chr14.7725_chr14_15847804_15848689_-_1.R 

fitVsDatCorrelation=0.905552389366145
cont.fitVsDatCorrelation=0.244274904586704

fstatistic=9547.22872552192,50,646
cont.fstatistic=1816.84927693078,50,646

residuals=-0.579538868381036,-0.0968949461740505,0.000468027266303795,0.0990789670342425,0.501398295440473
cont.residuals=-0.704600797318384,-0.324463482955954,-0.0365055292416532,0.281605023513623,1.10973606729247

predictedValues:
Include	Exclude	Both
chr14.7725_chr14_15847804_15848689_-_1.R.tl.Lung	119.622999484869	61.8864638796323	78.6265905027563
chr14.7725_chr14_15847804_15848689_-_1.R.tl.cerebhem	98.9289347215732	61.8689871254646	80.8605614007267
chr14.7725_chr14_15847804_15848689_-_1.R.tl.cortex	102.311532272693	59.7519940657524	123.447226820436
chr14.7725_chr14_15847804_15848689_-_1.R.tl.heart	100.563522332685	60.9550020904267	80.343404003148
chr14.7725_chr14_15847804_15848689_-_1.R.tl.kidney	137.329993371284	62.2138605383153	75.9324845901497
chr14.7725_chr14_15847804_15848689_-_1.R.tl.liver	118.902030787036	61.4046211317478	72.4058543102615
chr14.7725_chr14_15847804_15848689_-_1.R.tl.stomach	99.0022775080093	57.2007659787434	73.7409770598083
chr14.7725_chr14_15847804_15848689_-_1.R.tl.testicle	97.31330946447	63.538144965203	73.6579142585633


diffExp=57.7365356052363,37.0599475961086,42.5595382069406,39.6085202422588,75.1161328329691,57.4974096552882,41.8015115292658,33.775164499267
diffExpScore=0.997410364695319
diffExp1.5=1,1,1,1,1,1,1,1
diffExp1.5Score=0.888888888888889
diffExp1.4=1,1,1,1,1,1,1,1
diffExp1.4Score=0.888888888888889
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	70.118675688696	88.577154345384	78.4152385778683
cerebhem	77.9166123464338	78.9494034989054	74.4727840634147
cortex	81.5367698846569	100.728200771110	78.9508299540065
heart	76.8296831996625	89.1774343498214	80.9099051978084
kidney	75.1589590155331	84.2709949733412	80.3135630879849
liver	88.411632904868	86.1240058232082	81.3626936348585
stomach	88.2635317913977	77.9404466851252	82.8910901303617
testicle	79.021644628208	83.1630268466707	79.5340168117507
cont.diffExp=-18.4584786566880,-1.03279115247163,-19.1914308864530,-12.3477511501589,-9.11203595780808,2.28762708165981,10.3230851062725,-4.14138221846278
cont.diffExpScore=1.45984378707933

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

tran.correlation=0.288894162897591
cont.tran.correlation=-0.165848405768704

tran.covariance=0.00115404687469359
cont.tran.covariance=-0.00114722415140305

tran.mean=85.174652482369
cont.tran.mean=82.8867610470639

weightedLogRatios:
wLogRatio
Lung	2.93592299985658
cerebhem	2.04637273843776
cortex	2.34441714523579
heart	2.18308167968577
kidney	3.58410907513875
liver	2.93923313357592
stomach	2.37031551457645
testicle	1.86068880165224

cont.weightedLogRatios:
wLogRatio
Lung	-1.02050889631343
cerebhem	-0.0574417675435826
cortex	-0.952597397116884
heart	-0.658163559482328
kidney	-0.500850246726028
liver	0.117153754632131
stomach	0.549536541019898
testicle	-0.224514670248132

varWeightedLogRatios=0.329354798985511
cont.varWeightedLogRatios=0.294116551413034

