chr4.17381_chr4_135642358_135680045_+_2.R 

fitVsDatCorrelation=0.886300255582116
cont.fitVsDatCorrelation=0.241668754227273

fstatistic=10073.5360306280,67,1037
cont.fstatistic=2282.54510773862,67,1037

residuals=-0.551721343386214,-0.106271774781958,-0.00236459792258007,0.102001819628064,1.08640746445169
cont.residuals=-0.775994551227946,-0.275862599288426,-0.0327427237111925,0.23223729249814,1.40048765908934

predictedValues:
Include	Exclude	Both
chr4.17381_chr4_135642358_135680045_+_2.R.tl.Lung	70.4270543107096	114.171190147146	102.862096804720
chr4.17381_chr4_135642358_135680045_+_2.R.tl.cerebhem	61.270204892614	69.0113048832182	106.559126164358
chr4.17381_chr4_135642358_135680045_+_2.R.tl.cortex	79.0878808240695	89.4372446910928	128.218920224687
chr4.17381_chr4_135642358_135680045_+_2.R.tl.heart	63.0669737730614	112.811932851730	86.8518136361586
chr4.17381_chr4_135642358_135680045_+_2.R.tl.kidney	67.909353224417	135.699050261615	96.328975866702
chr4.17381_chr4_135642358_135680045_+_2.R.tl.liver	55.8878861802997	143.915655337214	74.251260768257
chr4.17381_chr4_135642358_135680045_+_2.R.tl.stomach	56.6901978406506	89.308401380578	79.6596190179413
chr4.17381_chr4_135642358_135680045_+_2.R.tl.testicle	60.5180294437044	120.830071006405	91.3015240989493


diffExp=-43.7441358364364,-7.74109999060416,-10.3493638670233,-49.7449590786685,-67.7896970371985,-88.027769156914,-32.6182035399274,-60.3120415627004
diffExpScore=0.997232425884136
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	84.537688240215	88.5779694808485	82.2665056229497
cerebhem	75.6574226674756	97.9481988045643	88.567929761392
cortex	79.2671940685784	85.6293193971178	85.0664508748757
heart	81.5182910689812	80.8598198177388	83.4605876950728
kidney	87.328402243263	94.6306332288751	81.8345325409384
liver	85.445797661832	88.7055053811512	82.983710452551
stomach	78.1397286761372	86.6904481654796	85.6754813240191
testicle	85.8756072090576	79.4937450798055	84.879846765227
cont.diffExp=-4.04028124063346,-22.2907761370887,-6.3621253285394,0.658471251242361,-7.30223098561217,-3.25970771931929,-8.55071948934234,6.38186212925216
cont.diffExpScore=1.28581933140938

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

tran.correlation=-0.169665429763366
cont.tran.correlation=-0.225134416419402

tran.covariance=-0.00348329047214769
cont.tran.covariance=-0.000859330881218998

tran.mean=86.8776519405328
cont.tran.mean=85.019110699445

weightedLogRatios:
wLogRatio
Lung	-2.17218107813796
cerebhem	-0.496701615463203
cortex	-0.545042470318521
heart	-2.57903941160955
kidney	-3.15971337718426
liver	-4.25294731975711
stomach	-1.93834907509578
testicle	-3.07600088879345

cont.weightedLogRatios:
wLogRatio
Lung	-0.208243561183601
cerebhem	-1.1504688408583
cortex	-0.340577053093549
heart	0.035659535218804
kidney	-0.362163993944249
liver	-0.167228355720032
stomach	-0.458000579298758
testicle	0.340877940569442

varWeightedLogRatios=1.67256994939772
cont.varWeightedLogRatios=0.186028923057650

