chr7.22034_chr7_110570098_110573880_+_2.R 

fitVsDatCorrelation=0.813661989187283
cont.fitVsDatCorrelation=0.296622659355902

fstatistic=9169.32867801735,53,715
cont.fstatistic=3389.27368512015,53,715

residuals=-0.764770806050716,-0.0842844919890069,-0.00286304239966114,0.0748594910446893,0.736250988693463
cont.residuals=-0.633853930923164,-0.172617051917124,-0.0428520009443221,0.134521770630287,1.16081359497584

predictedValues:
Include	Exclude	Both
chr7.22034_chr7_110570098_110573880_+_2.R.tl.Lung	59.5238652019803	46.051851264305	68.6231170082095
chr7.22034_chr7_110570098_110573880_+_2.R.tl.cerebhem	63.9784371879486	53.8748874780826	65.9842172543705
chr7.22034_chr7_110570098_110573880_+_2.R.tl.cortex	66.3110022324635	42.9027171074338	75.9318469189554
chr7.22034_chr7_110570098_110573880_+_2.R.tl.heart	58.8367851772043	43.8230602538219	65.6311457270308
chr7.22034_chr7_110570098_110573880_+_2.R.tl.kidney	57.2359883012699	44.0169421098402	66.3558757717188
chr7.22034_chr7_110570098_110573880_+_2.R.tl.liver	57.4050958407642	49.6632692283465	63.1165200221472
chr7.22034_chr7_110570098_110573880_+_2.R.tl.stomach	61.5562566761628	45.6497781537913	71.0439127793761
chr7.22034_chr7_110570098_110573880_+_2.R.tl.testicle	66.9330099288308	48.0196844639318	71.3535555546136


diffExp=13.4720139376753,10.1035497098660,23.4082851250297,15.0137249233825,13.2190461914296,7.74182661241773,15.9064785223715,18.9133254648990
diffExpScore=0.991580950250578
diffExp1.5=0,0,1,0,0,0,0,0
diffExp1.5Score=0.5
diffExp1.4=0,0,1,0,0,0,0,0
diffExp1.4Score=0.5
diffExp1.3=0,0,1,1,1,0,1,1
diffExp1.3Score=0.833333333333333
diffExp1.2=1,0,1,1,1,0,1,1
diffExp1.2Score=0.857142857142857

cont.predictedValues:
Include	Exclude	Both
Lung	61.8628838626095	50.1782371837207	63.6499278436945
cerebhem	54.0809352085504	55.3037643790913	58.2360601365776
cortex	58.8532730195476	63.5420721291303	56.3667595423228
heart	61.8495720296142	59.315936963595	61.1644842653432
kidney	57.550571483275	52.5203354371039	55.9310513539035
liver	56.0321952992872	48.6996026829527	51.7882764255079
stomach	56.9426739394978	62.4595767341962	56.5233212496602
testicle	57.3720452327374	52.0165993379636	63.003729718157
cont.diffExp=11.6846466788888,-1.22282917054092,-4.68879910958268,2.53363506601927,5.03023604617107,7.33259261633447,-5.51690279469836,5.3554458947738
cont.diffExpScore=2.01622821800647

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

tran.correlation=0.150482694276136
cont.tran.correlation=0.105603195236386

tran.covariance=0.000693592207656883
cont.tran.covariance=0.00049697386923367

tran.mean=54.1114144128861
cont.tran.mean=56.7862671826795

weightedLogRatios:
wLogRatio
Lung	1.01567850776791
cerebhem	0.700006107024427
cortex	1.73151364505145
heart	1.15705865128774
kidney	1.02834209721164
liver	0.576239228236279
stomach	1.18698446520197
testicle	1.34082839500920

cont.weightedLogRatios:
wLogRatio
Lung	0.841595201766004
cerebhem	-0.089474160670977
cortex	-0.315309890036122
heart	0.171649939401415
kidney	0.366488565070573
liver	0.554822795380206
stomach	-0.378062000681716
testicle	0.392032008072802

varWeightedLogRatios=0.130527654385779
cont.varWeightedLogRatios=0.183720244947554

