chr8.23778_chr8_112494273_112541020_+_2.R 

fitVsDatCorrelation=0.791361723271223
cont.fitVsDatCorrelation=0.245594563228770

fstatistic=8449.34960801038,53,715
cont.fstatistic=3352.49231368015,53,715

residuals=-0.549664875612731,-0.0891633000705181,-0.00733621351074939,0.076789653479553,0.841042286101451
cont.residuals=-0.59869003123067,-0.165831768791928,-0.0517026520085209,0.110615026378599,1.55870793813201

predictedValues:
Include	Exclude	Both
chr8.23778_chr8_112494273_112541020_+_2.R.tl.Lung	51.6287525187594	51.8235075505715	57.6570116306622
chr8.23778_chr8_112494273_112541020_+_2.R.tl.cerebhem	61.5175047327588	73.5669964306249	85.0224857894827
chr8.23778_chr8_112494273_112541020_+_2.R.tl.cortex	48.1963266106283	57.6202045404181	67.2752739584646
chr8.23778_chr8_112494273_112541020_+_2.R.tl.heart	50.0428562071927	51.5689752671541	52.6157526499425
chr8.23778_chr8_112494273_112541020_+_2.R.tl.kidney	49.8342586753422	50.8499498263776	60.2848288123463
chr8.23778_chr8_112494273_112541020_+_2.R.tl.liver	50.4477188522961	51.704086598569	55.2568379863425
chr8.23778_chr8_112494273_112541020_+_2.R.tl.stomach	49.7915833809423	54.3524994469881	58.6041765496232
chr8.23778_chr8_112494273_112541020_+_2.R.tl.testicle	51.4058364735911	58.2891148526838	52.3474696026168


diffExp=-0.194755031812093,-12.0494916978661,-9.42387792978978,-1.52611905996134,-1.01569115103538,-1.25636774627289,-4.56091606604576,-6.8832783790927
diffExpScore=0.973622081547287
diffExp1.5=0,0,0,0,0,0,0,0
diffExp1.5Score=0
diffExp1.4=0,0,0,0,0,0,0,0
diffExp1.4Score=0
diffExp1.3=0,0,0,0,0,0,0,0
diffExp1.3Score=0
diffExp1.2=0,0,0,0,0,0,0,0
diffExp1.2Score=0

cont.predictedValues:
Include	Exclude	Both
Lung	55.3230744519265	53.081710599657	55.7264121485783
cerebhem	56.0864832826881	52.433752254103	51.3161878947447
cortex	54.9465747785064	60.1871031252788	51.0823486540512
heart	55.3824103950325	55.2202940794802	52.2420278725998
kidney	52.8144701052821	57.2826033640322	54.0926720414605
liver	53.605537600676	53.1713766799835	51.23460105493
stomach	54.5362523653005	51.0970108047882	53.6004716515956
testicle	50.4996461803352	50.7852046916404	57.2122716329195
cont.diffExp=2.24136385226948,3.65273102858511,-5.24052834677246,0.162116315552296,-4.46813325875006,0.434160920692513,3.43924156051234,-0.285558511305219
cont.diffExpScore=18.7147410165129

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=0.875226375416953
cont.tran.correlation=0.220400699333358

tran.covariance=0.00778839125303765
cont.tran.covariance=0.000466343987491447

tran.mean=53.9150107478061
cont.tran.mean=54.1533440474194

weightedLogRatios:
wLogRatio
Lung	-0.0148570311665169
cerebhem	-0.752840708685328
cortex	-0.70803586682219
heart	-0.117995980560868
kidney	-0.0790673399561714
liver	-0.0967548540646887
stomach	-0.346342540570969
testicle	-0.502979259735563

cont.weightedLogRatios:
wLogRatio
Lung	0.165120864331502
cerebhem	0.268920917099472
cortex	-0.36911580715104
heart	0.0117635498705773
kidney	-0.325447296316273
liver	0.0323463560973056
stomach	0.258363173811434
testicle	-0.0221308304452532

varWeightedLogRatios=0.0876385409720824
cont.varWeightedLogRatios=0.0585889491015881

