chr6.20187_chr6_72748623_72752123_+_2.R 

fitVsDatCorrelation=0.94121693078909
cont.fitVsDatCorrelation=0.180888519778354

fstatistic=8373.5731674056,57,807
cont.fstatistic=975.34919937197,57,807

residuals=-1.0047251283064,-0.104225518267124,0.00881507559636256,0.118549856918558,0.732023405270636
cont.residuals=-1.02040380941394,-0.411328055781119,-0.105900006235961,0.332340658898656,1.87484175153049

predictedValues:
Include	Exclude	Both
chr6.20187_chr6_72748623_72752123_+_2.R.tl.Lung	69.2003922148145	48.5529270124834	96.3488089080354
chr6.20187_chr6_72748623_72752123_+_2.R.tl.cerebhem	75.3836384682116	61.0815491045305	88.6095226433063
chr6.20187_chr6_72748623_72752123_+_2.R.tl.cortex	85.7054893444637	47.2912755656878	138.088638522789
chr6.20187_chr6_72748623_72752123_+_2.R.tl.heart	166.788772918194	47.3838453724184	281.625641820725
chr6.20187_chr6_72748623_72752123_+_2.R.tl.kidney	100.847294413114	46.6586740857467	169.961605531727
chr6.20187_chr6_72748623_72752123_+_2.R.tl.liver	68.7538704133264	54.4588868989821	94.6279114716977
chr6.20187_chr6_72748623_72752123_+_2.R.tl.stomach	85.1606202219129	49.2293966410714	141.773136477530
chr6.20187_chr6_72748623_72752123_+_2.R.tl.testicle	87.8505601077591	50.679014366477	141.274634847911


diffExp=20.6474652023311,14.3020893636811,38.4142137787758,119.404927545776,54.1886203273668,14.2949835143443,35.9312235808414,37.1715457412821
diffExpScore=0.997018085926598
diffExp1.5=0,0,1,1,1,0,1,1
diffExp1.5Score=0.833333333333333
diffExp1.4=1,0,1,1,1,0,1,1
diffExp1.4Score=0.857142857142857
diffExp1.3=1,0,1,1,1,0,1,1
diffExp1.3Score=0.857142857142857
diffExp1.2=1,1,1,1,1,1,1,1
diffExp1.2Score=0.888888888888889

cont.predictedValues:
Include	Exclude	Both
Lung	89.20041325198	91.0064583256296	80.114852860634
cerebhem	93.6549483209808	96.8622884368831	90.8753755171317
cortex	93.6091532604439	105.383027380221	106.281219291992
heart	95.4328551002853	95.4515215946343	97.606972254316
kidney	87.1018167530331	101.314436927717	90.9950091770432
liver	98.3473557621661	104.17780202405	86.1304856761383
stomach	82.904286817614	88.9337112949593	88.0077276840572
testicle	90.2361083670071	94.2957275880816	84.180977900632
cont.diffExp=-1.80604507364966,-3.20734011590233,-11.7738741197767,-0.01866649434902,-14.2126201746835,-5.83044626188394,-6.02942447734532,-4.05961922107451
cont.diffExpScore=0.97913973777984

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=-0.424096150284932
cont.tran.correlation=0.618814651670183

tran.covariance=-0.0125029020256489
cont.tran.covariance=0.00211045854652177

tran.mean=71.5641379468246
cont.tran.mean=94.2444944503553

weightedLogRatios:
wLogRatio
Lung	1.43860925803508
cerebhem	0.887258364407549
cortex	2.46970606925922
heart	5.64728611916135
kidney	3.25890471842851
liver	0.958917412936989
stomach	2.28564319393610
testicle	2.31084226343656

cont.weightedLogRatios:
wLogRatio
Lung	-0.0902198118962913
cerebhem	-0.153429453862378
cortex	-0.544784026058712
heart	-0.000891551238129623
kidney	-0.686627391943786
liver	-0.265926214826645
stomach	-0.312605843898107
testicle	-0.199103186478747

varWeightedLogRatios=2.37106284225577
cont.varWeightedLogRatios=0.0533109992746288

