chr2.14234_chr2_175576482_175583978_+_2.R 

fitVsDatCorrelation=0.935023316666302
cont.fitVsDatCorrelation=0.245611479694363

fstatistic=4343.94895332096,56,784
cont.fstatistic=569.106936561321,56,784

residuals=-1.48093650717427,-0.151124461291322,0.0206688165693018,0.171631288804003,1.9386244467321
cont.residuals=-1.99889389772698,-0.653142291848936,-0.0486360941099127,0.506318576284951,2.72053755903699

predictedValues:
Include	Exclude	Both
chr2.14234_chr2_175576482_175583978_+_2.R.tl.Lung	325.760513549937	107.011839446103	361.931290498744
chr2.14234_chr2_175576482_175583978_+_2.R.tl.cerebhem	491.942648486184	58.6465256108882	513.153206422261
chr2.14234_chr2_175576482_175583978_+_2.R.tl.cortex	718.799389746967	66.4003900277567	609.433572665934
chr2.14234_chr2_175576482_175583978_+_2.R.tl.heart	299.650390673314	191.129263018210	332.328127449788
chr2.14234_chr2_175576482_175583978_+_2.R.tl.kidney	203.713874548972	117.603746787306	236.238098666249
chr2.14234_chr2_175576482_175583978_+_2.R.tl.liver	171.81627695725	76.033980896271	147.015358841143
chr2.14234_chr2_175576482_175583978_+_2.R.tl.stomach	268.86252604709	100.400733571251	229.166855832931
chr2.14234_chr2_175576482_175583978_+_2.R.tl.testicle	237.261882610056	76.3677174817781	222.28802148043


diffExp=218.748674103834,433.296122875295,652.39899971921,108.521127655103,86.1101277616658,95.7822960609791,168.461792475839,160.894165128278
diffExpScore=0.999480577036842
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	239.525947271339	290.200595110424	324.88602686522
cerebhem	214.096741515095	231.001588156397	288.615508644485
cortex	256.291663501204	267.446014338426	275.65280247971
heart	261.555654174473	231.035290576031	239.334395430995
kidney	265.075070085120	242.422185627907	249.111513796657
liver	230.116450805596	180.354422064403	208.981788171333
stomach	223.457985444868	233.628850530599	258.47262061036
testicle	330.184211766259	290.539425597889	355.571777378857
cont.diffExp=-50.6746478390843,-16.9048466413017,-11.1543508372217,30.520363598442,22.6528844572132,49.7620287411933,-10.1708650857306,39.6447861683699
cont.diffExpScore=4.23380485944866

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

tran.correlation=-0.347371036615425
cont.tran.correlation=0.558342868450641

tran.covariance=-0.0645650828324293
cont.tran.covariance=0.0112891739861389

tran.mean=219.462606216208
cont.tran.mean=249.183256035377

weightedLogRatios:
wLogRatio
Lung	5.82165650300619
cerebhem	10.9211751319120
cortex	12.8303329555910
heart	2.46317538994049
kidney	2.7700625576904
liver	3.86328734921891
stomach	5.02531609872283
testicle	5.55733975836783

cont.weightedLogRatios:
wLogRatio
Lung	-1.06982833436089
cerebhem	-0.41071807421591
cortex	-0.237189521989927
heart	0.682993227711042
kidney	0.494485240483589
liver	1.29548875811382
stomach	-0.241756933925116
testicle	0.733660965308017

varWeightedLogRatios=14.1943278693772
cont.varWeightedLogRatios=0.594436272426094

