chr17.10313_chr17_34912345_34912928_+_2.R 

fitVsDatCorrelation=0.892313568400547
cont.fitVsDatCorrelation=0.293244494500091

fstatistic=10202.7080049086,51,669
cont.fstatistic=2264.48376476276,51,669

residuals=-0.519875369510566,-0.0864975069467043,-0.00517905727197021,0.0821424417451888,0.748760524166723
cont.residuals=-0.568825850235504,-0.217453830321501,-0.0581137521048997,0.143730332349898,1.30366990414381

predictedValues:
Include	Exclude	Both
chr17.10313_chr17_34912345_34912928_+_2.R.tl.Lung	56.3403792261867	54.4520297582949	102.414374958211
chr17.10313_chr17_34912345_34912928_+_2.R.tl.cerebhem	54.7511666747671	51.3528976344704	85.2270792487916
chr17.10313_chr17_34912345_34912928_+_2.R.tl.cortex	70.3189226622158	52.5313400105282	167.704340357181
chr17.10313_chr17_34912345_34912928_+_2.R.tl.heart	74.5751917366955	50.6419078386137	191.215187510210
chr17.10313_chr17_34912345_34912928_+_2.R.tl.kidney	54.8060529092206	50.0773866673886	85.3194114184869
chr17.10313_chr17_34912345_34912928_+_2.R.tl.liver	53.1521405373918	47.6033156444786	77.4515782362665
chr17.10313_chr17_34912345_34912928_+_2.R.tl.stomach	54.6305992823404	47.5720166893225	82.4873846244732
chr17.10313_chr17_34912345_34912928_+_2.R.tl.testicle	57.1588521542443	49.786056049525	92.2257503594261


diffExp=1.88834946789176,3.39826904029673,17.7875826516876,23.9332838980818,4.72866624183199,5.54882489291321,7.05858259301787,7.37279610471928
diffExpScore=0.986247935536556
diffExp1.5=0,0,0,0,0,0,0,0
diffExp1.5Score=0
diffExp1.4=0,0,0,1,0,0,0,0
diffExp1.4Score=0.5
diffExp1.3=0,0,1,1,0,0,0,0
diffExp1.3Score=0.666666666666667
diffExp1.2=0,0,1,1,0,0,0,0
diffExp1.2Score=0.666666666666667

cont.predictedValues:
Include	Exclude	Both
Lung	70.0966117288163	69.211815104537	63.220900043961
cerebhem	58.73629706395	64.8712399118244	63.6246982083489
cortex	66.400083561107	56.0479001469795	52.8496791888297
heart	62.875235121686	66.45245108988	59.3615834772492
kidney	68.678055117098	63.1482458461643	58.109461164969
liver	65.0223955145211	66.3210033037287	59.6606736838408
stomach	61.1363724185452	59.1595603707594	69.5271619019959
testicle	60.7313496716793	58.1992150514214	66.345452811926
cont.diffExp=0.884796624279232,-6.13494284787443,10.3521834141275,-3.57721596819394,5.5298092709337,-1.29860778920764,1.97681204778588,2.53213462025786
cont.diffExpScore=2.8660976799991

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=0.328293216707641
cont.tran.correlation=0.293011424102714

tran.covariance=0.00209799224341348
cont.tran.covariance=0.00126468221099419

tran.mean=54.9843909672302
cont.tran.mean=63.5679894389186

weightedLogRatios:
wLogRatio
Lung	0.13685521929717
cerebhem	0.254435635522658
cortex	1.19779421534739
heart	1.59389681742598
kidney	0.357196510953940
liver	0.431986211612388
stomach	0.543909709676478
testicle	0.549191273176797

cont.weightedLogRatios:
wLogRatio
Lung	0.0539049276330197
cerebhem	-0.409578893960008
cortex	0.696772040231356
heart	-0.230678721536083
kidney	0.351514631752324
liver	-0.0827503508745026
stomach	0.134652612633874
testicle	0.173979726623072

varWeightedLogRatios=0.251888672985416
cont.varWeightedLogRatios=0.118434090997902

