chr15.8813_chr15_9353060_9379294_+_2.R 

fitVsDatCorrelation=0.856699887833065
cont.fitVsDatCorrelation=0.266895011458081

fstatistic=1917.11201878467,52,692
cont.fstatistic=539.702561660976,52,692

residuals=-1.31595845837534,-0.170856639380766,0.0136940400576894,0.190152874697035,1.47540635383687
cont.residuals=-1.14085526448137,-0.359651026134356,-0.194128140772542,0.0546053868599002,2.93835170318709

predictedValues:
Include	Exclude	Both
chr15.8813_chr15_9353060_9379294_+_2.R.tl.Lung	47.780364785539	45.1099333215082	52.1805318358304
chr15.8813_chr15_9353060_9379294_+_2.R.tl.cerebhem	51.0222491066967	44.2912460342062	52.0971845601193
chr15.8813_chr15_9353060_9379294_+_2.R.tl.cortex	56.45302010514	43.944997392858	68.5342636006028
chr15.8813_chr15_9353060_9379294_+_2.R.tl.heart	63.3803704565212	43.4512590388513	80.0708507458607
chr15.8813_chr15_9353060_9379294_+_2.R.tl.kidney	185.135475323921	47.8314367613349	441.880935966298
chr15.8813_chr15_9353060_9379294_+_2.R.tl.liver	104.381208050675	48.9262484547325	186.665920056398
chr15.8813_chr15_9353060_9379294_+_2.R.tl.stomach	48.231760627797	46.1214754143943	55.2703823040578
chr15.8813_chr15_9353060_9379294_+_2.R.tl.testicle	47.9625351480131	46.5368992560354	50.1723761531672


diffExp=2.67043146403078,6.73100307249052,12.508022712282,19.9291114176699,137.304038562586,55.4549595959424,2.11028521340268,1.42563589197769
diffExpScore=0.995818235209737
diffExp1.5=0,0,0,0,1,1,0,0
diffExp1.5Score=0.666666666666667
diffExp1.4=0,0,0,1,1,1,0,0
diffExp1.4Score=0.75
diffExp1.3=0,0,0,1,1,1,0,0
diffExp1.3Score=0.75
diffExp1.2=0,0,1,1,1,1,0,0
diffExp1.2Score=0.8

cont.predictedValues:
Include	Exclude	Both
Lung	66.4770751056009	69.0626617062557	59.4631645415893
cerebhem	69.4657354249728	66.6702405336273	72.6684493574314
cortex	59.8116738808642	52.1805349331992	58.071284080308
heart	58.5670613614149	54.3723122477919	67.8731325326576
kidney	61.8753521966451	67.7674058721455	53.1767426176213
liver	81.2687754931299	70.888974088554	62.7251896755365
stomach	59.1736722901878	57.0678479460788	68.0028404004094
testicle	65.9610905166613	47.9488935223367	81.7662934930704
cont.diffExp=-2.58558660065479,2.79549489134551,7.63113894766492,4.19474911362307,-5.89205367550039,10.3798014045758,2.10582434410896,18.0121969943246
cont.diffExpScore=1.42387399074668

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=0,0,0,0,0,0,0,1
cont.diffExp1.3Score=0.5
cont.diffExp1.2=0,0,0,0,0,0,0,1
cont.diffExp1.2Score=0.5

tran.correlation=0.618581289040182
cont.tran.correlation=0.591310262724631

tran.covariance=0.0128518038307445
cont.tran.covariance=0.00924632097006199

tran.mean=60.660029954889
cont.tran.mean=63.0349566949666

weightedLogRatios:
wLogRatio
Lung	0.220724089149468
cerebhem	0.546308177288713
cortex	0.978880277792041
heart	1.49510678843315
kidney	6.15039293454736
liver	3.23491119100585
stomach	0.172408569981094
testicle	0.116333350872432

cont.weightedLogRatios:
wLogRatio
Lung	-0.160867796293183
cerebhem	0.173348373511348
cortex	0.549098488740155
heart	0.299723045717549
kidney	-0.379355534462829
liver	0.591604636529771
stomach	0.147202996889892
testicle	1.28515764856712

varWeightedLogRatios=4.43230003764552
cont.varWeightedLogRatios=0.261361064521347

