chr12.5589_chr12_10448921_10451357_+_0.R 

fitVsDatCorrelation=0.818115034758972
cont.fitVsDatCorrelation=0.246174260886617

fstatistic=10635.0706293030,51,669
cont.fstatistic=3735.2669281177,51,669

residuals=-0.672205819922111,-0.0826670747252954,-0.00197657685149362,0.0820247551159709,0.786683072003407
cont.residuals=-0.522132087807776,-0.175616972669378,-0.0292748113967339,0.130812910075857,0.824947451575172

predictedValues:
Include	Exclude	Both
chr12.5589_chr12_10448921_10451357_+_0.R.tl.Lung	73.0276450948831	59.448060672799	60.5983814781601
chr12.5589_chr12_10448921_10451357_+_0.R.tl.cerebhem	64.4297256677255	48.2611239051535	59.223013159465
chr12.5589_chr12_10448921_10451357_+_0.R.tl.cortex	71.0330125700686	51.6181081736537	54.5131803985669
chr12.5589_chr12_10448921_10451357_+_0.R.tl.heart	70.1864549582857	57.1035455154747	57.5084396497491
chr12.5589_chr12_10448921_10451357_+_0.R.tl.kidney	87.1989321836568	58.8931208814396	61.4262216245681
chr12.5589_chr12_10448921_10451357_+_0.R.tl.liver	84.0029493262713	61.6012981912238	59.5383670163863
chr12.5589_chr12_10448921_10451357_+_0.R.tl.stomach	74.2121879059787	54.6416734625111	58.831786761677
chr12.5589_chr12_10448921_10451357_+_0.R.tl.testicle	77.60072661016	56.112856251617	62.265284706537


diffExp=13.5795844220841,16.1686017625720,19.4149043964149,13.0829094428111,28.3058113022172,22.4016511350476,19.5705144434676,21.4878703585431
diffExpScore=0.993548880181382
diffExp1.5=0,0,0,0,0,0,0,0
diffExp1.5Score=0
diffExp1.4=0,0,0,0,1,0,0,0
diffExp1.4Score=0.5
diffExp1.3=0,1,1,0,1,1,1,1
diffExp1.3Score=0.857142857142857
diffExp1.2=1,1,1,1,1,1,1,1
diffExp1.2Score=0.888888888888889

cont.predictedValues:
Include	Exclude	Both
Lung	60.2236887395458	59.7124084625756	60.6701812360405
cerebhem	60.9214142562728	59.8108249892513	59.3046221552061
cortex	60.3727698534488	64.7230879781915	62.9353423827874
heart	63.5387103378199	69.0243945629498	60.7258447961856
kidney	61.9406164813482	59.8862111207436	60.553292259616
liver	66.7569818722886	58.5598978947701	61.0004642862604
stomach	60.2690453714918	61.1650063372878	59.9560275850869
testicle	56.731153162442	68.20480030442	62.5358363207012
cont.diffExp=0.511280276970197,1.11058926702158,-4.35031812474272,-5.48568422512984,2.05440536060460,8.19708397751844,-0.895960965796078,-11.4736471419779
cont.diffExpScore=3.00725492305022

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,-1
cont.diffExp1.2Score=0.5

tran.correlation=0.761340580986097
cont.tran.correlation=-0.373151900715539

tran.covariance=0.00611718591381192
cont.tran.covariance=-0.00118377759598800

tran.mean=65.5857138356814
cont.tran.mean=61.990063232803

weightedLogRatios:
wLogRatio
Lung	0.861612402602858
cerebhem	1.16189205615039
cortex	1.31013619100985
heart	0.85568955599253
kidney	1.67660600859271
liver	1.32621035487989
stomach	1.27162841139714
testicle	1.35827605038177

cont.weightedLogRatios:
wLogRatio
Lung	0.0349034754807125
cerebhem	0.0754392171153352
cortex	-0.287735348029346
heart	-0.347229601623723
kidney	0.138606438474002
liver	0.541793880760016
stomach	-0.0605935300158928
testicle	-0.760787904710666

varWeightedLogRatios=0.0733912842689045
cont.varWeightedLogRatios=0.150016148497794