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.1308758277659	0.08082132742151	51.1112098694199	1.37579979763958e-285	***
df.mm.trans1	0.0409599327754405	0.0687030125823218	0.596188307264709	0.551179546128502	   
df.mm.trans2	0.619211002959497	0.0601993858488315	10.2860019953429	1.07161362516800e-23	***
df.mm.exp2	-0.678023253788981	0.0756753670346209	-8.95962953808722	1.48178503184118e-18	***
df.mm.exp3	-0.348529513191476	0.0756753670346209	-4.6055873509279	4.6233606847241e-06	***
df.mm.exp4	0.0468287354551644	0.0756753670346209	0.618810813745253	0.536176902085216	   
df.mm.exp5	0.201956929543076	0.0756753670346209	2.66872745328981	0.00773277252810986	** 
df.mm.exp6	0.326233046728233	0.0756753670346209	4.31095427101112	1.78036932720156e-05	***
df.mm.exp7	-0.206953161404772	0.0756753670346209	-2.73474935787351	0.00634920117523769	** 
df.mm.exp8	0.0242717855710482	0.0756753670346209	0.320735617442649	0.748475374993976	   
df.mm.trans1:exp2	0.538739441086425	0.0682128540332207	7.89791673024047	7.19525340197465e-15	***
df.mm.trans2:exp2	0.17459459387726	0.046341508833164	3.76756385955894	0.000174130867416335	***
df.mm.trans1:exp3	0.464511679349295	0.0682128540332207	6.8097382221109	1.65309411121675e-11	***
df.mm.trans2:exp3	0.104367725921066	0.0463415088331640	2.25214345732256	0.0245217340663392	*  
df.mm.trans1:exp4	-0.157208981493754	0.0682128540332207	-2.30468265434533	0.0213811740688867	*  
df.mm.trans2:exp4	-0.0588056042697651	0.046341508833164	-1.26896179581622	0.204739436799350	   
df.mm.trans1:exp5	-0.238360638001783	0.0682128540332207	-3.49436541514152	0.000495263765802816	***
df.mm.trans2:exp5	-0.0292163515118435	0.046341508833164	-0.630457493670015	0.528534209541675	   
df.mm.trans1:exp6	-0.557462878761729	0.0682128540332207	-8.17240220575196	8.74598809351117e-16	***
df.mm.trans2:exp6	-0.0947046355581828	0.046341508833164	-2.04362434333187	0.04124295095418	*  
df.mm.trans1:exp7	-0.0100230039246250	0.0682128540332207	-0.146937172863984	0.883210171315318	   
df.mm.trans2:exp7	-0.0386502647045266	0.046341508833164	-0.834031210413821	0.404455470665218	   
df.mm.trans1:exp8	-0.175907941123774	0.0682128540332207	-2.57880928187090	0.0100510278558838	*  
df.mm.trans2:exp8	0.0324144111473438	0.046341508833164	0.699468186589268	0.484416350242172	   
df.mm.trans1:probe2	-0.170599884454551	0.0518113819654309	-3.29271055862546	0.00102577002429097	** 
df.mm.trans1:probe3	0.617113185495726	0.0518113819654309	11.9107648181913	9.4983043894748e-31	***
df.mm.trans1:probe4	0.644325181777555	0.0518113819654309	12.4359775272440	3.40477881982372e-33	***
df.mm.trans1:probe5	0.395702028116843	0.0518113819654309	7.63735714250703	5.02352358899742e-14	***
df.mm.trans1:probe6	0.0649614670826581	0.0518113819654309	1.25380687830333	0.210194783646851	   
df.mm.trans1:probe7	0.026005930943563	0.0518113819654309	0.501934709267443	0.615820000214203	   
df.mm.trans1:probe8	0.00826662232757861	0.0518113819654309	0.159552245355937	0.873264869554666	   
df.mm.trans1:probe9	0.0414293053354973	0.0518113819654309	0.799617840017073	0.424115368191545	   
df.mm.trans1:probe10	0.0975362559313782	0.0518113819654309	1.88252565809681	0.060044460134346	.  
df.mm.trans1:probe11	0.105666785911584	0.0518113819654309	2.0394512152192	0.0416580943069303	*  
