chr4.16708_chr4_129834828_129845552_+_2.R 

fitVsDatCorrelation=0.88553693578308
cont.fitVsDatCorrelation=0.270696012540847

fstatistic=13390.1527354215,53,715
cont.fstatistic=3108.07900685934,53,715

residuals=-0.442701771224228,-0.0771312133209626,-0.00901828757843274,0.074135838649077,0.762399600020074
cont.residuals=-0.675124871927201,-0.206852795767794,-0.0335675885005279,0.186031687717743,0.938837846751469

predictedValues:
Include	Exclude	Both
chr4.16708_chr4_129834828_129845552_+_2.R.tl.Lung	68.1364153770439	61.324706810548	51.3209087594442
chr4.16708_chr4_129834828_129845552_+_2.R.tl.cerebhem	69.1245673728786	67.1186881541769	46.9988447120609
chr4.16708_chr4_129834828_129845552_+_2.R.tl.cortex	70.7962350117854	66.1986799279594	56.7385366377335
chr4.16708_chr4_129834828_129845552_+_2.R.tl.heart	73.1908057111597	72.7741953587007	57.5198478641231
chr4.16708_chr4_129834828_129845552_+_2.R.tl.kidney	72.5957465179047	63.4232393272539	55.9929326509054
chr4.16708_chr4_129834828_129845552_+_2.R.tl.liver	72.2390898442631	65.944826140771	60.0698871818797
chr4.16708_chr4_129834828_129845552_+_2.R.tl.stomach	71.5882465104732	83.4579482938583	54.608379950792
chr4.16708_chr4_129834828_129845552_+_2.R.tl.testicle	74.645371679744	68.8430774646888	53.5203398615893


diffExp=6.8117085664959,2.00587921870164,4.59755508382597,0.416610352459031,9.17250719065088,6.29426370349213,-11.8697017833851,5.80229421505528
diffExpScore=1.93843812448287
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	62.2066034156023	59.3121334530003	61.923590098948
cerebhem	61.9195024884773	67.2829561120388	56.6020749278298
cortex	63.7694446510348	63.2220736847693	59.9998332427817
heart	61.6087570558622	67.6435085816282	55.1675766279093
kidney	65.8601843972631	62.2821355422503	62.0767875886833
liver	64.3022745987155	60.6296768307962	68.9292437133523
stomach	64.8494138188895	56.1357938408495	68.6501384882048
testicle	62.8986022059041	59.2056972971588	55.2259139935993
cont.diffExp=2.89446996260200,-5.36345362356144,0.547370966265447,-6.03475152576605,3.57804885501285,3.67259776791929,8.71361997803999,3.69290490874528
cont.diffExpScore=2.71614369088892

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=0.302193824556149
cont.tran.correlation=-0.513227216731345

tran.covariance=0.00095316531243922
cont.tran.covariance=-0.0007846804428092

tran.mean=70.0876149689506
cont.tran.mean=62.69554737339

weightedLogRatios:
wLogRatio
Lung	0.439100496672853
cerebhem	0.124304162084886
cortex	0.283771691683822
heart	0.0244901597254832
kidney	0.56966519099253
liver	0.386020108697502
stomach	-0.666979611658896
testicle	0.345708707238154

cont.weightedLogRatios:
wLogRatio
Lung	0.195670033899921
cerebhem	-0.346190839854026
cortex	0.0357839827915023
heart	-0.389444518872072
kidney	0.232353174241779
liver	0.243133830318581
stomach	0.591594893513889
testicle	0.248757235333689

varWeightedLogRatios=0.149108316696539
cont.varWeightedLogRatios=0.107671511052889