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.47932320414457	0.073220561610236	61.1757559029482	3.28451756744619e-276	***
df.mm.trans1	-0.158204498318372	0.0577170904945584	-2.74103384219077	0.00628815983249245	** 
df.mm.trans2	-0.415342780667409	0.0577170904945584	-7.19618361058182	1.66677122629147e-12	***
df.mm.exp2	-0.310781634786072	0.0763525339234057	-4.07035128785428	5.25525520940045e-05	***
df.mm.exp3	-0.0630981217388064	0.0763525339234057	-0.82640507782105	0.408868973908148	   
df.mm.exp4	-0.0275830490323617	0.0763525339234057	-0.36125911760875	0.718019807966325	   
df.mm.exp5	0.154406683204979	0.0763525339234057	2.02228629844655	0.0435442229124089	*  
df.mm.exp6	0.193241039147708	0.0763525339234057	2.53090538346194	0.0116049110426638	*  
df.mm.exp7	-0.0386299504022703	0.0763525339234057	-0.505941956569805	0.613064064627531	   
df.mm.exp8	-0.0241351854217254	0.0763525339234057	-0.316101957348751	0.75202371661332	   
df.mm.trans1:exp2	0.185518670703519	0.0577170904945584	3.21427620681971	0.00137058802464074	** 
df.mm.trans2:exp2	0.102304981798690	0.0577170904945584	1.77252493017359	0.0767624809084547	.  
df.mm.trans1:exp3	0.0354047871030687	0.0577170904945584	0.613419470726901	0.53980751111792	   
df.mm.trans2:exp3	-0.0781323351960388	0.0577170904945584	-1.35371229780554	0.176285335685157	   
df.mm.trans1:exp4	-0.0120996772547318	0.0577170904945584	-0.209637685320825	0.834014287191502	   
df.mm.trans2:exp4	-0.0126537446002546	0.0577170904945584	-0.219237395576057	0.826531997163021	   
df.mm.trans1:exp5	0.022947332645135	0.0577170904945584	0.397582976697318	0.691064434480382	   
df.mm.trans2:exp5	-0.163785394010189	0.0577170904945584	-2.83772783081695	0.00468123547931784	** 
df.mm.trans1:exp6	-0.0532271992833083	0.0577170904945584	-0.922208635730288	0.356752215956373	   
df.mm.trans2:exp6	-0.157661095754955	0.0577170904945584	-2.73161890878438	0.00646860013127299	** 
df.mm.trans1:exp7	0.0547202751902176	0.0577170904945584	0.948077505663191	0.343432332228001	   
df.mm.trans2:exp7	-0.0456762092025687	0.0577170904945584	-0.79138100710179	0.429002171554428	   
df.mm.trans1:exp8	0.0848739067104744	0.0577170904945584	1.47051602884377	0.141892202802763	   
df.mm.trans2:exp8	-0.0336028630663204	0.0577170904945584	-0.582199531861165	0.56062843487277	   
df.mm.trans1:probe2	-0.0373133603521294	0.0432878178709188	-0.86198293624768	0.389005770183346	   
df.mm.trans1:probe3	-0.204067433412790	0.0432878178709188	-4.71420005557464	2.95394515027747e-06	***
df.mm.trans1:probe4	-0.182184375583818	0.0432878178709188	-4.20867543212918	2.91956586573615e-05	***
df.mm.trans1:probe5	-0.127279562469298	0.0432878178709188	-2.9403090460424	0.00339200126067494	** 
df.mm.trans1:probe6	-0.175890542660971	0.0432878178709188	-4.06328041726346	5.41310340006152e-05	***
df.mm.trans2:probe2	0.0112327194901191	0.0432878178709188	0.259489159828159	0.79533767498009	   
df.mm.trans2:probe3	0.0515490644255338	0.0432878178709188	1.19084460619497	0.234136943213570	   
df.mm.trans2:probe4	-0.00330215982609443	0.0432878178709188	-0.0762838135186494	0.93921610988385	   
df.mm.trans2:probe5	0.139052897337222	0.0432878178709188	3.21228706311480	0.00137996711189157	** 
df.mm.trans2:probe6	0.308409350101485	0.0432878178709188	7.12462224409508	2.70674809265769e-12	***
