chr1.570_chr1_172205356_172206243_-_0.R 

fitVsDatCorrelation=0.921894923667428
cont.fitVsDatCorrelation=0.26269618061453

fstatistic=11123.9619105073,59,853
cont.fstatistic=1781.4629326168,59,853

residuals=-0.615367623189548,-0.0840136610171054,-0.00717838751804735,0.082954036926693,0.697855749053468
cont.residuals=-0.690980124637631,-0.238704386339530,-0.0736936070133428,0.116273485515063,1.96924048626147

predictedValues:
Include	Exclude	Both
chr1.570_chr1_172205356_172206243_-_0.R.tl.Lung	57.6759714522494	61.5649398127996	69.2819726233301
chr1.570_chr1_172205356_172206243_-_0.R.tl.cerebhem	55.793696014936	59.4630377259469	60.4424191108688
chr1.570_chr1_172205356_172206243_-_0.R.tl.cortex	47.8117355864793	58.471573232213	58.5349077913075
chr1.570_chr1_172205356_172206243_-_0.R.tl.heart	51.4921712944571	56.4347575820511	62.0268684890916
chr1.570_chr1_172205356_172206243_-_0.R.tl.kidney	55.3450514747807	65.749456432676	64.8343327677391
chr1.570_chr1_172205356_172206243_-_0.R.tl.liver	58.3977738291563	65.8794646835047	64.5412205004456
chr1.570_chr1_172205356_172206243_-_0.R.tl.stomach	51.5360600443306	58.6948523942682	63.6714174449786
chr1.570_chr1_172205356_172206243_-_0.R.tl.testicle	54.7201263945154	65.1972857599918	60.7771688299719


diffExp=-3.88896836055019,-3.66934171101084,-10.6598376457336,-4.94258628759404,-10.4044049578953,-7.4816908543484,-7.1587923499376,-10.4771593654764
diffExpScore=0.983244748747934
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,-1,0,0,0,0,0
diffExp1.2Score=0.5

cont.predictedValues:
Include	Exclude	Both
Lung	65.38748132994	61.3039087595657	67.5348168866655
cerebhem	60.9266507912893	70.4273770083876	59.47767526358
cortex	60.0783724155549	60.4531991276515	60.0755855626378
heart	59.4420202678261	68.9774041169251	70.1980328110815
kidney	60.8888699314208	57.2142873502107	63.7642290647248
liver	67.3126604558467	59.522301186513	56.8733402355164
stomach	65.400907827115	67.7652938093765	67.926555154149
testicle	64.3782835993814	63.0982530541291	59.0545000374005
cont.diffExp=4.08357257037431,-9.50072621709828,-0.374826712096620,-9.53538384909901,3.67458258121012,7.79035926933368,-2.36438598226151,1.28003054525233
cont.diffExpScore=6.49156048224572

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=0.671665531972647
cont.tran.correlation=-0.240632347621587

tran.covariance=0.00274030752867456
cont.tran.covariance=-0.000813810301797314

tran.mean=57.7642471071472
cont.tran.mean=63.2860794394458

weightedLogRatios:
wLogRatio
Lung	-0.266714970518795
cerebhem	-0.258184198708343
cortex	-0.798618776089213
heart	-0.365453903124045
kidney	-0.706234677188595
liver	-0.497572340036172
stomach	-0.521232797748846
testicle	-0.716481076609001

cont.weightedLogRatios:
wLogRatio
Lung	0.267498603754187
cerebhem	-0.606037667096871
cortex	-0.0254925669272181
heart	-0.618824031285825
kidney	0.253837712921127
liver	0.510174257237508
stomach	-0.149098324439696
testicle	0.0834407059595976

varWeightedLogRatios=0.0439853702557324
cont.varWeightedLogRatios=0.166602372030206