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.82109221553632	0.0824261719399342	58.4898230995073	2.76430428454088e-260	***
df.mm.trans1	-0.0460644233295921	0.0650523147907385	-0.708113515680003	0.479130179641427	   
df.mm.trans2	-0.687858769112741	0.0650523147907385	-10.5739322470762	3.28010174024865e-24	***
df.mm.exp2	-0.218242068567789	0.0861402860608481	-2.53356563517361	0.011526163226426	*  
df.mm.exp3	-0.642525452444217	0.0861402860608481	-7.45905872648655	2.81985327405321e-13	***
df.mm.exp4	-0.210321147023471	0.0861402860608481	-2.44161189428723	0.0148891112797361	*  
df.mm.exp5	0.178183307448549	0.0861402860608481	2.06852467755544	0.0389880410916457	*  
df.mm.exp6	0.068561160454517	0.0861402860608481	0.795924457530666	0.426368315887757	   
df.mm.exp7	-0.203785159427032	0.0861402860608481	-2.36573581010726	0.0182885839587202	*  
df.mm.exp8	-0.114792054584160	0.0861402860608481	-1.33261752234109	0.18312719603078	   
df.mm.trans1:exp2	0.0282987034292608	0.0653191059914381	0.433237764046712	0.66498666462665	   
df.mm.trans2:exp2	0.217959628414374	0.0653191059914381	3.33684341060859	0.000895947372436541	***
df.mm.trans1:exp3	0.486202722572808	0.0653191059914381	7.4434993436153	3.14338484403711e-13	***
df.mm.trans2:exp3	0.607426537634415	0.0653191059914381	9.29937004517537	2.14846046218692e-19	***
df.mm.trans1:exp4	0.036765611452907	0.0653191059914382	0.562861522595336	0.573724467331278	   
df.mm.trans2:exp4	0.195155589785234	0.0653191059914381	2.98772597730922	0.00291720203049404	** 
df.mm.trans1:exp5	-0.0401416935886733	0.0653191059914381	-0.614547504583651	0.539069973884094	   
df.mm.trans2:exp5	-0.172906972841522	0.0653191059914381	-2.64711174804178	0.00831620855664516	** 
df.mm.trans1:exp6	-0.074606403527392	0.0653191059914381	-1.14218347595221	0.253800927751552	   
df.mm.trans2:exp6	-0.0763775439514039	0.0653191059914381	-1.16929867290920	0.242714580150757	   
df.mm.trans1:exp7	0.0145828880146188	0.0653191059914381	0.223256087070914	0.82340677938886	   
df.mm.trans2:exp7	0.125050970409960	0.0653191059914381	1.91446236919335	0.0560025449328545	.  
df.mm.trans1:exp8	-0.0916173040737906	0.0653191059914381	-1.40261111482144	0.161213220993507	   
df.mm.trans2:exp8	0.141131009693408	0.0653191059914381	2.16063902821797	0.0310901669669606	*  
df.mm.trans1:probe2	0.129269840607967	0.0486330387323578	2.65806628533697	0.00805355097923445	** 
df.mm.trans1:probe3	-0.00342046132536648	0.0486330387323578	-0.070332050279447	0.943951139556058	   
df.mm.trans1:probe4	0.189691279353677	0.0486330387323578	3.90046117409206	0.000106062287375465	***
df.mm.trans1:probe5	-0.142779290054858	0.0486330387323578	-2.93584965645711	0.00344460624018506	** 
df.mm.trans1:probe6	0.0415373181811315	0.0486330387323578	0.85409670593943	0.393368012927376	   
df.mm.trans2:probe2	0.114634952946665	0.0486330387323578	2.35714148107288	0.0187136161522491	*  
df.mm.trans2:probe3	-0.183713252141100	0.0486330387323578	-3.77754006185237	0.000173013690528069	***
df.mm.trans2:probe4	-0.0579499949541126	0.0486330387323578	-1.19157668253117	0.233864855351340	   
df.mm.trans2:probe5	0.0637901191049056	0.0486330387323578	1.31166221086784	0.190100086732944	   
