chr8.23371_chr8_26161452_26169840_+_2.R 

fitVsDatCorrelation=0.702857510307575
cont.fitVsDatCorrelation=0.244303249361809

fstatistic=10677.1606000117,52,692
cont.fstatistic=5739.31654413648,52,692

residuals=-0.569367531971513,-0.0858858338770832,-0.0102279502044936,0.0735560444287858,1.07909065812354
cont.residuals=-0.465137022477407,-0.123369141759008,-0.0196504866919896,0.098272437609294,1.25287698542500

predictedValues:
Include	Exclude	Both
chr8.23371_chr8_26161452_26169840_+_2.R.tl.Lung	51.0009629030186	54.3789909006814	55.7562597351858
chr8.23371_chr8_26161452_26169840_+_2.R.tl.cerebhem	57.5303926452527	71.1209516605342	52.7246358053271
chr8.23371_chr8_26161452_26169840_+_2.R.tl.cortex	51.1349536349684	49.9485010204892	51.5056109642342
chr8.23371_chr8_26161452_26169840_+_2.R.tl.heart	49.7132379447784	51.7070957366028	55.4745343009715
chr8.23371_chr8_26161452_26169840_+_2.R.tl.kidney	49.8178404596661	50.2858195366076	57.6052587185666
chr8.23371_chr8_26161452_26169840_+_2.R.tl.liver	49.0255454952321	51.7851655580625	52.6917022746026
chr8.23371_chr8_26161452_26169840_+_2.R.tl.stomach	53.5638790496244	55.2978696627958	50.5162468911057
chr8.23371_chr8_26161452_26169840_+_2.R.tl.testicle	51.7246416754401	53.2399369829405	54.2194972794644


diffExp=-3.37802799766278,-13.5905590152815,1.1864526144792,-1.99385779182442,-0.467979076941482,-2.75962006283043,-1.73399061317144,-1.51529530750037
diffExpScore=1.05436628924803
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,-1,0,0,0,0,0,0
diffExp1.2Score=0.5

cont.predictedValues:
Include	Exclude	Both
Lung	52.6305721334761	51.6346192279828	53.1608347149585
cerebhem	54.6576199955488	53.5754951467139	51.9846210194988
cortex	53.2520709906345	50.3222267123972	60.5905408993979
heart	56.9484887399077	52.0765245663142	53.4748199801168
kidney	53.394175010279	54.4578363272262	50.3395781427546
liver	53.5575200854847	49.4716093630133	47.9401171645962
stomach	52.670930980553	48.7719999882445	55.7835489784766
testicle	53.6281312136033	50.4663759960583	58.4542646515992
cont.diffExp=0.995952905493318,1.08212484883490,2.92984427823733,4.87196417359354,-1.06366131694726,4.08591072247143,3.8989309923085,3.16175521754501
cont.diffExpScore=1.05377723683824

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=0.919113831408792
cont.tran.correlation=0.34443414272161

tran.covariance=0.00538175655237189
cont.tran.covariance=0.00034710379194456

tran.mean=53.2047365541684
cont.tran.mean=52.5947622798398

weightedLogRatios:
wLogRatio
Lung	-0.254218981880612
cerebhem	-0.881854954017537
cortex	0.092089204679741
heart	-0.154382474906120
kidney	-0.0365868340428040
liver	-0.214652751965169
stomach	-0.127335966092474
testicle	-0.114353802941652

cont.weightedLogRatios:
wLogRatio
Lung	0.0755355321668582
cerebhem	0.0798092487819535
cortex	0.223345459046625
heart	0.357501780201621
kidney	-0.0786550990276825
liver	0.312753124010164
stomach	0.301908193366007
testicle	0.240130299069815

varWeightedLogRatios=0.0848221363547192
cont.varWeightedLogRatios=0.0223837011368965