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.90605401783598	0.0843371697761561	46.3147391381908	1.98365215480402e-217	***
df.mm.trans1	-0.0735833707840544	0.074893038962592	-0.982512818324922	0.326179608288053	   
df.mm.trans2	0.042066204357427	0.0681249580604963	0.617485948689633	0.537110846873177	   
df.mm.exp2	0.137191777758317	0.0918425670316836	1.49377115854121	0.135676593502766	   
df.mm.exp3	-0.117047415854696	0.0918425670316836	-1.27443536954185	0.202923199495393	   
df.mm.exp4	0.0553737114014499	0.0918425670316836	0.60291990077267	0.54675316096571	   
df.mm.exp5	-0.098909401657294	0.0918425670316836	-1.07694509043037	0.28186802160251	   
df.mm.exp6	0.0170715221662399	0.0918425670316836	0.185878103345594	0.852593073712021	   
df.mm.exp7	-0.00488013764700628	0.0918425670316836	-0.0531359020629589	0.957638468300944	   
df.mm.exp8	0.209852749539696	0.0918425670316836	2.28491816291787	0.0226096648435398	*  
df.mm.trans1:exp2	0.0380512497014731	0.0872088262136492	0.436323378648084	0.662733837953045	   
df.mm.trans2:exp2	0.213160869304174	0.073436403582585	2.90265942918157	0.00381397042317578	** 
df.mm.trans1:exp3	0.0482514859550011	0.0872088262136493	0.553286726240206	0.58024004499192	   
df.mm.trans2:exp3	0.223076835280396	0.073436403582585	3.03768736481667	0.00247078098345788	** 
df.mm.trans1:exp4	-0.0865726856048458	0.0872088262136493	-0.992705547862266	0.321189296685685	   
df.mm.trans2:exp4	-0.0602973342931621	0.073436403582585	-0.821082342701506	0.411873042404517	   
df.mm.trans1:exp5	0.0635333377292324	0.0872088262136492	0.728519583253932	0.466534118723256	   
df.mm.trans2:exp5	0.0799446774120723	0.073436403582585	1.08862462637033	0.276686246891516	   
df.mm.trans1:exp6	-0.0402127290531463	0.0872088262136493	-0.461108477192788	0.644861010171022	   
df.mm.trans2:exp6	-0.0193785593566892	0.073436403582585	-0.263882194814953	0.791946731815358	   
df.mm.trans1:exp7	-0.0313526376749923	0.0872088262136493	-0.359512208066908	0.71931809844645	   
df.mm.trans2:exp7	0.0525268781011385	0.073436403582585	0.715270295638428	0.474675531752839	   
df.mm.trans1:exp8	-0.214179770109292	0.0872088262136492	-2.45594143859456	0.0142884266044614	*  
df.mm.trans2:exp8	-0.0922812428727185	0.073436403582585	-1.25661440880531	0.209303674169617	   
df.mm.trans1:probe2	-0.0376147222615569	0.0477662413307635	-0.78747502867326	0.431264800968308	   
df.mm.trans1:probe3	-0.062731106711059	0.0477662413307635	-1.31329376068486	0.189505268976121	   
df.mm.trans1:probe4	0.00975992069660006	0.0477662413307635	0.204326746771140	0.838156315747135	   
df.mm.trans1:probe5	-0.0657215647126921	0.0477662413307635	-1.37589985901538	0.169283455349902	   
df.mm.trans1:probe6	0.132761936918173	0.0477662413307635	2.77940933218601	0.0055888315320833	** 
df.mm.trans1:probe7	0.0627662543938703	0.0477662413307635	1.31402958753311	0.189257664004006	   
df.mm.trans1:probe8	0.0681971511249818	0.0477662413307635	1.4277269725441	0.153807066048547	   
df.mm.trans1:probe9	0.368476101489459	0.0477662413307635	7.71415315971584	4.09712934056421e-14	***
df.mm.trans1:probe10	0.140068018949659	0.0477662413307635	2.93236426077027	0.00347140124344364	** 
df.mm.trans1:probe11	0.708771451645171	0.0477662413307635	14.8383341853756	1.27867754514833e-43	***
df.mm.trans1:probe12	0.35032377976443	0.0477662413307635	7.33412908373024	6.063732749683e-13	***
