm.trans3:probe11	0.573631719590376	0.0633278922597267	9.05812113938263	8.87933253509301e-19	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.5430462389126	0.25771341797055	17.6282875555659	1.51788943549426e-59	***
df.mm.trans1	-0.290768381863770	0.22175531744492	-1.31121266995544	0.190138771480564	   
df.mm.trans2	0.0580264174234526	0.195959001319774	0.296115090568168	0.767214265104413	   
df.mm.exp2	-0.0582146068658398	0.251279876205861	-0.231672379598546	0.816848049179687	   
df.mm.exp3	0.207346830382999	0.251279876205861	0.82516289610526	0.409509815029257	   
df.mm.exp4	0.142439496259011	0.251279876205860	0.566855963198254	0.570961171556028	   
df.mm.exp5	0.0917000932833673	0.251279876205861	0.364932101479715	0.715252549648139	   
df.mm.exp6	-0.063018989438232	0.251279876205860	-0.250792026762238	0.802035302758747	   
df.mm.exp7	0.0721548956565455	0.251279876205861	0.287149519277193	0.77406757612191	   
df.mm.exp8	0.108463303077795	0.251279876205861	0.431643411782553	0.666109676325141	   
df.mm.trans1:exp2	0.0467554658923076	0.230845617351994	0.202539976407760	0.83954290720736	   
df.mm.trans2:exp2	0.0557776744445122	0.169292664377698	0.329474845525912	0.741877689012858	   
df.mm.trans1:exp3	-0.189199835448389	0.230845617351994	-0.819594660789666	0.4126761590494	   
df.mm.trans2:exp3	-0.138960663047706	0.169292664377698	-0.820830976690638	0.411971882864143	   
df.mm.trans1:exp4	-0.025946941805921	0.230845617351994	-0.112399542618810	0.910533062767687	   
df.mm.trans2:exp4	-0.0684517167794694	0.169292664377698	-0.404339532555003	0.686064418496091	   
df.mm.trans1:exp5	-0.0424412902936563	0.230845617351994	-0.183851401557872	0.854173725568717	   
df.mm.trans2:exp5	0.161251155287730	0.169292664377698	0.952499364815788	0.34111360754541	   
df.mm.trans1:exp6	0.0964012957386562	0.230845617351994	0.417600718802745	0.676344161485639	   
df.mm.trans2:exp6	0.0476367157959706	0.169292664377698	0.281386768712502	0.778482009742518	   
df.mm.trans1:exp7	-0.0120721284913313	0.230845617351994	-0.0522952466233037	0.958305684733547	   
df.mm.trans2:exp7	0.0871576259729545	0.169292664377698	0.514834037808648	0.606802371974236	   
df.mm.trans1:exp8	0.0276594834528771	0.230845617351994	0.119818100816278	0.904655456706217	   
df.mm.trans2:exp8	-0.167965227397622	0.169292664377698	-0.992158922036251	0.321401362584765	   
df.mm.trans1:probe2	0.256138848434725	0.160814108462067	1.59276353849975	0.111583718390677	   
df.mm.trans1:probe3	0.125496414593222	0.160814108462067	0.780381869435441	0.435382630678134	   
df.mm.trans1:probe4	-0.0312165115189472	0.160814108462067	-0.194115502784450	0.846131660628932	   
df.mm.trans1:probe5	0.289498159565936	0.160814108462067	1.80020374042133	0.072181675965753	.  
df.mm.trans1:probe6	0.0473053336611502	0.160814108462067	0.294161588890123	0.768705995463387	   
df.mm.trans1:probe7	0.195939899194671	0.160814108462067	1.21842480780155	0.223399461828616	   
df.mm.trans1:probe8	0.121994574246943	0.160814108462067	0.758606165924296	0.448297736134234	   
df.mm.trans1:probe9	-0.0487653934037738	0.160814108462067	-0.303240765814254	0.761780325348186	   
df.mm.trans1:probe10	0.217504882521468	0.160814108462067	1.35252363490715	0.176566287195808	   
df.mm.trans1:probe11	0.127197863022951	0.160814108462067	0.790962088086656	0.429185976034387	   
df.mm.trans1:probe12	0.206227279162263	0.160814108462067	1.28239543864964	0.200052349758706	   
df.mm.trans1:probe13	0.114959420154539	0.160814108462067	0.714859045975159	0.474891740084431	   
df.mm.trans1:probe14	0.142239242216907	0.160814108462067	0.884494796987655	0.376678409729185	   
df.mm.trans1:probe15	0.0667517376156894	0.160814108462067	0.4150863270273	0.678183088993685	   
df.mm.trans1:probe16	0.141825477539170	0.160814108462067	0.881921859316364	0.378067510391766	   
df.mm.trans1:probe17	-0.0343338229086328	0.160814108462067	-0.213500066859690	0.83098795496124	   
df.mm.trans1:probe18	0.187892923249314	0.160814108462067	1.16838581543754	0.242977612577421	   
df.mm.trans1:probe19	0.0804577134856622	0.160814108462067	0.500315017476471	0.616982332041796	   
df.mm.trans1:probe20	-0.0130209061956773	0.160814108462067	-0.080968680672372	0.935485853113713	   
df.mm.trans1:probe21	0.25500807284538	0.160814108462067	1.58573196894308	0.113170744822501	   
df.mm.trans2:probe2	-0.287139000071757	0.160814108462067	-1.78553363767512	0.0745299905830959	.  
df.mm.trans2:probe3	-0.117445432361702	0.160814108462067	-0.730317964542302	0.465396375512514	   
df.mm.trans2:probe4	-0.294692837947105	0.160814108462067	-1.83250612004989	0.067224505117595	.  
df.mm.trans2:probe5	0.0675363683372301	0.160814108462067	0.419965443225776	0.674616457325396	   
df.mm.trans2:probe6	-0.0461108024757557	0.160814108462067	-0.286733564092931	0.774385966770786	   
df.mm.trans3:probe2	0.215600603190718	0.160814108462067	1.34068214071885	0.18038060198661	   
df.mm.trans3:probe3	0.109211294800464	0.160814108462067	0.679115133895263	0.49724913595014	   
df.mm.trans3:probe4	-0.0140639155717952	0.160814108462067	-0.0874544883299997	0.930330785483428	   
df.mm.trans3:probe5	0.0462682267351976	0.160814108462067	0.287712484791789	0.77363671784567	   
df.mm.trans3:probe6	0.0901402103491264	0.160814108462067	0.560524267498511	0.57526908040721	   
df.mm.trans3:probe7	0.0408355134815505	0.160814108462067	0.253929918662471	0.799610895139234	   
df.mm.trans3:probe8	0.184350041291480	0.160814108462067	1.14635490041574	0.251969806570977	   
df.mm.trans3:probe9	0.0369010559721173	0.160814108462067	0.229464045941103	0.818563271008975	   
df.mm.trans3:probe10	0.133216586458711	0.160814108462067	0.828388676420972	0.40768213474446	   
df.mm.trans3:probe11	0.0752798399997248	0.160814108462067	0.468117136734193	0.639820409849517