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.37476017251198	0.0915077244949477	36.8795114416631	2.79030268669703e-175	***
df.mm.trans1	0.701898717570463	0.0794624124147119	8.83309097019702	6.27417924793531e-18	***
df.mm.trans2	0.503055309179566	0.0706306695734186	7.12233527188432	2.3509647631692e-12	***
df.mm.exp2	0.398874786722759	0.0917982771825159	4.3451227949486	1.56957793138347e-05	***
df.mm.exp3	-0.172339060310149	0.0917982771825159	-1.87736704434550	0.060828306537264	.  
df.mm.exp4	-0.217255122387555	0.0917982771825159	-2.36665794888070	0.0181847121092346	*  
df.mm.exp5	-0.230792255184275	0.0917982771825159	-2.51412403661354	0.0121263794325735	*  
df.mm.exp6	0.126340620892448	0.0917982771825159	1.37628531569557	0.169115079179556	   
df.mm.exp7	-0.164884068140805	0.091798277182516	-1.79615645523475	0.0728435664907807	.  
df.mm.exp8	-0.101242642737657	0.0917982771825159	-1.10288172986475	0.270407308814416	   
df.mm.trans1:exp2	-0.313291062150502	0.0853856502175263	-3.66913013313560	0.000259361523591026	***
df.mm.trans2:exp2	-0.169319426338884	0.0652748352336566	-2.59394643790047	0.00966015387261901	** 
df.mm.trans1:exp3	0.386249406438454	0.0853856502175263	4.5235868726707	6.99275601021638e-06	***
df.mm.trans2:exp3	0.146010408327179	0.0652748352336566	2.23685602276164	0.0255681415221047	*  
df.mm.trans1:exp4	1.09697677095125	0.0853856502175263	12.8473199906146	1.66448445999606e-34	***
df.mm.trans2:exp4	0.192881996530412	0.0652748352336566	2.9549212317423	0.0032184698612044	** 
df.mm.trans1:exp5	0.607393160940631	0.0853856502175263	7.11352738303511	2.49661544901237e-12	***
df.mm.trans2:exp5	0.190996623326331	0.0652748352336566	2.92603761683416	0.00352942463646294	** 
df.mm.trans1:exp6	-0.132814119460970	0.0853856502175263	-1.55546182669589	0.120228181402396	   
df.mm.trans2:exp6	-0.0115490542682917	0.0652748352336566	-0.176929657914125	0.859608036791151	   
df.mm.trans1:exp7	0.372416660707035	0.0853856502175263	4.36158370590697	1.45851327218758e-05	***
df.mm.trans2:exp7	0.178720524376389	0.0652748352336566	2.73796975107856	0.0063181255007905	** 
df.mm.trans1:exp8	0.339873302627354	0.0853856502175263	3.98044989716073	7.4983415037288e-05	***
df.mm.trans2:exp8	0.144100068286514	0.0652748352336566	2.20758991992391	0.0275535098754553	*  
df.mm.trans1:probe2	0.482642538778507	0.055898029340691	8.6343390718994	3.12681168016672e-17	***
df.mm.trans1:probe3	0.804714181248288	0.055898029340691	14.3961100371475	5.43795066615721e-42	***
df.mm.trans1:probe4	0.0224065152580788	0.055898029340691	0.400846246680971	0.688639430758998	   
df.mm.trans1:probe5	0.322922834965358	0.055898029340691	5.77699855923698	1.08543816282609e-08	***
df.mm.trans1:probe6	-0.378333549057560	0.055898029340691	-6.76828062670452	2.50597738129533e-11	***
df.mm.trans1:probe7	-0.0876906095570934	0.055898029340691	-1.56876030499449	0.117095795700802	   
df.mm.trans1:probe8	0.713518296434634	0.055898029340691	12.7646413451508	4.03402700241129e-34	***
df.mm.trans1:probe9	-0.257862280512006	0.055898029340691	-4.61308356579747	4.61250440813607e-06	***
df.mm.trans1:probe10	0.93013808772301	0.055898029340691	16.6399083955884	1.12371379128907e-53	***
df.mm.trans1:probe11	-0.0198754644313388	0.055898029340691	-0.355566460316525	0.722258183603762	   
df.mm.trans1:probe12	-0.0395065886034711	0.055898029340691	-0.706761742219637	0.479918566752684	   
df.mm.trans1:probe13	-0.0114322144761524	0.055898029340691	-0.204519096844624	0.837999438707362	   
df.mm.trans1:probe14	-0.0121442806211820	0.055898029340691	-0.217257759610169	0.828062389006426	   
df.mm.trans1:probe15	0.120489289963956	0.055898029340691	2.15551945900616	0.0314162502701071	*  
