chr14.7234_chr14_46600390_46601055_+_1.R 

fitVsDatCorrelation=0.911434608286343
cont.fitVsDatCorrelation=0.271861222405034

fstatistic=7820.7889467257,39,393
cont.fstatistic=1421.38365225057,39,393

residuals=-0.669496258322575,-0.0864771226732936,-0.0129446882601178,0.0750924065394108,0.739793615323213
cont.residuals=-0.715517762091675,-0.263302276211838,-0.0300602374423491,0.206566427367491,1.64646993819043

predictedValues:
Include	Exclude	Both
chr14.7234_chr14_46600390_46601055_+_1.R.tl.Lung	95.8988055992921	53.60700377896	85.7701317339426
chr14.7234_chr14_46600390_46601055_+_1.R.tl.cerebhem	80.9480127098924	67.2101984258713	83.6213457376081
chr14.7234_chr14_46600390_46601055_+_1.R.tl.cortex	83.601902383078	129.639311256341	162.389929955537
chr14.7234_chr14_46600390_46601055_+_1.R.tl.heart	82.857081254207	58.9817525860511	84.7370737237145
chr14.7234_chr14_46600390_46601055_+_1.R.tl.kidney	92.5172239231149	58.5563792290277	88.0828176721179
chr14.7234_chr14_46600390_46601055_+_1.R.tl.liver	84.48384444013	63.4433788177146	92.9018469156677
chr14.7234_chr14_46600390_46601055_+_1.R.tl.stomach	101.495404013427	58.6095791017858	86.5095862452617
chr14.7234_chr14_46600390_46601055_+_1.R.tl.testicle	85.8108702198708	59.9171682311468	85.4602728509332


diffExp=42.2918018203321,13.7378142840210,-46.0374088732633,23.8753286681559,33.9608446940871,21.0404656224154,42.8858249116411,25.893701988724
diffExpScore=1.57406713953423
diffExp1.5=1,0,-1,0,1,0,1,0
diffExp1.5Score=1.33333333333333
diffExp1.4=1,0,-1,1,1,0,1,1
diffExp1.4Score=1.2
diffExp1.3=1,0,-1,1,1,1,1,1
diffExp1.3Score=1.16666666666667
diffExp1.2=1,1,-1,1,1,1,1,1
diffExp1.2Score=1.14285714285714

cont.predictedValues:
Include	Exclude	Both
Lung	82.4983977594209	80.4131582637943	72.0162696334702
cerebhem	82.2988590411888	72.0556356122523	76.8668225316936
cortex	78.5811794212956	71.759425889703	78.7109289954475
heart	77.7126263197757	88.0252341398064	88.9148166668209
kidney	70.569399783978	75.5046249883303	85.9258544858713
liver	86.5614964439364	74.1102166515217	81.2168166669758
stomach	80.8768049041052	74.4992768065672	95.4668507679478
testicle	82.2698430697781	80.636211790559	83.2246290062548
cont.diffExp=2.08523949562658,10.2432234289365,6.8217535315927,-10.3126078200307,-4.93522520435229,12.4512797924146,6.37752809753799,1.63363127921920
cont.diffExpScore=2.16285717873176

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=-0.36855790808313
cont.tran.correlation=-0.106812984317849

tran.covariance=-0.00944578658337257
cont.tran.covariance=-0.000398423498597869

tran.mean=78.5986197481194
cont.tran.mean=78.6482744303758

weightedLogRatios:
wLogRatio
Lung	2.48493718309538
cerebhem	0.799874940620271
cortex	-2.03789445045446
heart	1.44356766529942
kidney	1.96624252808904
liver	1.22967023307138
stomach	2.38615657743755
testicle	1.53462724423015

cont.weightedLogRatios:
wLogRatio
Lung	0.112644062426696
cerebhem	0.577385289744924
cortex	0.392196464315241
heart	-0.550174471198314
kidney	-0.290019104959332
liver	0.680719087206604
stomach	0.35745141683808
testicle	0.088249386997157

varWeightedLogRatios=2.06514778818591
cont.varWeightedLogRatios=0.178791263592217