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.61717068343291	0.0777405553829931	46.5287476480291	3.00263365043226e-215	***
df.mm.trans1	0.0739268179730846	0.0698223874366	1.05878387559021	0.290067652909688	   
df.mm.trans2	0.372580169951355	0.0642111679977463	5.80242007067108	9.94983883294701e-09	***
df.mm.exp2	0.444779819865951	0.0879533982152364	5.0569941456668	5.46053091658311e-07	***
df.mm.exp3	-0.00306267921794155	0.0879533982152364	-0.0348216132644093	0.972232027887224	   
df.mm.exp4	-0.070890508272994	0.0879533982152364	-0.806000788048158	0.420519278823433	   
df.mm.exp5	-0.134350288399551	0.0879533982152364	-1.52751674325048	0.127089496089504	   
df.mm.exp6	-0.0318454723982269	0.0879533982152364	-0.362072109144615	0.717408683962887	   
df.mm.exp7	0.164481612625511	0.0879533982152364	1.87009957503856	0.0618919726363736	.  
df.mm.exp8	0.0208698245326238	0.0879533982152364	0.237282753777766	0.8125076702778	   
df.mm.trans1:exp2	-0.324310956959284	0.0842089676705553	-3.85126389659665	0.000128413307740243	***
df.mm.trans2:exp2	-0.176375730286301	0.073294498512697	-2.40639794070966	0.0163718152257199	*  
df.mm.trans1:exp3	0.00568645375993753	0.0842089676705553	0.0675278882670102	0.946180966875002	   
df.mm.trans2:exp3	-0.0819227083277132	0.073294498512697	-1.11771974691281	0.264074593721541	   
df.mm.trans1:exp4	0.0453172499491958	0.0842089676705553	0.538152303760417	0.59064494627574	   
df.mm.trans2:exp4	0.0205076460697790	0.073294498512697	0.279797890509154	0.779716182401453	   
df.mm.trans1:exp5	0.110878937441287	0.0842089676705553	1.31671175301745	0.188371157855272	   
df.mm.trans2:exp5	0.0560955254075776	0.073294498512697	0.765344282939053	0.444327503456853	   
df.mm.trans1:exp6	-0.00765754169992679	0.0842089676705553	-0.0909349907943871	0.927570561937739	   
df.mm.trans2:exp6	-0.0170286811287719	0.073294498512697	-0.232332323357420	0.816348601752986	   
df.mm.trans1:exp7	-0.115451183045640	0.0842089676705553	-1.37100817453684	0.170816870851594	   
df.mm.trans2:exp7	-0.147725110706114	0.073294498512697	-2.01550066790515	0.0442383296770948	*  
df.mm.trans1:exp8	-0.00678004141514947	0.0842089676705553	-0.0805144820403753	0.935851357802754	   
df.mm.trans2:exp8	-0.0420388972377545	0.073294498512697	-0.573561428085519	0.566450969928848	   
df.mm.trans1:probe2	0.204624179945086	0.0421044838352777	4.85991422542128	1.45397791931411e-06	***
df.mm.trans1:probe3	0.384966725250723	0.0421044838352777	9.1431289540753	6.65375963189756e-19	***
