chr6.20078_chr6_125352243_125353866_-_2.R 

fitVsDatCorrelation=0.827702654791129
cont.fitVsDatCorrelation=0.241281016092117

fstatistic=3847.63202350159,60,876
cont.fstatistic=1276.83164722078,60,876

residuals=-0.762136955080988,-0.128864397131117,-0.00809439028739342,0.130381754419390,1.554658809572
cont.residuals=-0.893699560412626,-0.330379368250378,-0.123736804368842,0.267188685783611,2.28142203787689

predictedValues:
Include	Exclude	Both
chr6.20078_chr6_125352243_125353866_-_2.R.tl.Lung	69.1747024336443	49.2274427673123	67.8681376319968
chr6.20078_chr6_125352243_125353866_-_2.R.tl.cerebhem	134.552516058073	54.6549021081784	136.943895091792
chr6.20078_chr6_125352243_125353866_-_2.R.tl.cortex	115.754318472671	46.1228428488792	128.991386671334
chr6.20078_chr6_125352243_125353866_-_2.R.tl.heart	63.3519629519259	48.6900134321893	59.4872797262844
chr6.20078_chr6_125352243_125353866_-_2.R.tl.kidney	72.305787503319	50.3391841066182	68.456901446734
chr6.20078_chr6_125352243_125353866_-_2.R.tl.liver	71.7408452230827	51.0287361940601	63.5452236919164
chr6.20078_chr6_125352243_125353866_-_2.R.tl.stomach	65.1955866068564	48.1187483329227	67.1195877829086
chr6.20078_chr6_125352243_125353866_-_2.R.tl.testicle	66.713691037917	50.8953351795663	63.6002152829835


diffExp=19.947259666332,79.8976139498948,69.6314756237918,14.6619495197367,21.9666033967007,20.7121090290226,17.0768382739337,15.8183558583507
diffExpScore=0.996164352954703
diffExp1.5=0,1,1,0,0,0,0,0
diffExp1.5Score=0.666666666666667
diffExp1.4=1,1,1,0,1,1,0,0
diffExp1.4Score=0.833333333333333
diffExp1.3=1,1,1,1,1,1,1,1
diffExp1.3Score=0.888888888888889
diffExp1.2=1,1,1,1,1,1,1,1
diffExp1.2Score=0.888888888888889

cont.predictedValues:
Include	Exclude	Both
Lung	83.814149145713	77.3769763881704	73.2128723708285
cerebhem	68.9157577877042	75.967525522433	68.8753047569742
cortex	79.2857193698057	80.0365813450309	71.9457884666805
heart	75.7530425239115	75.5131753585331	71.3684273866278
kidney	70.6205737996701	83.9083252767382	68.6437581391
liver	70.9617235653508	79.6555291374443	88.841818436166
stomach	77.9065969680681	80.001546328773	80.8028036458468
testicle	78.1563018085863	84.7795443383808	82.8747939734597
cont.diffExp=6.43717275754256,-7.05176773472878,-0.750861975225149,0.239867165378385,-13.2877514770680,-8.69380557209345,-2.09494936070485,-6.62324252979454
cont.diffExpScore=1.37635803087069

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=0.319531998612991
cont.tran.correlation=-0.00471468313123442

tran.covariance=0.00376431350426075
cont.tran.covariance=2.38940513239799e-05

tran.mean=66.116663453576
cont.tran.mean=77.6658167915196

weightedLogRatios:
wLogRatio
Lung	1.38337284737397
cerebhem	4.01042315419592
cortex	3.9487718104956
heart	1.05742639683747
kidney	1.48463711054697
liver	1.39768062246998
stomach	1.22263411282269
testicle	1.10017177483422

cont.weightedLogRatios:
wLogRatio
Lung	0.35070791793933
cerebhem	-0.417117717638465
cortex	-0.041263853670981
heart	0.0137193954720506
kidney	-0.748837822521559
liver	-0.499257415922841
stomach	-0.115926970458470
testicle	-0.357861610976574

varWeightedLogRatios=1.59015306824351
cont.varWeightedLogRatios=0.119747959685719

