chr6.20476_chr6_32948492_32959646_-_2.R 

fitVsDatCorrelation=0.922086067908145
cont.fitVsDatCorrelation=0.236423138761587

fstatistic=9450.99388829114,59,853
cont.fstatistic=1486.98729365752,59,853

residuals=-0.898683087822703,-0.085968414357258,-0.000419997709635161,0.0948330311109921,1.14395589666020
cont.residuals=-0.671716129657728,-0.259393309693845,-0.108688289552249,0.118963700859570,1.96972212974321

predictedValues:
Include	Exclude	Both
chr6.20476_chr6_32948492_32959646_-_2.R.tl.Lung	48.1578949570718	65.224254902597	65.0397498642979
chr6.20476_chr6_32948492_32959646_-_2.R.tl.cerebhem	50.9454456758569	73.9672961555212	68.8384981495709
chr6.20476_chr6_32948492_32959646_-_2.R.tl.cortex	46.9459263830373	70.8947363818982	82.6534506117314
chr6.20476_chr6_32948492_32959646_-_2.R.tl.heart	46.8871980275113	121.705859376783	182.420302706105
chr6.20476_chr6_32948492_32959646_-_2.R.tl.kidney	46.8654924710941	85.305445994994	93.4758770382416
chr6.20476_chr6_32948492_32959646_-_2.R.tl.liver	53.1034328333396	78.0996123369544	89.9210021778913
chr6.20476_chr6_32948492_32959646_-_2.R.tl.stomach	50.3600037174932	69.335372805338	99.5882662906277
chr6.20476_chr6_32948492_32959646_-_2.R.tl.testicle	48.7088283426794	81.3919947875169	99.78896436102


diffExp=-17.0663599455252,-23.0218504796643,-23.9488099988609,-74.8186613492722,-38.4399535238999,-24.9961795036149,-18.9753690878448,-32.6831664448375
diffExpScore=0.996077667676503
diffExp1.5=0,0,-1,-1,-1,0,0,-1
diffExp1.5Score=0.8
diffExp1.4=0,-1,-1,-1,-1,-1,0,-1
diffExp1.4Score=0.857142857142857
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	60.3790078677498	58.4576718958168	69.901814028875
cerebhem	62.1476120811281	54.2776009919938	58.538986675661
cortex	61.6306783892496	54.7733451551288	59.1793040637246
heart	59.875156585589	66.3353811102181	59.9205674131463
kidney	59.8522670554939	60.4716991478222	70.0315226924205
liver	60.5887663759137	55.5153676679414	71.8305923362616
stomach	61.9654500521002	57.6064217989885	67.7669932863496
testicle	57.8578968050454	62.9411188249403	55.0883366928397
cont.diffExp=1.92133597193308,7.87001108913433,6.8573332341208,-6.46022452462908,-0.61943209232831,5.07339870797228,4.35902825311172,-5.08322201989482
cont.diffExpScore=2.56357419294003

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=0,0,0,0,0,0,0,0
cont.diffExp1.2Score=0

tran.correlation=-0.360821891677925
cont.tran.correlation=-0.734095426447382

tran.covariance=-0.00310203681634690
cont.tran.covariance=-0.00123044534596222

tran.mean=64.8686746968554
cont.tran.mean=59.66721511282

weightedLogRatios:
wLogRatio
Lung	-1.22132027563481
cerebhem	-1.53516680563059
cortex	-1.67150970246344
heart	-4.12514604491012
kidney	-2.483729504733
liver	-1.60666547252209
stomach	-1.30431694798507
testicle	-2.1268636157378

cont.weightedLogRatios:
wLogRatio
Lung	0.132085940217451
cerebhem	0.549972426943425
cortex	0.479159109546178
heart	-0.424549437184197
kidney	-0.0421836604851045
liver	0.355079119364069
stomach	0.298344245035943
testicle	-0.345267829098293

varWeightedLogRatios=0.90494875932393
cont.varWeightedLogRatios=0.134310142531991

