chr13.6819_chr13_71824244_71830413_-_2.R 

fitVsDatCorrelation=0.893933632592463
cont.fitVsDatCorrelation=0.173721370319760

fstatistic=12821.6230690865,51,669
cont.fstatistic=2645.39064112916,51,669

residuals=-0.392420982722150,-0.0817584256967822,0.00208490010476045,0.0756103227888181,0.665744954352818
cont.residuals=-0.64246174897178,-0.173263435752899,-0.0538686096531101,0.076411181232565,1.36391857628921

predictedValues:
Include	Exclude	Both
chr13.6819_chr13_71824244_71830413_-_2.R.tl.Lung	52.4423622794607	57.6444173938248	81.1166210568086
chr13.6819_chr13_71824244_71830413_-_2.R.tl.cerebhem	50.5803832574763	58.6895188236317	48.0719665910742
chr13.6819_chr13_71824244_71830413_-_2.R.tl.cortex	48.2570847411249	47.8219106412311	58.7317457412345
chr13.6819_chr13_71824244_71830413_-_2.R.tl.heart	52.2454734876413	63.6272206277331	125.369709034371
chr13.6819_chr13_71824244_71830413_-_2.R.tl.kidney	49.8779488677956	51.5061943680198	65.8841915279475
chr13.6819_chr13_71824244_71830413_-_2.R.tl.liver	51.2901707582295	49.8975983366514	71.1379245195282
chr13.6819_chr13_71824244_71830413_-_2.R.tl.stomach	49.7736209566176	53.9580038483204	92.2984269507712
chr13.6819_chr13_71824244_71830413_-_2.R.tl.testicle	52.5273631951239	65.877891762897	124.041617330226


diffExp=-5.20205511436412,-8.10913556615542,0.435174099893871,-11.3817471400918,-1.62824550022419,1.39257242157812,-4.18438289170287,-13.350528567773
diffExpScore=1.06171496583996
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,-1,0,0,0,-1
diffExp1.2Score=0.666666666666667

cont.predictedValues:
Include	Exclude	Both
Lung	57.0607268751868	61.1780134789687	53.3083097564883
cerebhem	57.8137049738358	56.2281297542062	53.7081290469584
cortex	58.5735949989885	57.5566053181333	60.3856835308304
heart	57.2476882823067	56.3913197425976	55.5296365665481
kidney	59.4738221141721	57.9014626025416	59.3690456528996
liver	57.8235495755145	55.1954667985742	63.4582603107082
stomach	59.3429482829762	54.4109055385351	56.6023255476845
testicle	56.7365435534918	59.4888617959585	56.849797288959
cont.diffExp=-4.1172866037819,1.58557521962954,1.01698968085521,0.856368539709187,1.57235951163047,2.62808277694029,4.93204274444107,-2.75231824246671
cont.diffExpScore=2.89520424092211

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=0.780374564488033
cont.tran.correlation=-0.496509045891311

tran.covariance=0.00272165918674506
cont.tran.covariance=-0.000341363239127821

tran.mean=53.5010727091112
cont.tran.mean=57.6514589803742

weightedLogRatios:
wLogRatio
Lung	-0.37897723717465
cerebhem	-0.59447894224841
cortex	0.0350755419831847
heart	-0.79909325671905
kidney	-0.126103668212822
liver	0.108005771819987
stomach	-0.318673623316733
testicle	-0.922762109081025

cont.weightedLogRatios:
wLogRatio
Lung	-0.284187859403848
cerebhem	0.112439501660252
cortex	0.0711380170476881
heart	0.0608887224375867
kidney	0.109107300655606
liver	0.187649153801262
stomach	0.350541098237558
testicle	-0.192424246038965

varWeightedLogRatios=0.142094670587461
cont.varWeightedLogRatios=0.0410931899148958