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	5.7943055081465	0.153156558971826	37.8325652328895	5.14399104572527e-179	***
df.mm.trans1	0.0361887317013511	0.131626091635373	0.274935852396197	0.78343795793048	   
df.mm.trans2	-1.17877610117962	0.117254925657814	-10.0531051857016	1.90235295356293e-22	***
df.mm.exp2	-0.538331552226397	0.151297543312434	-3.55809843597214	0.000396007506642914	***
df.mm.exp3	-0.206892299281449	0.151297543312434	-1.36745313077695	0.171875204114234	   
df.mm.exp4	0.58179600381306	0.151297543312434	3.84537640913068	0.000130131731747890	***
df.mm.exp5	0.0515495606786666	0.151297543312434	0.340716442250587	0.733408338505908	   
df.mm.exp6	-0.0805785363156434	0.151297543312434	-0.532583243266855	0.594473013232155	   
df.mm.exp7	0.201271761574452	0.151297543312434	1.33030422813159	0.183804883415576	   
df.mm.exp8	-0.166896932415511	0.151297543312434	-1.10310404757111	0.270320464992523	   
df.mm.trans1:exp2	0.950531203418596	0.138266820511262	6.87461532639477	1.26912933503373e-11	***
df.mm.trans2:exp2	-0.0630795911696423	0.104605810443036	-0.603021867547147	0.546668538582948	   
df.mm.trans1:exp3	0.998312114813849	0.138266820511262	7.2201856607568	1.22922293292572e-12	***
df.mm.trans2:exp3	-0.270344247711174	0.104605810443036	-2.58440947559402	0.00993427400030462	** 
df.mm.trans1:exp4	-0.665342063532281	0.138266820511262	-4.81201535604913	1.79241179338282e-06	***
df.mm.trans2:exp4	-0.00178551231269838	0.104605810443036	-0.0170689592206802	0.986385945008702	   
df.mm.trans1:exp5	-0.520995617492836	0.138266820511262	-3.76804511426804	0.000176865220856737	***
df.mm.trans2:exp5	0.0428318573448444	0.104605810443036	0.40945963865142	0.682314222617978	   
df.mm.trans1:exp6	-0.559158205370694	0.138266820511262	-4.04405195189362	5.77265032805108e-05	***
df.mm.trans2:exp6	-0.261180583638632	0.104605810443036	-2.49680761070974	0.0127358477444240	*  
df.mm.trans1:exp7	-0.39323405858106	0.138266820511262	-2.84402329587836	0.00457074890467501	** 
df.mm.trans2:exp7	-0.265041725226713	0.104605810443036	-2.53371895981862	0.0114796251932224	*  
df.mm.trans1:exp8	-0.150101036973510	0.138266820511262	-1.08558970560319	0.277994239160045	   
df.mm.trans2:exp8	-0.170482484129534	0.104605810443036	-1.62976113284235	0.103553670387975	   
df.mm.trans1:probe2	-0.28301888894132	0.0946648206856702	-2.98969444923019	0.00287988959688759	** 
df.mm.trans1:probe3	-0.130960185220926	0.0946648206856702	-1.38340921445119	0.166933212921034	   
df.mm.trans1:probe4	-0.0131175220776848	0.0946648206856703	-0.138568076109718	0.889827054853272	   
df.mm.trans1:probe5	-0.38856988828917	0.0946648206856703	-4.10469153667334	4.4728212892931e-05	***
df.mm.trans1:probe6	-0.167838484366725	0.0946648206856703	-1.77297630895034	0.0766208429752436	.  
df.mm.trans1:probe7	-0.442442943101042	0.0946648206856703	-4.67378419878015	3.48014730789521e-06	***
df.mm.trans1:probe8	-0.663227160180222	0.0946648206856703	-7.00605732284049	5.28220204593514e-12	***
df.mm.trans1:probe9	-0.330269769717376	0.0946648206856702	-3.488833204618	0.000512192142727567	***
df.mm.trans1:probe10	0.191330642309433	0.0946648206856703	2.0211377460349	0.0436048947577417	*  
df.mm.trans1:probe11	-0.287151567898805	0.0946648206856702	-3.03335035992174	0.00249833433806196	** 
df.mm.trans1:probe12	-0.0610176133922589	0.0946648206856702	-0.644564823028237	0.519397781420043	   
df.mm.trans1:probe13	0.119082076545496	0.0946648206856703	1.25793378873977	0.208790230105261	   
df.mm.trans1:probe14	0.302004065007933	0.0946648206856703	3.19024599445154	0.00147808728352548	** 