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.86228994023469	0.0779404090855288	49.5543965646416	2.63176697379511e-253	***
df.mm.trans1	-0.0323439759930929	0.0673074307996917	-0.480540938924697	0.630966017060247	   
df.mm.trans2	0.389829164947069	0.0594658108873667	6.5555175172073	9.59237917443413e-11	***
df.mm.exp2	0.125297385882133	0.0764920464083545	1.63804463032967	0.101781176703049	   
df.mm.exp3	-0.181781824234123	0.0764920464083545	-2.37648007563658	0.0176985264634460	*  
df.mm.exp4	-0.434279438999979	0.0764920464083545	-5.67744568737994	1.87410975138703e-08	***
df.mm.exp5	-0.121501348116344	0.0764920464083545	-1.58841806202577	0.112562402948728	   
df.mm.exp6	-0.0460227423099795	0.0764920464083545	-0.601667029069743	0.547555672476348	   
df.mm.exp7	-0.320209739055186	0.0764920464083545	-4.18618345423443	3.13130566166136e-05	***
df.mm.exp8	-0.195238260611563	0.0764920464083545	-2.55239949483478	0.0108715708751042	*  
df.mm.trans1:exp2	-0.0690271089997063	0.0707031891460811	-0.976294136564168	0.329195513349425	   
df.mm.trans2:exp2	0.000494258328326575	0.0522177658139094	0.00946532890909166	0.99245008617974	   
df.mm.trans1:exp3	0.156293170437407	0.0707031891460811	2.21055333323773	0.0273314814088161	*  
df.mm.trans2:exp3	0.265146607523194	0.0522177658139094	5.07770877191698	4.69240925106886e-07	***
df.mm.trans1:exp4	0.407539023342759	0.0707031891460811	5.76408261444523	1.14687546541905e-08	***
df.mm.trans2:exp4	1.05805517644157	0.0522177658139094	20.2623601364371	7.90763474303227e-75	***
df.mm.trans1:exp5	0.0942978938692	0.0707031891460811	1.33371485795880	0.182653330936624	   
df.mm.trans2:exp5	0.389908238305884	0.0522177658139094	7.46696516460349	2.02789819546026e-13	***
df.mm.trans1:exp6	0.143779226248232	0.0707031891460811	2.03356069202434	0.0423049797888605	*  
df.mm.trans2:exp6	0.226176428004502	0.0522177658139094	4.33140760580482	1.65775051955633e-05	***
df.mm.trans1:exp7	0.364921931367545	0.0707031891460811	5.16132208143501	3.05218856417874e-07	***
df.mm.trans2:exp7	0.381333537653935	0.0522177658139094	7.30275475616688	6.46849333774522e-13	***
df.mm.trans1:exp8	0.206613463725846	0.0707031891460811	2.92226512299124	0.00356673222048109	** 
df.mm.trans2:exp8	0.416683777186817	0.0522177658139094	7.97973200676128	4.71599225759573e-15	***
df.mm.trans1:probe2	0.063621134912629	0.0484071644785788	1.31429170863298	0.189101354211474	   
df.mm.trans1:probe3	0.13123764685899	0.0484071644785788	2.71112031189238	0.00684042043145022	** 
df.mm.trans1:probe4	0.151146833142362	0.0484071644785788	3.12240625474454	0.00185429833432055	** 
df.mm.trans1:probe5	0.338685244861903	0.0484071644785788	6.99659334542882	5.30356464658344e-12	***
df.mm.trans1:probe6	0.071041551403425	0.0484071644785788	1.46758340771772	0.142586027331079	   
df.mm.trans1:probe7	0.140264746673897	0.0484071644785788	2.89760303427744	0.00385653591176641	** 
df.mm.trans1:probe8	-0.0410008291756958	0.0484071644785788	-0.846999191490332	0.397233142372746	   
df.mm.trans1:probe9	0.103406897626919	0.0484071644785788	2.13618993677431	0.0329480053700918	*  
df.mm.trans1:probe10	0.0733103322054443	0.0484071644785788	1.51445210631756	0.130281649027338	   
df.mm.trans1:probe11	0.0179762553078395	0.0484071644785788	0.371355263244025	0.710465158482328	   
df.mm.trans1:probe12	-0.0103947536731947	0.0484071644785788	-0.214735851297271	0.830024594920576	   
df.mm.trans1:probe13	0.0165779901961651	0.0484071644785788	0.342469764026381	0.732081762929098	   
df.mm.trans1:probe14	0.0880999690040685	0.0484071644785788	1.81997788866676	0.0691127275885367	.  
df.mm.trans1:probe15	-0.0253097455713228	0.0484071644785788	-0.522851231712258	0.601213560177345	   
df.mm.trans1:probe16	-0.0216373318446425	0.0484071644785788	-0.446986145082253	0.65499853118907	   
