chr16.9680_chr16_13470198_13572475_+_2.R 

fitVsDatCorrelation=0.897111847128815
cont.fitVsDatCorrelation=0.254581540462651

fstatistic=5882.41140307161,63,945
cont.fstatistic=1215.89411484737,63,945

residuals=-0.889089362728149,-0.118072813490732,-0.0096051327991057,0.104390213561652,1.55429249782505
cont.residuals=-0.901673823503437,-0.339564691885124,-0.103925118003781,0.217636983328352,1.72552429247229

predictedValues:
Include	Exclude	Both
chr16.9680_chr16_13470198_13572475_+_2.R.tl.Lung	62.805121285052	80.9225184332398	59.331249886194
chr16.9680_chr16_13470198_13572475_+_2.R.tl.cerebhem	89.971553785967	112.712193152346	108.892063288317
chr16.9680_chr16_13470198_13572475_+_2.R.tl.cortex	162.147213728405	74.5049344191847	210.885656802849
chr16.9680_chr16_13470198_13572475_+_2.R.tl.heart	61.296027748157	76.2664150389814	63.188806961403
chr16.9680_chr16_13470198_13572475_+_2.R.tl.kidney	63.5309543069629	73.0635880848391	58.2736653822882
chr16.9680_chr16_13470198_13572475_+_2.R.tl.liver	62.8822662214934	76.2280273164661	55.5892004023873
chr16.9680_chr16_13470198_13572475_+_2.R.tl.stomach	68.629011260791	87.1209473566277	60.912763761614
chr16.9680_chr16_13470198_13572475_+_2.R.tl.testicle	63.5447091089489	75.9222950187857	57.9200151046428


diffExp=-18.1173971481878,-22.7406393663788,87.6422793092203,-14.9703872908244,-9.53263377787618,-13.3457610949727,-18.4919360958367,-12.3775859098368
diffExpScore=8.599376131903
diffExp1.5=0,0,1,0,0,0,0,0
diffExp1.5Score=0.5
diffExp1.4=0,0,1,0,0,0,0,0
diffExp1.4Score=0.5
diffExp1.3=0,0,1,0,0,0,0,0
diffExp1.3Score=0.5
diffExp1.2=-1,-1,1,-1,0,-1,-1,0
diffExp1.2Score=1.2

cont.predictedValues:
Include	Exclude	Both
Lung	72.4733173156391	69.3407799645536	79.8322671829667
cerebhem	70.5301955024428	61.7663129556165	85.9579226844066
cortex	68.3709591845582	58.3038120969031	81.7313281332098
heart	82.320724769871	68.0519534418835	79.4396944196562
kidney	74.0999377812868	73.013129919465	86.904510509804
liver	77.7648429971619	75.1263807633095	65.2578917136739
stomach	76.2491447695993	88.3205869178862	70.0306517495163
testicle	79.7815890912464	78.3527449741612	73.8411923364744
cont.diffExp=3.13253735108547,8.7638825468263,10.0671470876551,14.2687713279875,1.08680786182181,2.63846223385241,-12.0714421482868,1.42884411708521
cont.diffExpScore=1.76341337205506

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

tran.correlation=0.0326944429235426
cont.tran.correlation=0.552561959736108

tran.covariance=0.00573866923580402
cont.tran.covariance=0.00500824661988451

tran.mean=80.7217360166405
cont.tran.mean=73.366650777849

weightedLogRatios:
wLogRatio
Lung	-1.08143496270847
cerebhem	-1.03932409435906
cortex	3.65465971989822
heart	-0.923231277513562
kidney	-0.590167868537244
liver	-0.815569885532796
stomach	-1.03735606312332
testicle	-0.754707966017144

cont.weightedLogRatios:
wLogRatio
Lung	0.188278988560348
cerebhem	0.555901084844317
cortex	0.660267458037888
heart	0.821451673291573
kidney	0.0635050927295289
liver	0.149683469025788
stomach	-0.64775566667905
testicle	0.078978241136883

varWeightedLogRatios=2.61158244615585
cont.varWeightedLogRatios=0.210030909845718