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	5.15892990779462	0.0697542875833716	73.9586065104395	0	***
df.mm.trans1	-0.436414086051962	0.0619431573487099	-7.04539621051544	4.35657405444207e-12	***
df.mm.trans2	-0.945615535174651	0.0563453567243192	-16.7824926515465	1.52268605235437e-53	***
df.mm.exp2	0.192653331536161	0.0759619139476313	2.53618322030403	0.0114185170011829	*  
df.mm.exp3	0.0144163391424715	0.0759619139476313	0.189783779703211	0.849532431132075	   
df.mm.exp4	0.128704806521952	0.0759619139476313	1.6943333814717	0.0906374264117233	.  
df.mm.exp5	0.00991483124293698	0.0759619139476313	0.130523715473682	0.896188805716841	   
df.mm.exp6	-0.0263053019666858	0.0759619139476313	-0.346295934365488	0.729222202722448	   
df.mm.exp7	0.295490081399335	0.0759619139476313	3.88997677971948	0.000109606848266609	***
df.mm.exp8	0.164920064719078	0.0759619139476313	2.1710888542484	0.0302526988739239	*  
df.mm.trans1:exp2	-0.178254934447	0.0721294010655194	-2.47132142806898	0.0136934198787750	*  
df.mm.trans2:exp2	-0.102373623571775	0.0607383912477036	-1.68548460814963	0.0923314366073745	.  
df.mm.trans1:exp3	0.0238776782300212	0.0721294010655194	0.331039463482189	0.740711668910326	   
df.mm.trans2:exp3	0.0620613737156685	0.0607383912477036	1.02178165145286	0.307229842281125	   
df.mm.trans1:exp4	-0.0571468025960125	0.0721294010655194	-0.792281673656249	0.428459238671375	   
df.mm.trans2:exp4	0.0424738172658741	0.0607383912477036	0.699291113797485	0.484597538514801	   
df.mm.trans1:exp5	0.0534796968502763	0.0721294010655194	0.741441022111046	0.458669531839432	   
df.mm.trans2:exp5	0.0237327047191909	0.0607383912477036	0.390736472133483	0.696108429620037	   
df.mm.trans1:exp6	0.0847748078274461	0.0721294010655194	1.17531556584589	0.240259718751376	   
df.mm.trans2:exp6	0.0989409175925538	0.0607383912477036	1.62896836020981	0.103760196584718	   
df.mm.trans1:exp7	-0.246070979902832	0.0721294010655194	-3.41152118647584	0.000682353015121824	***
df.mm.trans2:exp7	0.0126700011337846	0.0607383912477036	0.208599550852668	0.834820271044614	   
df.mm.trans1:exp8	-0.0736833470408719	0.0721294010655194	-1.02154386356184	0.307342346626509	   
df.mm.trans2:exp8	-0.0492731989953402	0.0607383912477036	-0.811236484588371	0.41749983669215	   
df.mm.trans1:probe2	-0.471457909937628	0.0395069000229221	-11.9335586863076	4.58149325607137e-30	***
df.mm.trans1:probe3	-0.719922944388766	0.0395069000229221	-18.2227141074360	3.13476543420659e-61	***
df.mm.trans1:probe4	-0.689976577545596	0.0395069000229221	-17.4647106491592	3.73907313844131e-57	***
df.mm.trans1:probe5	-0.838128195095918	0.0395069000229221	-21.2147294424425	7.4899501576033e-78	***
df.mm.trans1:probe6	-0.671349655513423	0.0395069000229221	-16.9932253637694	1.18553331169165e-54	***
df.mm.trans1:probe7	-0.648548081385194	0.0395069000229222	-16.4160711422284	1.24783396886405e-51	***
df.mm.trans1:probe8	-0.590311587518915	0.0395069000229221	-14.9419870244543	3.91600516610659e-44	***
df.mm.trans1:probe9	-0.942085455182584	0.0395069000229221	-23.8460991532107	6.2670266056304e-93	***
df.mm.trans1:probe10	-0.5473760626562	0.0395069000229221	-13.8552015556424	7.67557715364656e-39	***
df.mm.trans1:probe11	-0.347054202977748	0.0395069000229221	-8.7846478153534	1.15267241296512e-17	***
df.mm.trans1:probe12	-0.328944789108354	0.0395069000229221	-8.32626171421948	4.2378132808276e-16	***
