chr6.20016_chr6_149512268_149517478_-_2.R 

fitVsDatCorrelation=0.933835018355574
cont.fitVsDatCorrelation=0.233529317724722

fstatistic=7318.58188203056,53,715
cont.fstatistic=978.778244450873,53,715

residuals=-1.02731286820501,-0.106613159455995,-0.00405622062448870,0.0990727060081228,0.696968191348997
cont.residuals=-0.897564432991912,-0.4057022051251,-0.13032565806273,0.323882386101064,1.67783559557074

predictedValues:
Include	Exclude	Both
chr6.20016_chr6_149512268_149517478_-_2.R.tl.Lung	92.6707727699993	60.2967666088665	72.6984215187849
chr6.20016_chr6_149512268_149517478_-_2.R.tl.cerebhem	87.474422631188	74.0087900259545	75.7861592907172
chr6.20016_chr6_149512268_149517478_-_2.R.tl.cortex	92.8902637896301	55.1179581313581	74.3797510399796
chr6.20016_chr6_149512268_149517478_-_2.R.tl.heart	91.2983629795146	53.875288277742	66.7090406844702
chr6.20016_chr6_149512268_149517478_-_2.R.tl.kidney	99.8571203934667	59.1635723970497	70.358440262959
chr6.20016_chr6_149512268_149517478_-_2.R.tl.liver	108.064786076641	58.8565275640773	69.4960714646416
chr6.20016_chr6_149512268_149517478_-_2.R.tl.stomach	105.391705527768	59.4114617695212	72.3318636311767
chr6.20016_chr6_149512268_149517478_-_2.R.tl.testicle	113.135249024638	59.4968004120224	72.9264670961266


diffExp=32.3740061611328,13.4656326052335,37.772305658272,37.4230747017726,40.693547996417,49.2082585125632,45.980243758247,53.6384486126153
diffExpScore=0.9967902991852
diffExp1.5=1,0,1,1,1,1,1,1
diffExp1.5Score=0.875
diffExp1.4=1,0,1,1,1,1,1,1
diffExp1.4Score=0.875
diffExp1.3=1,0,1,1,1,1,1,1
diffExp1.3Score=0.875
diffExp1.2=1,0,1,1,1,1,1,1
diffExp1.2Score=0.875

cont.predictedValues:
Include	Exclude	Both
Lung	100.024116061970	84.5487552071473	80.1011281461781
cerebhem	104.39701143704	102.457490716271	75.7108414356579
cortex	88.4190596515464	105.663608732937	77.0427632747722
heart	93.0948879678384	78.7791455298634	97.901197334718
kidney	96.223671606909	102.775688845826	108.267503258398
liver	91.2459328745452	78.4395050527047	85.5340566137039
stomach	89.7185286692029	104.268368009714	98.1679286411396
testicle	102.158820827850	90.3160373572433	105.860425753821
cont.diffExp=15.4753608548224,1.93952072076871,-17.2445490813905,14.3157424379750,-6.55201723891669,12.8064278218405,-14.5498393405110,11.8427834706072
cont.diffExpScore=4.9768351123594

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=-0.275584760736349
cont.tran.correlation=-0.0488912228838733

tran.covariance=-0.00226781420248074
cont.tran.covariance=-0.000284010915562294

tran.mean=79.4381155237148
cont.tran.mean=94.533164284288

weightedLogRatios:
wLogRatio
Lung	1.85411911704239
cerebhem	0.733470089008278
cortex	2.22893111791453
heart	2.24192131051790
kidney	2.27276407499645
liver	2.66075323068143
stomach	2.50549212432221
testicle	2.83237182126754

cont.weightedLogRatios:
wLogRatio
Lung	0.759965247120778
cerebhem	0.0869921597172206
cortex	-0.814459757473154
heart	0.743043122707545
kidney	-0.302992278286213
liver	0.671153362737268
stomach	-0.687102552073888
testicle	0.562460564151279

varWeightedLogRatios=0.424945888614976
cont.varWeightedLogRatios=0.428783596394595