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.62434602671985	0.106942856419590	43.2412802644453	3.38581293444119e-226	***
df.mm.trans1	-0.526328390857998	0.093462154128477	-5.63146008955116	2.35617228825771e-08	***
df.mm.trans2	-0.279362125223335	0.0821827275777267	-3.39928028014305	0.000703884183140519	***
df.mm.exp2	0.0835814043374114	0.106400148824288	0.78553841569752	0.432334859763152	   
df.mm.exp3	-0.402338676253163	0.106400148824288	-3.78137324711449	0.000165757607395464	***
df.mm.exp4	-0.146572075125718	0.106400148824288	-1.37755517022604	0.168666821646450	   
df.mm.exp5	-0.072685501295315	0.106400148824288	-0.683133455154746	0.494689959139174	   
df.mm.exp6	0.00661184361864666	0.106400148824288	0.0621413004747356	0.950463447838474	   
df.mm.exp7	0.136177357533720	0.106400148824288	1.27986059266334	0.200908273792100	   
df.mm.exp8	-0.0280014938413292	0.106400148824288	-0.263171566494439	0.792475713257898	   
df.mm.trans1:exp2	0.275875527713461	0.100428951984765	2.74697208585141	0.00612921669141143	** 
df.mm.trans2:exp2	0.247764067770581	0.0745491631665033	3.32349898036022	0.000923100283639881	***
df.mm.trans1:exp3	1.35080670628770	0.100428951984765	13.4503714276798	7.31732255588905e-38	***
df.mm.trans2:exp3	0.319711898937953	0.0745491631665033	4.28860479927704	1.98271907485827e-05	***
df.mm.trans1:exp4	0.122250496500828	0.100428951984765	1.21728340368795	0.223800295721776	   
df.mm.trans2:exp4	0.0873126123218338	0.0745491631665033	1.17120848327732	0.241810213774777	   
df.mm.trans1:exp5	0.0841761385461062	0.100428951984765	0.83816605553024	0.402149391750802	   
df.mm.trans2:exp5	-0.0294765013838879	0.0745491631665033	-0.395396811068865	0.692639300707938	   
df.mm.trans1:exp6	-0.00538427500321798	0.100428951984765	-0.0536127769613168	0.957255007951431	   
df.mm.trans2:exp6	-0.0663747703223719	0.0745491631665033	-0.890348965743933	0.373505146099211	   
df.mm.trans1:exp7	-0.0474986267988409	0.100428951984765	-0.472957507373437	0.636352714530538	   
df.mm.trans2:exp7	-0.062372139132257	0.0745491631665033	-0.83665780383008	0.402996459159494	   
df.mm.trans1:exp8	0.0397086131732678	0.100428951984765	0.395390098059489	0.692644252488361	   
df.mm.trans2:exp8	-0.035780257199758	0.0745491631665033	-0.479955182325037	0.63137032962056	   
df.mm.trans1:probe2	-0.184064339546403	0.0657461820621814	-2.7996202026198	0.00522051325743784	** 
df.mm.trans1:probe3	0.364567858687166	0.0657461820621814	5.54508029595338	3.81298929975546e-08	***
df.mm.trans1:probe4	0.33541026116377	0.0657461820621814	5.1015929844648	4.07020963402160e-07	***
df.mm.trans1:probe5	-0.159880007773533	0.0657461820621814	-2.43177630637656	0.0152098723679096	*  
df.mm.trans1:probe6	-0.193358760411849	0.0657461820621814	-2.94098842468107	0.00335145919766145	** 
df.mm.trans1:probe7	0.190866530738117	0.0657461820621814	2.90308158970507	0.00378103786914117	** 
df.mm.trans1:probe8	0.149245707830467	0.0657461820621814	2.27002851191136	0.0234303498006579	*  
df.mm.trans1:probe9	-0.241940145377645	0.0657461820621814	-3.67991171181352	0.000246507708501378	***
df.mm.trans1:probe10	0.0537298414945885	0.0657461820621814	0.817231355636316	0.414002209483502	   
df.mm.trans1:probe11	0.518659555070344	0.0657461820621814	7.88881633582626	8.40429350004535e-15	***
df.mm.trans1:probe12	0.208545673918479	0.0657461820621814	3.17198151097566	0.00156286097264073	** 
df.mm.trans1:probe13	0.785046942982416	0.0657461820621814	11.940570818849	1.03861573758783e-30	***
df.mm.trans1:probe14	0.570471371779468	0.0657461820621814	8.67687451782262	1.75596612761169e-17	***