df.mm.trans1:probe13	-0.243780695349893	0.0395069000229221	-6.17058527012876	1.13900743498759e-09	***
df.mm.trans1:probe14	-0.222578932843871	0.0395069000229221	-5.63392553489971	2.53401336296481e-08	***
df.mm.trans1:probe15	-0.288298780706652	0.0395069000229222	-7.29742856410854	7.81946295296549e-13	***
df.mm.trans1:probe16	-0.319932427916274	0.0395069000229221	-8.09814052053305	2.40599271386434e-15	***
df.mm.trans1:probe17	-0.79611700181565	0.0395069000229222	-20.151340686152	7.30958790008443e-72	***
df.mm.trans1:probe18	-0.864187185569748	0.0395069000229221	-21.8743354975546	1.33153158707432e-81	***
df.mm.trans1:probe19	-0.90001084938314	0.0395069000229222	-22.7811052970734	8.58611405415602e-87	***
df.mm.trans1:probe20	-0.864430330469487	0.0395069000229221	-21.8804899895446	1.22814900816134e-81	***
df.mm.trans1:probe21	-0.875418578079473	0.0395069000229222	-22.1586248875905	3.1698385049872e-83	***
df.mm.trans1:probe22	-0.856194214912207	0.0395069000229221	-21.6720171518251	1.89291863860808e-80	***
df.mm.trans2:probe2	-0.237975571201923	0.0395069000229222	-6.02364576982371	2.72792761085194e-09	***
df.mm.trans2:probe3	-0.0452937613892204	0.0395069000229221	-1.14647723215288	0.251981270301504	   
df.mm.trans2:probe4	-0.146392295833661	0.0395069000229221	-3.70548678202348	0.00022727682934654	***
df.mm.trans2:probe5	-0.207619283322777	0.0395069000229222	-5.25526637631187	1.95317899955420e-07	***
df.mm.trans2:probe6	-0.334034722244663	0.0395069000229222	-8.45509827525961	1.56260961540068e-16	***
df.mm.trans3:probe2	0.524309411532752	0.0395069000229222	13.2713376961631	4.31541835555387e-36	***
df.mm.trans3:probe3	0.079126656220717	0.0395069000229221	2.00285661934516	0.0455697358615967	*  
df.mm.trans3:probe4	0.0413557751589808	0.0395069000229221	1.04679879046409	0.295546125761041	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.05065171478014	0.144542588877882	28.0239322280463	3.47670127077039e-117	***
df.mm.trans1	-0.00703081308073938	0.128356616297618	-0.0547756187685499	0.956332526161177	   
df.mm.trans2	0.0170923127568022	0.116757034074023	0.146392145812524	0.883653091113086	   
df.mm.exp2	0.21132265508244	0.157405832365306	1.34253383058897	0.179849045781688	   
df.mm.exp3	0.120212028535191	0.157405832365306	0.763707587760816	0.44529344590813	   
df.mm.exp4	0.237306166205915	0.157405832365306	1.50760720006344	0.132096785678550	   
df.mm.exp5	0.103462736778134	0.157405832365306	0.657299257742992	0.511200040816763	   
df.mm.exp6	-0.0520748772798881	0.157405832365306	-0.330831942485036	0.740868357434792	   
df.mm.exp7	-0.116555479915881	0.157405832365306	-0.740477517029866	0.459253384102968	   
df.mm.exp8	0.123735569300309	0.157405832365306	0.786092658962879	0.43207364026503	   
df.mm.trans1:exp2	-0.215948618928149	0.149464222564960	-1.44481813254201	0.148947065893336	   
df.mm.trans2:exp2	-0.085229599349693	0.125860138772511	-0.677177064803204	0.498512652866072	   
df.mm.trans1:exp3	-0.0953990352182198	0.149464222564960	-0.638273384633956	0.523500107466875	   
df.mm.trans2:exp3	-0.0563724176205958	0.125860138772511	-0.447897310223752	0.654362985654944	   
df.mm.trans1:exp4	-0.246963304120542	0.149464222564960	-1.65232387980480	0.0989075750070362	.  
df.mm.trans2:exp4	-0.105868668541565	0.125860138772511	-0.841161225262272	0.400538842636374	   
df.mm.trans1:exp5	-0.0463898183449498	0.149464222564960	-0.310374065103025	0.756366962537115	   
df.mm.trans2:exp5	-0.0546019974483109	0.125860138772511	-0.433830742448192	0.664542222262431	   