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.92574482565261	0.103671214054211	37.8672600824351	5.09535036528078e-173	***
df.mm.trans1	-0.0110501126129762	0.0920620444587927	-0.120028972612294	0.904493915451897	   
df.mm.trans2	0.103235212918549	0.0837424012243839	1.23277111008479	0.218066347530603	   
df.mm.exp2	0.105602684247864	0.112897201213904	0.935387973416463	0.349904196621274	   
df.mm.exp3	-0.110301265209962	0.112897201213904	-0.977006197000197	0.32889652295297	   
df.mm.exp4	-0.0415476726608429	0.112897201213904	-0.368013309578183	0.712972229438286	   
df.mm.exp5	0.0884316948975187	0.112897201213904	0.78329395190204	0.433713887056115	   
df.mm.exp6	0.174551496284718	0.112897201213904	1.54611004000001	0.122520467758449	   
df.mm.exp7	0.118894415447028	0.112897201213904	1.05312101778113	0.292641289522036	   
df.mm.exp8	0.183042957103743	0.112897201213904	1.62132413501496	0.105389011581997	   
df.mm.trans1:exp2	-0.163309380910895	0.107201189153111	-1.52339150527190	0.128102932996428	   
df.mm.trans2:exp2	0.0993027054846134	0.090271479768509	1.10004517195535	0.271682666333512	   
df.mm.trans1:exp3	0.11266696790344	0.107201189153111	1.05098617649216	0.293620016488641	   
df.mm.trans2:exp3	0.0204983666162888	0.090271479768509	0.227074671522551	0.820430587431908	   
df.mm.trans1:exp4	0.0266273954667553	0.107201189153111	0.248387127765202	0.803906214637404	   
df.mm.trans2:exp4	-0.0710589086185366	0.090271479768509	-0.78716897962412	0.431443797671786	   
df.mm.trans1:exp5	-0.0137444611856425	0.107201189153111	-0.128211835094589	0.898017386928732	   
df.mm.trans2:exp5	-0.107404154084309	0.090271479768509	-1.18979055577393	0.234523645473437	   
df.mm.trans1:exp6	-0.0208737124396941	0.107201189153111	-0.194715306841244	0.845671140789505	   
df.mm.trans2:exp6	-0.198727230605480	0.090271479768509	-2.20143982479398	0.0280236459424732	*  
df.mm.trans1:exp7	0.00973638787267563	0.107201189153111	0.0908235062464614	0.927658269334825	   
df.mm.trans2:exp7	-0.133685729161726	0.090271479768509	-1.48092985187069	0.139065785815412	   
df.mm.trans1:exp8	0.0164879054168497	0.107201189153111	0.153803381726491	0.877808166330223	   
df.mm.trans2:exp8	-0.196398901137859	0.090271479768509	-2.17564729903067	0.0299084690961371	*  
df.mm.trans1:probe2	0.381739999706166	0.0587165094905368	6.50140825839946	1.49334982704346e-10	***
df.mm.trans1:probe3	0.397143926546246	0.0587165094905368	6.76375230735153	2.79778462193514e-11	***
df.mm.trans1:probe4	0.81117151709427	0.0587165094905368	13.8150500452518	1.19233270560795e-38	***
df.mm.trans1:probe5	0.610124196519643	0.0587165094905368	10.3910161181835	1.190609003702e-23	***
df.mm.trans1:probe6	0.353970409650522	0.0587165094905368	6.02846478310449	2.65165501606797e-09	***
df.mm.trans1:probe7	0.568899844021955	0.0587165094905368	9.68892478381473	6.08916110716245e-21	***
df.mm.trans1:probe8	0.128764616244538	0.0587165094905368	2.19298826448958	0.0286296277869511	*  
df.mm.trans1:probe9	0.87356147123278	0.0587165094905368	14.8776124264262	8.17024272922735e-44	***
df.mm.trans1:probe10	0.37375773669959	0.0587165094905368	6.36546245583327	3.47926108729443e-10	***
df.mm.trans1:probe11	1.39747263545115	0.0587165094905368	23.8003356735022	1.15208089175685e-92	***
df.mm.trans1:probe12	1.34397157646725	0.0587165094905368	22.8891599335253	2.05562052007285e-87	***
df.mm.trans1:probe13	1.54284978963817	0.0587165094905368	26.2762518246563	5.0084873150792e-107	***
