chr10.2139_chr10_5679754_5681290_-_1.R 

fitVsDatCorrelation=0.734701751288758
cont.fitVsDatCorrelation=0.357758386362968

fstatistic=6639.92471693846,37,347
cont.fstatistic=3499.87231174404,37,347

residuals=-0.457285112347418,-0.0910088261659982,-0.0147719302260207,0.0793606243121852,0.816025525523064
cont.residuals=-0.549623623218904,-0.157644197690332,-0.0171243441057852,0.125974993211333,0.908277329969028

predictedValues:
Include	Exclude	Both
chr10.2139_chr10_5679754_5681290_-_1.R.tl.Lung	56.8939114636652	89.7992773102601	55.6537683996484
chr10.2139_chr10_5679754_5681290_-_1.R.tl.cerebhem	72.2526250084793	90.6282907297191	59.2806501123629
chr10.2139_chr10_5679754_5681290_-_1.R.tl.cortex	56.8724461797783	78.8937207951482	59.0624585625102
chr10.2139_chr10_5679754_5681290_-_1.R.tl.heart	57.4077018115589	80.6254315398037	62.1199107099717
chr10.2139_chr10_5679754_5681290_-_1.R.tl.kidney	62.374238255038	89.3537805971515	58.8147953799734
chr10.2139_chr10_5679754_5681290_-_1.R.tl.liver	59.2430149684104	90.0878617604587	57.4609452639218
chr10.2139_chr10_5679754_5681290_-_1.R.tl.stomach	62.5402418182163	83.2215137992855	59.1369394458226
chr10.2139_chr10_5679754_5681290_-_1.R.tl.testicle	57.5283788143378	79.9494470661966	59.600291752566


diffExp=-32.9053658465949,-18.3756657212399,-22.0212746153699,-23.2177297282448,-26.9795423421136,-30.8448467920483,-20.6812719810692,-22.4210682518588
diffExpScore=0.994960865204346
diffExp1.5=-1,0,0,0,0,-1,0,0
diffExp1.5Score=0.666666666666667
diffExp1.4=-1,0,0,-1,-1,-1,0,0
diffExp1.4Score=0.8
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	63.2486115353907	62.8488472699645	73.0697636736079
cerebhem	60.6359274364551	65.3335489668884	71.3362461950249
cortex	66.7278755556004	67.4905519833808	64.6672964382735
heart	68.4985352084422	62.6983062214917	60.053560450784
kidney	71.8359360233256	70.8325168654245	66.0148371083272
liver	65.9692834205112	63.9226788472955	67.1008119141715
stomach	65.2666611279185	63.1048075879721	68.4772512820922
testicle	66.6135510670997	65.8048987271905	71.4989335298298
cont.diffExp=0.399764265426178,-4.69762153043334,-0.762676427780377,5.80022898695056,1.00341915790119,2.04660457321566,2.1618535399464,0.808652339909173
cont.diffExpScore=2.27839025771822

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=0.51824763221195
cont.tran.correlation=0.548044427966217

tran.covariance=0.00258405726771267
cont.tran.covariance=0.00111363532959612

tran.mean=72.9794926198442
cont.tran.mean=65.677033615272

weightedLogRatios:
wLogRatio
Lung	-1.94849754508703
cerebhem	-0.995549927160176
cortex	-1.37607930665385
heart	-1.43326120870316
kidney	-1.55026920225982
liver	-1.79861005271534
stomach	-1.22239410179913
testicle	-1.38782898762238

cont.weightedLogRatios:
wLogRatio
Lung	0.0262747538027961
cerebhem	-0.309082807541411
cortex	-0.0478039329591958
heart	0.370065427722261
kidney	0.0600274662083424
liver	0.131525788387128
stomach	0.140182317741687
testicle	0.0512097916672908

varWeightedLogRatios=0.0923485613290646
cont.varWeightedLogRatios=0.0366184917536804