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.99531712025815	0.082202401094721	48.6034114216979	8.43308765847419e-229	***
df.mm.trans1	0.319810774787866	0.0729973230586888	4.3811301755647	1.35747565471987e-05	***
df.mm.trans2	-0.171814789329787	0.066400557926159	-2.58755038656233	0.00986226304365374	** 
df.mm.exp2	0.268279156133760	0.0895178193997411	2.99693578253690	0.00282149970900745	** 
df.mm.exp3	-0.0640610279623262	0.0895178193997412	-0.715623195380376	0.474457673481738	   
df.mm.exp4	-0.0166387699462643	0.0895178193997412	-0.185871037273193	0.852598612996611	   
df.mm.exp5	-0.0507906701181365	0.0895178193997411	-0.567380555723003	0.570633751559183	   
df.mm.exp6	0.122900314503755	0.0895178193997412	1.37291452503936	0.170209344851584	   
df.mm.exp7	-0.00986375944950545	0.0895178193997412	-0.110187664485647	0.912291464697606	   
df.mm.exp8	0.120140281531481	0.0895178193997411	1.34208230648465	0.179995317664002	   
df.mm.trans1:exp2	-0.196110376448084	0.0850013692710017	-2.30714373344792	0.0213316509702401	*  
df.mm.trans2:exp2	-0.111382659358433	0.0715775584866276	-1.55611146445071	0.120124086259818	   
df.mm.trans1:exp3	0.172039529611844	0.0850013692710017	2.02396186187715	0.0433454722375933	*  
df.mm.trans2:exp3	-0.00677177534424672	0.0715775584866276	-0.0946075206730032	0.924653082322448	   
df.mm.trans1:exp4	0.0050286995318538	0.0850013692710017	0.0591602179468578	0.952841026053464	   
df.mm.trans2:exp4	-0.0329690244777167	0.0715775584866276	-0.460605602856321	0.645221647188718	   
df.mm.trans1:exp5	0.0115962088022342	0.0850013692710017	0.136423788248201	0.89152467121054	   
df.mm.trans2:exp5	0.00559731480284237	0.0715775584866276	0.078199297673559	0.937691399322681	   
df.mm.trans1:exp6	-0.159144565370836	0.0850013692710017	-1.87225884401286	0.0615787614893086	.  
df.mm.trans2:exp6	-0.047402667437045	0.0715775584866276	-0.662255998098914	0.508020567972299	   
df.mm.trans1:exp7	0.0434379308759145	0.0850013692710017	0.511026248735188	0.609490430949802	   
df.mm.trans2:exp7	0.00109454368634712	0.0715775584866276	0.0152917158602386	0.987803717341874	   
df.mm.trans1:exp8	-0.00282534210002121	0.0850013692710017	-0.0332387833778706	0.973493447003462	   
df.mm.trans2:exp8	-0.0782972247626936	0.0715775584866276	-1.09387951221222	0.274376206091679	   
df.mm.trans1:probe2	-0.47290534774463	0.0465571673685541	-10.1575197649168	9.81797442075042e-23	***
df.mm.trans1:probe3	-0.441560252650859	0.0465571673685541	-9.48425940855457	3.52880571091374e-20	***
df.mm.trans1:probe4	-0.271319844392814	0.0465571673685541	-5.8276707911588	8.50214745916245e-09	***
df.mm.trans1:probe5	-0.0192212827958475	0.0465571673685541	-0.412853356040515	0.679837828829682	   
df.mm.trans1:probe6	-0.223045607753585	0.0465571673685541	-4.7907899118501	2.02072314325319e-06	***
df.mm.trans1:probe7	-0.237660222389808	0.0465571673685541	-5.10469678080822	4.25189559862859e-07	***
df.mm.trans1:probe8	0.0226319235870721	0.0465571673685541	0.486110407188524	0.627037834399297	   
df.mm.trans1:probe9	0.23419582096208	0.0465571673685541	5.03028500656296	6.20019348913178e-07	***
df.mm.trans1:probe10	-0.433727296245668	0.0465571673685541	-9.31601557311708	1.4644409601354e-19	***
df.mm.trans1:probe11	-0.308085668253746	0.0465571673685541	-6.61736281795002	7.1724965210505e-11	***
df.mm.trans1:probe12	-0.555421590560347	0.0465571673685541	-11.9298836667519	4.75333170962806e-30	***
