chr2.13849_chr2_72699288_72705964_+_2.R 

fitVsDatCorrelation=0.886797782574815
cont.fitVsDatCorrelation=0.300799541799317

fstatistic=9932.62992526768,52,692
cont.fstatistic=2322.37553790948,52,692

residuals=-0.435240420928825,-0.0917769183567845,-0.00480515630889636,0.0751116861149253,0.912161452910385
cont.residuals=-0.630781651193573,-0.247770892391381,-0.0368563198399034,0.174032044702187,1.30994824090171

predictedValues:
Include	Exclude	Both
chr2.13849_chr2_72699288_72705964_+_2.R.tl.Lung	58.1492430759654	45.6211715792418	84.6381372873606
chr2.13849_chr2_72699288_72705964_+_2.R.tl.cerebhem	69.372947438094	57.6200276627527	70.1806773832373
chr2.13849_chr2_72699288_72705964_+_2.R.tl.cortex	69.6046018406961	45.8789011245014	87.6046803436648
chr2.13849_chr2_72699288_72705964_+_2.R.tl.heart	90.1462594695279	46.6951425356145	123.140694685977
chr2.13849_chr2_72699288_72705964_+_2.R.tl.kidney	61.0698851153239	46.0855128972338	83.6671233989187
chr2.13849_chr2_72699288_72705964_+_2.R.tl.liver	64.4862908473309	47.6350482146084	83.894874951832
chr2.13849_chr2_72699288_72705964_+_2.R.tl.stomach	61.8712188932726	48.1684697634186	82.4439144659367
chr2.13849_chr2_72699288_72705964_+_2.R.tl.testicle	81.7930821538855	53.1064405217479	111.008814117451


diffExp=12.5280714967236,11.7529197753412,23.7257007161946,43.4511169339134,14.9843722180901,16.8512426327225,13.702749129854,28.6866416321376
diffExpScore=0.994000581266942
diffExp1.5=0,0,1,1,0,0,0,1
diffExp1.5Score=0.75
diffExp1.4=0,0,1,1,0,0,0,1
diffExp1.4Score=0.75
diffExp1.3=0,0,1,1,1,1,0,1
diffExp1.3Score=0.833333333333333
diffExp1.2=1,1,1,1,1,1,1,1
diffExp1.2Score=0.888888888888889

cont.predictedValues:
Include	Exclude	Both
Lung	69.9508037774872	68.5350715244779	68.427909086798
cerebhem	65.5458278747847	61.7208797168846	58.8538418980935
cortex	64.8961128810729	61.5687059651559	76.4325299984372
heart	66.497274036541	58.8296910960548	56.827875809642
kidney	67.3387225192442	68.1990273963288	70.8299402647276
liver	66.8357921319797	58.1569024401158	60.1998745494433
stomach	63.514589526836	58.1294741576295	66.0644593464163
testicle	68.0311479233229	51.7269200968174	74.8581300051062
cont.diffExp=1.41573225300931,3.82494815790017,3.32740691591698,7.66758294048628,-0.860304877084587,8.67888969186395,5.3851153692065,16.3042278265054
cont.diffExpScore=1.01541622341281

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=0.233502502318202
cont.tran.correlation=0.310981078858644

tran.covariance=0.00349751821446460
cont.tran.covariance=0.000736015612818992

tran.mean=59.206515195826
cont.tran.mean=63.7173089415458

weightedLogRatios:
wLogRatio
Lung	0.956416040203382
cerebhem	0.769735504820352
cortex	1.6816476703795
heart	2.74466679934048
kidney	1.11798963591177
liver	1.21608194237697
stomach	1.00137175830232
testicle	1.80887999646793

cont.weightedLogRatios:
wLogRatio
Lung	0.0866438105204485
cerebhem	0.249689706836628
cortex	0.218245367218496
heart	0.506707265060098
kidney	-0.0535225849958652
liver	0.574833336485699
stomach	0.363864509742949
testicle	1.11868253090034

varWeightedLogRatios=0.417103753783467
cont.varWeightedLogRatios=0.130998998234348

