chr3.15382_chr3_89759825_89761450_-_2.R 

fitVsDatCorrelation=0.883887829939503
cont.fitVsDatCorrelation=0.281951687875371

fstatistic=6890.08553547222,38,370
cont.fstatistic=1629.89131965394,38,370

residuals=-0.781074558806573,-0.0844411180868742,-0.00630953430006147,0.08495924934175,0.750575390166856
cont.residuals=-0.479640847817771,-0.215814818963612,-0.0973571707402651,0.138479391320135,1.31935775305039

predictedValues:
Include	Exclude	Both
chr3.15382_chr3_89759825_89761450_-_2.R.tl.Lung	54.0695094107936	50.4346738664229	71.4612695411034
chr3.15382_chr3_89759825_89761450_-_2.R.tl.cerebhem	61.6832430768603	62.3594915681239	75.3416603270673
chr3.15382_chr3_89759825_89761450_-_2.R.tl.cortex	54.185262659283	48.5589255909916	109.611698289710
chr3.15382_chr3_89759825_89761450_-_2.R.tl.heart	53.9734317359673	50.1381465006116	119.269936348388
chr3.15382_chr3_89759825_89761450_-_2.R.tl.kidney	53.9771189015538	51.7771572684673	87.3316724436266
chr3.15382_chr3_89759825_89761450_-_2.R.tl.liver	52.0862406640434	54.9370233871978	73.7216883291465
chr3.15382_chr3_89759825_89761450_-_2.R.tl.stomach	54.7804137207787	53.0253116565544	85.2350958893694
chr3.15382_chr3_89759825_89761450_-_2.R.tl.testicle	54.932406059397	54.040257282719	86.3946142241603


diffExp=3.63483554437069,-0.676248491263628,5.62633706829143,3.83528523535564,2.19996163308648,-2.85078272315443,1.75510206422427,0.892148776678027
diffExpScore=1.39269664332067
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	63.4489966258823	54.6920535213592	60.8069913033684
cerebhem	63.5184882010336	59.2826223524404	56.2440805939506
cortex	64.4228955770608	63.2346511305762	54.3128404323584
heart	64.5504190973505	53.6305009108348	62.2615576368598
kidney	54.7372548118648	55.2175186605164	69.9593460524859
liver	56.4887486256222	64.5892310367705	61.6706100053596
stomach	67.7036785318622	53.3287841827146	69.3864914075093
testicle	56.8681909623987	53.4223473371644	61.8999038897576
cont.diffExp=8.75694310452313,4.23586584859319,1.18824444648462,10.9199181865156,-0.48026384865166,-8.10048241114831,14.3748943491476,3.44584362523423
cont.diffExpScore=1.45730198076634

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

tran.correlation=0.785792796667494
cont.tran.correlation=-0.158463011151418

tran.covariance=0.00290157935314647
cont.tran.covariance=-0.00091268350357443

tran.mean=54.0599133343604
cont.tran.mean=59.3210238478407

weightedLogRatios:
wLogRatio
Lung	0.275267486997448
cerebhem	-0.045004151688503
cortex	0.431682090548552
heart	0.291274355025776
kidney	0.165102874051800
liver	-0.212056699045481
stomach	0.129831691821103
testicle	0.0654625806541827

cont.weightedLogRatios:
wLogRatio
Lung	0.60535583000549
cerebhem	0.284121756758772
cortex	0.0773738443398561
heart	0.755173926965525
kidney	-0.0350032536646109
liver	-0.549565465590266
stomach	0.977523187912716
testicle	0.25062074350001

varWeightedLogRatios=0.0415252847815709
cont.varWeightedLogRatios=0.235079533832186