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.50684324877442	0.0906242939034297	49.7310715995974	6.08060163226799e-160	***
df.mm.trans1	-0.508024181296952	0.0755024733591141	-6.7285766769603	7.09085233207512e-11	***
df.mm.trans2	0.0649322725168998	0.0755024733591141	0.860001926136392	0.390381750269032	   
df.mm.exp2	0.185036667656341	0.104026547307178	1.77874468052804	0.0761570224096754	.  
df.mm.exp3	-0.189298356651744	0.104026547307178	-1.81971200190629	0.0696643941500138	.  
df.mm.exp4	-0.208689428394247	0.104026547307178	-2.00611703258797	0.0456194671103297	*  
df.mm.exp5	0.0317469819711936	0.104026547307178	0.305181540606635	0.760410864992333	   
df.mm.exp6	0.0117123466496675	0.104026547307178	0.112589977778291	0.91042073544686	   
df.mm.exp7	-0.0421551169798897	0.104026547307178	-0.405234222139573	0.685555070848032	   
df.mm.exp8	-0.173603042582184	0.104026547307178	-1.66883403396591	0.0960522285065071	.  
df.mm.trans1:exp2	0.0539436597200687	0.0879184790613787	0.613564523590187	0.539905118199697	   
df.mm.trans2:exp2	-0.175847171146239	0.0879184790613787	-2.00011616469701	0.0462666806189482	*  
df.mm.trans1:exp3	0.188920999327730	0.0879184790613787	2.14882014958242	0.0323400598960781	*  
df.mm.trans2:exp3	0.0598230694853357	0.0879184790613787	0.680437948017405	0.496680944034583	   
df.mm.trans1:exp4	0.217679569367020	0.0879184790613787	2.47592510347059	0.0137656749525996	*  
df.mm.trans2:exp4	0.100926628421693	0.0879184790613787	1.14795694260399	0.251777127761504	   
df.mm.trans1:exp5	0.0602170284284169	0.0879184790613787	0.684918905232397	0.493852335892075	   
df.mm.trans2:exp5	-0.0367203565434352	0.0879184790613787	-0.417663691813863	0.676451336292664	   
df.mm.trans1:exp6	0.028747204333965	0.0879184790613787	0.326975678388336	0.743883429141498	   
df.mm.trans2:exp6	-0.00850383825646822	0.0879184790613787	-0.0967241283886567	0.923001317294162	   
df.mm.trans1:exp7	0.136777004365515	0.0879184790613787	1.55572532447958	0.120684970956823	   
df.mm.trans2:exp7	-0.0339159168063202	0.0879184790613787	-0.385765508780497	0.699906733485375	   
df.mm.trans1:exp8	0.184693081976170	0.0879184790613787	2.10073108575081	0.0363856837453113	*  
df.mm.trans2:exp8	0.0574206383373533	0.0879184790613787	0.653112280266657	0.514116385534081	   
df.mm.trans1:probe2	0.100522381653932	0.0481549342034627	2.08747833044912	0.0375740041131419	*  
df.mm.trans1:probe3	-0.0192514133846182	0.0481549342034627	-0.399780701667615	0.689564014948248	   
df.mm.trans1:probe4	-0.0414459985608545	0.0481549342034627	-0.860680203314952	0.390008488645074	   
df.mm.trans1:probe5	0.18788292594504	0.0481549342034627	3.90163394578016	0.000114758517171896	***
df.mm.trans1:probe6	0.195984742106054	0.0481549342034627	4.069878722666	5.82868218525837e-05	***
df.mm.trans2:probe2	-0.055348414048899	0.0481549342034627	-1.14938198887455	0.251190095077143	   
df.mm.trans2:probe3	-0.184615688367609	0.0481549342034627	-3.83378549719488	0.000149817878471198	***
df.mm.trans2:probe4	-0.117263852632304	0.0481549342034627	-2.43513680523047	0.0153893427494709	*  
df.mm.trans2:probe5	-0.168348430942904	0.0481549342034627	-3.49597468520263	0.000533640195815397	***
df.mm.trans2:probe6	-0.216409551863065	0.0481549342034627	-4.49402653004775	9.53563762177655e-06	***
df.mm.trans3:probe2	-0.0805117734896882	0.0481549342034627	-1.67193195923625	0.0954391691607	.  
df.mm.trans3:probe3	-0.0942583673130462	0.0481549342034627	-1.95739790474614	0.0511019974594819	.  