df.mm.trans1:probe13	0.291701340093337	0.0477662413307635	6.10685144919428	1.66726882549343e-09	***
df.mm.trans1:probe14	0.250620484767541	0.0477662413307635	5.246811927949	2.04143920793134e-07	***
df.mm.trans1:probe15	0.188012174240616	0.0477662413307635	3.9360889406956	9.09123733073638e-05	***
df.mm.trans1:probe16	0.204300150521774	0.0477662413307635	4.27708240862143	2.15096261238776e-05	***
df.mm.trans1:probe17	0.111670124037951	0.0477662413307635	2.33784616345835	0.019670111470322	*  
df.mm.trans1:probe18	-0.0490502893319849	0.0477662413307635	-1.02688191420233	0.304823339247254	   
df.mm.trans1:probe19	0.0913536640765088	0.0477662413307635	1.91251523107959	0.0562094058906168	.  
df.mm.trans1:probe20	0.116993946313471	0.0477662413307635	2.44930191394654	0.0145522763141680	*  
df.mm.trans1:probe21	0.050434920484703	0.0477662413307635	1.05586956560931	0.291384442185258	   
df.mm.trans1:probe22	-0.0292834068401297	0.0477662413307635	-0.61305654420981	0.540033903081934	   
df.mm.trans2:probe2	-0.0558232312001313	0.0477662413307635	-1.16867540013408	0.242923932874875	   
df.mm.trans2:probe3	0.291560717341196	0.0477662413307635	6.10390747143461	1.69673484593725e-09	***
df.mm.trans2:probe4	-0.104792079657077	0.0477662413307635	-2.19385232619479	0.02856715937818	*  
df.mm.trans2:probe5	-0.108759103749596	0.0477662413307635	-2.27690311650188	0.0230866390992071	*  
df.mm.trans2:probe6	-0.0249499242611013	0.0477662413307635	-0.522333840092888	0.601599701967467	   
df.mm.trans3:probe2	-0.0720421008070654	0.0477662413307635	-1.50822209995969	0.131939410662954	   
df.mm.trans3:probe3	0.484687833280214	0.0477662413307635	10.1470791876616	1.07804684021658e-22	***
df.mm.trans3:probe4	0.307254315657281	0.0477662413307635	6.4324574657164	2.29767450659303e-10	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.90430553440749	0.133727627841245	29.1959529787106	5.54177730601467e-124	***
df.mm.trans1	0.108417657231453	0.118752721592050	0.912969873683392	0.361566121547291	   
df.mm.trans2	0.0589093133611807	0.108021042944579	0.54535034800029	0.585682659895785	   
df.mm.exp2	0.0838708023845322	0.145628418129226	0.57592332226055	0.564848234441621	   
df.mm.exp3	0.205812134567654	0.145628418129226	1.41326903918591	0.158011819878244	   
df.mm.exp4	0.105136974466315	0.145628418129226	0.721953694319606	0.470558982101163	   
df.mm.exp5	0.0595151585617327	0.145628418129226	0.408678191566436	0.682898211181839	   
df.mm.exp6	0.0541891933026299	0.145628418129226	0.372105898002299	0.709924262544537	   
df.mm.exp7	-0.0135345038912045	0.145628418129226	-0.0929386177854	0.92597836068526	   
df.mm.exp8	-0.161765315009277	0.145628418129226	-1.11080870813094	0.267024100792879	   
df.mm.trans1:exp2	-0.0701660396172936	0.138281015207459	-0.507416289300636	0.612019229186079	   
df.mm.trans2:exp2	-0.0961527271972885	0.116443035429769	-0.82574906126766	0.409221888760123	   
df.mm.trans1:exp3	-0.212640870110257	0.138281015207459	-1.53774449653294	0.124553496562107	   
df.mm.trans2:exp3	-0.0801864747692744	0.116443035429769	-0.688632638897823	0.491277850860296	   
df.mm.trans1:exp4	-0.104065014050444	0.138281015207459	-0.752561831386025	0.451960947333892	   
df.mm.trans2:exp4	-0.0656388781469392	0.116443035429769	-0.563699476784324	0.573135422545284	   
df.mm.trans1:exp5	-0.105920031399703	0.138281015207459	-0.765976668892646	0.443942975739805	   
df.mm.trans2:exp5	0.0166493770832091	0.116443035429769	0.142983021884989	0.886343873855127	   
