chr19.12006_chr19_11125348_11127000_-_0.R 

fitVsDatCorrelation=0.882940521151456
cont.fitVsDatCorrelation=0.255445286875576

fstatistic=8552.18024935715,37,347
cont.fstatistic=2009.46029296624,37,347

residuals=-0.390938783941044,-0.093930983764313,-0.00403299226354952,0.0793185616071017,0.579681346445537
cont.residuals=-0.528553634852364,-0.201456456960302,-0.077136840605435,0.166378731736476,1.10511353628377

predictedValues:
Include	Exclude	Both
chr19.12006_chr19_11125348_11127000_-_0.R.tl.Lung	85.6906699666219	50.6981749817605	51.5567968648264
chr19.12006_chr19_11125348_11127000_-_0.R.tl.cerebhem	80.5550017157657	62.0984354872505	60.8654575169914
chr19.12006_chr19_11125348_11127000_-_0.R.tl.cortex	67.8005110751591	52.0314929563088	46.6809812709489
chr19.12006_chr19_11125348_11127000_-_0.R.tl.heart	68.2013472805827	51.6801409105158	47.3215321216851
chr19.12006_chr19_11125348_11127000_-_0.R.tl.kidney	92.2367766402549	56.5430240709335	50.8721004785197
chr19.12006_chr19_11125348_11127000_-_0.R.tl.liver	85.4602874702887	54.9376727149416	49.1823338422074
chr19.12006_chr19_11125348_11127000_-_0.R.tl.stomach	69.3009050680596	52.0088492746014	54.0704528100172
chr19.12006_chr19_11125348_11127000_-_0.R.tl.testicle	71.5002065014742	51.8096608540564	50.0835064624491


diffExp=34.9924949848615,18.4565662285151,15.7690181188503,16.5212063700669,35.6937525693214,30.522614755347,17.2920557934583,19.6905456474178
diffExpScore=0.994735131146689
diffExp1.5=1,0,0,0,1,1,0,0
diffExp1.5Score=0.75
diffExp1.4=1,0,0,0,1,1,0,0
diffExp1.4Score=0.75
diffExp1.3=1,0,1,1,1,1,1,1
diffExp1.3Score=0.875
diffExp1.2=1,1,1,1,1,1,1,1
diffExp1.2Score=0.888888888888889

cont.predictedValues:
Include	Exclude	Both
Lung	62.3744061535407	58.6727031822493	63.4229337074039
cerebhem	59.7926958856598	69.839496548493	60.0343569748371
cortex	59.2636533364596	64.3013905117173	72.8454672304556
heart	54.7865136724245	62.4715260871152	67.9356432959068
kidney	57.5318245393647	63.0395331584662	60.805237626544
liver	55.4978788980309	61.995112051815	57.4293726455715
stomach	58.8614539644478	59.5013612922969	65.8275053113133
testicle	58.4589655009648	61.762283198528	56.7207144957642
cont.diffExp=3.70170297129146,-10.0468006628332,-5.03773717525774,-7.68501241469064,-5.50770861910142,-6.49723315378411,-0.639907327849109,-3.30331769756318
cont.diffExpScore=1.17779329851430

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=0.441541188767391
cont.tran.correlation=-0.0629809592225698

tran.covariance=0.00382354507408536
cont.tran.covariance=-0.000168518773828507

tran.mean=65.784572310536
cont.tran.mean=60.5094248738484

weightedLogRatios:
wLogRatio
Lung	2.19825505272276
cerebhem	1.10823034715305
cortex	1.08117422880342
heart	1.13279966498888
kidney	2.09429195403537
liver	1.86776588817721
stomach	1.17542713060776
testicle	1.32348984341879

cont.weightedLogRatios:
wLogRatio
Lung	0.250996709066986
cerebhem	-0.647442007539795
cortex	-0.336357993608210
heart	-0.534134808623424
kidney	-0.374659215473894
liver	-0.450780947741745
stomach	-0.044122416000833
testicle	-0.225137650170898

varWeightedLogRatios=0.225169951960112
cont.varWeightedLogRatios=0.0828081405959667