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	2.96439187668799	0.084851245320506	34.9363390659817	6.57293428819407e-155	***
df.mm.trans1	1.17544115995090	0.0762088268608181	15.4239503266155	2.36592698973007e-46	***
df.mm.trans2	0.842105172849657	0.0700843664063264	12.0155922929717	2.43377825982979e-30	***
df.mm.exp2	0.597294373178213	0.095998225533205	6.22193139363409	8.50264418430466e-10	***
df.mm.exp3	0.151001799828952	0.095998225533205	1.57296448960634	0.116184112180025	   
df.mm.exp4	0.0867462411052504	0.095998225533205	0.903623380780572	0.366509588884704	   
df.mm.exp5	0.0706716038688674	0.095998225533205	0.736176147802052	0.461872976834511	   
df.mm.exp6	0.155457127599194	0.095998225533205	1.61937501173314	0.105822216713459	   
df.mm.exp7	0.142641725918415	0.095998225533205	1.48587877667672	0.137766610727096	   
df.mm.exp8	0.221881476958180	0.095998225533205	2.31130810726739	0.0211087774015503	*  
df.mm.trans1:exp2	-0.420810250156803	0.091911303421997	-4.57843849982973	5.55419145276207e-06	***
df.mm.trans2:exp2	-0.363796061222524	0.0799985212776708	-4.5475348220476	6.40763188405314e-06	***
df.mm.trans1:exp3	0.0288160215969277	0.091911303421997	0.313519888458368	0.753980190571451	   
df.mm.trans2:exp3	-0.145368356723488	0.0799985212776708	-1.81713804707617	0.0696283789730725	.  
df.mm.trans1:exp4	0.351674353257808	0.091911303421997	3.82623616643915	0.000141887142166407	***
df.mm.trans2:exp4	-0.0634779938569276	0.0799985212776708	-0.79348959009628	0.427764620330259	   
df.mm.trans1:exp5	-0.0216655999617645	0.0919113034219971	-0.235722910622756	0.813717435702756	   
df.mm.trans2:exp5	-0.0605448549004584	0.0799985212776708	-0.756824675425066	0.449412500163505	   
df.mm.trans1:exp6	-0.0520173335205553	0.091911303421997	-0.565951429082944	0.57161027118292	   
df.mm.trans2:exp6	-0.112260228063267	0.0799985212776708	-1.40327878903684	0.160982260645392	   
df.mm.trans1:exp7	-0.080599477821949	0.091911303421997	-0.876926719795154	0.3808307663311	   
df.mm.trans2:exp7	-0.0883089709900552	0.0799985212776708	-1.10388254157273	0.270027796216187	   
df.mm.trans1:exp8	0.119298330698782	0.091911303421997	1.29797235222573	0.194729290098889	   
df.mm.trans2:exp8	-0.069955163426984	0.0799985212776708	-0.874455706302035	0.382173512200401	   
df.mm.trans1:probe2	-0.296211091667631	0.0459556517109986	-6.44558570359126	2.15898535306865e-10	***
df.mm.trans1:probe3	0.181296994341052	0.0459556517109985	3.94504239611648	8.79217645518657e-05	***
df.mm.trans1:probe4	-0.298977043935173	0.0459556517109985	-6.50577312699973	1.48258516823591e-10	***
df.mm.trans1:probe5	-0.118320066176819	0.0459556517109985	-2.5746575616183	0.0102406287517713	*  
df.mm.trans1:probe6	-0.343951400045033	0.0459556517109985	-7.48442002755268	2.19051191624362e-13	***
df.mm.trans1:probe7	-0.0315439604619624	0.0459556517109986	-0.68640002453524	0.492690811562356	   
df.mm.trans1:probe8	-0.0878030140724282	0.0459556517109985	-1.91060317509140	0.0564685820170601	.  
df.mm.trans1:probe9	0.20321748763712	0.0459556517109985	4.42203472415307	1.13516394855030e-05	***
df.mm.trans1:probe10	-0.138599354936894	0.0459556517109985	-3.01593709971745	0.00265570558123689	** 
df.mm.trans1:probe11	0.0622766705679513	0.0459556517109985	1.35514715272870	0.175812857476293	   
df.mm.trans1:probe12	-0.0415229517987743	0.0459556517109985	-0.903543965819479	0.366551684916598	   