df.mm.trans2:probe6	-0.119197086050166	0.0486330387323578	-2.45094876152287	0.0145119829997426	*  
df.mm.trans3:probe2	0.586855131977284	0.0486330387323578	12.0670052144371	2.22273403448468e-30	***
df.mm.trans3:probe3	0.738844941066833	0.0486330387323578	15.1922429756635	8.55417618496276e-45	***
df.mm.trans3:probe4	-0.0316195398133049	0.0486330387323578	-0.650165826308256	0.515816253914486	   
df.mm.trans3:probe5	0.606860408928104	0.0486330387323578	12.4783567867893	3.60903872498315e-32	***
df.mm.trans3:probe6	0.465956616957711	0.0486330387323578	9.58107140954135	2.02356800184056e-20	***
df.mm.trans3:probe7	-0.0292473351818536	0.0486330387323578	-0.601388190912981	0.547792433597471	   
df.mm.trans3:probe8	-0.0420700807234377	0.0486330387323578	-0.865051451030276	0.387331667172458	   
df.mm.trans3:probe9	0.679072760407137	0.0486330387323578	13.9631982312328	6.49707783006611e-39	***
df.mm.trans3:probe10	-0.106323485772101	0.0486330387323578	-2.18623981851578	0.0291561927073715	*  
df.mm.trans3:probe11	0.53594115711069	0.0486330387323578	11.0201042558770	5.35496786137955e-26	***
df.mm.trans3:probe12	0.0630146248064317	0.0486330387323578	1.29571637818521	0.195535991146173	   
df.mm.trans3:probe13	0.659202363523963	0.0486330387323578	13.5546200835146	5.13587504834869e-37	***
df.mm.trans3:probe14	0.462659321026384	0.0486330387323578	9.51327190498083	3.59014684513775e-20	***
df.mm.trans3:probe15	-0.0753005112200955	0.0486330387323578	-1.54834065859007	0.122030034973909	   
df.mm.trans3:probe16	0.234926996727406	0.0486330387323578	4.83060493135704	1.70164690647716e-06	***
df.mm.trans3:probe17	-0.0305777180590741	0.0486330387323578	-0.628743727640636	0.529739091613112	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.39776222445999	0.188407978270787	23.3416985035493	7.42524210733457e-88	***
df.mm.trans1	-0.161156834379130	0.148695187743152	-1.08380665726387	0.278854867388509	   
df.mm.trans2	0.0888293386216825	0.148695187743152	0.597392154849834	0.550454923554629	   
df.mm.exp2	0.0419677553669217	0.196897620772908	0.213145060880777	0.831281064502523	   
df.mm.exp3	0.272609769420007	0.196897620772908	1.38452546226763	0.166675646612388	   
df.mm.exp4	0.0668379726351536	0.196897620772908	0.339455461029878	0.734376970911493	   
df.mm.exp5	-0.00434031917019647	0.196897620772908	-0.0220435328429	0.982420036686073	   
df.mm.exp6	0.166830013820799	0.196897620772908	0.847293193111828	0.397145511200866	   
df.mm.exp7	0.0466996026301701	0.196897620772908	0.237177079371777	0.81259461143201	   
df.mm.exp8	0.0422949750397991	0.196897620772908	0.214806938112168	0.829985635551323	   
df.mm.trans1:exp2	0.0634822534570723	0.149305013355106	0.425185009066551	0.670843404245728	   
df.mm.trans2:exp2	-0.157034542851849	0.149305013355106	-1.05177005998023	0.293298324268369	   
df.mm.trans1:exp3	-0.121744860206631	0.149305013355106	-0.815410396950794	0.415137964265695	   
df.mm.trans2:exp3	-0.144057934251348	0.149305013355106	-0.964856644891898	0.334977666681246	   
df.mm.trans1:exp4	0.0245639193238145	0.149305013355106	0.164521731533501	0.86937190487725	   
df.mm.trans2:exp4	-0.0600839159239245	0.149305013355106	-0.402423968048691	0.687505157233149	   
df.mm.trans1:exp5	0.0737564698554647	0.149305013355106	0.49399861530465	0.621475080615745	   