df.mm.trans1:probe14	1.30962849417568	0.0587165094905368	22.3042634097101	4.65525417440198e-84	***
df.mm.trans1:probe15	1.54721330864617	0.0587165094905368	26.3505668519947	1.85199414504075e-107	***
df.mm.trans1:probe16	1.64666327135534	0.0587165094905368	28.0442976880417	2.64788926035093e-117	***
df.mm.trans1:probe17	0.0892198903921868	0.0587165094905368	1.51950262654094	0.129078080515493	   
df.mm.trans1:probe18	0.125622811214505	0.0587165094905368	2.13948022974273	0.0327347573532483	*  
df.mm.trans1:probe19	0.388444207498382	0.0587165094905368	6.61558752161497	7.25408018798188e-11	***
df.mm.trans1:probe20	0.8933615537245	0.0587165094905368	15.2148273369091	1.70351214913485e-45	***
df.mm.trans1:probe21	1.05170860387227	0.0587165094905368	17.9116335933044	1.50344451978786e-59	***
df.mm.trans1:probe22	0.138029098038408	0.0587165094905368	2.35077151615516	0.0190052209600545	*  
df.mm.trans2:probe2	0.0681035268089165	0.0587165094905368	1.15987015236137	0.246488836859692	   
df.mm.trans2:probe3	0.197996260557387	0.0587165094905368	3.37207136928494	0.000786205301864042	***
df.mm.trans2:probe4	0.058097937102434	0.0587165094905368	0.989465102856591	0.322770356229830	   
df.mm.trans2:probe5	0.262292362008676	0.0587165094905368	4.46709731699819	9.21388217258243e-06	***
df.mm.trans2:probe6	0.116494333330402	0.0587165094905368	1.98401325864197	0.0476363295703396	*  
df.mm.trans3:probe2	0.183078546866250	0.0587165094905368	3.11800800924239	0.00189379564494053	** 
df.mm.trans3:probe3	0.412592382293708	0.0587165094905368	7.02685472746306	4.93358390057755e-12	***
df.mm.trans3:probe4	0.477888055187141	0.0587165094905368	8.1389043615435	1.76914618043664e-15	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.87651033150091	0.281810316635438	17.3042292763518	2.67426006402095e-56	***
df.mm.trans1	-0.176478953094903	0.250253015127919	-0.705202105176215	0.48091413597675	   
df.mm.trans2	-0.499833402396579	0.227637660271973	-2.19574125739737	0.0284310063449446	*  
df.mm.exp2	0.291277938802618	0.306889393662432	0.949130028009417	0.342875172803432	   
df.mm.exp3	0.138537731769391	0.306889393662433	0.451425610106869	0.651819717520895	   
df.mm.exp4	-0.343140926719129	0.306889393662433	-1.11812572804837	0.263888831572608	   
df.mm.exp5	-0.144830549509052	0.306889393662432	-0.471930775386655	0.637120187755931	   
df.mm.exp6	-0.232478239952338	0.306889393662433	-0.757531034806814	0.448981357599266	   
df.mm.exp7	-0.102483954299391	0.306889393662433	-0.333944269224629	0.738519532162578	   
df.mm.exp8	-0.191727505525391	0.306889393662432	-0.624744645741274	0.532337974965394	   
df.mm.trans1:exp2	-0.248488207379045	0.291405877075349	-0.852722017390177	0.394099025229404	   
df.mm.trans2:exp2	-0.0991583036369642	0.245385708354978	-0.4040916005325	0.686266197509475	   
df.mm.trans1:exp3	-0.261861495980919	0.291405877075349	-0.89861432655049	0.369160634518587	   
df.mm.trans2:exp3	0.0843944609136733	0.245385708354978	0.343925738297633	0.731003251524388	   
df.mm.trans1:exp4	0.27134888291558	0.291405877075349	0.931171620967058	0.352079090869808	   
df.mm.trans2:exp4	0.272460885249127	0.245385708354978	1.11033722002661	0.267227005458654	   
df.mm.trans1:exp5	0.106094625977938	0.291405877075349	0.364078538987409	0.715906998587039	   
df.mm.trans2:exp5	0.340051032063964	0.245385708354978	1.38578173253694	0.166245631272708	   