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.64211423461441	0.127431898552806	28.5808677103338	1.85514789733579e-127	***
df.mm.trans1	0.53713387911992	0.109813735263627	4.89131781038533	1.19164179875188e-06	***
df.mm.trans2	0.241876932056164	0.0967914752149787	2.49894870926332	0.0126383421581721	*  
df.mm.exp2	0.0679023686603736	0.123992321841963	0.547633657081765	0.584082974033724	   
df.mm.exp3	-0.192487099213130	0.123992321841963	-1.55241144252842	0.120924993175824	   
df.mm.exp4	0.0328975328707012	0.123992321841963	0.265319113167599	0.79082606368518	   
df.mm.exp5	0.0579637833197386	0.123992321841963	0.467478812064004	0.640273612177639	   
df.mm.exp6	0.138177544354674	0.123992321841963	1.11440403971781	0.265411543862215	   
df.mm.exp7	-0.0709320664070784	0.123992321841963	-0.572068216429451	0.567422529598321	   
df.mm.exp8	0.0620448103691813	0.123992321841963	0.500392358554763	0.616924518076381	   
df.mm.trans1:exp2	0.597416984119749	0.114315272358495	5.2260469821236	2.16582505502383e-07	***
df.mm.trans2:exp2	0.0366852941771866	0.0831765780979985	0.441053178864416	0.659283328667029	   
df.mm.trans1:exp3	0.707321876084883	0.114315272358495	6.18746613196799	9.37657418170947e-10	***
df.mm.trans2:exp3	0.127344185155874	0.0831765780979985	1.53101014814336	0.126127910090766	   
df.mm.trans1:exp4	-0.120826864777820	0.114315272358495	-1.05696170148556	0.290820455161400	   
df.mm.trans2:exp4	-0.0438748346248458	0.0831765780979985	-0.527490257812151	0.597986749009487	   
df.mm.trans1:exp5	-0.0136948329212453	0.114315272358495	-0.119798804120399	0.904669997982475	   
df.mm.trans2:exp5	-0.0356312492198295	0.0831765780979985	-0.428380801838817	0.66847920653343	   
df.mm.trans1:exp6	-0.101752514583064	0.114315272358495	-0.890104292136626	0.373654269664139	   
df.mm.trans2:exp6	-0.102239863346238	0.0831765780979985	-1.22919054479230	0.219330440968137	   
df.mm.trans1:exp7	0.0116886189518897	0.114315272358495	0.102248970856965	0.918582458460844	   
df.mm.trans2:exp7	0.0481526979858966	0.0831765780979985	0.578921363285265	0.562791056131487	   
df.mm.trans1:exp8	-0.0982698395917005	0.114315272358495	-0.859638765356955	0.390223383506249	   
df.mm.trans2:exp8	-0.0287247855997344	0.0831765780979985	-0.345347046687721	0.729916389942156	   
df.mm.trans1:probe2	-0.0725866929346137	0.0796355106014359	-0.911486501265741	0.362289847453907	   
df.mm.trans1:probe3	0.293632641510527	0.0796355106014359	3.68720736883468	0.000240684821000258	***
df.mm.trans1:probe4	-0.094397803119838	0.0796355106014359	-1.18537323873373	0.236191360384007	   
df.mm.trans1:probe5	0.253630891116025	0.0796355106014359	3.18489690341047	0.00149924743810904	** 
df.mm.trans1:probe6	-0.185154838264847	0.0796355106014359	-2.32502858167785	0.0202980979615414	*  
df.mm.trans1:probe7	0.26307109830492	0.0796355106014358	3.30343958766778	0.000993780524722315	***
df.mm.trans1:probe8	0.661013769350644	0.0796355106014359	8.30049012505139	3.90164700656553e-16	***
df.mm.trans1:probe9	0.466112788471499	0.0796355106014359	5.85307716308024	6.81649755863261e-09	***
df.mm.trans1:probe10	0.244875911040187	0.0796355106014359	3.07495876137161	0.00217063059581653	** 
df.mm.trans1:probe11	0.480005176676085	0.0796355106014359	6.02752682880934	2.45084065724017e-09	***
df.mm.trans1:probe12	0.288081252102528	0.0796355106014359	3.61749739440151	0.000314482829347379	***
df.mm.trans1:probe13	0.140350824242197	0.0796355106014359	1.76241507315288	0.078347892822823	.  
df.mm.trans1:probe14	0.0462030093054651	0.0796355106014359	0.580180989065349	0.561941771911242	   
df.mm.trans1:probe15	-0.144813527885086	0.0796355106014359	-1.81845418948661	0.0693361178811276	.  
df.mm.trans1:probe16	0.0161208490457388	0.0796355106014359	0.202432921243154	0.839625297897073	   
df.mm.trans1:probe17	-0.0713821151601932	0.0796355106014359	-0.89636036262077	0.370306582941013	   