df.mm.trans1:probe12	-0.0132333419710858	0.0518113819654309	-0.255413800386858	0.798454162003091	   
df.mm.trans1:probe13	0.0742226455132192	0.0518113819654309	1.43255483057258	0.152286467222762	   
df.mm.trans1:probe14	0.0198521947094352	0.0518113819654309	0.383162810107647	0.70167758136771	   
df.mm.trans1:probe15	0.260319116881969	0.0518113819654309	5.02436157861331	5.94549584410828e-07	***
df.mm.trans1:probe16	0.33235845448344	0.0518113819654309	6.41477686708286	2.13994218576141e-10	***
df.mm.trans1:probe17	0.147263994211931	0.0518113819654309	2.84230971314735	0.00456661647719275	** 
df.mm.trans1:probe18	0.214324644681470	0.0518113819654309	4.13663246474433	3.80971529385278e-05	***
df.mm.trans1:probe19	0.318051328441806	0.0518113819654309	6.13863819834054	1.18337256627330e-09	***
df.mm.trans1:probe20	0.126103004051014	0.0518113819654309	2.43388613210802	0.0151056807918136	*  
df.mm.trans2:probe2	-0.0040211350967774	0.0518113819654309	-0.0776110372709291	0.9381524341347	   
df.mm.trans2:probe3	-0.135313434391796	0.0518113819654309	-2.6116546067441	0.00914068141797736	** 
df.mm.trans2:probe4	-0.175213590509197	0.0518113819654309	-3.38175867661862	0.000747117295567717	***
df.mm.trans2:probe5	-0.194812159333429	0.0518113819654309	-3.76002630972881	0.000179388776243924	***
df.mm.trans2:probe6	0.187276459848907	0.0518113819654309	3.61458144416723	0.000315285713394956	***
df.mm.trans3:probe2	-0.649121633770792	0.0518113819654309	-12.5285527840947	1.2388915803906e-33	***
df.mm.trans3:probe3	-0.469287351886502	0.0518113819654309	-9.05761116736118	6.47134951661655e-19	***
df.mm.trans3:probe4	0.189821221046355	0.0518113819654309	3.66369731602615	0.00026117561128753	***
df.mm.trans3:probe5	-0.052925043146783	0.0518113819654309	-1.02149452763285	0.307258439503525	   
df.mm.trans3:probe6	-0.0373225772745374	0.0518113819654309	-0.720354791915016	0.471468914681461	   
df.mm.trans3:probe7	-0.271063962400348	0.0518113819654309	-5.23174546050915	2.03121649886936e-07	***
df.mm.trans3:probe8	-0.535945778334062	0.0518113819654309	-10.3441706822576	6.18766670971379e-24	***
df.mm.trans3:probe9	0.275696945048303	0.0518113819654309	5.32116563175735	1.26324927817686e-07	***
df.mm.trans3:probe10	0.210427271878721	0.0518113819654309	4.06141013608014	5.24520899490528e-05	***
df.mm.trans3:probe11	-0.0810120311464392	0.0518113819654309	-1.56359525790089	0.118217746453628	   
df.mm.trans3:probe12	0.339949786358038	0.0518113819654309	6.56129548107511	8.40723553527592e-11	***
df.mm.trans3:probe13	-0.627975022279708	0.0518113819654309	-12.1204067225750	1.02523116725562e-31	***
df.mm.trans3:probe14	-0.438018575530237	0.0518113819654309	-8.45409944522398	9.43907558866918e-17	***
df.mm.trans3:probe15	-0.551411092118273	0.0518113819654309	-10.6426632759223	3.55524057850494e-25	***
df.mm.trans3:probe16	0.00125085154868856	0.0518113819654309	0.0241424085063614	0.980743660755467	   
df.mm.trans3:probe17	-0.0277629044608135	0.0518113819654309	-0.535845665713707	0.59218012576464	   
df.mm.trans3:probe18	-0.413069045855866	0.0518113819654309	-7.9725541027157	4.08152636912734e-15	***
df.mm.trans3:probe19	-0.0183383159547315	0.0518113819654309	-0.353943771794526	0.723452972900842	   