df.mm.trans1:probe13	0.251295763919351	0.0459556517109985	5.4682232666327	6.35375073886868e-08	***
df.mm.trans1:probe14	-0.0105276045448496	0.0459556517109985	-0.229081824604612	0.81887300600599	   
df.mm.trans1:probe15	0.0320856560996914	0.0459556517109986	0.698187380770239	0.485294560141234	   
df.mm.trans1:probe16	0.0429713052771755	0.0459556517109985	0.935060295682656	0.350083402619466	   
df.mm.trans1:probe17	-0.204659974451216	0.0459556517109985	-4.45342339476027	9.85153042949496e-06	***
df.mm.trans1:probe18	0.0567028545842059	0.0459556517109985	1.23386030821178	0.217673852020514	   
df.mm.trans1:probe19	-0.302161519997063	0.0459556517109985	-6.57506767387975	9.5831787497958e-11	***
df.mm.trans1:probe20	-0.21896414245707	0.0459556517109985	-4.76468365271089	2.30588924489395e-06	***
df.mm.trans1:probe21	-0.356096493490662	0.0459556517109985	-7.74869858728252	3.31561781777394e-14	***
df.mm.trans1:probe22	-0.301012477123901	0.0459556517109986	-6.55006437547398	1.12223714227871e-10	***
df.mm.trans2:probe2	0.113662164320273	0.0459556517109985	2.47330110853526	0.0136261608422103	*  
df.mm.trans2:probe3	0.0455685588067073	0.0459556517109985	0.99157681612861	0.321750589809605	   
df.mm.trans2:probe4	-0.040388018957836	0.0459556517109985	-0.878847703255832	0.379788914732657	   
df.mm.trans2:probe5	0.00574457109081497	0.0459556517109985	0.125002494294736	0.900557879611537	   
df.mm.trans2:probe6	0.000286359011241499	0.0459556517109985	0.00623120335758322	0.995030047092385	   
df.mm.trans3:probe2	-1.06243951467826	0.0459556517109985	-23.1187998673073	4.58783834211562e-88	***
df.mm.trans3:probe3	-0.568220232607357	0.0459556517109986	-12.3645343162736	7.16946743457634e-32	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.20363230434582	0.175095149264324	24.0077027947816	4.03538386685217e-93	***
df.mm.trans1	0.0750267998936827	0.157261049782486	0.477084440155115	0.633452623452636	   
df.mm.trans2	-0.055464864874602	0.144622893284109	-0.383513727426558	0.701456687728185	   
df.mm.exp2	-0.019042303616757	0.198097547836279	-0.0961258926460556	0.923448417816656	   
df.mm.exp3	-0.292823971620533	0.198097547836279	-1.47818069844329	0.139814418137191	   
df.mm.exp4	-0.0175763737703238	0.198097547836279	-0.08872585230005	0.929325457300098	   
df.mm.exp5	-0.0774730798609264	0.198097547836279	-0.391085506646228	0.695854413204973	   
df.mm.exp6	-0.0816439785842045	0.198097547836279	-0.41214027874631	0.680364244788185	   
df.mm.exp7	-0.226045480733084	0.198097547836279	-1.141081670127	0.254230668856179	   
df.mm.exp8	-0.399007750177067	0.198097547836279	-2.01419833074781	0.044375189902948	*  
df.mm.trans1:exp2	-0.0460003279697554	0.189663962278511	-0.242535943134028	0.808436774601156	   
df.mm.trans2:exp2	-0.0856810229403997	0.165081289863566	-0.519023221900024	0.603910490646158	   
df.mm.trans1:exp3	0.217819507773960	0.189663962278511	1.14844963248265	0.251179823415559	   
df.mm.trans2:exp3	0.185632085725406	0.165081289863566	1.12448894649918	0.261195556486706	   
df.mm.trans1:exp4	-0.0330548631284503	0.189663962278511	-0.174281200979609	0.861695445976998	   
df.mm.trans2:exp4	-0.135122555459104	0.165081289863566	-0.818521321046005	0.413341343598255	   
df.mm.trans1:exp5	0.0394163310170388	0.189663962278511	0.207821931712879	0.835429153584652	   
df.mm.trans2:exp5	0.0725577762552298	0.165081289863566	0.439527558302921	0.66041654079517	   