df.mm.trans3:probe2	0.181716254732515	0.0432878178709188	4.19786128453922	3.05871660939083e-05	***
df.mm.trans3:probe3	0.147572425522242	0.0432878178709188	3.40909828169885	0.000690903205206867	***
df.mm.trans3:probe4	0.211864185426843	0.0432878178709188	4.89431428626425	1.23757357204433e-06	***
df.mm.trans3:probe5	1.43696034521250e-05	0.0432878178709188	0.00033195490461021	0.999735237279149	   
df.mm.trans3:probe6	0.114514703090134	0.0432878178709188	2.64542563525861	0.00835045366197505	** 
df.mm.trans3:probe7	0.656170164503462	0.0432878178709188	15.1583100460299	7.80297066954403e-45	***
df.mm.trans3:probe8	0.622905697715341	0.0432878178709188	14.389861359443	4.22988684048092e-41	***
df.mm.trans3:probe9	0.401336313315884	0.0432878178709188	9.27134545133785	2.48814682757997e-19	***
df.mm.trans3:probe10	0.134080486133225	0.0432878178709188	3.09741845923126	0.00203383004719472	** 
df.mm.trans3:probe11	-0.0719943371942293	0.0432878178709188	-1.66315468728203	0.0967498346540795	.  
df.mm.trans3:probe12	0.0381611085258746	0.0432878178709188	0.881566925818906	0.378327661151381	   
df.mm.trans3:probe13	0.125297303086147	0.0432878178709188	2.89451650022588	0.00392112818531253	** 
df.mm.trans3:probe14	0.0154938566323304	0.0432878178709188	0.357926488198874	0.720511226598543	   
df.mm.trans3:probe15	0.07001928571144	0.0432878178709188	1.61752865252373	0.106235585259711	   
df.mm.trans3:probe16	0.259112978381724	0.0432878178709188	5.98581751462687	3.51114542503864e-09	***
df.mm.trans3:probe17	-0.00600392879248588	0.0432878178709188	-0.138697885173819	0.889730628075007	   
df.mm.trans3:probe18	0.672599800621207	0.0432878178709188	15.5378541516427	1.03132209872312e-46	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.09061256838401	0.123409571787627	33.1466393500130	2.7468396301344e-143	***
df.mm.trans1	0.00552467169854797	0.0972792514304534	0.0567918812831084	0.954727938604305	   
df.mm.trans2	0.0102820663404042	0.0972792514304534	0.105696396602671	0.915854922790614	   
df.mm.exp2	0.0359308668227901	0.128688353505752	0.279208380898153	0.780171204072744	   
df.mm.exp3	0.0463949774341221	0.128688353505752	0.36052195999266	0.718570637113345	   
df.mm.exp4	0.197586639535945	0.128688353505752	1.53538866690927	0.125161161105490	   
df.mm.exp5	0.0329452744557778	0.128688353505752	0.256008205546784	0.798023198709654	   
df.mm.exp6	0.0780742476814576	0.128688353505752	0.606692412751772	0.544260881549306	   
df.mm.exp7	0.0366291501988406	0.128688353505752	0.284634539186978	0.776012230450769	   
df.mm.exp8	0.0429453807296095	0.128688353505752	0.333716141046827	0.73869834071793	   
df.mm.trans1:exp2	-0.0244118996609639	0.0972792514304534	-0.250946623272656	0.801932431811986	   
df.mm.trans2:exp2	-0.0342840481068702	0.0972792514304534	-0.35242919330419	0.724627408499488	   
df.mm.trans1:exp3	-0.0439225799593772	0.0972792514304534	-0.451510258493079	0.651768163255262	   
df.mm.trans2:exp3	0.0341831613214409	0.0972792514304534	0.351392108993345	0.725404840400158	   
df.mm.trans1:exp4	-0.144003083326373	0.0972792514304534	-1.48030624422849	0.139262300325133	   
df.mm.trans2:exp4	-0.0526664987758892	0.0972792514304534	-0.541394984042834	0.588415603666111	   
df.mm.trans1:exp5	-0.00483492265148415	0.0972792514304534	-0.0497014787880097	0.960375112651814	   