df.mm.trans1:probe16	-0.062751507063825	0.055898029340691	-1.12260678603467	0.261938410126732	   
df.mm.trans1:probe17	0.49791336973789	0.055898029340691	8.90752993639857	3.41221056159486e-18	***
df.mm.trans1:probe18	0.214390386365135	0.055898029340691	3.83538362432162	0.000135141523557688	***
df.mm.trans1:probe19	0.448410528652742	0.055898029340691	8.0219380529453	3.65712181972753e-15	***
df.mm.trans1:probe20	0.350012167633537	0.055898029340691	6.26161909036649	6.18691601859197e-10	***
df.mm.trans1:probe21	0.404481255281525	0.055898029340691	7.23605572597678	1.07582831506478e-12	***
df.mm.trans1:probe22	0.367986253357872	0.055898029340691	6.5831704211797	8.28875199742613e-11	***
df.mm.trans2:probe2	0.127737864572245	0.055898029340691	2.28519441702855	0.0225600395355931	*  
df.mm.trans2:probe3	0.0198241577111519	0.055898029340691	0.354648597544045	0.722945519321499	   
df.mm.trans2:probe4	0.00183989658073074	0.055898029340691	0.0329152315820799	0.973750325330735	   
df.mm.trans2:probe5	-0.0354949766114583	0.055898029340691	-0.634995133640959	0.525611579182329	   
df.mm.trans2:probe6	-0.0461609443786445	0.055898029340691	-0.825806292692356	0.409158044830793	   
df.mm.trans3:probe2	-0.411341320751767	0.055898029340691	-7.35878036495163	4.57380956903576e-13	***
df.mm.trans3:probe3	0.54819634746696	0.055898029340691	9.807078244669	1.58159368785975e-21	***
df.mm.trans3:probe4	0.442032820395692	0.055898029340691	7.90784264864799	8.60257053829375e-15	***
df.mm.trans3:probe5	-0.701073392632571	0.055898029340691	-12.5420055215117	4.29450073996946e-33	***
df.mm.trans3:probe6	0.343176572141798	0.055898029340691	6.13933221241455	1.29890242990859e-09	***
df.mm.trans3:probe7	0.0330296205247611	0.055898029340691	0.590890607671515	0.554759169264366	   
df.mm.trans3:probe8	-0.347933980070576	0.055898029340691	-6.22444090023219	7.76212948105934e-10	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.61098979802197	0.266422284814158	17.3070724967258	2.5957479378198e-57	***
df.mm.trans1	-0.119740378109001	0.231352681855195	-0.517566414829576	0.604902658640765	   
df.mm.trans2	-0.101868937560740	0.20563929951884	-0.49537679713506	0.620469029100802	   
df.mm.exp2	-0.0149364204076263	0.2672682211688	-0.0558855083567637	0.955446848376943	   
df.mm.exp3	-0.0877137119358843	0.2672682211688	-0.328186087939301	0.742856097486954	   
df.mm.exp4	-0.0822624055297774	0.2672682211688	-0.307789699688324	0.758321779041797	   
df.mm.exp5	-0.0438528824564863	0.2672682211688	-0.164078176839401	0.869710686023587	   
df.mm.exp6	0.160386429845330	0.2672682211688	0.600095399086126	0.54861112478406	   
df.mm.exp7	-0.190201459593937	0.2672682211688	-0.711650112243649	0.476887127327332	   
df.mm.exp8	-0.00245831778253192	0.2672682211688	-0.00919794269509996	0.992663480267933	   
df.mm.trans1:exp2	0.0636680139083365	0.248598029804051	0.256108280337220	0.79793249740788	   
df.mm.trans2:exp2	0.0772962087262775	0.190045931529842	0.406723827782337	0.684318680745882	   
df.mm.trans1:exp3	0.135956209437275	0.248598029804051	0.546891741436719	0.584604296507754	   
df.mm.trans2:exp3	0.234384829918274	0.190045931529842	1.233306222509	0.217820643366352	   
df.mm.trans1:exp4	0.149799645334122	0.248598029804051	0.602577765608989	0.546958896746992	   
df.mm.trans2:exp4	0.129950422238929	0.190045931529842	0.683784289370717	0.49430767582162	   
df.mm.trans1:exp5	0.0200449518962295	0.248598029804051	0.0806319821280536	0.935754622605265	   
df.mm.trans2:exp5	0.151151325508596	0.190045931529842	0.795341022519394	0.426649018037145	   
df.mm.trans1:exp6	-0.0627664438139532	0.248598029804051	-0.252481662318188	0.800733079117214	   