df.mm.trans1:probe15	0.274142197947285	0.0657461820621814	4.16970521098864	3.33029375819997e-05	***
df.mm.trans1:probe16	0.787695796171624	0.0657461820621814	11.9808598988552	6.8145934678105e-31	***
df.mm.trans1:probe17	-0.344567484253942	0.0657461820621814	-5.24087442717293	1.9714733301043e-07	***
df.mm.trans1:probe18	-0.383814989494825	0.0657461820621814	-5.83782932264904	7.2653235114437e-09	***
df.mm.trans1:probe19	-0.276682446508417	0.0657461820621814	-4.20834241365888	2.81774861512402e-05	***
df.mm.trans1:probe20	-0.238434590619673	0.0657461820621814	-3.62659219350816	0.000302542586297837	***
df.mm.trans1:probe21	-0.306369143260825	0.0657461820621814	-4.65987732901459	3.61777342377416e-06	***
df.mm.trans1:probe22	-0.196600361269656	0.0657461820621814	-2.99029320187315	0.00285935486567826	** 
df.mm.trans1:probe23	-0.205094527371244	0.0657461820621814	-3.11948954202801	0.00186656531211676	** 
df.mm.trans1:probe24	-0.194623426671314	0.0657461820621814	-2.96022400946786	0.00315094520865057	** 
df.mm.trans1:probe25	-0.225760276618616	0.0657461820621814	-3.4338157675087	0.000621002049299161	***
df.mm.trans1:probe26	0.288350664672974	0.0657461820621814	4.38581611324985	1.28532675391344e-05	***
df.mm.trans1:probe27	-0.146066218032125	0.0657461820621814	-2.22166844447300	0.0265419491252677	*  
df.mm.trans1:probe28	0.283207717599334	0.0657461820621814	4.30759184360671	1.82298666383727e-05	***
df.mm.trans2:probe2	-0.126270360419615	0.0657461820621814	-1.92057327831129	0.0550861969453238	.  
df.mm.trans2:probe3	0.57149649749965	0.0657461820621814	8.69246668892713	1.54650449267420e-17	***
df.mm.trans2:probe4	-0.0330304565845651	0.0657461820621814	-0.502393531434655	0.615507774135414	   
df.mm.trans2:probe5	-0.00714276506763072	0.0657461820621814	-0.10864151869496	0.913509891652557	   
df.mm.trans2:probe6	0.274062344127876	0.0657461820621814	4.16849063370209	3.34776265781667e-05	***
df.mm.trans3:probe2	0.647648793823284	0.0657461820621814	9.8507437771938	7.3610654015296e-22	***
df.mm.trans3:probe3	0.421072734939623	0.0657461820621814	6.40451995435083	2.37433378324162e-10	***
df.mm.trans3:probe4	0.115858366903266	0.0657461820621814	1.7622067665266	0.0783576293112651	.  
df.mm.trans3:probe5	0.0346822271413869	0.0657461820621814	0.527516975945237	0.597958456151476	   
df.mm.trans3:probe6	0.226261880031128	0.0657461820621814	3.44144515976813	0.000603963015326747	***
df.mm.trans3:probe7	0.207009722401452	0.0657461820621814	3.14861967506594	0.00169191121425868	** 
df.mm.trans3:probe8	0.463311363490352	0.0657461820621814	7.0469698613398	3.52303500624753e-12	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.04080811428108	0.234084223567972	17.2621975658592	3.01616055248245e-58	***
df.mm.trans1	0.148962324333765	0.204576691839203	0.728149052536491	0.466702732204886	   
df.mm.trans2	0.148094987021656	0.179887470933554	0.823264601214824	0.410565243241732	   
df.mm.exp2	-0.216782736552216	0.232896306110705	-0.930812257920356	0.352188409986858	   
df.mm.exp3	-0.255145613988799	0.232896306110705	-1.09553310762910	0.273562271785757	   
df.mm.exp4	0.113572285100262	0.232896306110705	0.487651723622771	0.62590966217767	   
df.mm.exp5	-0.0110798282981864	0.232896306110705	-0.047574083433164	0.962065739035705	   
df.mm.exp6	0.352190354791661	0.232896306110705	1.51221958249630	0.130812340610878	   
df.mm.exp7	0.423722526506825	0.232896306110705	1.81936130109944	0.0691726517947112	.  
df.mm.exp8	0.296273157717926	0.232896306110705	1.27212476086716	0.20364173815141	   