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.43056604684252	0.0658700545890646	52.0808137816853	1.44058137453483e-237	***
df.mm.trans1	0.460454268066406	0.0573213898928177	8.03285246445324	4.30366392725449e-15	***
df.mm.trans2	0.587002619739658	0.0519229546727085	11.3052622571226	3.05626629856548e-27	***
df.mm.exp2	0.50500555667386	0.0686876126998329	7.35220714222157	5.71210443108913e-13	***
df.mm.exp3	0.0529259474854743	0.0686876126998329	0.770531183210027	0.441256883555682	   
df.mm.exp4	-0.340392638586091	0.0686876126998329	-4.95566267637831	9.1431877637802e-07	***
df.mm.exp5	0.0452623254287021	0.068687612699833	0.658959070633302	0.510148788219591	   
df.mm.exp6	-0.0352688144301115	0.0686876126998329	-0.513466883530184	0.607794297884474	   
df.mm.exp7	-0.247456142737345	0.0686876126998329	-3.6026312898475	0.000338369628684589	***
df.mm.exp8	-0.289600217430703	0.068687612699833	-4.21619279004884	2.82641246328798e-05	***
df.mm.trans1:exp2	-0.541156443370122	0.0635923724428977	-8.50976968748963	1.1420063693596e-16	***
df.mm.trans2:exp2	-0.487037806585565	0.0519229546727085	-9.3800094708701	1.00470772237847e-19	***
df.mm.trans1:exp3	-0.136098001629345	0.0635923724428977	-2.14016235597364	0.0327026559330451	*  
df.mm.trans2:exp3	-0.239735437236346	0.0519229546727085	-4.6171378101939	4.66600335116022e-06	***
df.mm.trans1:exp4	0.336631188700021	0.0635923724428977	5.29357807813031	1.62838301699133e-07	***
df.mm.trans2:exp4	0.439140608819619	0.0519229546727085	8.45754274940054	1.71296051294856e-16	***
df.mm.trans1:exp5	-0.0953980319604232	0.0635923724428977	-1.50014896906205	0.134047581541032	   
df.mm.trans2:exp5	-0.157853651840509	0.0519229546727085	-3.04015156370673	0.00245690977180641	** 
df.mm.trans1:exp6	0.0130532399324255	0.0635923724428977	0.205264238948572	0.837428121572742	   
df.mm.trans2:exp6	-0.109051719335938	0.0519229546727085	-2.10026028031985	0.0360797465952507	*  
df.mm.trans1:exp7	0.195226581598449	0.0635923724428977	3.06996852136239	0.00222747945451918	** 
df.mm.trans2:exp7	0.181368774379205	0.0519229546727085	3.49303647148831	0.000509012879864174	***
df.mm.trans1:exp8	0.291219749802688	0.0635923724428977	4.57947610091425	5.55935026848481e-06	***
df.mm.trans2:exp8	0.423109715218503	0.0519229546727085	8.1487988864566	1.80820142451742e-15	***
df.mm.trans1:probe2	0.0532257061656719	0.0389422160045314	1.36678678376902	0.172151274147414	   
df.mm.trans1:probe3	0.124061624080650	0.0389422160045314	3.18578747717424	0.00151070768064943	** 
df.mm.trans1:probe4	0.0353346946631152	0.0389422160045314	0.907362196825256	0.364542004884662	   
df.mm.trans1:probe5	0.0135046724787362	0.0389422160045314	0.346787467800106	0.728860044630614	   
df.mm.trans1:probe6	0.0818004331908083	0.0389422160045314	2.10055927945369	0.0360533728226746	*  
df.mm.trans1:probe7	0.307954275074156	0.0389422160045314	7.90798025049016	1.08295945688448e-14	***
df.mm.trans1:probe8	0.131983826352593	0.0389422160045314	3.38922228609783	0.000742059522933329	***
df.mm.trans1:probe9	0.0123760245967234	0.0389422160045314	0.317804836665775	0.750732152018395	   
df.mm.trans1:probe10	0.0940418205776738	0.0389422160045314	2.41490675740515	0.0160064242159926	*  
df.mm.trans1:probe11	0.0612329845623542	0.0389422160045314	1.57240626869383	0.116329150981594	   