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.10767250419997	0.070849298210873	43.8631374293986	7.62303452674929e-221	***
df.mm.trans1	0.777308749121132	0.0599033239346093	12.9760537156443	2.86403236528238e-35	***
df.mm.trans2	1.03391590503319	0.0535016791990397	19.3249243857705	2.71385694116906e-69	***
df.mm.exp2	0.0685761715375394	0.0681634995016085	1.00605414978615	0.314674821078	   
df.mm.exp3	-0.07055991849981	0.0681634995016085	-1.03515692439096	0.300889003646768	   
df.mm.exp4	-0.0898010936611703	0.0681634995016085	-1.31743666797875	0.188046047830775	   
df.mm.exp5	0.0908549049846424	0.0681634995016085	1.33289672110362	0.182921596401004	   
df.mm.exp6	0.151051992134168	0.0681634995016085	2.21602460611054	0.0269530609304274	*  
df.mm.exp7	-0.0758504289824558	0.0681634995016085	-1.11277193126896	0.266119886454209	   
df.mm.exp8	0.135686755935049	0.0681634995016085	1.99060724474464	0.0468427951837014	*  
df.mm.trans1:exp2	-0.101755930651802	0.0604204845274016	-1.68412966972575	0.092522456389972	.  
df.mm.trans2:exp2	-0.103313816333665	0.0446234851570294	-2.31523414117265	0.0208366024903668	*  
df.mm.trans1:exp3	-0.117009605251696	0.0604204845274016	-1.93658833038042	0.0531256611296946	.  
df.mm.trans2:exp3	0.0190080773580889	0.0446234851570294	0.425965773206637	0.670240245944649	   
df.mm.trans1:exp4	-0.0236097714009448	0.0604204845274016	-0.390757730356125	0.696073893494194	   
df.mm.trans2:exp4	0.00279378191066463	0.0446234851570294	0.0626078823927211	0.950093419583162	   
df.mm.trans1:exp5	-0.132108301553155	0.0604204845274016	-2.18648199507969	0.0290514147166694	*  
df.mm.trans2:exp5	-0.0250960507685249	0.0446234851570294	-0.562395578924691	0.573994291381886	   
df.mm.trans1:exp6	-0.138614869866999	0.0604204845274016	-2.29417011384831	0.0220229346156140	*  
df.mm.trans2:exp6	-0.0833177621115524	0.0446234851570294	-1.86712807882124	0.0622265275685666	.  
df.mm.trans1:exp7	-0.0367084608111734	0.0604204845274016	-0.607549924471817	0.543647722530408	   
df.mm.trans2:exp7	0.0281099088935683	0.0446234851570294	0.629935308608235	0.528905608208275	   
df.mm.trans1:exp8	-0.18829582025882	0.0604204845274016	-3.11642353965939	0.00189190021106478	** 
df.mm.trans2:exp8	-0.0783614669408983	0.0446234851570294	-1.75605887046127	0.0794372106478715	.  
df.mm.trans1:probe2	0.109274442479007	0.0446234851570294	2.44881012978865	0.0145332119546239	*  
df.mm.trans1:probe3	0.0823166975484527	0.0446234851570294	1.84469449794837	0.0654285259918133	.  
df.mm.trans1:probe4	0.309619817856879	0.0446234851570294	6.93849475824965	7.83783557861226e-12	***
df.mm.trans1:probe5	-0.0158192930939186	0.0446234851570294	-0.354505996971117	0.723047331338899	   
df.mm.trans1:probe6	0.375122125220806	0.0446234851570294	8.4063834077674	1.76170449075076e-16	***
df.mm.trans1:probe7	1.90360375130132	0.0446234851570294	42.6592352570079	9.2772559044821e-214	***
df.mm.trans1:probe8	0.0244920272921326	0.0446234851570294	0.548859579343602	0.583245452367092	   
df.mm.trans1:probe9	-0.00121921224732988	0.0446234851570294	-0.0273222103347485	0.978209132845493	   
df.mm.trans1:probe10	0.178628091567621	0.0446234851570294	4.00300628556984	6.79849678773201e-05	***
df.mm.trans1:probe11	0.486559330653979	0.0446234851570294	10.9036604591010	5.24930912423688e-26	***
df.mm.trans1:probe12	0.564266558480938	0.0446234851570294	12.6450580113878	1.02472937385378e-33	***
df.mm.trans1:probe13	0.191018110920620	0.0446234851570294	4.28066320343269	2.07473728942334e-05	***
df.mm.trans1:probe14	0.468973439474895	0.0446234851570294	10.5095654860795	2.23491165752187e-24	***
df.mm.trans1:probe15	0.349077678337722	0.0446234851570294	7.82273453338131	1.52526803481237e-14	***
df.mm.trans1:probe16	0.239727653030223	0.0446234851570294	5.37223061324379	1.00373545483974e-07	***
