chr11.3485_chr11_107168114_107169994_-_2.R 

fitVsDatCorrelation=0.791202817644574
cont.fitVsDatCorrelation=0.257426373051253

fstatistic=7273.15050863747,59,853
cont.fstatistic=2904.53046737421,59,853

residuals=-0.678780037617486,-0.105957292373417,-0.00787781486955737,0.0815603179216422,1.36023156169992
cont.residuals=-0.635471656071884,-0.196314739254184,-0.0418103931602858,0.126666198010018,1.92188567421029

predictedValues:
Include	Exclude	Both
chr11.3485_chr11_107168114_107169994_-_2.R.tl.Lung	58.7424761434523	70.9043623670667	125.764634456037
chr11.3485_chr11_107168114_107169994_-_2.R.tl.cerebhem	70.3301199677814	79.0019865846532	73.3476811831028
chr11.3485_chr11_107168114_107169994_-_2.R.tl.cortex	50.63906039809	55.4030745318113	63.3415431978754
chr11.3485_chr11_107168114_107169994_-_2.R.tl.heart	54.3702916389505	59.9160136296509	82.111603415813
chr11.3485_chr11_107168114_107169994_-_2.R.tl.kidney	54.9485273918919	61.2624476131011	69.1899197700276
chr11.3485_chr11_107168114_107169994_-_2.R.tl.liver	55.7423315656688	61.4421484307202	69.0466254616159
chr11.3485_chr11_107168114_107169994_-_2.R.tl.stomach	55.417253803715	64.0386137454651	67.2787755133592
chr11.3485_chr11_107168114_107169994_-_2.R.tl.testicle	55.9499342208926	61.4336131274472	67.7972424813534


diffExp=-12.1618862236144,-8.67186661687178,-4.76401413372128,-5.54572199070036,-6.31392022120925,-5.69981686505136,-8.62135994175015,-5.48367890655465
diffExpScore=0.982836231963769
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=-1,0,0,0,0,0,0,0
diffExp1.2Score=0.5

cont.predictedValues:
Include	Exclude	Both
Lung	66.2490979215183	65.7373981717423	68.2682544561693
cerebhem	66.3665320373733	62.4536564758094	71.2816213654888
cortex	59.5695970676185	62.4366017356651	67.4060708782837
heart	65.3113410988576	61.8371292035759	66.7963175377144
kidney	66.0111277853439	62.930644516989	69.4719191567862
liver	65.2438507850715	66.9922058322508	66.1712721688646
stomach	62.9002577582248	64.8511894726254	78.4368174668503
testicle	62.7851075489181	74.3234118816957	60.8885675452298
cont.diffExp=0.511699749776042,3.91287556156384,-2.86700466804660,3.4742118952817,3.08048326835495,-1.74835504717937,-1.95093171440066,-11.5383043327776
cont.diffExpScore=3.57940946467485

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=0.956940729899019
cont.tran.correlation=-0.153118227745907

tran.covariance=0.0100992086599654
cont.tran.covariance=-0.000311490944228546

tran.mean=60.5963909475224
cont.tran.mean=64.74994683083

weightedLogRatios:
wLogRatio
Lung	-0.784146302265728
cerebhem	-0.501291359651702
cortex	-0.356921260564153
heart	-0.392814185491682
kidney	-0.441691959960234
liver	-0.396183091296061
stomach	-0.590988081558187
testicle	-0.380657348955130

cont.weightedLogRatios:
wLogRatio
Lung	0.032485138875144
cerebhem	0.253087555532871
cortex	-0.193226549525626
heart	0.226946424448058
kidney	0.199090093205042
liver	-0.110838181648449
stomach	-0.126970113276952
testicle	-0.71263514089256

varWeightedLogRatios=0.0209121972126011
cont.varWeightedLogRatios=0.100929633067506