df.mm.trans1:probe12	0.168597658367636	0.0389422160045314	4.32943154411187	1.72381020207503e-05	***
df.mm.trans1:probe13	0.00934120305426465	0.0389422160045314	0.239873433324331	0.810501854104484	   
df.mm.trans1:probe14	0.144027195869738	0.0389422160045314	3.69848484875587	0.000234689273012247	***
df.mm.trans1:probe15	0.0512962768490949	0.0389422160045314	1.31724082787497	0.188208884756421	   
df.mm.trans1:probe16	0.0210262897281948	0.0389422160045314	0.539935624766401	0.589421105134532	   
df.mm.trans1:probe17	0.20071063566156	0.0389422160045314	5.15406302605391	3.35957886586387e-07	***
df.mm.trans1:probe18	0.138150044819024	0.0389422160045314	3.54756505903383	0.000415981545953108	***
df.mm.trans2:probe2	0.105541103248848	0.0389422160045314	2.71019767433283	0.00689665507853387	** 
df.mm.trans2:probe3	0.144976547319450	0.0389422160045314	3.72286331375133	0.000213558123659227	***
df.mm.trans2:probe4	0.0571738620007203	0.0389422160045314	1.46817176490592	0.142527570155258	   
df.mm.trans2:probe5	0.099390515754682	0.0389422160045314	2.55225629027164	0.0109238453386970	*  
df.mm.trans2:probe6	0.0336148427609586	0.0389422160045314	0.863197994614564	0.388337961240085	   
df.mm.trans3:probe2	0.210929269839195	0.0389422160045314	5.41646807707735	8.4868075214503e-08	***
df.mm.trans3:probe3	-0.233192146341716	0.0389422160045314	-5.98815810365238	3.46353595331772e-09	***
df.mm.trans3:probe4	0.262070679792633	0.0389422160045314	6.72973206666355	3.65640867338646e-11	***
df.mm.trans3:probe5	-0.313620073731773	0.0389422160045314	-8.05347270672219	3.69128450668128e-15	***
df.mm.trans3:probe6	-0.418998025431521	0.0389422160045314	-10.7594808005473	5.19215716855884e-25	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.20156645898165	0.144731333600075	29.0301094757513	1.52999849171702e-120	***
df.mm.trans1	-0.165176170721476	0.125947993435770	-1.31146329699735	0.190151190029503	   
df.mm.trans2	-0.0881563418411278	0.114086416371134	-0.772715496245821	0.439963679936504	   
df.mm.exp2	-0.0787330781886267	0.150922142844294	-0.521680097464926	0.60206574647539	   
df.mm.exp3	-0.159510875775189	0.150922142844294	-1.05690836857356	0.290934904865144	   
df.mm.exp4	-0.119026094949196	0.150922142844294	-0.788658925098853	0.430590759163644	   
df.mm.exp5	-0.121305805402884	0.150922142844294	-0.803764133723145	0.421818703027194	   
df.mm.exp6	-0.263917148516498	0.150922142844294	-1.74869733190034	0.0808019827609048	.  
df.mm.exp7	-0.137963898529488	0.150922142844294	-0.914139541947968	0.360972867782094	   
df.mm.exp8	-0.0980167740935662	0.150922142844294	-0.649452573667007	0.516268801621534	   
df.mm.trans1:exp2	0.0918428515435089	0.139726753345991	0.657303267586041	0.511212005149071	   
df.mm.trans2:exp2	-0.00563762879099793	0.114086416371134	-0.0494154253444004	0.960602984581412	   
df.mm.trans1:exp3	0.185678789030579	0.139726753345991	1.32887070359963	0.184343679869401	   
df.mm.trans2:exp3	0.0984919115597956	0.114086416371134	0.863309714623627	0.388276593892668	   
df.mm.trans1:exp4	0.122297272728697	0.139726753345991	0.875260247590989	0.381746443455620	   
df.mm.trans2:exp4	0.0375534682450137	0.114086416371134	0.329166867007627	0.74213258718828	   
df.mm.trans1:exp5	0.162725972182782	0.139726753345991	1.16460139727029	0.244595495341159	   