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.6952783850231	0.185168959368475	19.9562518341410	2.46456183605881e-70	***
df.mm.trans1	0.174133012534662	0.164234185126103	1.06027263691148	0.289390503885100	   
df.mm.trans2	0.125732190100865	0.149670287951732	0.840061122494889	0.401164257938784	   
df.mm.exp2	0.0489301596529002	0.201874204831051	0.242379454541258	0.808557969065577	   
df.mm.exp3	-0.131994014231945	0.201874204831051	-0.653842893609964	0.513430238933083	   
df.mm.exp4	-0.183125627642206	0.201874204831051	-0.907127425197608	0.364655184691649	   
df.mm.exp5	-0.723277295724718	0.201874204831051	-3.58281186211993	0.000363751709042188	***
df.mm.exp6	-0.411964582800945	0.201874204831051	-2.04069946997795	0.0416597066401724	*  
df.mm.exp7	-0.0259485368055852	0.201874204831051	-0.128538149920153	0.897760456332496	   
df.mm.exp8	0.0741933414292239	0.201874204831051	0.36752264357557	0.713341578100867	   
df.mm.trans1:exp2	0.0167168583734801	0.191241678898309	0.0874122130164371	0.930369149908027	   
df.mm.trans2:exp2	-0.0672455818680255	0.161628718602331	-0.416049712263547	0.677502622388153	   
df.mm.trans1:exp3	0.298788027370854	0.191241678898309	1.56235831588642	0.118660778827498	   
df.mm.trans2:exp3	0.105830333633005	0.161628718602331	0.654774315778547	0.512830642353811	   
df.mm.trans1:exp4	0.465665050334961	0.191241678898309	2.43495587895656	0.0151452398209008	*  
df.mm.trans2:exp4	0.145662982374084	0.161628718602331	0.901219681958076	0.367785072081454	   
df.mm.trans1:exp5	2.07775037529156	0.191241678898309	10.8645269549029	1.69914453008379e-25	***
df.mm.trans2:exp5	0.78185791859324	0.161628718602331	4.83737002529181	1.62285559594116e-06	***
df.mm.trans1:exp6	1.19339946597344	0.191241678898309	6.24026871573331	7.61054010623578e-10	***
df.mm.trans2:exp6	0.493176140195107	0.161628718602331	3.05129029333278	0.00236575055735602	** 
df.mm.trans1:exp7	0.0353514984874068	0.191241678898309	0.184852479287240	0.853398906087467	   
df.mm.trans2:exp7	0.0481247491783662	0.161628718602331	0.297748751549356	0.765984298960629	   
df.mm.trans1:exp8	-0.070387929593214	0.191241678898309	-0.368057475748485	0.712942931829852	   
df.mm.trans2:exp8	-0.0430502844165789	0.161628718602331	-0.266352940175807	0.790046747998691	   
df.mm.trans1:probe2	-0.160378198882816	0.104747381467764	-1.53109506543773	0.126202896221147	   
df.mm.trans1:probe3	0.0398554108917248	0.104747381467764	0.380490761041033	0.703697918248978	   
df.mm.trans1:probe4	0.197875176517302	0.104747381467764	1.8890703876755	0.0593002713195074	.  