df.mm.trans3:probe20	0.0029564917461796	0.0518113819654309	0.0570625919253072	0.954506327880903	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.6466255816819	0.169345310500242	27.4387614747399	4.70757158538453e-125	***
df.mm.trans1	-0.230615430163404	0.143953747967753	-1.60201060006484	0.109457810433034	   
df.mm.trans2	-0.134791994726081	0.126136058559477	-1.06862380405301	0.285487906142339	   
df.mm.exp2	-0.0842320953155821	0.158562955305866	-0.531221779722127	0.595378861305271	   
df.mm.exp3	-0.131697215217362	0.158562955305866	-0.830567360221813	0.40640925631539	   
df.mm.exp4	-0.141946634589622	0.158562955305866	-0.895206792253642	0.370884292744769	   
df.mm.exp5	0.103841100975179	0.158562955305866	0.654888783921004	0.512684592917945	   
df.mm.exp6	0.00344327627186394	0.158562955305866	0.021715515236342	0.98267906486966	   
df.mm.exp7	-0.140840940869233	0.158562955305866	-0.888233576358061	0.374621095343492	   
df.mm.exp8	-0.123775106364625	0.158562955305866	-0.780605445489233	0.435212734821601	   
df.mm.trans1:exp2	-0.0267498003296066	0.142926716436101	-0.187157453810015	0.851573792354057	   
df.mm.trans2:exp2	0.184787675375241	0.0970995831517765	1.90307382768471	0.0573076251167203	.  
df.mm.trans1:exp3	0.0673241146929962	0.142926716436101	0.471039399572964	0.637711669549597	   
df.mm.trans2:exp3	0.0978417808067596	0.0970995831517765	1.00764367498698	0.313860610840565	   
df.mm.trans1:exp4	0.105576610344727	0.142926716436101	0.738676525825927	0.460270589694289	   
df.mm.trans2:exp4	0.050780495241535	0.0970995831517764	0.522973359856344	0.601104510340398	   
df.mm.trans1:exp5	-0.0713627999449285	0.142926716436101	-0.499296434735021	0.617676473878515	   
df.mm.trans2:exp5	-0.0377430340826296	0.0970995831517764	-0.388704388397152	0.697574628220801	   
df.mm.trans1:exp6	0.00724150356155401	0.142926716436101	0.0506658498993189	0.959601546600896	   
df.mm.trans2:exp6	-0.00200449668563559	0.0970995831517764	-0.0206437208129139	0.983533834990484	   
df.mm.trans1:exp7	0.0621421086061143	0.142926716436101	0.43478301437014	0.663810395649626	   
df.mm.trans2:exp7	0.119301472250267	0.0970995831517764	1.22865071484176	0.219481543525963	   
df.mm.trans1:exp8	0.139477478124724	0.142926716436101	0.975867084913274	0.329357921589818	   
df.mm.trans2:exp8	0.0155702714537313	0.0970995831517765	0.160353638484661	0.872633737881085	   
df.mm.trans1:probe2	0.0671245530317028	0.108560634257133	0.618313935719223	0.536504194257696	   
df.mm.trans1:probe3	0.0374965251940568	0.108560634257133	0.345397071881912	0.72986592736692	   
df.mm.trans1:probe4	-0.0105011826108245	0.108560634257133	-0.0967310359107868	0.922958683078856	   
df.mm.trans1:probe5	0.0666631681449481	0.108560634257133	0.614063915535462	0.53930777698908	   
df.mm.trans1:probe6	0.0214855117346704	0.108560634257133	0.197912547966334	0.843152274879326	   
df.mm.trans1:probe7	-0.0595790699309507	0.108560634257133	-0.548809154797622	0.583254565955357	   
df.mm.trans1:probe8	-0.0277836897297446	0.108560634257133	-0.255927850089169	0.798057306103041	   
df.mm.trans1:probe9	0.0468865899455097	0.108560634257133	0.431893109932057	0.665908885042215	   
df.mm.trans1:probe10	0.0359859222333942	0.108560634257133	0.331482240129136	0.740347229937025	   