df.mm.trans1:probe17	0.0227311788319688	0.0484071644785788	0.469582944525244	0.63877302428283	   
df.mm.trans1:probe18	0.114820603881748	0.0484071644785788	2.37197541146122	0.0179143126488228	*  
df.mm.trans1:probe19	0.068729648554713	0.0484071644785788	1.41982388960476	0.156024314004294	   
df.mm.trans1:probe20	0.0478660430006526	0.0484071644785788	0.988821458894464	0.32303090339546	   
df.mm.trans1:probe21	0.0529961946825952	0.0484071644785788	1.09480064063755	0.273913019427109	   
df.mm.trans1:probe22	0.0210824352173876	0.0484071644785788	0.435523035577037	0.663293003862662	   
df.mm.trans2:probe2	-0.259536454093814	0.0484071644785788	-5.36152978364729	1.06299722507658e-07	***
df.mm.trans2:probe3	-0.273728232574112	0.0484071644785788	-5.65470494962047	2.12965719584719e-08	***
df.mm.trans2:probe4	-0.0442210072552972	0.0484071644785788	-0.91352194931529	0.361226225710619	   
df.mm.trans2:probe5	-0.344435680039923	0.0484071644785788	-7.11538640509181	2.36579182920378e-12	***
df.mm.trans2:probe6	-0.266681789529983	0.0484071644785788	-5.50913883105042	4.77583743346268e-08	***
df.mm.trans3:probe2	0.603132633316151	0.0484071644785788	12.4595736976713	7.40352759437966e-33	***
df.mm.trans3:probe3	-0.537120092727829	0.0484071644785788	-11.0958800936485	8.11695982222112e-27	***
df.mm.trans3:probe4	-0.132416491958501	0.0484071644785788	-2.73547301075852	0.00635839515466726	** 
df.mm.trans3:probe5	0.305578563202459	0.0484071644785788	6.31267223548456	4.40569280539018e-10	***
df.mm.trans3:probe6	-0.455892378962028	0.0484071644785788	-9.41786993459966	4.18185883791772e-20	***
df.mm.trans3:probe7	0.251517711272770	0.0484071644785788	5.19587779994987	2.55057085170586e-07	***
df.mm.trans3:probe8	0.390702792267931	0.0484071644785788	8.07117699366228	2.35921919910533e-15	***
df.mm.trans3:probe9	-0.379128758664251	0.0484071644785788	-7.8320794607175	1.42311424106685e-14	***
df.mm.trans3:probe10	-0.494139076060567	0.0484071644785788	-10.2079739927596	3.67640356412037e-23	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.90326553733699	0.195694511737012	19.9457077395327	6.00497527366356e-73	***
df.mm.trans1	0.18638253326012	0.168996993487220	1.10287484655291	0.270392571993399	   
df.mm.trans2	0.113005197851078	0.149308079893173	0.756859226452653	0.449343200973608	   
df.mm.exp2	0.132078234268507	0.192057930530250	0.687699976272024	0.491828683243013	   
df.mm.exp3	0.121938731454517	0.19205793053025	0.634905994862372	0.525659984948897	   
df.mm.exp4	0.272112441843728	0.19205793053025	1.41682481474447	0.156899257660893	   
df.mm.exp5	0.0232564912882624	0.19205793053025	0.12109102302651	0.903647457266497	   
df.mm.exp6	-0.0753939095215094	0.19205793053025	-0.392558168847053	0.694743912430405	   
df.mm.exp7	0.0422829448204968	0.19205793053025	0.220157244763382	0.825801371351115	   
df.mm.exp8	0.269398771207710	0.19205793053025	1.40269537667062	0.161071546160906	   
df.mm.trans1:exp2	-0.103207331586495	0.177523139030597	-0.581373967078774	0.561142028281602	   
df.mm.trans2:exp2	-0.206269532191	0.131109527199645	-1.5732612007433	0.116029162629438	   
df.mm.trans1:exp3	-0.101420451761403	0.177523139030597	-0.57130835064787	0.567941134359758	   
df.mm.trans2:exp3	-0.187037993118577	0.131109527199645	-1.42657819849939	0.154067412785099	   
df.mm.trans1:exp4	-0.28049226358008	0.177523139030597	-1.58003213052545	0.114470229008657	   
df.mm.trans2:exp4	-0.145691970262931	0.131109527199645	-1.11122336701802	0.266785329531424	   
df.mm.trans1:exp5	-0.0320186737182275	0.177523139030597	-0.180363381884031	0.856910140248617	   
df.mm.trans2:exp5	0.0106160466160597	0.131109527199645	0.0809708252543256	0.93548414809125	   
df.mm.trans1:exp6	0.0788619194060815	0.177523139030597	0.444234592947848	0.656985661114961	   
df.mm.trans2:exp6	0.0237508518560403	0.131109527199645	0.181152753452265	0.8562907118554	   
