chr8.23243_chr8_70253071_70255638_-_2.R 

fitVsDatCorrelation=0.852722130467893
cont.fitVsDatCorrelation=0.351549388670315

fstatistic=10663.5143996607,42,462
cont.fstatistic=3312.43420454648,42,462

residuals=-0.384920528425703,-0.0848630759778811,-0.00449408874775196,0.0868580046252804,0.558125888076195
cont.residuals=-0.556642870940714,-0.194246602024316,-0.00101324308599728,0.179603121213628,0.782381755999

predictedValues:
Include	Exclude	Both
chr8.23243_chr8_70253071_70255638_-_2.R.tl.Lung	73.7561612619503	51.5351733734752	59.4086586467896
chr8.23243_chr8_70253071_70255638_-_2.R.tl.cerebhem	66.064769065952	53.933664705138	69.9243515462105
chr8.23243_chr8_70253071_70255638_-_2.R.tl.cortex	78.6178079277593	51.5888843028941	58.2645498977208
chr8.23243_chr8_70253071_70255638_-_2.R.tl.heart	73.6167126961903	51.3287911760539	59.9555211589886
chr8.23243_chr8_70253071_70255638_-_2.R.tl.kidney	80.2440695327084	49.0002152212529	59.4514649808742
chr8.23243_chr8_70253071_70255638_-_2.R.tl.liver	76.4592173614303	48.6763671361839	53.8897567454501
chr8.23243_chr8_70253071_70255638_-_2.R.tl.stomach	77.8382037856638	53.2658886367349	59.4945612445125
chr8.23243_chr8_70253071_70255638_-_2.R.tl.testicle	72.25003194663	48.6778010442909	56.1304305220801


diffExp=22.2209878884751,12.1311043608140,27.0289236248652,22.2879215201364,31.2438543114555,27.7828502252463,24.5723151489289,23.5722309023391
diffExpScore=0.994787327876824
diffExp1.5=0,0,1,0,1,1,0,0
diffExp1.5Score=0.75
diffExp1.4=1,0,1,1,1,1,1,1
diffExp1.4Score=0.875
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	68.2984483745088	65.39058256915	66.8604099945905
cerebhem	65.220868446627	59.0401476752396	60.4787856874139
cortex	68.4466747114109	60.8182023294448	56.498939018721
heart	67.3316553054814	61.7259892628584	69.0428342110377
kidney	68.4010922709501	65.7369965187469	55.2607347452968
liver	64.24089617687	66.9320820979201	65.0079602825917
stomach	70.1828284973972	55.6824335970219	64.755725583142
testicle	61.9804710578797	70.7069283731697	55.1136075084405
cont.diffExp=2.90786580535880,6.18072077138748,7.62847238196617,5.60566604262302,2.66409575220325,-2.69118592105021,14.5003949003752,-8.72645731529005
cont.diffExpScore=1.75113889392746

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=0,0,0,0,0,0,1,0
cont.diffExp1.2Score=0.5

tran.correlation=-0.408108498661863
cont.tran.correlation=-0.675648224712764

tran.covariance=-0.00101630327479342
cont.tran.covariance=-0.00210363145989593

tran.mean=62.9283599483943
cont.tran.mean=65.0085185790423

weightedLogRatios:
wLogRatio
Lung	1.4775628879703
cerebhem	0.829618997288533
cortex	1.75002688141548
heart	1.48523683356316
kidney	2.04128228072318
liver	1.85636797151980
stomach	1.57992181025401
testicle	1.61228901009769

cont.weightedLogRatios:
wLogRatio
Lung	0.182829739954317
cerebhem	0.410990987384826
cortex	0.492393777897236
heart	0.362145905156882
kidney	0.167072541077774
liver	-0.171670099236730
stomach	0.957088980193535
testicle	-0.55227766300147

varWeightedLogRatios=0.128807142190824
cont.varWeightedLogRatios=0.203886011026532