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.24570845594433	0.0821330511213863	39.5176900362246	4.17903097255952e-177	***
df.mm.trans1	0.552021844393446	0.0736856634390834	7.4915773113695	2.16013147672465e-13	***
df.mm.trans2	0.744667195357092	0.067874250015572	10.9712769597638	7.2242164362976e-26	***
df.mm.exp2	0.0964962901820599	0.0930038479559683	1.03755158848637	0.299853727368342	   
df.mm.exp3	-0.30745620974649	0.0930038479559683	-3.30584396778994	0.000997493229547766	***
df.mm.exp4	-0.416516613332622	0.0930038479559682	-4.47848796030265	8.83842581903504e-06	***
df.mm.exp5	0.0712636532056745	0.0930038479559683	0.766244136902954	0.443801327023781	   
df.mm.exp6	0.0867033121547625	0.0930038479559682	0.932255106216803	0.351541016157848	   
df.mm.exp7	0.050488951463346	0.0930038479559683	0.542869489521009	0.587400473819373	   
df.mm.exp8	0.0296253013639647	0.0930038479559682	0.318538447763909	0.750175953341813	   
df.mm.trans1:exp2	-0.125109106039121	0.0888682538384904	-1.40780425669773	0.159653522217022	   
df.mm.trans2:exp2	-0.155095052451107	0.077570571446368	-1.99940582567887	0.0459684340348288	*  
df.mm.trans1:exp3	0.529085649048062	0.0888682538384904	5.95359564518535	4.23518354301423e-09	***
df.mm.trans2:exp3	0.27154602766508	0.077570571446368	3.50063203869558	0.000494980004387254	***
df.mm.trans1:exp4	0.696913021333933	0.0888682538384903	7.84209198709481	1.75410330190400e-14	***
df.mm.trans2:exp4	0.343975938841897	0.077570571446368	4.43436128454617	1.07929581528934e-05	***
df.mm.trans1:exp5	-0.0988745042583396	0.0888682538384904	-1.11259645585064	0.266281409906462	   
df.mm.trans2:exp5	-0.155014237089756	0.077570571446368	-1.99836399551255	0.0460814765115998	*  
df.mm.trans1:exp6	-0.144956428116254	0.0888682538384904	-1.63113847583524	0.103331738831829	   
df.mm.trans2:exp6	-0.221121023101837	0.077570571446368	-2.85057875659352	0.00449837969403819	** 
df.mm.trans1:exp7	-0.081306292731033	0.0888682538384904	-0.914908183959589	0.36056947133091	   
df.mm.trans2:exp7	-0.185564373931186	0.077570571446368	-2.39220068218119	0.0170226900119994	*  
df.mm.trans1:exp8	-0.0152025232350717	0.0888682538384903	-0.171068098881529	0.864221945884597	   
df.mm.trans2:exp8	-0.119210481701082	0.077570571446368	-1.53680035454558	0.124815002052564	   
df.mm.trans1:probe2	0.112715917050784	0.0444341269192452	2.53669701343822	0.0114165299707510	*  
df.mm.trans1:probe3	0.0880147396647991	0.0444341269192452	1.98079147194132	0.0480237946901148	*  