df.mm.trans1:probe13	-0.481547211304019	0.0465571673685541	-10.3431380928314	1.84023255959193e-23	***
df.mm.trans1:probe14	-0.355938212821040	0.0465571673685541	-7.64518618590721	6.73680514254069e-14	***
df.mm.trans1:probe15	-0.340441065394471	0.0465571673685541	-7.31232342164386	7.05361056595245e-13	***
df.mm.trans1:probe16	-0.44328116559702	0.0465571673685541	-9.52122284605363	2.57466962132765e-20	***
df.mm.trans1:probe17	-0.223532821931151	0.0465571673685541	-4.80125477054111	1.92105358877289e-06	***
df.mm.trans1:probe18	-0.366071787408422	0.0465571673685541	-7.86284493020243	1.38508155543250e-14	***
df.mm.trans1:probe19	-0.295632160156119	0.0465571673685541	-6.34987429144576	3.82988180285432e-10	***
df.mm.trans1:probe20	-0.28116154242126	0.0465571673685541	-6.03906032760842	2.49120049557572e-09	***
df.mm.trans1:probe21	-0.130927155004218	0.0465571673685541	-2.81218043116278	0.00505557724820502	** 
df.mm.trans1:probe22	-0.322862253810964	0.0465571673685541	-6.93474865545694	9.1145545290784e-12	***
df.mm.trans2:probe2	0.00123042268481911	0.0465571673685541	0.0264282119029898	0.978923166399947	   
df.mm.trans2:probe3	0.0485084464629923	0.0465571673685541	1.04191146508102	0.297804892230921	   
df.mm.trans2:probe4	0.0163695881840178	0.0465571673685541	0.351601893097007	0.725240435238056	   
df.mm.trans2:probe5	-0.0460952704205659	0.0465571673685541	-0.990078929322917	0.322470471672365	   
df.mm.trans2:probe6	0.0426431345304017	0.0465571673685541	0.915930606190701	0.360012100332016	   
df.mm.trans3:probe2	0.478189384041857	0.0465571673685541	10.2710154218884	3.53625441395295e-23	***
df.mm.trans3:probe3	-0.166439918302929	0.0465571673685541	-3.57495800776201	0.000373841203905872	***
df.mm.trans3:probe4	0.0295159537677742	0.0465571673685541	0.633972284742349	0.526301670605227	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.94090927693413	0.135038184446750	29.1836660354993	6.52832363711049e-124	***
df.mm.trans1	0.216920576217599	0.119916521221316	1.80892986227689	0.0708818123367939	.  
df.mm.trans2	-0.0515732813267561	0.109079670048417	-0.472803789229142	0.636497461918835	   
df.mm.exp2	0.051714345507824	0.147055604780253	0.351665246524274	0.725192937418454	   
df.mm.exp3	0.307766468791485	0.147055604780253	2.09285779519512	0.0367137502279462	*  
df.mm.exp4	0.206912897657187	0.147055604780253	1.40703850061600	0.159850499923329	   
df.mm.exp5	0.102641190797035	0.147055604780253	0.697975374351847	0.485419514281201	   
df.mm.exp6	0.0773299089141422	0.147055604780253	0.525854890262068	0.599152085234604	   
df.mm.exp7	0.254807693717344	0.147055604780253	1.73273024240121	0.08357481549078	.  
df.mm.exp8	-0.0291774774463733	0.147055604780253	-0.19841118935911	0.842779764062714	   
df.mm.trans1:exp2	-0.186153006217586	0.139636195889429	-1.33312859915627	0.182914206351199	   
df.mm.trans2:exp2	0.0455452221951983	0.117584199688128	0.38734134616725	0.69861878918595	   
df.mm.trans1:exp3	-0.357639405679219	0.139636195889429	-2.56122277895923	0.0106345142133539	*  
df.mm.trans2:exp3	-0.0716456395327814	0.117584199688128	-0.609313493843638	0.542510223044024	   
df.mm.trans1:exp4	-0.207128103683948	0.139636195889429	-1.48334106615137	0.138424463420087	   
df.mm.trans2:exp4	-0.0396162867298196	0.117584199688128	-0.336918453626379	0.736277243267617	   
df.mm.trans1:exp5	-0.174897510826305	0.139636195889429	-1.25252274105775	0.210788958708274	   
df.mm.trans2:exp5	-0.0570221650008611	0.117584199688128	-0.484947511248131	0.627862116679379	   