df.mm.trans1:exp6	-0.0857268981451418	0.138281015207459	-0.619946982718693	0.53549021032866	   
df.mm.trans2:exp6	-0.0525014098432032	0.116443035429769	-0.450876341804648	0.652215375277835	   
df.mm.trans1:exp7	-0.000789915587990062	0.138281015207459	-0.00571239361242016	0.995443787513453	   
df.mm.trans2:exp7	-0.0245719333467311	0.116443035429769	-0.211021064987192	0.832930961398694	   
df.mm.trans1:exp8	0.0705415639078004	0.138281015207459	0.510131949797802	0.610116458921623	   
df.mm.trans2:exp8	0.117537945180039	0.116443035429769	1.00940296468766	0.313122884615346	   
df.mm.trans1:probe2	0.0962800607417658	0.07573963130384	1.27119790635797	0.204071637666464	   
df.mm.trans1:probe3	-0.0520013249461748	0.07573963130384	-0.686580117317501	0.492569957991707	   
df.mm.trans1:probe4	0.0596171415378306	0.07573963130384	0.787132713898066	0.431465011005511	   
df.mm.trans1:probe5	0.068889016012587	0.07573963130384	0.909550453661825	0.363366132740217	   
df.mm.trans1:probe6	0.0236292105585388	0.07573963130384	0.311979476949748	0.755147074229584	   
df.mm.trans1:probe7	-0.0217260258331143	0.07573963130384	-0.286851486587745	0.774309142445669	   
df.mm.trans1:probe8	-0.0284971850506265	0.07573963130384	-0.376251964263017	0.706841203211031	   
df.mm.trans1:probe9	0.00372015994927273	0.07573963130384	0.0491177456931205	0.960839178449475	   
df.mm.trans1:probe10	-0.0155363427273482	0.07573963130384	-0.205128312085676	0.837530259602488	   
df.mm.trans1:probe11	-0.0597308963756453	0.0757396313038401	-0.788634633512098	0.430586982833896	   
df.mm.trans1:probe12	0.0161677773681496	0.07573963130384	0.213465224081832	0.831024963834878	   
df.mm.trans1:probe13	0.0277305741934276	0.07573963130384	0.366130303462695	0.714376151289025	   
df.mm.trans1:probe14	-0.0408072789447992	0.07573963130384	-0.538783702036985	0.590203814190272	   
df.mm.trans1:probe15	0.0297828474848032	0.07573963130384	0.393226729152208	0.694269247939341	   
df.mm.trans1:probe16	-0.0973533870820953	0.07573963130384	-1.28536917075221	0.199079486149404	   
df.mm.trans1:probe17	0.0147873943453552	0.07573963130384	0.195239851195387	0.845260649476041	   
df.mm.trans1:probe18	-0.0769846276951336	0.07573963130384	-1.01643784594487	0.309764746315142	   
df.mm.trans1:probe19	0.09811725170394	0.07573963130384	1.29545457265733	0.195581545706397	   
df.mm.trans1:probe20	0.0557304316008068	0.07573963130384	0.735815987501133	0.462084001260139	   
df.mm.trans1:probe21	-0.0475161191278131	0.07573963130384	-0.627361373561426	0.530622668202998	   
df.mm.trans1:probe22	-0.0421595535918486	0.07573963130384	-0.556637956457957	0.577948989991021	   
df.mm.trans2:probe2	-0.0453921439512656	0.07573963130384	-0.599318258748431	0.549150524129409	   
df.mm.trans2:probe3	0.0901401960125071	0.07573963130384	1.19013249022691	0.234389330879681	   
df.mm.trans2:probe4	-0.061968763310654	0.07573963130384	-0.818181475719861	0.413526152526148	   
df.mm.trans2:probe5	0.0417386254380062	0.07573963130384	0.55108038842394	0.58175072348207	   
df.mm.trans2:probe6	0.0616579657816925	0.07573963130384	0.81407797635485	0.415871314502780	   
df.mm.trans3:probe2	-0.0774357013758313	0.07573963130384	-1.02239342920996	0.306940518094795	   
df.mm.trans3:probe3	-0.0761158084785699	0.07573963130384	-1.00496671515631	0.315252855402909	   
df.mm.trans3:probe4	-0.0511616288099699	0.07573963130384	-0.675493502268685	0.499580676299353