df.mm.trans1:probe4	0.148413006875258	0.0444341269192452	3.34006803250539	0.00088410019393418	***
df.mm.trans1:probe5	0.143302897930927	0.0444341269192452	3.22506388369837	0.00132074094445459	** 
df.mm.trans1:probe6	0.718246501225086	0.0444341269192451	16.1642987276521	7.34889425267948e-50	***
df.mm.trans1:probe7	0.153202668312645	0.0444341269192452	3.44786043824100	0.00060045486434525	***
df.mm.trans1:probe8	0.179431122668874	0.0444341269192452	4.03813769076578	6.01163192779793e-05	***
df.mm.trans1:probe9	0.769607826354636	0.0444341269192452	17.3201968782536	8.38665646221462e-56	***
df.mm.trans1:probe10	0.144850075366014	0.0444341269192452	3.25988345915438	0.00117106052217652	** 
df.mm.trans1:probe11	0.0807637970787346	0.0444341269192452	1.81760738149565	0.0695713435014728	.  
df.mm.trans1:probe12	0.152748881826379	0.0444341269192452	3.43764787151069	0.000623148431983311	***
df.mm.trans1:probe13	0.451686505005614	0.0444341269192452	10.1653061806866	1.13780673691570e-22	***
df.mm.trans1:probe14	0.190144753129387	0.0444341269192452	4.27925034906069	2.14909941293252e-05	***
df.mm.trans1:probe15	0.0883287277447134	0.0444341269192451	1.98785784415754	0.0472346037373668	*  
df.mm.trans1:probe16	0.427370068092385	0.0444341269192452	9.61805930988786	1.34077996293038e-20	***
df.mm.trans1:probe17	0.432452522204331	0.0444341269192452	9.73244108048467	5.02728587713013e-21	***
df.mm.trans1:probe18	0.282336111317832	0.0444341269192452	6.3540375583603	3.87811906803110e-10	***
df.mm.trans1:probe19	0.413391348618069	0.0444341269192452	9.30346509045556	1.90467511216824e-19	***
df.mm.trans1:probe20	0.345410111539872	0.0444341269192452	7.77353209094492	2.88734115883616e-14	***
df.mm.trans1:probe21	0.285931052802238	0.0444341269192452	6.43494252338728	2.35474803422572e-10	***
df.mm.trans2:probe2	-0.0493825676077367	0.0444341269192452	-1.11136576842131	0.266810183056086	   
df.mm.trans2:probe3	0.145998249469839	0.0444341269192452	3.28572337508008	0.00107031152313690	** 
df.mm.trans2:probe4	0.0156000355908372	0.0444341269192452	0.35108230255517	0.725637136387609	   
df.mm.trans2:probe5	-0.0374578662123598	0.0444341269192452	-0.84299768690034	0.399531026291695	   
df.mm.trans2:probe6	-0.0122575775569261	0.0444341269192452	-0.275859534254000	0.782741144269768	   
df.mm.trans3:probe2	0.116707891507921	0.0444341269192452	2.62653729463451	0.00882330196043258	** 
df.mm.trans3:probe3	0.143180871020299	0.0444341269192452	3.22231764068452	0.00133326903365688	** 