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.11931004549743	0.0859580708495536	47.9223184604407	9.2566834652061e-161	***
df.mm.trans1	-0.0749535055598385	0.0707898934986182	-1.05881647584767	0.29037410531277	   
df.mm.trans2	-0.155605384289211	0.0707898934986182	-2.1981299391593	0.0285586533579394	*  
df.mm.exp2	0.291101234107316	0.0967678201591974	3.00824420379017	0.00280741278285132	** 
df.mm.exp3	-0.463550843111186	0.0967678201591974	-4.79034086278451	2.41365207885039e-06	***
df.mm.exp4	-0.519908974753108	0.0967678201591974	-5.37274657936679	1.37449681646976e-07	***
df.mm.exp5	-0.175997615741496	0.0967678201591974	-1.81876180998966	0.0697560491883063	.  
df.mm.exp6	0.0169975605427672	0.0967678201591974	0.175653027161341	0.860662630884381	   
df.mm.exp7	-0.113104902421997	0.0967678201591974	-1.16882763542594	0.243225572082503	   
df.mm.exp8	-0.104886339776873	0.0967678201591974	-1.08389689469412	0.279116302332582	   
df.mm.trans1:exp2	-0.159359357296382	0.0802356378121618	-1.98614183973280	0.0477550628948563	*  
df.mm.trans2:exp2	-0.0788642551962521	0.0802356378121618	-0.982908061139613	0.326294964525469	   
df.mm.trans1:exp3	0.46568937779914	0.0802356378121618	5.80402163549016	1.39298804688694e-08	***
df.mm.trans2:exp3	0.425649952154067	0.0802356378121618	5.30499867341428	1.94436107057514e-07	***
df.mm.trans1:exp4	0.518130465224732	0.0802356378121618	6.45761010135818	3.3471477900883e-10	***
df.mm.trans2:exp4	0.51401218824621	0.0802356378121618	6.40628282222364	4.53522712102645e-10	***
df.mm.trans1:exp5	0.174287418335036	0.0802356378121618	2.17219458942991	0.0304754199589382	*  
df.mm.trans2:exp5	0.202267776301568	0.0802356378121618	2.52092189726333	0.0121243716873334	*  
df.mm.trans1:exp6	-0.0543671715316888	0.0802356378121618	-0.677593810109253	0.498452744754233	   
df.mm.trans2:exp6	0.0685110272469595	0.0802356378121619	0.853872781660306	0.393727952389667	   
df.mm.trans1:exp7	0.126167188504974	0.0802356378121618	1.57245822361806	0.116699013869980	   
df.mm.trans2:exp7	0.163195368323244	0.0802356378121618	2.03395115653343	0.042669448193847	*  
df.mm.trans1:exp8	0.120719358325927	0.0802356378121618	1.50456033774594	0.133290270640008	   
df.mm.trans2:exp8	0.173936701753541	0.0802356378121618	2.16782350706480	0.0308091610417101	*  
df.mm.trans1:probe2	-0.0953411914890988	0.0468475194906708	-2.03513852015335	0.0425492350372511	*  
df.mm.trans1:probe3	-0.144061477763049	0.0468475194906708	-3.07511431404042	0.00226057647623350	** 
df.mm.trans1:probe4	-0.217897354889696	0.0468475194906708	-4.65120367649537	4.60098596767575e-06	***
df.mm.trans1:probe5	-0.160066778076196	0.0468475194906708	-3.41676101139296	0.000704102661156688	***
df.mm.trans1:probe6	0.0224195943238936	0.0468475194906708	0.47856523819491	0.632530616366909	   
df.mm.trans2:probe2	-0.0585694012635474	0.0468475194906708	-1.25021349903512	0.212011688779570	   
df.mm.trans2:probe3	0.00124294410772803	0.0468475194906708	0.0265316951941405	0.97884755709576	   
df.mm.trans2:probe4	-0.117213660089741	0.0468475194906708	-2.50202489617583	0.0127794450301212	*  
df.mm.trans2:probe5	-0.171256904167992	0.0468475194906708	-3.65562373482968	0.000293686810518767	***
df.mm.trans2:probe6	-0.127486219083230	0.0468475194906708	-2.72130137239428	0.00680981275699436	** 
df.mm.trans3:probe2	0.439950134017107	0.0468475194906708	9.39110840446352	6.2223673380446e-19	***
df.mm.trans3:probe3	0.563296840367461	0.0468475194906708	12.0240483699385	2.45000622343227e-28	***
df.mm.trans3:probe4	0.313833502277023	0.0468475194906708	6.69904203443515	7.8262425612251e-11	***