df.mm.trans1:probe15	-0.0556954059052233	0.0946648206856703	-0.588343225094749	0.556471382783624	   
df.mm.trans1:probe16	0.334850719183787	0.0946648206856702	3.53722445950267	0.000428125506195566	***
df.mm.trans1:probe17	0.290657901323315	0.0946648206856703	3.07038981554119	0.00221156465473865	** 
df.mm.trans1:probe18	0.132141085992023	0.0946648206856702	1.39588376162239	0.163144658124786	   
df.mm.trans1:probe19	0.167622204393204	0.0946648206856703	1.77069161679168	0.0770005178417208	.  
df.mm.trans2:probe2	0.16825242840164	0.0946648206856702	1.77734904247391	0.0758984377893805	.  
df.mm.trans2:probe3	0.228659554475927	0.0946648206856702	2.41546493005231	0.0159428680463634	*  
df.mm.trans2:probe4	0.225642369002564	0.0946648206856702	2.38359263101336	0.0173816808820076	*  
df.mm.trans2:probe5	0.137520162324615	0.0946648206856702	1.45270609851197	0.146705475443146	   
df.mm.trans2:probe6	0.158486612241262	0.0946648206856702	1.67418700097165	0.0944926984726813	.  
df.mm.trans3:probe2	2.43768533325181	0.0946648206856703	25.7506993157049	1.90587713590090e-106	***
df.mm.trans3:probe3	-0.288277688512555	0.0946648206856703	-3.04524623217496	0.00240271665131498	** 
df.mm.trans3:probe4	2.22634390831952	0.0946648206856703	23.5181759411131	5.76247985956737e-93	***
df.mm.trans3:probe5	0.193768252017807	0.0946648206856703	2.04688764648068	0.0410020363857164	*  
df.mm.trans3:probe6	1.56259217666569	0.0946648206856703	16.5065772622566	9.28311229427153e-53	***
df.mm.trans3:probe7	1.73315250686171	0.0946648206856702	18.3083060244370	1.30660666254527e-62	***
df.mm.trans3:probe8	2.019276875935	0.0946648206856703	21.3308054809495	5.73748812807056e-80	***
df.mm.trans3:probe9	0.133547418649913	0.0946648206856702	1.41073967797764	0.158718042976315	   
df.mm.trans3:probe10	2.37927371571264	0.0946648206856703	25.1336631546887	1.04770970944843e-102	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	5.39911700381561	0.41869961915852	12.8949651654006	1.21515830849984e-34	***
df.mm.trans1	0.155967542126906	0.359839596874158	0.433436296288012	0.664817065379973	   
df.mm.trans2	0.278259659992801	0.32055168284643	0.868064885892706	0.385624443125126	   
df.mm.exp2	-0.222002527944602	0.413617439499858	-0.536733964150652	0.591603664308916	   
df.mm.exp3	0.150332017929414	0.413617439499858	0.363456671728333	0.716361754403269	   
df.mm.exp4	0.165596134134401	0.413617439499858	0.40036061906538	0.688999993160906	   
df.mm.exp5	0.187033494096908	0.413617439499858	0.45218957479904	0.65125750106405	   
df.mm.exp6	-0.0744974023945057	0.413617439499858	-0.180111850420493	0.85711130262834	   
df.mm.exp7	-0.0575923200331948	0.413617439499858	-0.139240550647078	0.889295825099513	   
df.mm.exp8	0.231903158124336	0.413617439499858	0.560670648715273	0.575182268494587	   
df.mm.trans1:exp2	0.109768753651119	0.37799403093781	0.290398113903493	0.771588481547561	   
df.mm.trans2:exp2	-0.00614527755994553	0.285971513647838	-0.021489124848684	0.982860946387175	   
df.mm.trans1:exp3	-0.0826776617402288	0.377994030937810	-0.218727426819688	0.826919307663728	   
df.mm.trans2:exp3	-0.231986678656763	0.285971513647838	-0.81122303301316	0.417483802753693	   
df.mm.trans1:exp4	-0.077610796923004	0.377994030937810	-0.205322810866749	0.837373220930546	   
df.mm.trans2:exp4	-0.393598053363436	0.285971513647838	-1.37635405828615	0.169105010199842	   
df.mm.trans1:exp5	-0.085682175207981	0.37799403093781	-0.226676000664354	0.820734778261861	   
df.mm.trans2:exp5	-0.366925110360915	0.285971513647838	-1.28308272974618	0.199842252689966	   
df.mm.trans1:exp6	0.0344211407173262	0.377994030937810	0.091062656814783	0.92746606543435	   