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.53587176214550	0.0899143587583802	39.3248843785582	9.20098257511363e-194	***
df.mm.trans1	0.348791166190810	0.0776478408444995	4.49196220264917	8.0283386669386e-06	***
df.mm.trans2	0.697707182367077	0.0686015164241346	10.1704338145158	5.18698501793871e-23	***
df.mm.exp2	0.827379404168724	0.0882434847804827	9.37609622089312	5.99191533891332e-20	***
df.mm.exp3	0.290734048087772	0.0882434847804827	3.29468004137655	0.0010259628901946	** 
df.mm.exp4	0.180599505029602	0.0882434847804827	2.04660440913986	0.0410029783912487	*  
df.mm.exp5	0.384625892916548	0.0882434847804827	4.35868884681238	1.46797280578889e-05	***
df.mm.exp6	0.403971039260256	0.0882434847804827	4.57791348862965	5.39444001593659e-06	***
df.mm.exp7	0.465449551642081	0.0882434847804827	5.27460529012367	1.68768433690761e-07	***
df.mm.exp8	0.425810007077954	0.0882434847804827	4.82539881711622	1.65501343692569e-06	***
df.mm.trans1:exp2	-0.647342327246153	0.0815652880044056	-7.93649287686188	6.52850155057412e-15	***
df.mm.trans2:exp2	-0.719238365471438	0.0602399574757258	-11.9395563278952	1.7009618385984e-30	***
df.mm.trans1:exp3	-0.439173904143873	0.0815652880044056	-5.38432358775158	9.406173933358e-08	***
df.mm.trans2:exp3	-0.537430919005074	0.0602399574757258	-8.92150229723579	2.76364394816744e-18	***
df.mm.trans1:exp4	-0.257944689097765	0.0815652880044056	-3.16243214986053	0.00161990875714296	** 
df.mm.trans2:exp4	-0.34898765633858	0.0602399574757258	-5.7932918773923	9.70454833802089e-09	***
df.mm.trans1:exp5	-0.451392090661469	0.0815652880044056	-5.53411998786895	4.16318909831125e-08	***
df.mm.trans2:exp5	-0.530790797897784	0.0602399574757258	-8.81127444539898	6.8379387826524e-18	***
df.mm.trans1:exp6	-0.456394267952340	0.0815652880044056	-5.59544726829982	2.96520571846902e-08	***
df.mm.trans2:exp6	-0.547206943179029	0.0602399574757258	-9.0837870096361	7.16264086869783e-19	***
df.mm.trans1:exp7	-0.523721645055896	0.0815652880044056	-6.420888810294	2.24720636052988e-10	***
df.mm.trans2:exp7	-0.567295270540525	0.0602399574757258	-9.41725881478455	4.2039579827892e-20	***
df.mm.trans1:exp8	-0.474515827177138	0.0815652880044056	-5.81761971037861	8.43943474888988e-09	***
df.mm.trans2:exp8	-0.569184836740557	0.0602399574757258	-9.44862613772453	3.20640248968643e-20	***
df.mm.trans1:probe2	0.186972600917759	0.0558439351867731	3.34812724591164	0.000849235192079694	***
df.mm.trans1:probe3	0.241858402635802	0.0558439351867731	4.33096990437535	1.66097831239680e-05	***
df.mm.trans1:probe4	0.0887160107821533	0.0558439351867731	1.58864181912392	0.112511843563721	   
df.mm.trans1:probe5	0.48230735108297	0.0558439351867731	8.63670064564516	2.81790746940364e-17	***
df.mm.trans1:probe6	0.0875895578484708	0.0558439351867731	1.56847037293347	0.117142260906909	   
df.mm.trans1:probe7	0.0653555856700934	0.0558439351867731	1.17032557701222	0.242196838270795	   