df.mm.trans3:probe5	0.584941836076341	0.0468475194906708	12.4860791443361	4.25348114019554e-30	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.9707870910402	0.176332729853073	22.5187184157406	2.45234257369749e-71	***
df.mm.trans1	0.198362899564428	0.145217023174788	1.36597552564945	0.172776331652584	   
df.mm.trans2	-0.0142819539877946	0.145217023174788	-0.098349034263045	0.92170840061948	   
df.mm.exp2	0.159696396801442	0.198507641248339	0.804484884295495	0.421633597881692	   
df.mm.exp3	0.273310814006218	0.198507641248339	1.37682767417652	0.169398020116800	   
df.mm.exp4	-0.0260296545684727	0.198507641248339	-0.131126713333462	0.895746336795681	   
df.mm.exp5	-0.278339514469056	0.198507641248339	-1.40216020259313	0.161705809855041	   
df.mm.exp6	0.0360316586734997	0.198507641248339	0.181512703727223	0.85606455621937	   
df.mm.exp7	-0.0923254942452498	0.198507641248339	-0.465097936102861	0.64213492655161	   
df.mm.exp8	-0.150803362929142	0.198507641248339	-0.75968543065041	0.447926388132102	   
df.mm.trans1:exp2	-0.158601760923841	0.164593841009805	-0.963594749054997	0.335878480128124	   
df.mm.trans2:exp2	-0.0790986051195564	0.164593841009805	-0.480568438249428	0.631107268674012	   
df.mm.trans1:exp3	-0.258078103112215	0.164593841009805	-1.56796938165409	0.117743068447541	   
df.mm.trans2:exp3	-0.128176810762113	0.164593841009805	-0.778746093874056	0.436627046640173	   
df.mm.trans1:exp4	0.0432398840238809	0.164593841009805	0.262706573700441	0.792922964524555	   
df.mm.trans2:exp4	0.00642918260128913	0.164593841009805	0.039060894149169	0.96886290616795	   
df.mm.trans1:exp5	0.130647686825270	0.164593841009805	0.793758053300958	0.427845051048706	   
df.mm.trans2:exp5	0.287901359398068	0.164593841009805	1.74916240870105	0.0810921027291907	.  
df.mm.trans1:exp6	-0.152226560137985	0.164593841009805	-0.9248618247442	0.355640577539416	   
df.mm.trans2:exp6	0.130297610959410	0.164593841009805	0.791631145855865	0.429082977325624	   
df.mm.trans1:exp7	0.157229628044306	0.164593841009805	0.955258271389025	0.340070795263921	   
df.mm.trans2:exp7	0.0670832955567918	0.164593841009805	0.407568686320382	0.683826068678626	   
df.mm.trans1:exp8	0.0413031332743988	0.164593841009805	0.250939725453873	0.802000007078442	   
df.mm.trans2:exp8	0.127314085770894	0.164593841009805	0.773504555151064	0.439717735250359	   
df.mm.trans1:probe2	-0.00458066540079434	0.0961020985812168	-0.0476645720376561	0.962009286323242	   
df.mm.trans1:probe3	-0.0715430485328554	0.0961020985812168	-0.744448348049275	0.457077823953449	   
df.mm.trans1:probe4	-0.0915967873585664	0.0961020985812168	-0.953119533400793	0.341151746026188	   
df.mm.trans1:probe5	0.00784342120701721	0.0961020985812168	0.0816155039568533	0.93499660266473	   
df.mm.trans1:probe6	-0.0481726319844008	0.0961020985812168	-0.501265140882326	0.616482627824472	   
df.mm.trans2:probe2	0.188075641435066	0.0961020985812168	1.95703990039428	0.051094379978656	.  
df.mm.trans2:probe3	0.0130577505041031	0.0961020985812168	0.135873729053563	0.891994996547664	   
df.mm.trans2:probe4	0.155102528563469	0.0961020985812168	1.61393487606714	0.107394021055361	   
df.mm.trans2:probe5	0.0672106106395369	0.0961020985812168	0.699366732171166	0.484762291804378	   
df.mm.trans2:probe6	0.0738996367445982	0.0961020985812168	0.76897006241903	0.442401654152461	   
df.mm.trans3:probe2	-0.0876571068124417	0.0961020985812168	-0.912124793386918	0.362296932210202	   
df.mm.trans3:probe3	-0.0936574599184545	0.0961020985812168	-0.974562067854363	0.330414248705033	   
df.mm.trans3:probe4	-0.0199965633539271	0.0961020985812168	-0.208076240260537	0.835283925307852	   
df.mm.trans3:probe5	-0.0345051984809059	0.0961020985812168	-0.359047294391237	0.71976451128874