df.mm.trans1:probe18	-0.183921848955876	0.0796355106014359	-2.30954567336647	0.0211450878916582	*  
df.mm.trans1:probe19	0.229821235235022	0.0796355106014359	2.88591400368165	0.00399864247443378	** 
df.mm.trans1:probe20	-0.0424271375953666	0.0796355106014359	-0.532766567011898	0.594330296749651	   
df.mm.trans1:probe21	-0.335326024199239	0.0796355106014359	-4.21076001982956	2.80816428167269e-05	***
df.mm.trans1:probe22	-0.359134818930304	0.0796355106014358	-4.50973210591593	7.37376466690435e-06	***
df.mm.trans2:probe2	0.121318870602743	0.0796355106014359	1.52342679398298	0.128012865565416	   
df.mm.trans2:probe3	0.00516970083632937	0.0796355106014359	0.0649170300697006	0.948254872134195	   
df.mm.trans2:probe4	-0.0337894426703367	0.0796355106014359	-0.42430119949187	0.671450343145708	   
df.mm.trans2:probe5	0.105650584754442	0.0796355106014359	1.32667680481397	0.184961348173796	   
df.mm.trans2:probe6	0.0134716660228070	0.0796355106014359	0.169166568043128	0.865704679712988	   
df.mm.trans3:probe2	-0.235242118216072	0.0796355106014359	-2.95398518122681	0.00322091288067602	** 
df.mm.trans3:probe3	-0.206210117305845	0.0796355106014359	-2.58942418713050	0.00977318722426292	** 
df.mm.trans3:probe4	-0.667585495463883	0.0796355106014359	-8.3830126839401	2.0437271321105e-16	***
df.mm.trans3:probe5	0.0747273058948748	0.0796355106014359	0.93836663230395	0.348314673614363	   
df.mm.trans3:probe6	-0.161452653292092	0.0796355106014359	-2.02739521694209	0.0429243426649538	*  
df.mm.trans3:probe7	-0.542936513284722	0.0796355106014359	-6.81776897246306	1.72097740855763e-11	***
df.mm.trans3:probe8	-0.438383140394313	0.0796355106014359	-5.50487008978138	4.85389437491721e-08	***
df.mm.trans3:probe9	-0.0495603351941645	0.0796355106014359	-0.622339642451805	0.533880511606366	   
df.mm.trans3:probe10	0.278589312530669	0.0796355106014359	3.49830509563715	0.000491797213285028	***
df.mm.trans3:probe11	-0.291088377703003	0.0796355106014359	-3.65525850847944	0.000272217931943357	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.68990066993049	0.220374642785101	21.2814896063330	2.45623433665588e-81	***
df.mm.trans1	-0.219517051242444	0.189906632141963	-1.15592093212599	0.248028659458566	   
df.mm.trans2	-0.319248904908143	0.167386557191605	-1.90725533916505	0.0568143560162893	.  
df.mm.exp2	-0.153026735521225	0.214426402999050	-0.713656216682899	0.475629873376226	   
df.mm.exp3	-0.00429092521469507	0.21442640299905	-0.0200111793822055	0.984039011435528	   
df.mm.exp4	-0.0999896736278008	0.21442640299905	-0.466312320821068	0.641107894795151	   
df.mm.exp5	-0.0258037059166814	0.21442640299905	-0.120338286497282	0.904242770350028	   
df.mm.exp6	-0.330925242202938	0.21442640299905	-1.54330454447069	0.123118052696211	   
df.mm.exp7	-0.138374919088620	0.21442640299905	-0.645325935394405	0.518884969312847	   
df.mm.exp8	-0.102485833823298	0.21442640299905	-0.477953425463897	0.632802598261079	   
df.mm.trans1:exp2	-0.0426902448729389	0.197691375526714	-0.215943891124224	0.829081755326438	   
df.mm.trans2:exp2	0.134643415073505	0.143841603982992	0.936053348580744	0.349503693007875	   
df.mm.trans1:exp3	-0.0512528834268842	0.197691375526714	-0.259257053021811	0.795497824734394	   
df.mm.trans2:exp3	0.0380854485271086	0.143841603982992	0.264773524992197	0.791246218907146	   
df.mm.trans1:exp4	-0.00113355491353687	0.197691375526714	-0.00573396239728068	0.995426290498434	   
df.mm.trans2:exp4	0.0756075490583149	0.143841603982992	0.525630603140762	0.599277913768385	   
df.mm.trans1:exp5	-0.145476615900130	0.197691375526714	-0.735877402403279	0.462002300164756	   
df.mm.trans2:exp5	0.106839269373874	0.143841603982992	0.742756382127845	0.457828314711821	   
df.mm.trans1:exp6	0.164464031705316	0.197691375526714	0.831923149237693	0.405679044255333	   
df.mm.trans2:exp6	0.359947420411398	0.143841603982992	2.50238742091584	0.0125171159749141	*  