df.mm.trans1:probe4	0.201462006223549	0.0421044838352777	4.78481120945964	2.09311544928833e-06	***
df.mm.trans1:probe5	0.179707764940759	0.0421044838352777	4.26813841594203	2.24603876582283e-05	***
df.mm.trans1:probe6	0.198540270625592	0.0421044838352777	4.71541870462839	2.91812536439277e-06	***
df.mm.trans1:probe7	0.263506880783038	0.0421044838352777	6.25840425485173	6.81849564529487e-10	***
df.mm.trans1:probe8	0.180357006063309	0.0421044838352777	4.28355817800562	2.09957438429587e-05	***
df.mm.trans1:probe9	0.357574940041662	0.0421044838352776	8.49256201407377	1.23185531990763e-16	***
df.mm.trans1:probe10	0.0811696698160925	0.0421044838352776	1.92781533989698	0.0542870128740557	.  
df.mm.trans1:probe11	0.288132544504509	0.0421044838352777	6.8432745935504	1.70670607561381e-11	***
df.mm.trans1:probe12	0.311847026575528	0.0421044838352777	7.4065039675001	3.78320626242951e-13	***
df.mm.trans1:probe13	0.220651915843171	0.0421044838352777	5.24057999871015	2.12788300305530e-07	***
df.mm.trans1:probe14	0.112542477700041	0.0421044838352776	2.67293331846397	0.00769630828979354	** 
df.mm.trans1:probe15	0.10464095224398	0.0421044838352776	2.48526861541301	0.0131805038221006	*  
df.mm.trans1:probe16	0.409267932377405	0.0421044838352776	9.7202933060183	5.07473991187968e-21	***
df.mm.trans1:probe17	0.303212074906542	0.0421044838352777	7.20142006948183	1.55859974475877e-12	***
df.mm.trans1:probe18	0.424818546021984	0.0421044838352777	10.0896272160459	1.99579840189302e-22	***
df.mm.trans1:probe19	0.500573805260368	0.0421044838352777	11.8888479245756	8.61708396809546e-30	***
df.mm.trans1:probe20	0.35913142347091	0.0421044838352776	8.52952917974044	9.23011784606798e-17	***
df.mm.trans1:probe21	0.342537826377651	0.0421044838352777	8.13542395431653	1.90279963104454e-15	***
df.mm.trans1:probe22	0.589409320814059	0.0421044838352777	13.9987304706065	2.18521581500879e-39	***
df.mm.trans2:probe2	0.144088141552997	0.0421044838352777	3.42215670228146	0.000657822924241686	***
df.mm.trans2:probe3	0.0541066314277683	0.0421044838352777	1.28505628140333	0.199202559435686	   
df.mm.trans2:probe4	-0.100516985460311	0.0421044838352777	-2.38732259142651	0.0172390634120253	*  
df.mm.trans2:probe5	-0.0575607384903691	0.0421044838352777	-1.36709284254760	0.172040122796309	   
df.mm.trans2:probe6	0.0159262138224174	0.0421044838352777	0.378254579363194	0.705357488512165	   
df.mm.trans3:probe2	-0.0246255441080925	0.0421044838352777	-0.584867497828337	0.558827457805464	   
df.mm.trans3:probe3	-0.103438411116374	0.0421044838352777	-2.45670773500153	0.0142661363234984	*  

