chr11.3274_chr11_79138083_79138614_+_1.R 

fitVsDatCorrelation=0.952482706536544
cont.fitVsDatCorrelation=0.254115429312216

fstatistic=8612.02373122611,57,807
cont.fstatistic=841.39793571385,57,807

residuals=-0.884727743928593,-0.10022682791247,-0.000399400853487707,0.0973392230546141,0.950617124135967
cont.residuals=-1.09993647677330,-0.345258972286131,-0.132819161249029,0.157035873643609,2.66046635808986

predictedValues:
Include	Exclude	Both
chr11.3274_chr11_79138083_79138614_+_1.R.tl.Lung	72.3230549892345	52.0504142279384	73.1023951700672
chr11.3274_chr11_79138083_79138614_+_1.R.tl.cerebhem	76.9796056720842	55.7336632728351	82.6197166123508
chr11.3274_chr11_79138083_79138614_+_1.R.tl.cortex	77.8293432931857	47.5457018195433	96.1328930155691
chr11.3274_chr11_79138083_79138614_+_1.R.tl.heart	66.6722487554274	47.2226016953084	75.6385436663038
chr11.3274_chr11_79138083_79138614_+_1.R.tl.kidney	76.5084299548866	51.6113926824943	60.7545874905355
chr11.3274_chr11_79138083_79138614_+_1.R.tl.liver	185.192002291857	58.9484862600364	381.18189861763
chr11.3274_chr11_79138083_79138614_+_1.R.tl.stomach	72.9737103417586	47.0549272083679	74.0206722235745
chr11.3274_chr11_79138083_79138614_+_1.R.tl.testicle	71.8364948772286	48.3173902719021	60.061617302703


diffExp=20.2726407612961,21.2459423992491,30.2836414736424,19.4496470601190,24.8970372723923,126.24351603182,25.9187831333907,23.5191046053265
diffExpScore=0.99658505299314
diffExp1.5=0,0,1,0,0,1,1,0
diffExp1.5Score=0.75
diffExp1.4=0,0,1,1,1,1,1,1
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	73.1467027845414	100.997551116386	81.2538454677125
cerebhem	78.0058176985878	89.2496907707987	78.636635210382
cortex	79.0367263906151	67.1358137557406	82.0023776143036
heart	66.3132060083232	85.4225569073289	79.8952692139002
kidney	84.8731605955983	88.1062146586771	86.3460466964669
liver	103.813383110611	91.9038384175893	81.1586481311567
stomach	63.2996493712869	87.879456329626	78.7787504088507
testicle	69.1637847545505	70.8612261924463	93.5226396080747
cont.diffExp=-27.8508483318447,-11.2438730722109,11.9009126348745,-19.1093508990057,-3.23305406307875,11.9095446930213,-24.5798069583392,-1.69744143789585
cont.diffExpScore=1.71830663692766

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=-1,0,0,0,0,0,-1,0
cont.diffExp1.3Score=0.666666666666667
cont.diffExp1.2=-1,0,0,-1,0,0,-1,0
cont.diffExp1.2Score=0.75

tran.correlation=0.74882432196055
cont.tran.correlation=0.182396249334323

tran.covariance=0.0207459656533112
cont.tran.covariance=0.00347484470197709

tran.mean=69.2999667258805
cont.tran.mean=81.2005486789192

weightedLogRatios:
wLogRatio
Lung	1.35409968911574
cerebhem	1.35062296267766
cortex	2.02458558086358
heart	1.38909151931008
kidney	1.62997121199289
liver	5.3218786725173
stomach	1.78615990027877
testicle	1.61658256168549

cont.weightedLogRatios:
wLogRatio
Lung	-1.43692009637813
cerebhem	-0.595726615953189
cortex	0.699831575167008
heart	-1.09416843218989
kidney	-0.166732213954655
liver	0.55828596249035
stomach	-1.41468271351314
testicle	-0.103011649228035

varWeightedLogRatios=1.79275170275006
cont.varWeightedLogRatios=0.697133335690142