df.mm.trans2:exp5	-0.0300388398978992	0.0972792514304534	-0.308789792850888	0.757577568199833	   
df.mm.trans1:exp6	0.0249188658960347	0.0972792514304534	0.25615807615306	0.797907525325994	   
df.mm.trans2:exp6	-0.0975639673758465	0.0972792514304534	-1.00292679005242	0.316258796941111	   
df.mm.trans1:exp7	-0.0358762975986752	0.0972792514304534	-0.368797015510792	0.712395710044198	   
df.mm.trans2:exp7	-0.0125937618359450	0.0972792514304534	-0.129459896645570	0.897032667916522	   
df.mm.trans1:exp8	-0.102687657961527	0.0972792514304534	-1.05559671205879	0.291533555312623	   
df.mm.trans2:exp8	0.09002972159247	0.0972792514304534	0.925477121468536	0.355051493109186	   
df.mm.trans1:probe2	0.0183907813253542	0.0729594385728401	0.252068569675101	0.80106548172378	   
df.mm.trans1:probe3	0.0360858769584818	0.07295943857284	0.494601900238787	0.621043539391412	   
df.mm.trans1:probe4	0.0228013440488424	0.0729594385728401	0.312520826569661	0.754742126409081	   
df.mm.trans1:probe5	0.0492946374362942	0.07295943857284	0.675644418330881	0.499499904747676	   
df.mm.trans1:probe6	-0.080287788055859	0.0729594385728401	-1.10044415947229	0.271534445885399	   
df.mm.trans2:probe2	-0.0608264020719049	0.07295943857284	-0.833701619169917	0.404746707811687	   
df.mm.trans2:probe3	-0.0563911996919414	0.07295943857284	-0.772911645086776	0.439847658455238	   
df.mm.trans2:probe4	0.00511995959150234	0.07295943857284	0.0701754247518058	0.944075005415176	   
df.mm.trans2:probe5	-0.106396709030508	0.07295943857284	-1.45829944845704	0.145227313371077	   
df.mm.trans2:probe6	-0.0540205842865539	0.07295943857284	-0.740419407594833	0.459305317776145	   
df.mm.trans3:probe2	0.103750720132306	0.07295943857284	1.42203287418015	0.155482746073109	   
df.mm.trans3:probe3	0.0447109324946311	0.07295943857284	0.612819031632121	0.540204262746234	   
df.mm.trans3:probe4	-0.0781460954320732	0.07295943857284	-1.07108959389887	0.284515399262034	   
df.mm.trans3:probe5	0.0376956090065814	0.07295943857284	0.516665283395066	0.605560581347282	   
df.mm.trans3:probe6	-0.099514791879639	0.07295943857284	-1.36397420027139	0.173034399364337	   
df.mm.trans3:probe7	-0.0221700136886728	0.07295943857284	-0.303867657459275	0.761323202658822	   
df.mm.trans3:probe8	-0.0640674960627799	0.07295943857284	-0.878124850135972	0.380191224944328	   
df.mm.trans3:probe9	0.0130307790753985	0.07295943857284	0.178603061239144	0.858303462331774	   
df.mm.trans3:probe10	0.0247233017983160	0.07295943857284	0.338863651940429	0.734818779465113	   
df.mm.trans3:probe11	-0.0380070848677996	0.07295943857284	-0.520934448116055	0.60258481415193	   
df.mm.trans3:probe12	-0.0569602245287317	0.07295943857284	-0.780710839377755	0.435248737357716	   
df.mm.trans3:probe13	-0.0178062803576325	0.07295943857284	-0.244057255729228	0.807261302838566	   
df.mm.trans3:probe14	0.0183317572994839	0.07295943857284	0.251259571867212	0.801690585639256	   
df.mm.trans3:probe15	0.0698431191466309	0.07295943857284	0.957286959889392	0.338768240155341	   
df.mm.trans3:probe16	0.0412204684605934	0.07295943857284	0.564977873554227	0.572278212262073	   
df.mm.trans3:probe17	-0.0556175894468257	0.07295943857284	-0.762308352898016	0.446144665840071	   
df.mm.trans3:probe18	0.0615772987086083	0.07295943857284	0.84399359305831	0.398974673231283