df.mm.trans2:probe2	-0.107539373343378	0.0446234851570294	-2.40992770880509	0.0161664442345314	*  
df.mm.trans2:probe3	-0.190756691177716	0.0446234851570294	-4.27480485906571	2.12886647135419e-05	***
df.mm.trans2:probe4	-0.124555596774819	0.0446234851570294	-2.79125658465513	0.00536766855132231	** 
df.mm.trans2:probe5	0.0959272710338456	0.0446234851570294	2.14970369742029	0.0318592723361813	*  
df.mm.trans2:probe6	-0.145984521140470	0.0446234851570294	-3.27147287189139	0.00111284382344637	** 
df.mm.trans3:probe2	-0.533656167429879	0.0446234851570294	-11.9590875869949	1.39082316178326e-30	***
df.mm.trans3:probe3	-0.936465102493637	0.0446234851570294	-20.9859247702915	3.6618777721631e-79	***
df.mm.trans3:probe4	-0.99208178574514	0.0446234851570294	-22.2322793088442	9.77202982726987e-87	***
df.mm.trans3:probe5	-0.194402706720873	0.0446234851570294	-4.35651106220799	1.48232553092005e-05	***
df.mm.trans3:probe6	-0.188102249006043	0.0446234851570294	-4.21531954180884	2.76037489801668e-05	***
df.mm.trans3:probe7	-0.620271150333993	0.0446234851570294	-13.9001054747577	9.60974429197117e-40	***
df.mm.trans3:probe8	-0.955328766494531	0.0446234851570294	-21.4086542799771	1.02139161077954e-81	***
df.mm.trans3:probe9	-0.672150251280296	0.0446234851570294	-15.0627018242750	1.22318356088753e-45	***
df.mm.trans3:probe10	-0.816031328135677	0.0446234851570294	-18.2870370896418	2.76617337732663e-63	***
df.mm.trans3:probe11	-0.694273921177271	0.0446234851570294	-15.558487167332	3.09532863863971e-48	***
df.mm.trans3:probe12	-0.730170935849779	0.0446234851570294	-16.3629293695981	1.51585938299286e-52	***
df.mm.trans3:probe13	-0.76074068665441	0.0446234851570294	-17.0479890572728	2.64650644573008e-56	***
df.mm.trans3:probe14	-0.929748662084888	0.0446234851570294	-20.835411192405	2.94717440734171e-78	***
df.mm.trans3:probe15	-0.936373380414915	0.0446234851570294	-20.9838693037944	3.76778682195784e-79	***
df.mm.trans3:probe16	-0.931601647058162	0.0446234851570294	-20.8769360748016	1.65859687885014e-78	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.13837086513243	0.176442733579787	23.4544703608384	2.84269481104599e-94	***
df.mm.trans1	0.0725259127178423	0.149182934657720	0.486154216527804	0.626982695719517	   
df.mm.trans2	-0.0232119101913507	0.133240311017487	-0.174210867672804	0.861741081631724	   
df.mm.exp2	0.195120565769188	0.16975403407147	1.14943109797932	0.250700440826424	   
df.mm.exp3	0.0183847276923534	0.16975403407147	0.108302154896732	0.91378148286017	   
df.mm.exp4	-0.0160710833009531	0.16975403407147	-0.0946727622047956	0.924596987559849	   
df.mm.exp5	-0.0828694737174584	0.16975403407147	-0.488173810836028	0.625552194179312	   
df.mm.exp6	0.171341538789373	0.16975403407147	1.00935179376788	0.313092174804938	   
df.mm.exp7	0.094628104585681	0.16975403407147	0.557442449620023	0.57737141665218	   
df.mm.exp8	0.147477544002014	0.16975403407147	0.868771954720813	0.385216244728383	   
df.mm.trans1:exp2	-0.265780694325803	0.150470868779811	-1.7663265752438	0.077698704009142	.  
df.mm.trans2:exp2	-0.0563821055779864	0.111130101522375	-0.507352236753194	0.612038834559666	   
df.mm.trans1:exp3	-0.103065634057650	0.150470868779811	-0.68495407046841	0.493558980091191	   
df.mm.trans2:exp3	-0.0323588354911844	0.111130101522375	-0.291179752811342	0.770984634504562	   
df.mm.trans1:exp4	-0.0792583516792431	0.150470868779811	-0.52673552244338	0.598514206725082	   
df.mm.trans2:exp4	0.134006452360340	0.111130101522375	1.20585197461877	0.228208940992714	   
df.mm.trans1:exp5	0.0115890488167360	0.150470868779811	0.0770185545595181	0.938626845450925	   
df.mm.trans2:exp5	0.0138295144240950	0.111130101522375	0.124444360570574	0.900992770914555	   
df.mm.trans1:exp6	-0.142324023297629	0.150470868779811	-0.945857656380626	0.344489043854031	   
df.mm.trans2:exp6	-0.200834091943506	0.111130101522375	-1.80719795260036	0.071083637292731	.  