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.59105014766368	0.0862622069433289	53.2220344267314	9.75207291943644e-182	***
df.mm.trans1	-0.00535151245019121	0.070432797032508	-0.075980405090561	0.93947335067331	   
df.mm.trans2	-0.593398806920773	0.070432797032508	-8.42503538013537	6.87169966965016e-16	***
df.mm.exp2	0.0820308859141659	0.0956993262365717	0.857173076761094	0.391871632923529	   
df.mm.exp3	0.107519499663210	0.0956993262365717	1.12351365355925	0.261905236964628	   
df.mm.exp4	-0.0385103066495839	0.0956993262365717	-0.402409381173544	0.687601550943228	   
df.mm.exp5	0.0258049642486225	0.0956993262365717	0.269646247924796	0.78757394064585	   
df.mm.exp6	-0.0381377876443878	0.0956993262365717	-0.398516783181002	0.690465712932506	   
df.mm.exp7	0.137354011159616	0.0956993262365717	1.43526622977546	0.152006611218251	   
df.mm.exp8	0.00375472367358951	0.0956993262365717	0.039234588384747	0.968723280171931	   
df.mm.trans1:exp2	-0.251517282855916	0.0781381726692478	-3.21887848491886	0.00139380420430988	** 
df.mm.trans2:exp2	0.144114385331549	0.0781381726692478	1.84435315555142	0.0658841182034918	.  
df.mm.trans1:exp3	-0.244746751217217	0.0781381726692478	-3.13223028971012	0.00186476126589455	** 
df.mm.trans2:exp3	0.775556838797268	0.0781381726692478	9.92545400415408	7.2514840613543e-21	***
df.mm.trans1:exp4	-0.107666009513451	0.0781381726692478	-1.37789259507247	0.169020499792058	   
df.mm.trans2:exp4	0.134058697458003	0.0781381726692478	1.71566204939886	0.0870120580658516	.  
df.mm.trans1:exp5	-0.0617036596541484	0.0781381726692478	-0.789673696559743	0.430194535386966	   
df.mm.trans2:exp5	0.062505346329064	0.0781381726692478	0.799933556082042	0.424232546182283	   
df.mm.trans1:exp6	-0.088595413493468	0.0781381726692478	-1.13383011743165	0.257556972978340	   
df.mm.trans2:exp6	0.206605896546552	0.0781381726692478	2.64410965202754	0.0085186502869216	** 
df.mm.trans1:exp7	-0.0806340215230679	0.0781381726692478	-1.03194147967070	0.302734161117828	   
df.mm.trans2:exp7	-0.0481355890933721	0.0781381726692478	-0.616031671192593	0.53823024259971	   
df.mm.trans1:exp8	-0.114902559829410	0.0781381726692478	-1.47050482375346	0.142225239252250	   
df.mm.trans2:exp8	0.107528628200449	0.0781381726692478	1.37613441071381	0.169563657493662	   
df.mm.trans1:probe2	-0.0176272063820874	0.0478496631182858	-0.368387261964884	0.712782845846453	   
df.mm.trans1:probe3	-0.108377658313844	0.0478496631182858	-2.26496178344936	0.0240588598451877	*  
df.mm.trans1:probe4	-0.16659788231599	0.0478496631182858	-3.48169394430542	0.000554197449566139	***
df.mm.trans1:probe5	-0.0370306068701582	0.0478496631182858	-0.77389482928265	0.43945826861679	   
df.mm.trans1:probe6	0.0607720572906553	0.0478496631182858	1.27006238561022	0.204813852156310	   
df.mm.trans2:probe2	-0.00925214042708922	0.0478496631182858	-0.193358528025947	0.846778084378166	   
df.mm.trans2:probe3	0.00374533694228466	0.0478496631182858	0.0782730054551497	0.937650726727406	   
df.mm.trans2:probe4	-0.113284348253362	0.0478496631182858	-2.36750565982710	0.0183920009189549	*  
df.mm.trans2:probe5	0.0738562459107898	0.0478496631182858	1.54350607920091	0.123512848416101	   
df.mm.trans2:probe6	-0.146724458386548	0.0478496631182858	-3.06636345639134	0.00231659655072415	** 
df.mm.trans3:probe2	0.88961797331434	0.0478496631182858	18.5919380689301	8.25811978408137e-56	***
df.mm.trans3:probe3	0.987257843424987	0.0478496631182858	20.6324930853631	1.30199004849233e-64	***
df.mm.trans3:probe4	-0.00127448355055851	0.0478496631182858	-0.0266351624547063	0.978764247040433	   
df.mm.trans3:probe5	0.220143668986796	0.0478496631182858	4.60073602697253	5.68826299986045e-06	***