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.14845221431638	0.0760272603342591	54.5653255960747	1.60728877980454e-203	***
df.mm.trans1	0.129966470362866	0.0669933732209732	1.93998994399312	0.0529891026797993	.  
df.mm.trans2	-0.143226752353585	0.0633411412183879	-2.26119627146860	0.0242113653905174	*  
df.mm.exp2	-0.227612597871431	0.0872707863768263	-2.60811902036294	0.00939897634207893	** 
df.mm.exp3	0.0843215189000536	0.0872707863768263	0.966205558592791	0.334446825539148	   
df.mm.exp4	-0.0150681751425958	0.0872707863768262	-0.172660013369571	0.862994288893513	   
df.mm.exp5	0.0331481819511728	0.0872707863768262	0.37983136542442	0.704245138947777	   
df.mm.exp6	0.0764216094342092	0.0872707863768263	0.875683749476354	0.381657024571206	   
df.mm.exp7	0.0854544966801457	0.0872707863768263	0.9791878843759	0.327999615883355	   
df.mm.exp8	-0.0209113371271426	0.0872707863768263	-0.239614400136714	0.810735469128106	   
df.mm.trans1:exp2	0.117483673908005	0.0807970481506223	1.45405898602869	0.146608936665213	   
df.mm.trans2:exp2	0.273102905237047	0.0737572764198782	3.70272491736752	0.000239059651658714	***
df.mm.trans1:exp3	-0.0204878154255942	0.0807970481506223	-0.253571335767127	0.799939545471528	   
df.mm.trans2:exp3	-0.0832798427774134	0.0737572764198782	-1.12910680572485	0.259438709007571	   
df.mm.trans1:exp4	0.0131757155110083	0.0807970481506223	0.163071743492981	0.870533252450323	   
df.mm.trans2:exp4	0.0110554487178439	0.0737572764198782	0.149889600788788	0.8809171288633	   
df.mm.trans1:exp5	0.0511601431589089	0.0807970481506223	0.633193220914902	0.526920774746821	   
df.mm.trans2:exp5	-0.0835880442517281	0.0737572764198782	-1.13328539649277	0.257682177846756	   
df.mm.trans1:exp6	-0.04042865140535	0.0807970481506223	-0.500372876617753	0.617050811782578	   
df.mm.trans2:exp6	-0.133492524212408	0.0737572764198782	-1.80988955520097	0.0709625771215138	.  
df.mm.trans1:exp7	-0.0315866690577535	0.0807970481506223	-0.390938404072256	0.696022981570016	   
df.mm.trans2:exp7	-0.052422911113875	0.0737572764198782	-0.710749008890283	0.477598427227581	   
df.mm.trans1:exp8	0.00027957202211018	0.0807970481506223	0.00346017618847907	0.99724067790379	   
df.mm.trans2:exp8	-0.0361301200914307	0.0737572764198782	-0.489851603057476	0.624471431062438	   
df.mm.trans1:probe2	-0.142917469989887	0.0403985240753112	-3.53769038006091	0.000444446100215943	***
df.mm.trans1:probe3	-0.0133279103245443	0.0403985240753112	-0.329910822972104	0.741616879802978	   
df.mm.trans1:probe4	-0.106987153519737	0.0403985240753112	-2.64829361885327	0.00836676791882588	** 
df.mm.trans1:probe5	0.0483713082961451	0.0403985240753111	1.19735335394855	0.231782833814819	   
df.mm.trans1:probe6	-0.0521473618290525	0.0403985240753112	-1.29082344027814	0.197410468821718	   
df.mm.trans1:probe7	0.105723094433579	0.0403985240753112	2.61700388451048	0.00916135388111388	** 
df.mm.trans1:probe8	0.162184743347637	0.0403985240753112	4.01462051052388	6.94661879712962e-05	***
df.mm.trans1:probe9	0.117254623351473	0.0403985240753112	2.90244819669369	0.00387964203688606	** 
df.mm.trans1:probe10	0.205248585433244	0.0403985240753112	5.08059613887424	5.47128164363051e-07	***
df.mm.trans1:probe11	0.160927333688322	0.0403985240753112	3.98349537196757	7.88787484258178e-05	***
df.mm.trans1:probe12	-0.149142049095443	0.0403985240753112	-3.69176974924658	0.000249286934507176	***
df.mm.trans2:probe2	-0.153081403834961	0.0403985240753112	-3.78928209232559	0.000171074133256818	***
df.mm.trans2:probe3	-0.125250437279639	0.0403985240753112	-3.10037161372891	0.00205091422985881	** 
df.mm.trans2:probe4	-0.101005012824953	0.0403985240753112	-2.50021541966876	0.0127573166439973	*  
df.mm.trans2:probe5	-0.0927003395150374	0.0403985240753112	-2.29464668912718	0.0222009562726283	*  
df.mm.trans2:probe6	-0.0946109901625718	0.0403985240753112	-2.34194174980743	0.0196075868583111	*  
df.mm.trans3:probe2	0.0393052908853787	0.0403985240753112	0.972938783904718	0.331092845218228	   