df.mm.trans1:exp7	-0.0944227882375141	0.150470868779811	-0.627515405494774	0.530489380076494	   
df.mm.trans2:exp7	0.00557846324331698	0.111130101522375	0.0501975897339914	0.959976683816719	   
df.mm.trans1:exp8	-0.163032002117105	0.150470868779811	-1.08347883839014	0.278902098494560	   
df.mm.trans2:exp8	-0.118628065532034	0.111130101522375	-1.06747014451480	0.286061602658096	   
df.mm.trans1:probe2	-0.0314335516777831	0.111130101522375	-0.282853621540644	0.777357672261434	   
df.mm.trans1:probe3	-0.126305457733768	0.111130101522375	-1.13655486680481	0.256043609169705	   
df.mm.trans1:probe4	0.00937325807206314	0.111130101522375	0.0843449069483297	0.932801999633547	   
df.mm.trans1:probe5	-0.122523527463725	0.111130101522375	-1.10252331083362	0.270545195621226	   
df.mm.trans1:probe6	-0.137093776595516	0.111130101522375	-1.23363314455277	0.217679444873385	   
df.mm.trans1:probe7	-0.0535590238310286	0.111130101522375	-0.481948842818658	0.629965917897275	   
df.mm.trans1:probe8	-0.162017484421610	0.111130101522375	-1.45790818331062	0.145233916286353	   
df.mm.trans1:probe9	0.153189952016016	0.111130101522375	1.37847396805602	0.168418417252852	   
df.mm.trans1:probe10	-0.0877008658183484	0.111130101522375	-0.789172911901738	0.430230243712556	   
df.mm.trans1:probe11	-0.0951634063366	0.111130101522375	-0.856324299473801	0.392058913186896	   
df.mm.trans1:probe12	-0.103774243017111	0.111130101522375	-0.933808586472107	0.350666893230083	   
df.mm.trans1:probe13	0.0579105127953057	0.111130101522375	0.52110555107921	0.602428496114451	   
df.mm.trans1:probe14	-0.126311987956847	0.111130101522375	-1.13661362876929	0.256019046435446	   
df.mm.trans1:probe15	0.0233315060729547	0.111130101522375	0.209947671722924	0.833758649262281	   
df.mm.trans1:probe16	-0.145466499279537	0.111130101522375	-1.30897477179258	0.190895415193980	   
df.mm.trans2:probe2	-0.0876963812059603	0.111130101522375	-0.789132557287402	0.430253814049083	   
df.mm.trans2:probe3	-0.00675381919992347	0.111130101522375	-0.0607739856924693	0.951553444292161	   
df.mm.trans2:probe4	0.111482480139576	0.111130101522375	1.00317086561043	0.316062912134238	   
df.mm.trans2:probe5	-0.073243642459171	0.111130101522375	-0.659080136306941	0.510022186336315	   
df.mm.trans2:probe6	0.0712736714887591	0.111130101522375	0.641353427310681	0.521465369343218	   
df.mm.trans3:probe2	0.0160340133737706	0.111130101522375	0.14428146068545	0.8853122977371	   
df.mm.trans3:probe3	-0.0124338667523493	0.111130101522375	-0.111885677975790	0.910940375036106	   
df.mm.trans3:probe4	-0.0587445685568481	0.111130101522375	-0.528610770188314	0.597212994517329	   
df.mm.trans3:probe5	0.0317660984146784	0.111130101522375	0.285846030728971	0.775065451426509	   
df.mm.trans3:probe6	-0.00730852625642484	0.111130101522375	-0.0657654960834653	0.947579936796573	   
df.mm.trans3:probe7	0.169849593143844	0.111130101522375	1.52838511633724	0.126787666349502	   
df.mm.trans3:probe8	0.124186530076911	0.111130101522375	1.11748777672004	0.264100464933154	   
df.mm.trans3:probe9	-0.126532133556938	0.111130101522375	-1.13859460059489	0.255191951710068	   
df.mm.trans3:probe10	0.0275649455374347	0.111130101522375	0.248042116040764	0.804161518915354	   
df.mm.trans3:probe11	-0.00580297536696565	0.111130101522375	-0.0522178535560618	0.958367333042828	   
df.mm.trans3:probe12	0.0733324259442388	0.111130101522375	0.659879051127062	0.509509577134511	   
df.mm.trans3:probe13	0.00493118395244047	0.111130101522375	0.0443730716060547	0.964617411410882	   
df.mm.trans3:probe14	0.144391261917864	0.111130101522375	1.29929928921006	0.194192298065508	   
df.mm.trans3:probe15	-0.0422115216452027	0.111130101522375	-0.379838775155837	0.704159647070635	   
df.mm.trans3:probe16	0.0603119872278177	0.111130101522375	0.54271512759911	0.587467724838817