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.28840152538063	0.0780031324463527	54.9772988710422	2.34099154281569e-173	***
df.mm.trans1	0.0913693165027678	0.0649873138403047	1.40595619519361	0.160631925003491	   
df.mm.trans2	-0.314062933784926	0.0649873138403047	-4.83268064528228	2.02617345130404e-06	***
df.mm.exp2	-0.0249546292829024	0.0895388664344836	-0.278701644063832	0.780639814605933	   
df.mm.exp3	-0.108867739449418	0.0895388664344835	-1.21587131694456	0.224860449525266	   
df.mm.exp4	-0.123377323863282	0.0895388664344835	-1.37791920733728	0.169116152372395	   
df.mm.exp5	0.196096304296735	0.0895388664344835	2.19006909630938	0.0291843699639768	*  
df.mm.exp6	0.124766809566628	0.0895388664344835	1.39343744828311	0.164379414189459	   
df.mm.exp7	-0.234365842115061	0.0895388664344835	-2.61747609108441	0.0092460557116321	** 
df.mm.exp8	-0.130364581841466	0.0895388664344835	-1.45595524080992	0.146309142695305	   
df.mm.trans1:exp2	-0.0368491196177995	0.0756741539306721	-0.486944586807781	0.626605040114016	   
df.mm.trans2:exp2	0.227785510928687	0.0756741539306721	3.01008335206985	0.00280297350404380	** 
df.mm.trans1:exp3	-0.125306478793904	0.0756741539306721	-1.65586891012619	0.098652364861641	.  
df.mm.trans2:exp3	0.134826994949623	0.0756741539306721	1.78167826062704	0.0756761808627696	.  
df.mm.trans1:exp4	-0.104902307778131	0.0756741539306721	-1.38623694259253	0.166564642710837	   
df.mm.trans2:exp4	0.142560996396309	0.0756741539306721	1.88387962060223	0.0604171489430005	.  
df.mm.trans1:exp5	-0.122481325446660	0.0756741539306721	-1.61853577588551	0.106455716060946	   
df.mm.trans2:exp5	-0.086984381482354	0.0756741539306721	-1.14945958381039	0.251158158225515	   
df.mm.trans1:exp6	-0.127458966700060	0.0756741539306721	-1.68431307229189	0.0930203832262008	.  
df.mm.trans2:exp6	-0.0444574038162266	0.0756741539306721	-0.587484649738611	0.557260339259214	   
df.mm.trans1:exp7	0.0220798572278377	0.0756741539306721	0.29177540918483	0.770632700697752	   
df.mm.trans2:exp7	0.259889811041243	0.0756741539306721	3.43432727743924	0.000665958314771522	***
df.mm.trans1:exp8	-0.0506790314731953	0.0756741539306721	-0.669700668468976	0.503494003807834	   
df.mm.trans2:exp8	0.152051303157177	0.0756741539306721	2.00928976750076	0.0452803845389466	*  
df.mm.trans1:probe2	0.128832735042164	0.0414484411279474	3.10826490782777	0.00203735854585708	** 
df.mm.trans1:probe3	0.185814547792881	0.0414484411279474	4.48302861908097	1.00122565631775e-05	***
df.mm.trans1:probe4	0.36382817017311	0.0414484411279474	8.77784930559891	7.70082744503272e-17	***
df.mm.trans1:probe5	-0.124842318925514	0.0414484411279474	-3.01199069321178	0.00278587320649757	** 
df.mm.trans1:probe6	0.156097958512998	0.0414484411279474	3.76607549681155	0.000194739369072748	***
df.mm.trans2:probe2	-0.128163394947279	0.0414484411279474	-3.09211616793141	0.00214832990023762	** 
df.mm.trans2:probe3	-0.182313096542941	0.0414484411279474	-4.39855134672394	1.45155491069961e-05	***
df.mm.trans2:probe4	-0.0442191417047066	0.0414484411279474	-1.06684691875881	0.286782652018464	   
df.mm.trans2:probe5	-0.0686737315276709	0.0414484411279474	-1.6568471493459	0.0984542319030973	.  
df.mm.trans2:probe6	-0.0611174158917085	0.0414484411279474	-1.47454076024343	0.141242720856349	   
df.mm.trans3:probe2	-0.155774152758335	0.0414484411279474	-3.75826324269893	0.000200672447105105	***
df.mm.trans3:probe3	-0.157422200548999	0.0414484411279474	-3.79802463651291	0.000172155306458077	***