df.mm.trans1:probe11	0.0488988586319646	0.108560634257133	0.450429006486316	0.652495286581479	   
df.mm.trans1:probe12	0.184252290998135	0.108560634257133	1.69722931575475	0.0899533763977367	.  
df.mm.trans1:probe13	-0.0242994755357532	0.108560634257133	-0.223833212674479	0.82293117388112	   
df.mm.trans1:probe14	0.0620319940574689	0.108560634257133	0.571404123437066	0.567849552740864	   
df.mm.trans1:probe15	0.00529194068203571	0.108560634257133	0.0487464053452508	0.961130780245352	   
df.mm.trans1:probe16	0.158831266294982	0.108560634257133	1.46306501782940	0.143752604158308	   
df.mm.trans1:probe17	0.128232522377352	0.108560634257133	1.18120645899715	0.237791542246876	   
df.mm.trans1:probe18	0.0708967176130545	0.108560634257133	0.653061011463245	0.51386170236124	   
df.mm.trans1:probe19	0.0456524551551257	0.108560634257133	0.420524948730448	0.674189134023518	   
df.mm.trans1:probe20	-0.0100749748170848	0.108560634257133	-0.0928050474836176	0.926076366637115	   
df.mm.trans2:probe2	0.0212489180630676	0.108560634257133	0.195733179052162	0.84485735957893	   
df.mm.trans2:probe3	-0.241916802277597	0.108560634257133	-2.22840262433068	0.0260674467430384	*  
df.mm.trans2:probe4	-0.177198163409473	0.108560634257133	-1.63225062769777	0.102930294802501	   
df.mm.trans2:probe5	-0.149298268432793	0.108560634257133	-1.37525235970131	0.169350237481861	   
df.mm.trans2:probe6	-0.179546388699018	0.108560634257133	-1.65388116905941	0.0984543020469686	.  
df.mm.trans3:probe2	0.202466771085187	0.108560634257133	1.86501094499533	0.0624621491976537	.  
df.mm.trans3:probe3	0.149260382407992	0.108560634257133	1.37490337477634	0.169458388303688	   
df.mm.trans3:probe4	0.0490035504272903	0.108560634257133	0.451393368900391	0.651800443387228	   
df.mm.trans3:probe5	0.0117132662627937	0.108560634257133	0.107896074326998	0.91409900263817	   
df.mm.trans3:probe6	0.164502022363676	0.108560634257133	1.51530085918660	0.130000968268741	   
df.mm.trans3:probe7	0.0772225319140512	0.108560634257133	0.711330883818758	0.477039188504518	   
df.mm.trans3:probe8	0.207855206446538	0.108560634257133	1.91464620549490	0.0558125603201744	.  
df.mm.trans3:probe9	0.345440270257184	0.108560634257133	3.18200305866846	0.00150606596591855	** 
df.mm.trans3:probe10	0.170698959059614	0.108560634257133	1.57238358294133	0.116166655330672	   
df.mm.trans3:probe11	0.110426144764509	0.108560634257133	1.01718404208065	0.309303139811132	   
df.mm.trans3:probe12	0.175963832921752	0.108560634257133	1.62088066384147	0.105347239613606	   
df.mm.trans3:probe13	0.218778986479449	0.108560634257133	2.0152699731033	0.0441340064605616	*  
df.mm.trans3:probe14	0.202823486770830	0.108560634257133	1.86829681089031	0.0620025296783925	.  
df.mm.trans3:probe15	0.063071673397926	0.108560634257133	0.580981069514911	0.561379454202318	   
df.mm.trans3:probe16	0.0601004976262176	0.108560634257133	0.553612255837284	0.579963577990518	   
df.mm.trans3:probe17	0.146402718633114	0.108560634257133	1.34858017028852	0.177766293446683	   
df.mm.trans3:probe18	0.154307494542041	0.108560634257133	1.42139455612016	0.155502738067034	   
df.mm.trans3:probe19	-0.0141617541190935	0.108560634257133	-0.130450178520056	0.896235569327088	   
df.mm.trans3:probe20	0.079041738501693	0.108560634257133	0.728088400022403	0.466723841209914