df.mm.trans2:exp6	-0.401151062347213	0.285971513647838	-1.40276581128711	0.161082554523827	   
df.mm.trans1:exp7	-0.0118460184914392	0.377994030937810	-0.0313391681399016	0.97500703026271	   
df.mm.trans2:exp7	-0.159246323793619	0.285971513647838	-0.556860792749182	0.577781467102023	   
df.mm.trans1:exp8	0.0890858077440631	0.377994030937809	0.235680461733853	0.813742182516057	   
df.mm.trans2:exp8	-0.230736265835773	0.285971513647838	-0.806850524699166	0.419997300598945	   
df.mm.trans1:probe2	-0.0461594478612342	0.25879482168368	-0.178363104643778	0.858483900612125	   
df.mm.trans1:probe3	-0.154570537121081	0.25879482168368	-0.597270594965804	0.550499186629173	   
df.mm.trans1:probe4	-0.235771800853999	0.25879482168368	-0.911037552143058	0.362555608236192	   
df.mm.trans1:probe5	-0.394637085043774	0.25879482168368	-1.52490332873094	0.127686484809444	   
df.mm.trans1:probe6	-0.0683678023189819	0.25879482168368	-0.264177628726075	0.791712475965899	   
df.mm.trans1:probe7	-0.206208769068871	0.25879482168368	-0.796804077173212	0.425806052525778	   
df.mm.trans1:probe8	-0.392801334212894	0.25879482168368	-1.51780986828634	0.129465453531809	   
df.mm.trans1:probe9	0.056996195985345	0.25879482168368	0.220237003254302	0.82574391463831	   
df.mm.trans1:probe10	-0.0249447342958837	0.25879482168368	-0.0963880735077966	0.923236996925412	   
df.mm.trans1:probe11	-0.318474281036533	0.25879482168368	-1.23060530718732	0.218839599779373	   
df.mm.trans1:probe12	-0.0912788793309057	0.25879482168368	-0.352707518400326	0.724402522736113	   
df.mm.trans1:probe13	-0.359762930850764	0.25879482168368	-1.39014733181368	0.164878682033206	   
df.mm.trans1:probe14	-0.0185157977186575	0.25879482168368	-0.0715462450067453	0.942981267457284	   
df.mm.trans1:probe15	0.110289385949098	0.25879482168368	0.426165350726773	0.670104340580949	   
df.mm.trans1:probe16	-0.0970412744437546	0.25879482168368	-0.374973787390407	0.70778137362403	   
df.mm.trans1:probe17	0.273066526403490	0.25879482168368	1.05514679400059	0.291683239268041	   
df.mm.trans1:probe18	-0.211283448185874	0.25879482168368	-0.816412966887421	0.414511972328331	   
df.mm.trans1:probe19	-0.0367950590413581	0.25879482168368	-0.142178498016208	0.886975543647818	   
df.mm.trans2:probe2	-0.168062036546152	0.25879482168368	-0.649402625032316	0.516268370796559	   
df.mm.trans2:probe3	0.209443981087289	0.25879482168368	0.809305146543033	0.418585187659058	   
df.mm.trans2:probe4	0.0505408288214056	0.25879482168368	0.195293045249494	0.845214141663981	   
df.mm.trans2:probe5	-0.0959410191302488	0.25879482168368	-0.370722329396203	0.710944499617203	   
df.mm.trans2:probe6	-0.104850116948920	0.25879482168368	-0.405147662023457	0.685479499042856	   
df.mm.trans3:probe2	-0.138111469090624	0.25879482168368	-0.533671687061168	0.593719967430254	   
df.mm.trans3:probe3	0.138168179656118	0.25879482168368	0.533890820369652	0.593568411760145	   
df.mm.trans3:probe4	0.0607147964088387	0.25879482168368	0.234605916817954	0.814575872652732	   
df.mm.trans3:probe5	-0.157793379099093	0.25879482168368	-0.609723865696049	0.54222140864054	   
df.mm.trans3:probe6	0.0472526068376494	0.25879482168368	0.182587141930550	0.855169176637045	   
df.mm.trans3:probe7	0.10582905900865	0.25879482168368	0.408930357725638	0.682702449917916	   
df.mm.trans3:probe8	0.00233933025648030	0.25879482168368	0.00903932405316678	0.992790060694164	   
df.mm.trans3:probe9	-0.390741035467646	0.25879482168368	-1.50984874011599	0.131484926042433	   
df.mm.trans3:probe10	-0.166355805300892	0.25879482168368	-0.642809636678998	0.520535572408135