df.mm.trans1:probe8	0.326317934738655	0.0558439351867731	5.8433907576045	7.27463187738978e-09	***
df.mm.trans1:probe9	0.09627811891785	0.0558439351867731	1.72405684871316	0.0850598947684539	.  
df.mm.trans1:probe10	0.186583667213124	0.0558439351867731	3.34116259158822	0.000870542684047824	***
df.mm.trans1:probe11	0.506856354716443	0.0558439351867731	9.07630081979777	7.62624472685252e-19	***
df.mm.trans1:probe12	0.698519364914587	0.0558439351867731	12.5084194474897	4.40662542265513e-33	***
df.mm.trans1:probe13	0.364736169397918	0.0558439351867731	6.53134791053027	1.11889230889559e-10	***
df.mm.trans1:probe14	0.351008725322302	0.0558439351867731	6.28552991740883	5.2079897761887e-10	***
df.mm.trans1:probe15	0.634658809196776	0.0558439351867731	11.3648654428475	5.72237914282251e-28	***
df.mm.trans1:probe16	0.388950048348454	0.0558439351867731	6.96494699106696	6.5631826946891e-12	***
df.mm.trans1:probe17	0.198019618588708	0.0558439351867731	3.54594671608332	0.000412509476098276	***
df.mm.trans1:probe18	0.166267933907082	0.0558439351867731	2.97736779027105	0.00298959228495130	** 
df.mm.trans1:probe19	0.115267751439504	0.0558439351867731	2.06410510029397	0.0393096460848608	*  
df.mm.trans1:probe20	0.368293502517623	0.0558439351867731	6.59504924367964	7.44917841829689e-11	***
df.mm.trans1:probe21	0.298551191100945	0.0558439351867731	5.34617036035201	1.15402389274039e-07	***
df.mm.trans1:probe22	0.178896127734243	0.0558439351867731	3.20350145697854	0.00140806156740223	** 
df.mm.trans2:probe2	0.0469277007576008	0.0558439351867731	0.840336566551919	0.400955183421289	   
df.mm.trans2:probe3	0.196939977355434	0.0558439351867731	3.52661352923567	0.000443359668879979	***
df.mm.trans2:probe4	0.0493121161805354	0.0558439351867731	0.883034406791146	0.377466470821078	   
df.mm.trans2:probe5	0.0533355924216952	0.0558439351867731	0.95508298695841	0.339806314660252	   
df.mm.trans2:probe6	0.0975328625993402	0.0558439351867731	1.74652560341846	0.081079603726719	.  
df.mm.trans3:probe2	0.308739444299643	0.0558439351867731	5.52861189432741	4.29133838223271e-08	***
df.mm.trans3:probe3	-0.0109576738144349	0.0558439351867731	-0.196219585489210	0.84448503535931	   
df.mm.trans3:probe4	0.418236108817175	0.0558439351867731	7.48937386698057	1.72809652107434e-13	***
df.mm.trans3:probe5	0.195297824247529	0.0558439351867731	3.49720741552944	0.000494444813736133	***
df.mm.trans3:probe6	0.353950786571167	0.0558439351867731	6.3382135479414	3.76180625924471e-10	***
df.mm.trans3:probe7	0.506812226370853	0.0558439351867731	9.07551061141718	7.67688017866779e-19	***
df.mm.trans3:probe8	0.675536692177844	0.0558439351867731	12.0968676351062	3.33990456235442e-31	***
df.mm.trans3:probe9	-0.0600866386230775	0.0558439351867731	-1.07597429196410	0.282242982140776	   
df.mm.trans3:probe10	0.132891918844588	0.0558439351867731	2.37970190317218	0.0175455947443446	*  