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.35407239627092	0.090134820433472	37.2117277223239	2.91775569675681e-177	***
df.mm.trans1	0.92808213124927	0.0706748279317516	13.1317211291337	7.70190226121205e-36	***
df.mm.trans2	0.585730761677786	0.0706748279317516	8.28768571242094	4.79687327824641e-16	***
df.mm.exp2	0.0083819260839975	0.093090842253929	0.09004028625215	0.928277543021994	   
df.mm.exp3	-0.291016200444424	0.0930908422539289	-3.12615283521234	0.00183455656974506	** 
df.mm.exp4	-0.212799136224357	0.093090842253929	-2.28592986240143	0.0225167604639296	*  
df.mm.exp5	0.232806193902524	0.093090842253929	2.50084958161068	0.0125867777400806	*  
df.mm.exp6	-0.586714179264384	0.0930908422539289	-6.30259824767695	4.81183859018564e-10	***
df.mm.exp7	-0.104424160490720	0.0930908422539289	-1.12174471690649	0.262304656498612	   
df.mm.exp8	0.115318605435802	0.093090842253929	1.23877497123982	0.215789035217002	   
df.mm.trans1:exp2	0.0540156414336067	0.0693858171208316	0.77848245758267	0.436512836579185	   
df.mm.trans2:exp2	0.0599896525490884	0.0693858171208316	0.864580904835634	0.387525772912314	   
df.mm.trans1:exp3	0.364391765819514	0.0693858171208316	5.25167506761427	1.92946148719924e-07	***
df.mm.trans2:exp3	0.200494839191886	0.0693858171208316	2.88956515194935	0.00396113120822503	** 
df.mm.trans1:exp4	0.131444984077824	0.0693858171208316	1.89440709257513	0.0585282829668828	.  
df.mm.trans2:exp4	0.115459010381895	0.0693858171208316	1.66401456627411	0.0964977348682175	.  
df.mm.trans1:exp5	-0.176548221504998	0.0693858171208316	-2.5444424931618	0.0111304845066391	*  
df.mm.trans2:exp5	-0.241276510663772	0.0693858171208316	-3.47731742127649	0.000533544132766216	***
df.mm.trans1:exp6	1.52696435852216	0.0693858171208316	22.0068656950892	1.92380139791525e-84	***
df.mm.trans2:exp6	0.711165374248166	0.0693858171208316	10.2494343045598	2.94727826480795e-23	***
df.mm.trans1:exp7	0.113380446618623	0.0693858171208316	1.63405795771170	0.102636701111877	   
df.mm.trans2:exp7	0.00352699055338315	0.0693858171208316	0.050831577687427	0.959472306637317	   
df.mm.trans1:exp8	-0.122068931169219	0.0693858171208316	-1.75927785006326	0.078909236743952	.  
df.mm.trans2:exp8	-0.189739815840365	0.0693858171208316	-2.73456195680370	0.00638328179390482	** 
df.mm.trans1:probe2	-0.0799449485539792	0.0537460228343948	-1.48745794270787	0.137284512782735	   
df.mm.trans1:probe3	-0.0468123172925745	0.0537460228343949	-0.870991281286342	0.384017937008145	   
df.mm.trans1:probe4	0.0764931157358982	0.0537460228343948	1.42323304501233	0.155055079118479	   
df.mm.trans1:probe5	0.0230329422589709	0.0537460228343948	0.428551566130599	0.668363959780957	   
df.mm.trans1:probe6	-0.00311588217614776	0.0537460228343948	-0.0579741906810218	0.953783538418143	   
df.mm.trans2:probe2	0.0649409771149918	0.0537460228343948	1.20829363160678	0.227288281882682	   
df.mm.trans2:probe3	0.00464762040859042	0.0537460228343948	0.0864737549587793	0.931111268786565	   
df.mm.trans2:probe4	0.134763842815690	0.0537460228343949	2.50741981841022	0.0123569990609165	*  
df.mm.trans2:probe5	0.0687723082516189	0.0537460228343948	1.27957948560257	0.201060819723602	   
df.mm.trans2:probe6	0.0991631119184068	0.0537460228343949	1.84503162632059	0.0653991720831943	.  
df.mm.trans3:probe2	-0.170572052072793	0.0537460228343948	-3.17366835864989	0.00156231117751104	** 
df.mm.trans3:probe3	-0.608587944345933	0.0537460228343948	-11.3234042679055	1.08739732346940e-27	***
df.mm.trans3:probe4	-0.90948267771465	0.0537460228343948	-16.9218600698511	3.32686299298535e-55	***
df.mm.trans3:probe5	-0.0595015270215109	0.0537460228343948	-1.10708707144434	0.268586165082039	   