df.mm.trans1:probe5	0.0873272503238808	0.104747381467764	0.833693874731904	0.404741183013929	   
df.mm.trans1:probe6	0.318198031312328	0.104747381467764	3.03776597422871	0.00247305715341597	** 
df.mm.trans1:probe7	-0.252816813651034	0.104747381467764	-2.41358600194544	0.0160551187329137	*  
df.mm.trans1:probe8	-0.34819824867598	0.104747381467764	-3.32417139022362	0.000933559286742208	***
df.mm.trans1:probe9	0.0493180544762395	0.104747381467764	0.470828518910683	0.637911572495699	   
df.mm.trans1:probe10	-0.389287083942597	0.104747381467764	-3.71643737998741	0.000218371031139517	***
df.mm.trans1:probe11	-0.375373962361176	0.104747381467764	-3.58361189655799	0.000362659244750903	***
df.mm.trans1:probe12	-0.42944089536967	0.104747381467764	-4.09977690470316	4.62651227186977e-05	***
df.mm.trans1:probe13	-0.451259606804234	0.104747381467764	-4.30807529964948	1.88529763227828e-05	***
df.mm.trans1:probe14	-0.355883393148419	0.104747381467764	-3.3975397586234	0.00071887542448593	***
df.mm.trans1:probe15	-0.411523230570198	0.104747381467764	-3.92872093606317	9.39662999140132e-05	***
df.mm.trans1:probe16	0.71041427220052	0.104747381467764	6.78216736538805	2.54151529287417e-11	***
df.mm.trans1:probe17	0.222339229396547	0.104747381467764	2.1226232702053	0.0341399097038384	*  
df.mm.trans1:probe18	0.607884655810937	0.104747381467764	5.80333987631009	9.89790972043007e-09	***
df.mm.trans1:probe19	0.514658401964896	0.104747381467764	4.91332952435936	1.11872402676372e-06	***
df.mm.trans1:probe20	0.301246653910985	0.104747381467764	2.87593493689094	0.0041521925848138	** 
df.mm.trans1:probe21	0.0551287716463494	0.104747381467764	0.52630214592348	0.598846928111345	   
df.mm.trans2:probe2	-0.0234878953844516	0.104747381467764	-0.224233723605588	0.822641632045103	   
df.mm.trans2:probe3	0.00941502143219946	0.104747381467764	0.0898831197522294	0.92840610371712	   
df.mm.trans2:probe4	-0.0366993543019516	0.104747381467764	-0.350360589331256	0.726174717578788	   
df.mm.trans2:probe5	-0.0205714409412677	0.104747381467764	-0.196390980404590	0.844361815443691	   
df.mm.trans2:probe6	-0.0477373491625629	0.104747381467764	-0.455737876151627	0.648721454461012	   
df.mm.trans3:probe2	0.272754186192451	0.104747381467764	2.60392367208141	0.00941401757872855	** 
df.mm.trans3:probe3	-0.221340780088460	0.104747381467764	-2.11309129628771	0.0349503796793984	*  
df.mm.trans3:probe4	-0.213149868788015	0.104747381467764	-2.03489448424648	0.0422421485812103	*  