df.mm.trans1:exp7	-0.0163474649972876	0.177523139030597	-0.0920863899013751	0.926651023409531	   
df.mm.trans2:exp7	-0.0569518287747768	0.131109527199645	-0.43438360271145	0.66411975924619	   
df.mm.trans1:exp8	-0.312050314715251	0.177523139030597	-1.75780079385295	0.079140059906903	.  
df.mm.trans2:exp8	-0.195502038681227	0.131109527199645	-1.49113525810774	0.136295684525614	   
df.mm.trans1:probe2	-0.00435123236838588	0.121541784657730	-0.0358003001242681	0.971449969664516	   
df.mm.trans1:probe3	-0.00227966354428982	0.121541784657730	-0.0187562125297857	0.98503997121379	   
df.mm.trans1:probe4	0.0171790261495085	0.121541784657730	0.141342553080703	0.887632707269845	   
df.mm.trans1:probe5	0.270418424547869	0.121541784657730	2.22490088745518	0.0263487707353277	*  
df.mm.trans1:probe6	0.164123202944135	0.121541784657730	1.35034386245288	0.17726386337383	   
df.mm.trans1:probe7	0.00930315796302317	0.121541784657730	0.0765428777372451	0.939005151359165	   
df.mm.trans1:probe8	-0.0669481565892705	0.121541784657730	-0.550824202374528	0.581898422076688	   
df.mm.trans1:probe9	-0.0315854091333274	0.121541784657730	-0.259872843090746	0.795024570546268	   
df.mm.trans1:probe10	0.0343331124025018	0.121541784657730	0.282479910091713	0.77764407652428	   
df.mm.trans1:probe11	-0.0791714988117974	0.121541784657730	-0.651393255700087	0.514968111621872	   
df.mm.trans1:probe12	0.0638103726701399	0.121541784657730	0.52500769879128	0.599714262394265	   
df.mm.trans1:probe13	0.0096503565207924	0.121541784657730	0.0793994966255309	0.936733491820589	   
df.mm.trans1:probe14	0.0859983288717768	0.121541784657730	0.707561840678531	0.479410665888926	   
df.mm.trans1:probe15	0.0221665599806344	0.121541784657730	0.182378101844209	0.85532934353199	   
df.mm.trans1:probe16	-0.0468147336735823	0.121541784657730	-0.385173986093885	0.700204538999168	   
df.mm.trans1:probe17	-0.00358386938722812	0.121541784657730	-0.0294867267032532	0.97648330224971	   
df.mm.trans1:probe18	-0.0611144992196838	0.121541784657730	-0.502827068006173	0.615215657342147	   
df.mm.trans1:probe19	-0.0443232468799624	0.121541784657730	-0.364674971696194	0.715444432087893	   
df.mm.trans1:probe20	-0.121631137811105	0.121541784657730	-1.00073516407239	0.317238657735319	   
df.mm.trans1:probe21	0.0860501787689657	0.121541784657730	0.70798844209248	0.479145839937373	   
df.mm.trans1:probe22	0.050560233001396	0.121541784657730	0.415990543036514	0.677521559046945	   
df.mm.trans2:probe2	0.172826345141329	0.121541784657730	1.42195003659046	0.155406286302871	   
df.mm.trans2:probe3	0.188468980983574	0.121541784657730	1.55065174922613	0.121356083390177	   
df.mm.trans2:probe4	0.164337362077725	0.121541784657730	1.35210588309618	0.176699818165608	   
df.mm.trans2:probe5	0.180343625332250	0.121541784657730	1.48379938504367	0.138231545622541	   
df.mm.trans2:probe6	0.126538883574333	0.121541784657730	1.04111424668212	0.298117519872197	   
df.mm.trans3:probe2	0.121773130334583	0.121541784657730	1.00190342504435	0.316674364517443	   
df.mm.trans3:probe3	-0.0174321045958747	0.121541784657730	-0.143424787162413	0.885988582045218	   
df.mm.trans3:probe4	0.0638188803142112	0.121541784657730	0.525077696480513	0.599665624468949	   
df.mm.trans3:probe5	0.119687358944971	0.121541784657730	0.984742484093177	0.325029807602077	   
df.mm.trans3:probe6	0.0579588402418814	0.121541784657730	0.476863495176557	0.633581467102588	   
df.mm.trans3:probe7	-0.0254067607399664	0.121541784657730	-0.209037252591886	0.834469066106484	   
df.mm.trans3:probe8	0.126898364461014	0.121541784657730	1.04407191994398	0.296747907754518	   
df.mm.trans3:probe9	-0.0759352543283418	0.121541784657730	-0.624766655699362	0.532291296081005	   
df.mm.trans3:probe10	0.073020867637592	0.121541784657730	0.600788180321887	0.548140675772946