df.mm.trans2:exp6	-0.0252178302293099	0.190045931529842	-0.132693344321081	0.894468985169424	   
df.mm.trans1:exp7	0.117002558660316	0.248598029804051	0.470649581384611	0.638018174906388	   
df.mm.trans2:exp7	0.167162260291716	0.190045931529842	0.879588733871246	0.379343984579416	   
df.mm.trans1:exp8	0.0140023067917800	0.248598029804051	0.0563250915657573	0.95509677246343	   
df.mm.trans2:exp8	0.0379637251905946	0.190045931529842	0.199760788799803	0.841717993245942	   
df.mm.trans1:probe2	-0.0684669932363648	0.162745612741993	-0.420699471296398	0.674086552975936	   
df.mm.trans1:probe3	0.0241771478906694	0.162745612741993	0.148557908771393	0.881939600946565	   
df.mm.trans1:probe4	-0.0103764085664546	0.162745612741993	-0.0637584534023952	0.9491783493418	   
df.mm.trans1:probe5	-0.0348073991133945	0.162745612741993	-0.213876113321568	0.830697692592445	   
df.mm.trans1:probe6	-0.142497095948776	0.162745612741993	-0.875581796325793	0.381517953927216	   
df.mm.trans1:probe7	-0.0577717776545479	0.162745612741993	-0.354982089416664	0.722695760110027	   
df.mm.trans1:probe8	-0.00770084210882891	0.162745612741993	-0.0473182777654188	0.962271268049932	   
df.mm.trans1:probe9	0.1212757570286	0.162745612741993	0.745186029812449	0.456376235525968	   
df.mm.trans1:probe10	0.0395368789389128	0.162745612741993	0.242936680582549	0.808116182545846	   
df.mm.trans1:probe11	-0.163728294187004	0.162745612741993	-1.00603814399943	0.314698772643135	   
df.mm.trans1:probe12	-0.00156602909994723	0.162745612741993	-0.00962255801285356	0.992324806218222	   
df.mm.trans1:probe13	-0.0389554353081756	0.162745612741993	-0.239363965957922	0.810884147403122	   
df.mm.trans1:probe14	0.0289231223378523	0.162745612741993	0.177719828206400	0.858987610934744	   
df.mm.trans1:probe15	0.154705293245305	0.162745612741993	0.95059578343636	0.342094209582609	   
df.mm.trans1:probe16	-0.0509468770175456	0.162745612741993	-0.313046085600561	0.754326533409425	   
df.mm.trans1:probe17	0.0427129425163856	0.162745612741993	0.262452190241835	0.793039822329663	   
df.mm.trans1:probe18	0.115064604474772	0.162745612741993	0.70702123723107	0.479757381174181	   
df.mm.trans1:probe19	-0.0736330395829337	0.162745612741993	-0.452442547251133	0.651071797657536	   
df.mm.trans1:probe20	0.0356516045851663	0.162745612741993	0.219063383549922	0.826656065115158	   
df.mm.trans1:probe21	0.0232631472105952	0.162745612741993	0.142941777776063	0.886371845079398	   
df.mm.trans1:probe22	0.0542272695554218	0.162745612741993	0.333202650699964	0.739067865244367	   
df.mm.trans2:probe2	0.0482290558199997	0.162745612741993	0.296346273226174	0.76704189789128	   
df.mm.trans2:probe3	-0.0212667924904259	0.162745612741993	-0.130675058652063	0.896064930346788	   
df.mm.trans2:probe4	-0.07136340838524	0.162745612741993	-0.43849666472039	0.661143647052179	   
df.mm.trans2:probe5	-0.0258481451056233	0.162745612741993	-0.158825449547457	0.87384613490636	   
df.mm.trans2:probe6	0.0955838882421851	0.162745612741993	0.587320829309961	0.55715253724989	   
df.mm.trans3:probe2	-0.20660531121529	0.162745612741993	-1.26949849974039	0.204629295948734	   
df.mm.trans3:probe3	0.0411557233568032	0.162745612741993	0.252883765426285	0.800422435967989	   
df.mm.trans3:probe4	0.104223756996004	0.162745612741993	0.640409011585669	0.522088514948414	   
df.mm.trans3:probe5	0.0220220612375712	0.162745612741993	0.135315851939331	0.892395895889541	   
df.mm.trans3:probe6	-0.0340610931312166	0.162745612741993	-0.209290392271373	0.83427437090727	   
df.mm.trans3:probe7	0.0567697762859603	0.162745612741993	0.348825233009259	0.727311507181033	   
df.mm.trans3:probe8	-0.0308586454981366	0.162745612741993	-0.189612764228907	0.84966026444623