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.37210848391023	0.345961256322036	12.6375667911221	4.3515317439833e-33	***
df.mm.trans1	-0.238983128715526	0.306847676905646	-0.778833104182219	0.436344274914416	   
df.mm.trans2	-0.0798303686698544	0.279637154253392	-0.285478404624003	0.775363073382493	   
df.mm.exp2	-0.191829354908128	0.377172576659481	-0.508598362603957	0.611195880893512	   
df.mm.exp3	-0.362275251742022	0.377172576659481	-0.960502629726156	0.337137789563977	   
df.mm.exp4	-0.498127109166615	0.377172576659481	-1.32068750485095	0.187042175984921	   
df.mm.exp5	0.0210677724006964	0.377172576659481	0.0558571160906983	0.9554717569844	   
df.mm.exp6	0.173599320595808	0.377172576659481	0.460264959168909	0.645470637914338	   
df.mm.exp7	-0.441346230564842	0.377172576659481	-1.17014400801280	0.242345855983062	   
df.mm.exp8	-0.691178691363693	0.377172576659481	-1.83252636627319	0.0673025751001639	.  
df.mm.trans1:exp2	0.235805817465943	0.357307249111531	0.659952514404033	0.509503892013921	   
df.mm.trans2:exp2	0.156573806198229	0.301979741831952	0.518491092310956	0.60428142001819	   
df.mm.trans1:exp3	0.256618956072799	0.357307249111531	0.718202490184287	0.472874845709734	   
df.mm.trans2:exp3	0.081970549930967	0.301979741831952	0.271443870485135	0.786130619924374	   
df.mm.trans1:exp4	0.371442401934749	0.357307249111531	1.03956021843488	0.298907346460747	   
df.mm.trans2:exp4	0.258967934270721	0.301979741831952	0.857567241761645	0.391428371765227	   
df.mm.trans1:exp5	-0.092803012433879	0.357307249111531	-0.259728882256490	0.795150164978803	   
df.mm.trans2:exp5	-0.0400006655528178	0.301979741831952	-0.132461420458720	0.894657842045479	   
df.mm.trans1:exp6	0.0273054039380160	0.357307249111531	0.0764199551112182	0.939107082460555	   
df.mm.trans2:exp6	-0.147498645869182	0.301979741831952	-0.488438876642471	0.625393751050017	   
df.mm.trans1:exp7	0.324965795734648	0.357307249111531	0.90948559410059	0.363410512298959	   
df.mm.trans2:exp7	0.250572872222455	0.301979741831952	0.829767158228433	0.406956589981122	   
df.mm.trans1:exp8	0.68338656894531	0.357307249111531	1.91260202709181	0.0562115404676583	.  
df.mm.trans2:exp8	0.326300183614389	0.301979741831952	1.08053666658200	0.280279701312031	   
df.mm.trans1:probe2	0.441359674841631	0.195705240298503	2.25522665702993	0.0244307577665710	*  
df.mm.trans1:probe3	0.0818433303893608	0.195705240298503	0.41819692852643	0.675932884334292	   
df.mm.trans1:probe4	0.187015129074812	0.195705240298503	0.955595919606257	0.339610124708937	   
df.mm.trans1:probe5	-0.126128081971617	0.195705240298503	-0.644479840086231	0.519477897788114	   
df.mm.trans1:probe6	0.0600924369065141	0.195705240298503	0.307055839766258	0.758893246631568	   
df.mm.trans1:probe7	0.232738838254862	0.195705240298503	1.18923150907903	0.234756477438237	   
df.mm.trans1:probe8	-0.139200555117938	0.195705240298503	-0.711276585673534	0.477152539431326	   
df.mm.trans1:probe9	0.318123486436852	0.195705240298503	1.62552359840558	0.104506344212319	   
df.mm.trans1:probe10	-0.0463988082343255	0.195705240298503	-0.237085160129360	0.812660892974636	   
df.mm.trans1:probe11	-0.0816161270525432	0.195705240298503	-0.417035981908592	0.676781428018478	   
df.mm.trans1:probe12	-0.03056771919742	0.195705240298503	-0.156192645382393	0.875926727562667	   
df.mm.trans1:probe13	0.0717466919285795	0.195705240298503	0.366605880451369	0.714025085578581	   
df.mm.trans1:probe14	0.116867156797563	0.195705240298503	0.597159057260343	0.550596523902139	   
df.mm.trans1:probe15	0.130377915737631	0.195705240298503	0.666195322816955	0.505508285709371	   
df.mm.trans1:probe16	-0.0498023224126707	0.195705240298503	-0.254476182327611	0.799203303323391	   
df.mm.trans1:probe17	0.0236214683569607	0.195705240298503	0.120699212350838	0.903964319076528	   
df.mm.trans1:probe18	0.341678951227667	0.195705240298503	1.74588555067056	0.0812746162704728	.  
df.mm.trans1:probe19	0.0425750382993356	0.195705240298503	0.217546746496912	0.8278464091607	   
df.mm.trans1:probe20	0.139696349786118	0.195705240298503	0.713809960188312	0.475585376602039	   
df.mm.trans1:probe21	-0.120727909598386	0.195705240298503	-0.61688644317466	0.5375125315877	   
df.mm.trans2:probe2	-0.0943323056506506	0.195705240298503	-0.482012160260852	0.629949718163385	   
df.mm.trans2:probe3	-0.122865354967768	0.195705240298503	-0.627808201662689	0.530336707342006	   
df.mm.trans2:probe4	-0.141651705646236	0.195705240298503	-0.723801291320452	0.469432340410053	   
df.mm.trans2:probe5	-0.0586538257630385	0.195705240298503	-0.299704932139659	0.764492234561505	   
df.mm.trans2:probe6	-0.155135628802338	0.195705240298503	-0.792700433395215	0.428224056950290	   
df.mm.trans3:probe2	-0.0262244916830958	0.195705240298503	-0.133999946261513	0.893441577824669	   
df.mm.trans3:probe3	0.0967422062867262	0.195705240298503	0.494326090293588	0.621232784651514	   
df.mm.trans3:probe4	0.0577304893198956	0.195705240298503	0.294986936639209	0.768092336635885