df.mm.trans1:exp6	0.03609053420199	0.189663962278511	0.190286724839129	0.849140262365687	   
df.mm.trans2:exp6	-0.0825570561941243	0.165081289863566	-0.500099413218512	0.617164069096312	   
df.mm.trans1:exp7	0.129522924781236	0.189663962278511	0.682907407528684	0.494893907977363	   
df.mm.trans2:exp7	0.061372709130591	0.165081289863566	0.371772653226259	0.710175934724519	   
df.mm.trans1:exp8	0.371181216384019	0.189663962278511	1.95704662037461	0.0507436668533628	.  
df.mm.trans2:exp8	0.117640487070287	0.165081289863566	0.712621564609248	0.476320173724055	   
df.mm.trans1:probe2	0.0316139466371237	0.0948319811392557	0.333367986805004	0.738957507742808	   
df.mm.trans1:probe3	-0.186779634109234	0.0948319811392557	-1.9695848580339	0.0492844277439024	*  
df.mm.trans1:probe4	0.0176104797660835	0.0948319811392557	0.185701907252401	0.85273295096047	   
df.mm.trans1:probe5	-0.184013867293589	0.0948319811392557	-1.94041994148973	0.0527345174277859	.  
df.mm.trans1:probe6	-0.107682913635342	0.0948319811392557	-1.13551264395938	0.256553712398248	   
df.mm.trans1:probe7	-0.0124851239566554	0.0948319811392557	-0.131655205413474	0.895295285562241	   
df.mm.trans1:probe8	0.0318571187854257	0.0948319811392557	0.335932228797849	0.737023801838328	   
df.mm.trans1:probe9	-0.0815416446970015	0.0948319811392557	-0.859853856445981	0.3901673887041	   
df.mm.trans1:probe10	-0.0689260686553289	0.0948319811392557	-0.726823038254517	0.467580160247346	   
df.mm.trans1:probe11	-0.0322839372264895	0.0948319811392557	-0.340433014671309	0.733633777837583	   
df.mm.trans1:probe12	-0.0682014122046294	0.0948319811392557	-0.719181560748787	0.472271846896007	   
df.mm.trans1:probe13	-0.00433329244190716	0.0948319811392557	-0.0456944206991095	0.963566993701595	   
df.mm.trans1:probe14	-0.0376526564814906	0.0948319811392557	-0.397045975726266	0.691455982038659	   
df.mm.trans1:probe15	0.0236335307515713	0.0948319811392557	0.249214774041963	0.803268603461543	   
df.mm.trans1:probe16	-0.0481195178088239	0.0948319811392557	-0.507418670692569	0.612022758939783	   
df.mm.trans1:probe17	-0.110558176250873	0.0948319811392557	-1.16583218997106	0.244083961836269	   
df.mm.trans1:probe18	0.193342367961464	0.0948319811392557	2.03878866220828	0.0418506702399466	*  
df.mm.trans1:probe19	-0.126723185132513	0.0948319811392557	-1.33629165614949	0.181893190678229	   
df.mm.trans1:probe20	0.0289294198337442	0.0948319811392557	0.305059743413595	0.760412380701287	   
df.mm.trans1:probe21	-0.0586425658452876	0.0948319811392557	-0.618383852586335	0.536525818245427	   
df.mm.trans1:probe22	0.0292843207332761	0.0948319811392557	0.308802161269557	0.757564968528189	   
df.mm.trans2:probe2	0.0417733020076728	0.0948319811392557	0.440498041966781	0.659713995449138	   
df.mm.trans2:probe3	0.301065598928965	0.0948319811392557	3.17472645105734	0.00156627326068966	** 
df.mm.trans2:probe4	0.110632456556913	0.0948319811392557	1.16661547325955	0.243767567776489	   
df.mm.trans2:probe5	0.119618567585727	0.0948319811392557	1.26137370693620	0.207599280140988	   
df.mm.trans2:probe6	0.139513585402532	0.0948319811392557	1.47116598985382	0.141700806978572	   
df.mm.trans3:probe2	-0.0278490466727457	0.0948319811392557	-0.293667245355244	0.769100238740751	   
df.mm.trans3:probe3	0.0356086355560154	0.0948319811392557	0.375491844926513	0.70740977800007