df.mm.trans3:probe6	-0.773333522937906	0.0537460228343948	-14.3886650984528	5.92436630335106e-42	***
df.mm.trans3:probe7	-0.957439087435646	0.0537460228343949	-17.8141383667729	4.04961862942364e-60	***
df.mm.trans3:probe8	-0.761327184888672	0.0537460228343948	-14.1652748378148	7.65242131033969e-41	***
df.mm.trans3:probe9	-0.948378635830982	0.0537460228343948	-17.6455593514924	3.50370026418187e-59	***
df.mm.trans3:probe10	-0.967410089142308	0.0537460228343948	-17.9996591026492	3.73007893528946e-61	***
df.mm.trans3:probe11	-0.369628838398445	0.0537460228343948	-6.87732447733604	1.22235843942221e-11	***
df.mm.trans3:probe12	-0.429604587165262	0.0537460228343948	-7.99323493180105	4.53950414781969e-15	***
df.mm.trans3:probe13	-0.838757534066679	0.0537460228343948	-15.6059460743933	3.52037378862913e-48	***
df.mm.trans3:probe14	-0.765990110879585	0.0537460228343948	-14.2520333688652	2.8409923235931e-41	***
df.mm.trans3:probe15	-0.496740342615396	0.0537460228343948	-9.24236467033066	2.09625206049988e-19	***
df.mm.trans3:probe16	-0.316290935205876	0.0537460228343948	-5.88491796277556	5.8353354327749e-09	***
df.mm.trans3:probe17	-0.590211596915551	0.0537460228343948	-10.9814934350425	3.03782405783163e-26	***
df.mm.trans3:probe18	-0.473569237296338	0.0537460228343948	-8.81124243845028	7.49651598242428e-18	***
df.mm.trans3:probe19	-0.851005712885442	0.0537460228343949	-15.8338360311349	2.24253170689840e-49	***
df.mm.trans3:probe20	-0.456416553607164	0.0537460228343948	-8.49209912728797	9.6928149625738e-17	***
df.mm.trans3:probe21	-0.76853205891054	0.0537460228343948	-14.2993289248319	1.65283507906979e-41	***
df.mm.trans3:probe22	-0.309390781247941	0.0537460228343948	-5.75653350576754	1.21963517669596e-08	***
df.mm.trans3:probe23	-0.451551298075905	0.0537460228343948	-8.40157604716631	1.97562715080739e-16	***
df.mm.trans3:probe24	-0.550857466890696	0.0537460228343948	-10.2492693940913	2.95173051424121e-23	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.37533819462611	0.286205331252270	15.2874098308447	1.59459090138688e-46	***
df.mm.trans1	-0.088954444836967	0.224413966124601	-0.396385511887335	0.691925439690387	   
df.mm.trans2	0.249592325639737	0.224413966124601	1.11219604532615	0.266385075756634	   
df.mm.exp2	-0.0266014949677589	0.295591595076219	-0.0899940844424202	0.928314246124164	   
df.mm.exp3	-0.34010314103128	0.295591595076219	-1.15058461301508	0.250243981316272	   
df.mm.exp4	-0.248702553843219	0.295591595076219	-0.841372210800145	0.400388690192162	   
df.mm.exp5	-0.0486472090712753	0.295591595076219	-0.164575752090419	0.869319130443859	   
df.mm.exp6	0.256946658972680	0.295591595076219	0.869262398703949	0.384962080006589	   
df.mm.exp7	-0.252782617656236	0.295591595076219	-0.85517525486831	0.392707946992599	   
df.mm.exp8	-0.550987927156067	0.295591595076219	-1.86401757131827	0.0626821643249328	.  
df.mm.trans1:exp2	0.0909178530208248	0.220320966722672	0.412660920897588	0.679964667103576	   
df.mm.trans2:exp2	-0.097056819306348	0.220320966722672	-0.440524661588462	0.65967512815783	   
df.mm.trans1:exp3	0.417548724755928	0.220320966722672	1.89518379011796	0.0584251945649463	.  
df.mm.trans2:exp3	-0.068275490507621	0.220320966722672	-0.309891026365922	0.7567238313266	   
df.mm.trans1:exp4	0.150624565111641	0.220320966722672	0.683659695907376	0.494386324847131	   
df.mm.trans2:exp4	0.0812164819903427	0.220320966722672	0.368628021193160	0.712501688762019	   
df.mm.trans1:exp5	0.197338071058571	0.220320966722672	0.895684482480366	0.3706883833456	   
df.mm.trans2:exp5	-0.0879059896882368	0.220320966722673	-0.398990577228575	0.69000570258008	   
df.mm.trans1:exp6	0.0931811834151137	0.220320966722672	0.422933798817272	0.672456236872292	   