df.mm.trans3:probe3	-0.191561135232731	0.0403985240753112	-4.74178548888622	2.82650675966642e-06	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.21132134725215	0.136254188620816	30.9078303564811	1.58359404904281e-114	***
df.mm.trans1	0.083804824937582	0.120063878022998	0.698001982923867	0.485527103820372	   
df.mm.trans2	-0.0557016388369576	0.113518437532582	-0.490683628560074	0.623883199541943	   
df.mm.exp2	-0.0479537723594286	0.156404559835451	-0.306600858759358	0.759285330861933	   
df.mm.exp3	0.0980639496801777	0.156404559835451	0.626989071056165	0.530976109714044	   
df.mm.exp4	-0.104049834491763	0.156404559835451	-0.665260876033484	0.506215614864195	   
df.mm.exp5	0.197329771642863	0.156404559835451	1.26166252346139	0.207706863215134	   
df.mm.exp6	-0.00984958916859978	0.156404559835451	-0.0629750768069824	0.949813586938725	   
df.mm.exp7	-0.101512014034005	0.156404559835451	-0.64903487558677	0.516638337281442	   
df.mm.exp8	0.174307985393494	0.156404559835451	1.11446869309232	0.265657589347743	   
df.mm.trans1:exp2	0.00184620975860373	0.144802485191739	0.0127498485689599	0.989832872056295	   
df.mm.trans2:exp2	-0.0542067967580213	0.132185979203872	-0.410079776119202	0.681937517503328	   
df.mm.trans1:exp3	-0.0958960274667782	0.144802485191739	-0.662254016840929	0.508138650117509	   
df.mm.trans2:exp3	-0.170553075775854	0.132185979203872	-1.29025087836893	0.197608959767664	   
df.mm.trans1:exp4	0.0897932731862644	0.144802485191739	0.620108647081336	0.535491994558575	   
df.mm.trans2:exp4	0.0463766458534421	0.132185979203872	0.350843910471888	0.725865374760682	   
df.mm.trans1:exp5	-0.195828026790654	0.144802485191739	-1.35238028913212	0.176915258044619	   
df.mm.trans2:exp5	-0.192046142403283	0.132185979203872	-1.45284805211518	0.146944791055503	   
df.mm.trans1:exp6	-0.0513974393631269	0.144802485191739	-0.354948599777618	0.722790073993599	   
df.mm.trans2:exp6	0.0331497437062391	0.132185979203872	0.250781088175107	0.802094855334306	   
df.mm.trans1:exp7	0.128728638322762	0.144802485191739	0.888994675418084	0.374468574167602	   
df.mm.trans2:exp7	-0.0592015147328016	0.132185979203872	-0.447865311354197	0.654460338398696	   
df.mm.trans1:exp8	-0.271375681425707	0.144802485191739	-1.87410928111052	0.0615462409395665	.  
df.mm.trans2:exp8	-0.0961426711816105	0.132185979203872	-0.727328811729181	0.467392954621292	   
df.mm.trans1:probe2	-0.083311574255018	0.0724012425958695	-1.15069260233623	0.250453938973091	   
df.mm.trans1:probe3	0.0456764728075061	0.0724012425958695	0.630879680649458	0.528431161046651	   
df.mm.trans1:probe4	-0.189700245083420	0.0724012425958695	-2.62012416198839	0.00907918842578684	** 
df.mm.trans1:probe5	-0.223372055413587	0.0724012425958695	-3.08519643316633	0.00215624420675219	** 
df.mm.trans1:probe6	-0.000453368481463932	0.0724012425958695	-0.00626188812800564	0.995006471717701	   
df.mm.trans1:probe7	-0.0869820812649326	0.0724012425958695	-1.20138934286599	0.230215718762319	   
df.mm.trans1:probe8	-0.110839873979140	0.0724012425958695	-1.53091121098333	0.126475749860654	   
df.mm.trans1:probe9	-0.0487181567417898	0.0724012425958695	-0.67289116864645	0.501352957148725	   
df.mm.trans1:probe10	-0.119128554335877	0.0724012425958695	-1.64539378144144	0.100568761562586	   
df.mm.trans1:probe11	-0.192418497516430	0.0724012425958695	-2.65766844072657	0.00814104798188468	** 
df.mm.trans1:probe12	-0.0593389207468317	0.0724012425958695	-0.819584286392027	0.412875736174238	   
df.mm.trans2:probe2	0.00330329782804458	0.0724012425958695	0.0456248775519363	0.96362895431184	   
df.mm.trans2:probe3	0.083369758723545	0.0724012425958695	1.15149624142364	0.250123697244774	   
df.mm.trans2:probe4	0.0770052963002072	0.0724012425958695	1.06359081058921	0.2880696985549	   
df.mm.trans2:probe5	0.0346541424089764	0.0724012425958695	0.478640160948749	0.632421076894536	   
df.mm.trans2:probe6	0.0244943851307756	0.0724012425958695	0.338314430147267	0.735279938139322	   
df.mm.trans3:probe2	-0.103395878748823	0.0724012425958695	-1.42809536192576	0.153940045996146	   
df.mm.trans3:probe3	-0.0070566819830561	0.0724012425958695	-0.0974663103842735	0.922398355789872