df.mm.trans2:exp5	0.066260582410683	0.114086416371134	0.580792915741444	0.561575623458111	   
df.mm.trans1:exp6	0.277197188828008	0.139726753345991	1.98385192663579	0.0476806422285024	*  
df.mm.trans2:exp6	0.161010107122545	0.114086416371134	1.41129954155773	0.158621188926523	   
df.mm.trans1:exp7	0.177181112246682	0.139726753345991	1.26805431317757	0.205219674174417	   
df.mm.trans2:exp7	0.0207406336679638	0.114086416371134	0.181797573520871	0.85579665737316	   
df.mm.trans1:exp8	0.0923191998467894	0.139726753345991	0.660712409299232	0.509024207160938	   
df.mm.trans2:exp8	0.0700180043246096	0.114086416371134	0.613727791193253	0.53960383928763	   
df.mm.trans1:probe2	0.0402446172315840	0.0855648122783501	0.470340741246117	0.638264888291395	   
df.mm.trans1:probe3	-0.0158554516344431	0.0855648122783502	-0.185303411674227	0.853047226498114	   
df.mm.trans1:probe4	0.00714080202159244	0.0855648122783502	0.083454890292551	0.933514809221103	   
df.mm.trans1:probe5	-0.0158206478516872	0.0855648122783502	-0.184896658222321	0.853366129185894	   
df.mm.trans1:probe6	0.0599027841896502	0.0855648122783502	0.700086666406524	0.484116557105347	   
df.mm.trans1:probe7	-0.0248132184243102	0.0855648122783502	-0.289993254979518	0.771911256771027	   
df.mm.trans1:probe8	-0.000643981554479044	0.0855648122783501	-0.00752624282496073	0.993997227432369	   
df.mm.trans1:probe9	-0.00484939689343253	0.0855648122783502	-0.0566751303988957	0.95482090756487	   
df.mm.trans1:probe10	0.0149878847941432	0.0855648122783501	0.175164117060016	0.861003679108164	   
df.mm.trans1:probe11	0.0422397943335984	0.0855648122783501	0.493658470215403	0.621709422820449	   
df.mm.trans1:probe12	-0.00743255704726595	0.0855648122783502	-0.0868646450492658	0.930805094527855	   
df.mm.trans1:probe13	-0.00568725676652736	0.0855648122783502	-0.0664672382851282	0.947025698054798	   
df.mm.trans1:probe14	0.0592721155885492	0.0855648122783501	0.692716012696103	0.488728172930771	   
df.mm.trans1:probe15	-0.00383646987767516	0.0855648122783502	-0.0448370045526983	0.964250609023574	   
df.mm.trans1:probe16	-0.0268554817304983	0.0855648122783502	-0.313861282639585	0.753724237519029	   
df.mm.trans1:probe17	0.121141559999898	0.0855648122783502	1.41578712994558	0.157303213607577	   
df.mm.trans1:probe18	-0.05371598683345	0.0855648122783502	-0.62778127367015	0.530361457763494	   
df.mm.trans2:probe2	0.0239199756708807	0.0855648122783501	0.279553884756585	0.779906197190459	   
df.mm.trans2:probe3	-0.00473865928447775	0.0855648122783501	-0.0553809347359105	0.955851519116421	   
df.mm.trans2:probe4	0.0426871589823319	0.0855648122783501	0.498886841982037	0.618023100311143	   
df.mm.trans2:probe5	-0.0210348663214963	0.0855648122783501	-0.245835475604948	0.805884994538679	   
df.mm.trans2:probe6	-0.0363005976478729	0.0855648122783501	-0.424246798202323	0.671522220973407	   
df.mm.trans3:probe2	0.0530166809450212	0.0855648122783501	0.619608452742853	0.535726561030484	   
df.mm.trans3:probe3	0.0257166568735431	0.0855648122783502	0.300551782780571	0.763849678762048	   
df.mm.trans3:probe4	0.0280617764050946	0.0855648122783501	0.327959305442138	0.74304504340144	   
df.mm.trans3:probe5	-0.0370580503624971	0.0855648122783501	-0.433099183832063	0.665082312653844	   
df.mm.trans3:probe6	0.097412603993568	0.0855648122783501	1.13846570102528	0.255333591015022