df.mm.trans3:probe4	-0.178899072207881	0.0414484411279474	-4.3161833675635	2.07351439601423e-05	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.08074232247896	0.160634066328619	25.4039657698183	3.54132757479889e-81	***
df.mm.trans1	0.00741739880763163	0.133830221358378	0.0554239448485175	0.955832617350592	   
df.mm.trans2	0.026881591748412	0.133830221358378	0.200863388519899	0.840923077011184	   
df.mm.exp2	0.186862096157836	0.184389931003324	1.01340726763690	0.311571763032990	   
df.mm.exp3	-0.0980669674430491	0.184389931003324	-0.531845567214194	0.595173284426975	   
df.mm.exp4	-0.135710005027287	0.184389931003324	-0.735994662446293	0.462231166401046	   
df.mm.exp5	0.0331202713154040	0.184389931003324	0.179620823844263	0.857555096542787	   
df.mm.exp6	0.037540351790331	0.184389931003324	0.203592200431238	0.838791529075931	   
df.mm.exp7	-0.0811562323403256	0.184389931003324	-0.440133752958899	0.66011426008177	   
df.mm.exp8	0.0981743553311577	0.184389931003324	0.532427962833761	0.594770378435009	   
df.mm.trans1:exp2	-0.229133618483353	0.155837934716557	-1.47033274600378	0.142377800840457	   
df.mm.trans2:exp2	-0.0126369895224274	0.155837934716557	-0.0810905864827584	0.935416661957678	   
df.mm.trans1:exp3	0.0469081235285243	0.155837934716557	0.301005808462761	0.763590346292981	   
df.mm.trans2:exp3	0.189673627600752	0.155837934716557	1.21712102990672	0.224385280100884	   
df.mm.trans1:exp4	0.00599903438345797	0.155837934716557	0.0384953406522564	0.969314883562787	   
df.mm.trans2:exp4	0.198446279125525	0.155837934716557	1.27341445769584	0.203723380841345	   
df.mm.trans1:exp5	-0.113937039812289	0.155837934716557	-0.731125191177111	0.465196091119449	   
df.mm.trans2:exp5	0.0386671724969395	0.155837934716557	0.248124261703471	0.80418503307061	   
df.mm.trans1:exp6	-0.154350583263613	0.155837934716557	-0.99045578051551	0.322641533172185	   
df.mm.trans2:exp6	0.0175405960442661	0.155837934716557	0.112556651088642	0.910447138832119	   
df.mm.trans1:exp7	0.0231876434790393	0.155837934716557	0.148793318656421	0.88180315541463	   
df.mm.trans2:exp7	0.0951808272636494	0.155837934716557	0.610768022797319	0.541753008379352	   
df.mm.trans1:exp8	-0.163004325090388	0.155837934716557	-1.04598617394966	0.296295482752373	   
df.mm.trans2:exp8	-0.0468560776385616	0.155837934716557	-0.300671834003607	0.763844814578474	   
df.mm.trans1:probe2	0.052716765048734	0.0853559521592758	0.617610883777191	0.537236958298276	   
df.mm.trans1:probe3	0.139606337609205	0.0853559521592758	1.63557823534903	0.102834600247996	   
df.mm.trans1:probe4	0.116329786998844	0.0853559521592759	1.36287844088213	0.173804580612185	   
df.mm.trans1:probe5	0.110635496899401	0.0853559521592758	1.29616616182728	0.195779647775559	   
df.mm.trans1:probe6	0.0306647349963875	0.0853559521592759	0.359257136973489	0.719621248359637	   
df.mm.trans2:probe2	-0.0949751689099368	0.0853559521592759	-1.11269532478194	0.266609541955583	   
df.mm.trans2:probe3	-0.0385104691941475	0.0853559521592759	-0.451174970461183	0.652145269462079	   
df.mm.trans2:probe4	-0.124887650893260	0.0853559521592759	-1.46313933280502	0.144334442416402	   
df.mm.trans2:probe5	-0.0864059497880906	0.0853559521592759	-1.01230139905013	0.312099299664234	   
df.mm.trans2:probe6	-0.0117139412014907	0.0853559521592759	-0.137236371982967	0.89092355510697	   
df.mm.trans3:probe2	0.0865590077921313	0.0853559521592759	1.01409457222867	0.311244193265174	   
df.mm.trans3:probe3	-1.76103272180757e-05	0.0853559521592758	-0.000206316334978192	0.999835501908358	   
df.mm.trans3:probe4	0.0525954561359033	0.0853559521592759	0.616189671667643	0.538173343326413