df.mm.trans3:probe6	0.660481013461041	0.0478496631182858	13.8032531562095	1.29427810798210e-35	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.51895936832566	0.201760321814307	22.3976613820272	3.36531055612821e-72	***
df.mm.trans1	-0.086759595107535	0.164736612928259	-0.52665642181995	0.598729318621456	   
df.mm.trans2	-0.183759200044466	0.164736612928259	-1.1154727341911	0.265329510086461	   
df.mm.exp2	-0.177343199486102	0.223832980201722	-0.792301471062385	0.428662905584368	   
df.mm.exp3	-0.251395208578989	0.223832980201722	-1.12313747666866	0.262064747462566	   
df.mm.exp4	-0.180102159494382	0.223832980201722	-0.804627447358611	0.42152118130501	   
df.mm.exp5	-0.395758869244611	0.223832980201722	-1.76809900349781	0.0778201562238563	.  
df.mm.exp6	-0.153778459536138	0.223832980201722	-0.687023241157535	0.492473280002751	   
df.mm.exp7	-0.378127221253607	0.223832980201722	-1.68932755536218	0.0919497921904454	.  
df.mm.exp8	-0.1446555198633	0.223832980201722	-0.646265441906432	0.518484670326152	   
df.mm.trans1:exp2	0.17492157160687	0.182758863033570	0.957116764152443	0.339096724317751	   
df.mm.trans2:exp2	0.0676039141555198	0.182758863033570	0.369907719020456	0.71165050509653	   
df.mm.trans1:exp3	0.202748559721677	0.182758863033570	1.10937744061384	0.267945768505192	   
df.mm.trans2:exp3	0.137536603083801	0.182758863033570	0.75255777367436	0.452166218856011	   
df.mm.trans1:exp4	0.120341032510043	0.182758863033570	0.658468927375296	0.510622418405548	   
df.mm.trans2:exp4	0.270547861664393	0.182758863033570	1.48035426120318	0.139579932675029	   
df.mm.trans1:exp5	0.239576616909562	0.182758863033570	1.31088918443072	0.190660679433607	   
df.mm.trans2:exp5	0.332774958955442	0.182758863033570	1.8208417005435	0.0693912100843343	.  
df.mm.trans1:exp6	0.201854690369027	0.182758863033570	1.10448646384908	0.270057930796023	   
df.mm.trans2:exp6	0.0721540360813114	0.182758863033570	0.394804579562622	0.693201292871814	   
df.mm.trans1:exp7	0.358275418978396	0.182758863033570	1.96037233451484	0.0506583710803152	.  
df.mm.trans2:exp7	0.30173881650608	0.182758863033570	1.6510215236492	0.0995330093728048	.  
df.mm.trans1:exp8	0.141881261485812	0.182758863033570	0.776330401331895	0.438020891675879	   
df.mm.trans2:exp8	0.147425523487804	0.182758863033570	0.806666889040145	0.420346311359506	   
df.mm.trans1:probe2	-0.143116292352786	0.111916490100861	-1.27877752620554	0.201730015366370	   
df.mm.trans1:probe3	-0.00135160334413908	0.111916490100861	-0.0120768918228314	0.990370396942584	   
df.mm.trans1:probe4	0.0181059305544100	0.111916490100861	0.161780721840835	0.871561674841965	   
df.mm.trans1:probe5	-0.142553490500985	0.111916490100861	-1.27374876010241	0.203505261506719	   
df.mm.trans1:probe6	0.0358646416753231	0.111916490100861	0.320458956879377	0.748790758574466	   
df.mm.trans2:probe2	0.110209004951332	0.111916490100861	0.98474322105714	0.32535607269422	   
df.mm.trans2:probe3	0.243174064519418	0.111916490100861	2.17281710943816	0.0303909461991171	*  
df.mm.trans2:probe4	0.151022566694858	0.111916490100861	1.34942193557673	0.177978326975089	   
df.mm.trans2:probe5	0.0523057174280862	0.111916490100861	0.467363811900706	0.640498635984958	   
df.mm.trans2:probe6	0.0670205005302323	0.111916490100861	0.598843838560629	0.549622039361402	   
df.mm.trans3:probe2	0.0685519721727454	0.111916490100861	0.612527895674401	0.540542800321236	   
df.mm.trans3:probe3	0.0517932866465924	0.111916490100861	0.462785123085216	0.643774533935361	   
df.mm.trans3:probe4	0.155042988800486	0.111916490100861	1.38534534688104	0.166732655050514	   
df.mm.trans3:probe5	-0.0301570657604296	0.111916490100861	-0.269460431910003	0.787716807192523	   
df.mm.trans3:probe6	-0.0745222571762216	0.111916490100861	-0.665873787759612	0.505882418825085