df.mm.trans1:exp6	0.140625342650512	0.291405877075349	0.482575519965063	0.629544870347859	   
df.mm.trans2:exp6	0.157477578705225	0.245385708354978	0.641755299283427	0.521237757390943	   
df.mm.trans1:exp7	-0.006250052855822	0.291405877075349	-0.0214479300093386	0.982894323611396	   
df.mm.trans2:exp7	0.312123638726602	0.245385708354978	1.27197154560884	0.203796771540916	   
df.mm.trans1:exp8	0.212844857244285	0.291405877075349	0.730406879162735	0.465380766503008	   
df.mm.trans2:exp8	0.257714198363148	0.245385708354978	1.05024127155089	0.293962038566131	   
df.mm.trans1:probe2	-0.267993420360211	0.159609572263746	-1.67905606511724	0.093578025826921	.  
df.mm.trans1:probe3	-0.0651528235799366	0.159609572263746	-0.408201229136027	0.683248156986848	   
df.mm.trans1:probe4	-0.127464470145299	0.159609572263746	-0.798601664909364	0.424786601000223	   
df.mm.trans1:probe5	-0.0181854030570411	0.159609572263746	-0.113936794636544	0.909319882393998	   
df.mm.trans1:probe6	-0.110727452677167	0.159609572263746	-0.69373942368692	0.488070949482975	   
df.mm.trans1:probe7	-0.157195279412354	0.159609572263746	-0.98487375902867	0.325019232662355	   
df.mm.trans1:probe8	-0.113249502596364	0.159609572263746	-0.709540793764082	0.478220259382587	   
df.mm.trans1:probe9	-0.147103633817078	0.159609572263746	-0.92164668904693	0.357023768707557	   
df.mm.trans1:probe10	-0.0966942205625517	0.159609572263746	-0.605817177448291	0.544828421532912	   
df.mm.trans1:probe11	-0.252603672933264	0.159609572263746	-1.58263485924171	0.113946919516693	   
df.mm.trans1:probe12	0.0863132967945071	0.159609572263746	0.540777696289287	0.588829241334018	   
df.mm.trans1:probe13	-0.0452303766175837	0.159609572263746	-0.283381353487014	0.776966550591595	   
df.mm.trans1:probe14	8.91911396963527e-05	0.159609572263746	0.000558808212009798	0.99955429144389	   
df.mm.trans1:probe15	-0.136115669816988	0.159609572263746	-0.852803925769966	0.394053624214479	   
df.mm.trans1:probe16	-0.168809942060565	0.159609572263746	-1.05764297006959	0.290575438251132	   
df.mm.trans1:probe17	-0.179793972014595	0.159609572263746	-1.12646108541344	0.260348328140862	   
df.mm.trans1:probe18	-0.150468361254118	0.159609572263746	-0.942727676792949	0.346138632221538	   
df.mm.trans1:probe19	-0.226303251437411	0.159609572263746	-1.41785513379772	0.156668716757568	   
df.mm.trans1:probe20	0.026873145861386	0.159609572263746	0.168368008761903	0.866341388736938	   
df.mm.trans1:probe21	-0.124349884023050	0.159609572263746	-0.7790878846387	0.436185721893318	   
df.mm.trans1:probe22	-0.185955880121832	0.159609572263746	-1.16506721673654	0.24438032968952	   
df.mm.trans2:probe2	0.127718398855198	0.159609572263746	0.800192601507322	0.423864997332158	   
df.mm.trans2:probe3	0.070930440833806	0.159609572263746	0.444399667437222	0.656888130130433	   
df.mm.trans2:probe4	0.231341346875135	0.159609572263746	1.44942025465024	0.147658707811650	   
df.mm.trans2:probe5	0.0587460579677435	0.159609572263746	0.368060994929984	0.712936689066367	   
df.mm.trans2:probe6	0.117777991139098	0.159609572263746	0.737913080454072	0.460809379091958	   
df.mm.trans3:probe2	0.12156416674329	0.159609572263746	0.761634562508644	0.446529279843429	   
df.mm.trans3:probe3	0.363309759956123	0.159609572263746	2.27624042094276	0.02312646513642	*  
df.mm.trans3:probe4	0.247493922051212	0.159609572263746	1.55062079636578	0.121435078404223