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.61690853472163	0.173946554631464	26.5421096985988	1.36934485832911e-106	***
df.mm.trans1	-0.162721447493509	0.156056144340956	-1.04271093061219	0.29745883904083	   
df.mm.trans2	-0.33989091933982	0.143748366549226	-2.36448543728965	0.0183397301925943	*  
df.mm.exp2	-0.247950567600859	0.196969413634711	-1.25882776937487	0.208531630528906	   
df.mm.exp3	-0.0859577434737026	0.196969413634711	-0.436401479232279	0.662686264998332	   
df.mm.exp4	-0.0864193369224058	0.196969413634711	-0.438744957035179	0.660988001440976	   
df.mm.exp5	-0.0278248061649677	0.196969413634711	-0.141264603734720	0.887703437119649	   
df.mm.exp6	-0.0598457764290963	0.196969413634711	-0.303832840463662	0.761349717703679	   
df.mm.exp7	-0.388783407223412	0.196969413634711	-1.97382629134708	0.0488125222654659	*  
df.mm.exp8	-0.364954424940458	0.196969413634711	-1.85284820727183	0.064344300808149	.  
df.mm.trans1:exp2	0.0711339939073496	0.188210791639453	0.377948539973296	0.705588707352963	   
df.mm.trans2:exp2	0.183183361882939	0.164283847484830	1.11504182965921	0.265232884753385	   
df.mm.trans1:exp3	0.0317816003576311	0.188210791639453	0.168861732532923	0.865956441084384	   
df.mm.trans2:exp3	-0.125007158189686	0.164283847484830	-0.760921783264355	0.446971898989103	   
df.mm.trans1:exp4	-0.0223027532028409	0.188210791639453	-0.118498801309785	0.905708015534777	   
df.mm.trans2:exp4	0.0457344210754868	0.164283847484830	0.278386595978099	0.780801628813758	   
df.mm.trans1:exp5	0.00738006570644535	0.188210791639453	0.0392117032299774	0.968733301255235	   
df.mm.trans2:exp5	-0.0638617095532664	0.164283847484830	-0.38872786662221	0.697601149295098	   
df.mm.trans1:exp6	-0.0152969246885667	0.188210791639453	-0.0812754919912898	0.935247172482314	   
df.mm.trans2:exp6	0.0171808288100594	0.164283847484830	0.104580146332681	0.916740314391434	   
df.mm.trans1:exp7	0.252015931502017	0.188210791639453	1.33900893411464	0.181022543374501	   
df.mm.trans2:exp7	0.231850027293384	0.164283847484830	1.41127707223191	0.158627809035417	   
df.mm.trans1:exp8	0.221540000689267	0.188210791639453	1.17708447405960	0.239580399849962	   
df.mm.trans2:exp8	0.191654705943584	0.164283847484830	1.16660711858043	0.243784751724057	   
df.mm.trans1:probe2	-0.255083754454817	0.0941053958197266	-2.71061773060781	0.00688802175775342	** 
df.mm.trans1:probe3	-0.301170037083832	0.0941053958197266	-3.20034823147409	0.00143751822986047	** 
df.mm.trans1:probe4	-0.179383021971602	0.0941053958197266	-1.90619273644243	0.0570534494946031	.  
df.mm.trans1:probe5	-0.253962142957682	0.0941053958197266	-2.69869905700397	0.00713679943621647	** 
df.mm.trans1:probe6	-0.279430071153602	0.0941053958197265	-2.96933102209032	0.00309127924383334	** 
df.mm.trans1:probe7	-0.28901308694721	0.0941053958197266	-3.07116382041322	0.00221870616659265	** 
df.mm.trans1:probe8	-0.273033425334234	0.0941053958197266	-2.90135781222653	0.00383757666683784	** 
df.mm.trans1:probe9	-0.284943613188125	0.0941053958197266	-3.02792003270438	0.00255714467368511	** 
df.mm.trans1:probe10	-0.25961870548332	0.0941053958197266	-2.75880785816639	0.00595984593675023	** 
df.mm.trans1:probe11	-0.220930273864229	0.0941053958197266	-2.34768975721068	0.0191806622254018	*  
df.mm.trans1:probe12	-0.169507396786765	0.0941053958197266	-1.80125055859159	0.0721135703791144	.  
df.mm.trans1:probe13	-0.228727865428628	0.0941053958197266	-2.43054995344573	0.0153377472837263	*  
df.mm.trans1:probe14	-0.223300015822910	0.0941053958197266	-2.37287154342006	0.0179320906249157	*  
df.mm.trans1:probe15	-0.161587311550371	0.0941053958197265	-1.71708869765466	0.0864257946838643	.  
df.mm.trans1:probe16	-0.175890866220091	0.0941053958197266	-1.86908375112769	0.0620478782847552	.  
df.mm.trans1:probe17	-0.217479354139620	0.0941053958197266	-2.31101896172070	0.0211349359357549	*  
df.mm.trans1:probe18	-0.234434877630140	0.0941053958197266	-2.49119485219780	0.0129726825822034	*  
df.mm.trans1:probe19	-0.399369381384903	0.0941053958197266	-4.24385209696112	2.50745925358576e-05	***
df.mm.trans1:probe20	-0.292327656290585	0.0941053958197266	-3.10638570449864	0.00197400486982713	** 
df.mm.trans1:probe21	-0.204310242628600	0.0941053958197266	-2.17107893600477	0.0302760536810675	*  
df.mm.trans2:probe2	-0.0455526359180852	0.0941053958197266	-0.484059766406469	0.628501869702794	   
df.mm.trans2:probe3	0.00793036777199886	0.0941053958197266	0.0842711271008381	0.932866078506807	   
df.mm.trans2:probe4	-0.180570980966652	0.0941053958197266	-1.91881644398546	0.0554327671182014	.  
df.mm.trans2:probe5	0.0150787008264979	0.0941053958197266	0.160232053594286	0.872746648119796	   
df.mm.trans2:probe6	-0.155499711161074	0.0941053958197266	-1.65239952296633	0.0989223417856978	.  
df.mm.trans3:probe2	0.0595910568691843	0.0941053958197266	0.633237407378214	0.526795025862805	   
df.mm.trans3:probe3	0.0374252696141834	0.0941053958197266	0.397695257409865	0.69098169724067