df.mm.trans1:exp6	0.0852087243353223	0.149464222564960	0.570094453863626	0.568792723634262	   
df.mm.trans2:exp6	0.0740454707401733	0.125860138772511	0.588315502130572	0.556506325250632	   
df.mm.trans1:exp7	0.158162193259161	0.149464222564960	1.05819433269672	0.290324222721921	   
df.mm.trans2:exp7	0.0615152289419282	0.125860138772511	0.488758629553996	0.625162466615671	   
df.mm.trans1:exp8	-0.112672786670579	0.149464222564960	-0.753844530396624	0.451190755900803	   
df.mm.trans2:exp8	-0.125531690335968	0.125860138772511	-0.997390369661543	0.318912482461772	   
df.mm.trans1:probe2	0.0856931262656903	0.0818649262388011	1.04676239511561	0.295562903935175	   
df.mm.trans1:probe3	-0.0591012714269087	0.0818649262388011	-0.721936415779689	0.470569599059035	   
df.mm.trans1:probe4	0.187668919851252	0.0818649262388011	2.29242153475860	0.0221709415690634	*  
df.mm.trans1:probe5	0.113177164864274	0.0818649262388011	1.38248661623581	0.167253996354707	   
df.mm.trans1:probe6	0.135703890794171	0.0818649262388011	1.65765605649384	0.0978255552937944	.  
df.mm.trans1:probe7	0.105645900950298	0.0818649262388011	1.29049039441052	0.197297598091811	   
df.mm.trans1:probe8	0.145768029271013	0.0818649262388011	1.78059195760839	0.07540365491595	.  
df.mm.trans1:probe9	0.196191160445278	0.0818649262388011	2.39652277793527	0.0168073381331106	*  
df.mm.trans1:probe10	0.114185826337560	0.0818649262388011	1.39480766164106	0.163507000488138	   
df.mm.trans1:probe11	0.106688946924926	0.0818649262388011	1.30323145486888	0.192915261183924	   
df.mm.trans1:probe12	0.096061450640666	0.0818649262388011	1.17341400101496	0.241020560844946	   
df.mm.trans1:probe13	0.0316316569660866	0.0818649262388011	0.3863883890131	0.69932400218049	   
df.mm.trans1:probe14	0.153005009891649	0.0818649262388011	1.86899343737673	0.0620323566083043	.  
df.mm.trans1:probe15	0.064439911280033	0.0818649262388011	0.787149201015108	0.431455366928895	   
df.mm.trans1:probe16	0.114125051751535	0.0818649262388011	1.39406528528017	0.163730956690502	   
df.mm.trans1:probe17	0.126120937111516	0.0818649262388011	1.54059794476110	0.123857097406081	   
df.mm.trans1:probe18	0.0432636312440262	0.0818649262388011	0.528475786050616	0.597333141433829	   
df.mm.trans1:probe19	0.0608241553137899	0.0818649262388011	0.742981861809354	0.457736701054508	   
df.mm.trans1:probe20	0.230978766748135	0.0818649262388011	2.82146185625779	0.00491316212319936	** 
df.mm.trans1:probe21	0.0790289814115942	0.0818649262388011	0.965358243664272	0.334691800461745	   
df.mm.trans1:probe22	0.126745426229354	0.0818649262388011	1.54822623133667	0.122010322388616	   
df.mm.trans2:probe2	0.107894988325983	0.0818649262388011	1.31796354413429	0.187937944688214	   
df.mm.trans2:probe3	0.0427981126115598	0.0818649262388011	0.522789362647407	0.601282796331093	   
df.mm.trans2:probe4	-0.0772621083123834	0.0818649262388011	-0.943775458698988	0.345603195492652	   
df.mm.trans2:probe5	0.00427203004005325	0.0818649262388011	0.0521838867550149	0.958396747462678	   
df.mm.trans2:probe6	0.0729956661924816	0.0818649262388011	0.891659829748728	0.372875253772435	   
df.mm.trans3:probe2	0.0746454563518296	0.0818649262388011	0.9118124181055	0.362174787688476	   
df.mm.trans3:probe3	0.0935500989714486	0.0818649262388011	1.14273722911032	0.253530204116367	   
df.mm.trans3:probe4	0.0925564157914743	0.0818649262388011	1.13059914720360	0.258602946506071