df.mm.trans2:exp5	-0.0454959168748416	0.149305013355106	-0.304717945181348	0.760679122762762	   
df.mm.trans1:exp6	0.064984367593166	0.149305013355106	0.435245717024971	0.663529456760455	   
df.mm.trans2:exp6	-0.194915800699985	0.149305013355106	-1.30548731298392	0.192191709737761	   
df.mm.trans1:exp7	0.183438242657002	0.149305013355106	1.22861408692764	0.219663921183434	   
df.mm.trans2:exp7	-0.174628544324437	0.149305013355106	-1.16960938149546	0.242589552971755	   
df.mm.trans1:exp8	0.0772376490179974	0.149305013355106	0.517314504599359	0.605113711379911	   
df.mm.trans2:exp8	-0.105366087574112	0.149305013355106	-0.70571031210794	0.480622708543908	   
df.mm.trans1:probe2	0.0844037983539681	0.111164358225997	0.759270324597886	0.44796782501011	   
df.mm.trans1:probe3	0.155198710210059	0.111164358225997	1.39611933794950	0.163158131060458	   
df.mm.trans1:probe4	0.0353341116610394	0.111164358225997	0.317854681346743	0.75069788807377	   
df.mm.trans1:probe5	-0.0111765322962292	0.111164358225997	-0.100540609189749	0.919946339122092	   
df.mm.trans1:probe6	0.0486669311342054	0.111164358225997	0.437792579481867	0.661682986724636	   
df.mm.trans2:probe2	-0.145304808439159	0.111164358225997	-1.30711687413114	0.191638088336754	   
df.mm.trans2:probe3	0.147381852007068	0.111164358225997	1.32580131221053	0.185374133440682	   
df.mm.trans2:probe4	0.00190349877951966	0.111164358225997	0.0171232831268621	0.986343551442633	   
df.mm.trans2:probe5	-0.089944558760613	0.111164358225997	-0.809113282314428	0.418747885397532	   
df.mm.trans2:probe6	0.0234594383098858	0.111164358225997	0.211033812314131	0.832927439643852	   
df.mm.trans3:probe2	-0.0631131357778931	0.111164358225997	-0.567746144403447	0.57040461317882	   
df.mm.trans3:probe3	0.075105167664258	0.111164358225997	0.675622734326137	0.49952197645239	   
df.mm.trans3:probe4	0.152999693640164	0.111164358225997	1.37633766867179	0.169193993735291	   
df.mm.trans3:probe5	0.0425129427298100	0.111164358225997	0.382433213381049	0.702265844085817	   
df.mm.trans3:probe6	0.110684054763018	0.111164358225997	0.995679339397595	0.319778773617950	   
df.mm.trans3:probe7	0.102402713970495	0.111164358225997	0.921182972714248	0.357298786125894	   
df.mm.trans3:probe8	-0.04111128718527	0.111164358225997	-0.369824355947713	0.711634571985693	   
df.mm.trans3:probe9	0.121610129919041	0.111164358225997	1.09396691403380	0.274377230249541	   
df.mm.trans3:probe10	-0.00282141249092828	0.111164358225997	-0.0253805494490632	0.97975926338165	   
df.mm.trans3:probe11	-0.0194984835586778	0.111164358225997	-0.175402295032707	0.860818501084997	   
df.mm.trans3:probe12	-0.0724920219861863	0.111164358225997	-0.652115688364884	0.51455849747517	   
df.mm.trans3:probe13	0.0853426289400986	0.111164358225997	0.767715752620974	0.442936590987015	   
df.mm.trans3:probe14	-0.0430925725320663	0.111164358225997	-0.387647382846032	0.698404689496052	   
df.mm.trans3:probe15	0.0938827974790865	0.111164358225997	0.844540453228931	0.398680119444962	   
df.mm.trans3:probe16	0.0160520398532495	0.111164358225997	0.144399159131704	0.885230316934907	   
df.mm.trans3:probe17	0.0634570840685534	0.111164358225997	0.570840196275369	0.56830648544266