df.mm.trans1:exp6	-0.176323852673676	0.139636195889429	-1.26273744103784	0.207095212259007	   
df.mm.trans2:exp6	-0.107240447782920	0.117584199688128	-0.912031106792887	0.362059737556718	   
df.mm.trans1:exp7	-0.337683037671007	0.139636195889429	-2.41830590929590	0.0158418180366406	*  
df.mm.trans2:exp7	-0.0358695289383632	0.117584199688128	-0.305053987130082	0.760413812741144	   
df.mm.trans1:exp8	-0.0461857400630574	0.139636195889429	-0.330757650399110	0.740924454219713	   
df.mm.trans2:exp8	0.0651589526632136	0.117584199688128	0.554147179944554	0.579651392475075	   
df.mm.trans1:probe2	0.0133768514133626	0.0764818943328505	0.174902197834514	0.86120599808404	   
df.mm.trans1:probe3	0.0144578143122812	0.0764818943328505	0.189035776877604	0.850118421328888	   
df.mm.trans1:probe4	0.0180677952001010	0.0764818943328505	0.236236240716915	0.813317015400591	   
df.mm.trans1:probe5	-0.0579502481693292	0.0764818943328505	-0.757698912596604	0.448880891640292	   
df.mm.trans1:probe6	-0.0238301911937267	0.0764818943328505	-0.311579510439651	0.755450935702154	   
df.mm.trans1:probe7	0.082132718737939	0.0764818943328505	1.07388447232355	0.283236742345702	   
df.mm.trans1:probe8	-0.0777145046395105	0.0764818943328505	-1.01611636737573	0.309917684097837	   
df.mm.trans1:probe9	-0.0487683415626816	0.0764818943328505	-0.637645575963914	0.523908558345439	   
df.mm.trans1:probe10	-0.141628207846927	0.0764818943328505	-1.85178739468139	0.0644684217502625	.  
df.mm.trans1:probe11	-0.0783122694091995	0.0764818943328505	-1.02393213573376	0.306213627000753	   
df.mm.trans1:probe12	0.0377729340691085	0.0764818943328505	0.49388073345464	0.621542091958741	   
df.mm.trans1:probe13	-0.106436565125502	0.0764818943328505	-1.39165701966388	0.164459064435685	   
df.mm.trans1:probe14	-0.0214879381697238	0.0764818943328505	-0.280954575683075	0.77882652048965	   
df.mm.trans1:probe15	-0.0364620267275897	0.0764818943328505	-0.476740633134769	0.633692489539817	   
df.mm.trans1:probe16	-0.0105426285785554	0.0764818943328505	-0.137844762744418	0.890401915764438	   
df.mm.trans1:probe17	-0.0634566880282942	0.0764818943328505	-0.829695558430204	0.406987851866363	   
df.mm.trans1:probe18	-0.0263579252996752	0.0764818943328505	-0.344629608479166	0.730474186474965	   
df.mm.trans1:probe19	-0.105879516767286	0.0764818943328505	-1.38437361797679	0.166675977763782	   
df.mm.trans1:probe20	-0.0461407467133942	0.0764818943328505	-0.603289799708529	0.54650723930476	   
df.mm.trans1:probe21	-0.0374055199364288	0.0764818943328505	-0.489076797361207	0.62493731579104	   
df.mm.trans1:probe22	-0.139080958345834	0.0764818943328505	-1.81848213304643	0.0694087274604449	.  
df.mm.trans2:probe2	0.00525976982540911	0.0764818943328505	0.0687714376231125	0.945190781447289	   
df.mm.trans2:probe3	0.0443546741187255	0.0764818943328505	0.579936918477636	0.562139856066514	   
df.mm.trans2:probe4	0.0243571491082844	0.0764818943328505	0.318469479878226	0.750221843456141	   
df.mm.trans2:probe5	0.0344699572173033	0.0764818943328505	0.450694344301797	0.652346496283238	   
df.mm.trans2:probe6	0.154012598287688	0.0764818943328505	2.01371317527024	0.0444138203276874	*  
df.mm.trans3:probe2	0.0783045900520759	0.0764818943328505	1.02383172821652	0.306261025013247	   
df.mm.trans3:probe3	0.0742329980278411	0.0764818943328505	0.970595703406323	0.332077862934533	   
df.mm.trans3:probe4	0.0360288900637817	0.0764818943328505	0.471077375607138	0.637729171074193