df.mm.trans2:exp6	-0.351300133328577	0.220320966722672	-1.59449251950121	0.111217305531733	   
df.mm.trans1:exp7	0.108195355898372	0.220320966722672	0.491080615285072	0.62350294848478	   
df.mm.trans2:exp7	0.113652408470032	0.220320966722672	0.515849263738439	0.606100988176134	   
df.mm.trans1:exp8	0.494998259356913	0.220320966722672	2.24671426746229	0.024927886908399	*  
df.mm.trans2:exp8	0.196615060706347	0.220320966722672	0.892402859478349	0.372443056575467	   
df.mm.trans1:probe2	0.0619571016389528	0.170659886987446	0.363044314236013	0.716666850884352	   
df.mm.trans1:probe3	-0.0383165081669249	0.170659886987446	-0.224519709014829	0.822409766130464	   
df.mm.trans1:probe4	0.0308041128476435	0.170659886987446	0.180500019022687	0.856805356753259	   
df.mm.trans1:probe5	0.0834318369929099	0.170659886987446	0.488877840397535	0.625061015385676	   
df.mm.trans1:probe6	0.0446225150471126	0.170659886987446	0.261470435934339	0.793796461876242	   
df.mm.trans2:probe2	-0.110451154611178	0.170659886987446	-0.647200443882298	0.517686273659036	   
df.mm.trans2:probe3	-0.266975562102845	0.170659886987446	-1.56437207838116	0.118122243583032	   
df.mm.trans2:probe4	-0.230181404789694	0.170659886987446	-1.34877274825939	0.177788326679042	   
df.mm.trans2:probe5	0.165189302900185	0.170659886987446	0.967944522970047	0.333362069885473	   
df.mm.trans2:probe6	0.147391315875000	0.170659886987446	0.86365529988803	0.388033887260595	   
df.mm.trans3:probe2	0.0188755564214675	0.170659886987446	0.110603357090328	0.911958385145783	   
df.mm.trans3:probe3	-0.17311711394866	0.170659886987446	-1.01439838619719	0.310696724281729	   
df.mm.trans3:probe4	-0.223058293001361	0.170659886987446	-1.30703410707034	0.191573429423885	   
df.mm.trans3:probe5	-0.413981055946483	0.170659886987446	-2.42576661249598	0.0154943839233019	*  
df.mm.trans3:probe6	-0.272783424265758	0.170659886987446	-1.59840387264422	0.110344557814317	   
df.mm.trans3:probe7	-0.193230369188395	0.170659886987446	-1.13225417290127	0.257863900764854	   
df.mm.trans3:probe8	-0.0886479310623904	0.170659886987446	-0.519442105741648	0.603594908334826	   
df.mm.trans3:probe9	-0.00394749997726452	0.170659886987446	-0.0231308015430416	0.981551654200425	   
df.mm.trans3:probe10	0.0588172465813322	0.170659886987446	0.344645995140375	0.730450318978836	   
df.mm.trans3:probe11	-0.102805908719554	0.170659886987446	-0.602402301644071	0.54707560198059	   
df.mm.trans3:probe12	-0.155941696351587	0.170659886987446	-0.913757175774166	0.361117368923372	   
df.mm.trans3:probe13	-0.194915944211648	0.170659886987446	-1.14213098140623	0.253738335900018	   
df.mm.trans3:probe14	0.0358877903950526	0.170659886987446	0.210288375485052	0.833495688855088	   
df.mm.trans3:probe15	-0.111970261184986	0.170659886987446	-0.656101812567255	0.511945636402921	   
df.mm.trans3:probe16	-0.127633601486989	0.170659886987446	-0.747882843121639	0.454748705234154	   
df.mm.trans3:probe17	-0.307569811873651	0.170659886987446	-1.80223845979856	0.0718809335966936	.  
df.mm.trans3:probe18	-0.0102841199616493	0.170659886987446	-0.0602609092458022	0.951962754949787	   
df.mm.trans3:probe19	-0.200514902003044	0.170659886987446	-1.17493867799053	0.240365806679254	   
df.mm.trans3:probe20	-0.259731386611859	0.170659886987446	-1.52192405137925	0.128419834534736	   
df.mm.trans3:probe21	-0.157843318600313	0.170659886987446	-0.924899936280425	0.355294440307217	   
df.mm.trans3:probe22	-0.205322643943682	0.170659886987446	-1.20311016002716	0.229286528026485	   
df.mm.trans3:probe23	-0.158479697309730	0.170659886987446	-0.928628865911463	0.35335912477232	   
df.mm.trans3:probe24	-0.0733518498838234	0.170659886987446	-0.429813069600939	0.667446364897891