df.mm.trans3:probe4	-0.00363605315366518	0.0481549342034627	-0.075507384940082	0.939854534415518	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.94821740417134	0.124745676838328	31.6501341308067	2.51615571367936e-104	***
df.mm.trans1	0.123764511927414	0.103930267883655	1.19084184470652	0.234529642589144	   
df.mm.trans2	0.169859625475297	0.103930267883655	1.63436147076468	0.103089829087099	   
df.mm.exp2	0.0205975727279819	0.143194076268517	0.143843748741096	0.885707355030525	   
df.mm.exp3	0.246963680665863	0.143194076268517	1.72467805304151	0.0854759833762142	.  
df.mm.exp4	0.273518838576095	0.143194076268517	1.91012677132812	0.0569410303966374	.  
df.mm.exp5	0.348432386450905	0.143194076268517	2.43328771364484	0.0154668048863238	*  
df.mm.exp6	0.144276179259813	0.143194076268517	1.00755689773973	0.314369292359981	   
df.mm.exp7	0.100385603451170	0.143194076268517	0.701045783925638	0.48374428532946	   
df.mm.exp8	0.119528659002216	0.143194076268517	0.834731869620612	0.404443003400416	   
df.mm.trans1:exp2	-0.0627831686952915	0.121021082810257	-0.518778771742822	0.604245697550449	   
df.mm.trans2:exp2	0.0181755044456482	0.121021082810257	0.150184612660793	0.880706223575029	   
df.mm.trans1:exp3	-0.193414066035578	0.121021082810257	-1.59818489096501	0.110911985982613	   
df.mm.trans2:exp3	-0.17570865709769	0.121021082810257	-1.45188468833298	0.147437198614515	   
df.mm.trans1:exp4	-0.193779652711962	0.121021082810257	-1.60120574210842	0.110241306564192	   
df.mm.trans2:exp4	-0.275916999210332	0.121021082810257	-2.2799085316641	0.0232194094169078	*  
df.mm.trans1:exp5	-0.221120709245354	0.121021082810257	-1.82712552317879	0.0685396935105186	.  
df.mm.trans2:exp5	-0.228846807323676	0.121021082810257	-1.890966449891	0.0594616077185813	.  
df.mm.trans1:exp6	-0.102160123643422	0.121021082810257	-0.844151459160166	0.39916635882463	   
df.mm.trans2:exp6	-0.127334563201184	0.121021082810257	-1.05216843416304	0.293454420000579	   
df.mm.trans1:exp7	-0.0689774222432736	0.121021082810257	-0.569962031751277	0.569072271733357	   
df.mm.trans2:exp7	-0.0963212407195307	0.121021082810257	-0.795904634819274	0.426631598363014	   
df.mm.trans1:exp8	-0.0676938080340539	0.121021082810257	-0.559355497919216	0.576279968381944	   
df.mm.trans2:exp8	-0.0735669685975457	0.121021082810257	-0.607885559187136	0.543661013572679	   
df.mm.trans1:probe2	0.127597750132018	0.0662859769888784	1.92495842904189	0.0550517544114984	.  
df.mm.trans1:probe3	0.227331926526954	0.0662859769888784	3.42956288575329	0.000677366731893345	***
df.mm.trans1:probe4	0.100022641089438	0.0662859769888784	1.50895627752790	0.132219911902008	   
df.mm.trans1:probe5	0.0742104390540946	0.0662859769888784	1.11954960046143	0.263680075712357	   
df.mm.trans1:probe6	0.221749835780438	0.0662859769888784	3.3453506435855	0.000911674032097977	***
df.mm.trans2:probe2	0.0169343120004305	0.0662859769888784	0.255473521998051	0.798508753869645	   
df.mm.trans2:probe3	0.00887918190884533	0.0662859769888784	0.133952644468604	0.893517676223453	   
df.mm.trans2:probe4	0.0278263079829909	0.0662859769888784	0.419791775682203	0.674897366023455	   
df.mm.trans2:probe5	0.141438561052876	0.0662859769888784	2.13376293867717	0.0335630083023717	*  
df.mm.trans2:probe6	0.0314772795577973	0.0662859769888784	0.474870869944009	0.635177748477871	   
df.mm.trans3:probe2	0.124009886017937	0.0662859769888784	1.87083138321615	0.0622099219755203	.  
df.mm.trans3:probe3	-0.0234932240624249	0.0662859769888784	-0.354422234228615	0.723237757745781	   
df.mm.trans3:probe4	0.0977757779538545	0.0662859769888784	1.47505976973470	0.141103207219468