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.9091159247879	0.105977336538707	36.8863386499635	1.54869803760477e-165	***
df.mm.trans1	0.0146209062121557	0.0951831462336495	0.153608141679466	0.877963499982368	   
df.mm.trans2	0.0183228401604480	0.0875338300185247	0.209322957267726	0.83425773687	   
df.mm.exp2	0.0970648984950444	0.119899669309774	0.809551010889502	0.418476544846466	   
df.mm.exp3	-0.144822829297942	0.119899669309774	-1.20786679505993	0.227511139686301	   
df.mm.exp4	0.0814829301665724	0.119899669309774	0.679592618025096	0.496989703117228	   
df.mm.exp5	0.122169207872988	0.119899669309774	1.0189286473956	0.308592935155801	   
df.mm.exp6	0.0780349046536933	0.119899669309774	0.650835028177447	0.515369026443302	   
df.mm.exp7	-0.104426515527107	0.119899669309774	-0.87094915380717	0.384083955400662	   
df.mm.exp8	-0.0990311858140755	0.119899669309774	-0.825950449940088	0.409116863973205	   
df.mm.trans1:exp2	-0.0592734310886607	0.114795193608198	-0.516340704045188	0.605781425149738	   
df.mm.trans2:exp2	-0.0601654778510604	0.0999163910914783	-0.602158236439665	0.547266058201891	   
df.mm.trans1:exp3	0.156562354805339	0.114795193608198	1.36384067907663	0.173061167953725	   
df.mm.trans2:exp3	0.119077328956893	0.0999163910914783	1.19176971521992	0.233760109906838	   
df.mm.trans1:exp4	-0.00263294740693717	0.114795193608198	-0.0229360422172687	0.981707902344756	   
df.mm.trans2:exp4	-0.0729610298860972	0.0999163910914783	-0.730220828525501	0.465502341378371	   
df.mm.trans1:exp5	-0.10776472023002	0.114795193608198	-0.93875637857998	0.348183378530963	   
df.mm.trans2:exp5	-0.0689348137892696	0.0999163910914783	-0.68992497663528	0.490472671431428	   
df.mm.trans1:exp6	-0.0605758566867426	0.114795193608198	-0.527686349774286	0.59788619803006	   
df.mm.trans2:exp6	-0.120828310638168	0.0999163910914783	-1.20929418404978	0.226962834734846	   
df.mm.trans1:exp7	0.105193054424645	0.114795193608198	0.91635417057333	0.359800390586652	   
df.mm.trans2:exp7	0.0473905301886294	0.0999163910914783	0.474301860494952	0.635434290817436	   
df.mm.trans1:exp8	0.117807782118465	0.114795193608198	1.02624315893006	0.305135571218345	   
df.mm.trans2:exp8	0.0761461156818769	0.0999163910914783	0.762098338921804	0.446260980332396	   
df.mm.trans1:probe2	0.0332359776220010	0.0573975968040991	0.579048243699767	0.562745052378042	   
df.mm.trans1:probe3	-0.0114028849575618	0.0573975968040991	-0.198664849967159	0.842583273452965	   
df.mm.trans1:probe4	0.0395549043805781	0.0573975968040991	0.689138684944963	0.490966993038865	   
df.mm.trans1:probe5	0.0554875593389269	0.0573975968040991	0.966722692734135	0.334020408130466	   
df.mm.trans1:probe6	0.0427855689737556	0.0573975968040991	0.745424396770215	0.456268308588249	   
df.mm.trans1:probe7	-0.01560118543986	0.0573975968040991	-0.271809035718126	0.785849928618586	   
df.mm.trans1:probe8	0.0640184233273985	0.0573975968040991	1.11535023924253	0.265087542117437	   
df.mm.trans1:probe9	0.0328751754540299	0.0573975968040991	0.572762228464625	0.566991744518666	   
df.mm.trans1:probe10	0.0733199146380134	0.0573975968040991	1.27740391097310	0.201888084916727	   
df.mm.trans1:probe11	0.0551721092835155	0.0573975968040991	0.96122681707077	0.336773879043401	   
df.mm.trans1:probe12	0.0433722696130655	0.0573975968040991	0.755646090220419	0.450118543373459	   
df.mm.trans1:probe13	0.0376847277189184	0.0573975968040991	0.656555845840345	0.511684814091509	   
df.mm.trans1:probe14	0.0597261503777048	0.0573975968040991	1.04056883394532	0.29843911840782	   
df.mm.trans1:probe15	0.0571693113670805	0.0573975968040991	0.996022735275873	0.319587248437156	   
df.mm.trans1:probe16	0.0374215926229358	0.0573975968040991	0.651971418780086	0.514636092802445	   
df.mm.trans1:probe17	0.0448264707463358	0.0573975968040991	0.780981665475139	0.435080362155357	   
df.mm.trans1:probe18	0.0528187587346326	0.0573975968040991	0.920225961984186	0.35777536158948	   
df.mm.trans1:probe19	0.0597194326353242	0.0573975968040991	1.04045179520581	0.298493425936798	   
df.mm.trans1:probe20	0.0309202039078749	0.0573975968040991	0.538702064711997	0.59026569464015	   
df.mm.trans1:probe21	0.135888433330540	0.0573975968040991	2.36749342998338	0.0181831412742493	*  
df.mm.trans1:probe22	0.0600155655426444	0.0573975968040991	1.04561112109764	0.29610570868359	   
df.mm.trans2:probe2	0.0305548686163357	0.0573975968040991	0.532337071892069	0.594663436552925	   
df.mm.trans2:probe3	0.0284271414784188	0.0573975968040991	0.495267102827354	0.620568814792285	   
df.mm.trans2:probe4	-0.0195967887029592	0.0573975968040991	-0.341421763176671	0.732889739539159	   
df.mm.trans2:probe5	0.0468912391830874	0.0573975968040991	0.816954747132176	0.414235449656071	   
df.mm.trans2:probe6	0.0645059200491692	0.0573975968040991	1.12384356908411	0.261469103025986	   
df.mm.trans3:probe2	0.0270844599508984	0.0573975968040991	0.471874459192761	0.637165151257009	   
df.mm.trans3:probe3	0.0667023335431968	0.0573975968040991	1.16211021466378	0.245591340160686