df.mm.trans1:exp7	0.065283716007683	0.197691375526714	0.330230470771656	0.741304782891338	   
df.mm.trans2:exp7	0.171731609025614	0.143841603982992	1.19389386846604	0.232842685767449	   
df.mm.trans1:exp8	0.0325946873293471	0.197691375526714	0.164876627736057	0.869079126933167	   
df.mm.trans2:exp8	0.193850851437848	0.143841603982992	1.34766886679579	0.178113337718728	   
df.mm.trans1:probe2	-0.080579218649839	0.137717850876469	-0.585103660397064	0.558628695969835	   
df.mm.trans1:probe3	-0.0186828681919560	0.137717850876469	-0.135660468654237	0.892120866825836	   
df.mm.trans1:probe4	-0.0562087540941694	0.137717850876469	-0.40814428729786	0.683267485602512	   
df.mm.trans1:probe5	-0.0863955536871156	0.137717850876469	-0.627337365034917	0.53060159171316	   
df.mm.trans1:probe6	-0.0509703060988161	0.137717850876469	-0.370106749229886	0.71139241607874	   
df.mm.trans1:probe7	-0.0976407792209454	0.137717850876469	-0.708991453174273	0.478518419975617	   
df.mm.trans1:probe8	-0.245642107442396	0.137717850876469	-1.78366207342818	0.0748246957323295	.  
df.mm.trans1:probe9	0.00479195337078079	0.137717850876469	0.0347954411159023	0.972250782710559	   
df.mm.trans1:probe10	-0.132253483668754	0.137717850876469	-0.960322012194222	0.337158157802553	   
df.mm.trans1:probe11	-0.0880110430667384	0.137717850876469	-0.639067793366041	0.522945892847687	   
df.mm.trans1:probe12	-0.134200550946804	0.137717850876469	-0.974460101524388	0.330097145444635	   
df.mm.trans1:probe13	-0.0851503838999988	0.137717850876469	-0.618295909775543	0.536541018390642	   
df.mm.trans1:probe14	-0.0289687773351593	0.137717850876469	-0.210348746736862	0.833444407385415	   
df.mm.trans1:probe15	-0.039269134169486	0.137717850876469	-0.285141932723812	0.775602805931993	   
df.mm.trans1:probe16	-0.170263659825637	0.137717850876469	-1.23632237028126	0.216670140609413	   
df.mm.trans1:probe17	-0.106096546812068	0.137717850876469	-0.770390665675108	0.441275900482542	   
df.mm.trans1:probe18	-0.0404541351459785	0.137717850876469	-0.293746488843086	0.769021208503398	   
df.mm.trans1:probe19	0.0482119140114821	0.137717850876469	0.350077449688985	0.726364726380962	   
df.mm.trans1:probe20	-0.0451096832091523	0.137717850876469	-0.327551460628115	0.743329089725698	   
df.mm.trans1:probe21	0.139580177891764	0.137717850876469	1.01352277140140	0.311090376251319	   
df.mm.trans1:probe22	-0.0654858404542353	0.137717850876469	-0.475507278377262	0.634543992981036	   
df.mm.trans2:probe2	-0.165809264508031	0.137717850876469	-1.20397801340046	0.228923299561904	   
df.mm.trans2:probe3	0.166244909876582	0.137717850876469	1.20714133148724	0.227703567533375	   
df.mm.trans2:probe4	-0.177129701750367	0.137717850876469	-1.28617823051312	0.198720704569745	   
df.mm.trans2:probe5	-0.112752991888231	0.137717850876469	-0.818724596489452	0.413166223319803	   
df.mm.trans2:probe6	-0.083915304894232	0.137717850876469	-0.609327725927868	0.542465228614677	   
df.mm.trans3:probe2	0.0618961972765183	0.137717850876469	0.449442079458809	0.653223959298082	   
df.mm.trans3:probe3	0.329935936650582	0.137717850876469	2.39573834873832	0.0167958788167227	*  
df.mm.trans3:probe4	0.111355517989505	0.137717850876469	0.80857722714094	0.418977903389316	   
df.mm.trans3:probe5	0.113838320969814	0.137717850876469	0.826605412771984	0.408685835682311	   
df.mm.trans3:probe6	0.340821442802682	0.137717850876469	2.47478043429819	0.0135201228755130	*  
df.mm.trans3:probe7	0.102956403484693	0.137717850876469	0.747589385322634	0.454908498463416	   
df.mm.trans3:probe8	0.086513264460778	0.137717850876469	0.628192089189508	0.530041849032938	   
df.mm.trans3:probe9	0.191364589936400	0.137717850876469	1.38954092529408	0.165021380679804	   
df.mm.trans3:probe10	0.121272045719110	0.137717850876469	0.880583344477904	0.378784897529489	   
df.mm.trans3:probe11	0.104648262374606	0.137717850876469	0.759874349683793	0.447534141531028