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.12744488157964	0.14207098632331	29.0519900536683	1.49958597783350e-129	***
df.mm.trans1	0.0425060369252348	0.122689028615524	0.346453447426319	0.729087405889318	   
df.mm.trans2	0.052624837322715	0.108395202237298	0.485490466704507	0.627453144540207	   
df.mm.exp2	-0.0926658257239857	0.139430888375220	-0.664600411026677	0.506485728106276	   
df.mm.exp3	-0.145083064481816	0.139430888375220	-1.04053747467624	0.298385098228425	   
df.mm.exp4	-0.0536232495827629	0.139430888375220	-0.384586587718343	0.70063959379695	   
df.mm.exp5	-0.0647110356309127	0.139430888375220	-0.464108321943486	0.642688558158357	   
df.mm.exp6	0.0348166935444173	0.139430888375220	0.249705742752802	0.802875037193992	   
df.mm.exp7	-0.204292889100452	0.139430888375220	-1.46519104540655	0.143237281952816	   
df.mm.exp8	0.183453498261562	0.139430888375220	1.31573068492452	0.188617957212599	   
df.mm.trans1:exp2	0.0944368710613516	0.128878869588232	0.732756823233147	0.463908063705643	   
df.mm.trans2:exp2	0.0414226211338502	0.0951833532800784	0.435187663665972	0.663536302088829	   
df.mm.trans1:exp3	0.0388065435897422	0.128878869588232	0.301108658958053	0.763405020440087	   
df.mm.trans2:exp3	0.0935667442701008	0.0951833532800784	0.983015843062172	0.325878372855762	   
df.mm.trans1:exp4	0.03936709914887	0.128878869588231	0.305458135027472	0.76009177435626	   
df.mm.trans2:exp4	-0.00754076008601737	0.0951833532800784	-0.0792235178332977	0.936873420130466	   
df.mm.trans1:exp5	0.0611125177590626	0.128878869588232	0.474185705960313	0.635488841241152	   
df.mm.trans2:exp5	0.0210762850244657	0.0951833532800784	0.221428267634661	0.824811979792108	   
df.mm.trans1:exp6	-0.0501067411190383	0.128878869588231	-0.38878942125369	0.697528952242825	   
df.mm.trans2:exp6	-0.0159084016833639	0.0951833532800784	-0.167134284884388	0.867304002357763	   
df.mm.trans1:exp7	0.152421302208795	0.128878869588231	1.18267100491944	0.237269101019448	   
df.mm.trans2:exp7	0.190720151699999	0.0951833532800784	2.00371330834292	0.0454166103045772	*  
df.mm.trans1:exp8	-0.237157442345223	0.128878869588231	-1.84015768529738	0.0660923473373206	.  
df.mm.trans2:exp8	-0.0606954867223724	0.0951833532800784	-0.637669136784613	0.523860206422117	   
df.mm.trans1:probe2	0.138198206610736	0.0882373300740512	1.56621020258383	0.117670295046737	   
df.mm.trans1:probe3	-0.00924653524162116	0.0882373300740512	-0.104791648091133	0.916565772388907	   
df.mm.trans1:probe4	0.0432648385828138	0.0882373300740512	0.490323523462289	0.624031078658245	   
df.mm.trans1:probe5	0.0130434937879379	0.0882373300740512	0.147822852039963	0.882517508340138	   
df.mm.trans1:probe6	-0.0174119443346153	0.0882373300740512	-0.197330815880339	0.843615676358859	   
df.mm.trans1:probe7	0.0716531766129107	0.0882373300740512	0.81205059755069	0.416989152518679	   
df.mm.trans1:probe8	0.0604476819822737	0.0882373300740512	0.685057921987716	0.493493480056589	   
df.mm.trans1:probe9	0.0314803526451377	0.0882373300740512	0.356769097826493	0.721352907382877	   
df.mm.trans1:probe10	-0.0544254334051743	0.0882373300740512	-0.616807346272818	0.537526394291469	   
df.mm.trans1:probe11	0.116512906103532	0.0882373300740512	1.32044913423548	0.187039288258728	   
df.mm.trans1:probe12	0.00374769293157205	0.0882373300740512	0.0424728731980771	0.966131675904673	   
df.mm.trans1:probe13	-0.0282187961431965	0.0882373300740512	-0.319805643705612	0.749193981281806	   
df.mm.trans1:probe14	0.239915684145065	0.0882373300740512	2.71898168205816	0.00668133691527382	** 
df.mm.trans1:probe15	0.0296748156277914	0.0882373300740512	0.336306817113431	0.736722222425473	   
df.mm.trans1:probe16	-0.0182994535574613	0.0882373300740512	-0.207389021654485	0.83575555509537	   
df.mm.trans1:probe17	-0.0220149497060551	0.0882373300740512	-0.249497006398307	0.803036423636684	   
df.mm.trans1:probe18	0.0326045803996561	0.0882373300740512	0.369510051724065	0.711839293247283	   
df.mm.trans1:probe19	0.0220912152586800	0.0882373300740512	0.250361329384519	0.802368219115282	   
df.mm.trans1:probe20	0.0315700901838343	0.0882373300740512	0.357786099798575	0.72059190523639	   
df.mm.trans1:probe21	0.0696237906958545	0.0882373300740512	0.789051421177684	0.430301206327635	   
df.mm.trans1:probe22	-0.00314165350648963	0.0882373300740512	-0.0356045848605467	0.9716059825104	   
df.mm.trans2:probe2	0.0234848462877601	0.0882373300740512	0.266155449944496	0.790183810876168	   
df.mm.trans2:probe3	0.0861891849860114	0.0882373300740512	0.976788224594728	0.328950938697663	   
df.mm.trans2:probe4	-0.0377015039494394	0.0882373300740512	-0.427273852436369	0.669287706602232	   
df.mm.trans2:probe5	0.0750074185312703	0.0882373300740512	0.850064462153626	0.395527779044102	   
df.mm.trans2:probe6	-0.0574076098768697	0.0882373300740512	-0.650604566442476	0.515476981542313	   
df.mm.trans3:probe2	0.0617918640015577	0.0882373300740512	0.70029163336765	0.483936149298447	   
df.mm.trans3:probe3	0.0198407231504446	0.0882373300740512	0.224856340664362	0.82214488790043	   
df.mm.trans3:probe4	-0.0644066054615949	0.0882373300740512	-0.729924686156564	0.465636622037793	   
df.mm.trans3:probe5	-0.0344401718588952	0.0882373300740512	-0.390312941585972	0.696402602721547	   
df.mm.trans3:probe6	-0.0336095045085840	0.0882373300740512	-0.380898928836333	0.70337308960482	   
df.mm.trans3:probe7	0.0509031191181331	0.0882373300740512	0.576888705442626	0.564166848588834	   
df.mm.trans3:probe8	-0.0540845679692102	0.0882373300740512	-0.612944293801965	0.540076556641334	   
df.mm.trans3:probe9	0.0196332635098358	0.0882373300740512	0.222505185655085	0.823973901693749	   
df.mm.trans3:probe10	0.0430629503629805	0.0882373300740512	0.488035509764868	0.625650109444898