df.mm.trans1:exp2	0.189605202580509	0.219826120567248	0.862523534924985	0.388618316195238	   
df.mm.trans2:exp2	0.101107665989691	0.163178575565672	0.619613608215371	0.535661564935031	   
df.mm.trans1:exp3	0.196875318042644	0.219826120567248	0.895595653212727	0.370696823387755	   
df.mm.trans2:exp3	0.081779904203745	0.163178575565672	0.501168146126096	0.616369507777713	   
df.mm.trans1:exp4	0.0138321535927862	0.219826120567248	0.0629231574350363	0.949841000719284	   
df.mm.trans2:exp4	-0.132334039036402	0.163178575565672	-0.810976799973002	0.417583189585386	   
df.mm.trans1:exp5	0.0332760638484140	0.219826120567248	0.15137447616574	0.879712630194538	   
df.mm.trans2:exp5	0.0626859265830515	0.163178575565672	0.384155373128767	0.70094971468337	   
df.mm.trans1:exp6	-0.281719372329491	0.219826120567248	-1.28155549305301	0.200312976643139	   
df.mm.trans2:exp6	-0.272051771161097	0.163178575565672	-1.66720275758020	0.0958054317988987	.  
df.mm.trans1:exp7	-0.372934784311321	0.219826120567248	-1.69649895721666	0.090120755891388	.  
df.mm.trans2:exp7	-0.181782487244409	0.163178575565672	-1.11400952370276	0.265558355642590	   
df.mm.trans1:exp8	-0.200198850115524	0.219826120567248	-0.910714566580725	0.362678023220841	   
df.mm.trans2:exp8	-0.174085343361262	0.163178575565672	-1.06683945951716	0.28631680741555	   
df.mm.trans1:probe2	0.307704040379924	0.143909976746843	2.13817031546893	0.0327588568395189	*  
df.mm.trans1:probe3	0.0307653278750420	0.143909976746843	0.213781758363858	0.830763365954023	   
df.mm.trans1:probe4	0.258164001036238	0.143909976746843	1.79392705684598	0.0731444054741279	.  
df.mm.trans1:probe5	0.245427041977528	0.143909976746843	1.70542062145744	0.0884446346970365	.  
df.mm.trans1:probe6	0.127142553723572	0.143909976746843	0.883486722725503	0.377198053224281	   
df.mm.trans1:probe7	0.177160607328401	0.143909976746843	1.23105160137751	0.218609860006118	   
df.mm.trans1:probe8	-0.0281738079938293	0.143909976746843	-0.195773834661865	0.844829278390974	   
df.mm.trans1:probe9	0.121672807596862	0.143909976746843	0.845478613417475	0.398057685182633	   
df.mm.trans1:probe10	0.0623364639449983	0.143909976746843	0.433162907493595	0.664995272473977	   
df.mm.trans1:probe11	-0.00811149634277922	0.143909976746843	-0.0563650729862073	0.955062895266239	   
df.mm.trans1:probe12	0.0857176911255966	0.143909976746843	0.595634111430546	0.551562303021871	   
df.mm.trans1:probe13	0.339568955362425	0.143909976746843	2.35959287214514	0.0184975243876102	*  
df.mm.trans1:probe14	0.159958581097906	0.143909976746843	1.11151835830878	0.266627997132639	   
df.mm.trans1:probe15	0.125170573989235	0.143909976746843	0.8697838525082	0.384639405658496	   
df.mm.trans1:probe16	0.0890679121096648	0.143909976746843	0.618914088676055	0.536122118877177	   
df.mm.trans1:probe17	-0.0610219334619491	0.143909976746843	-0.424028513112019	0.671641522241033	   
df.mm.trans1:probe18	0.00313021838688677	0.143909976746843	0.0217512257151791	0.98265099294884	   
df.mm.trans1:probe19	0.158449172261183	0.143909976746843	1.10102979545272	0.271164054261273	   
df.mm.trans1:probe20	0.0897515840683446	0.143909976746843	0.623664780560902	0.532998261047406	   
df.mm.trans1:probe21	0.0905663000848501	0.143909976746843	0.629326069895545	0.529287712179876	   
df.mm.trans1:probe22	0.0625877030154478	0.143909976746843	0.434908714672006	0.663727987003233	   
df.mm.trans1:probe23	0.336763493391857	0.143909976746843	2.34009831010027	0.0194859768889824	*  
df.mm.trans1:probe24	0.101187855582152	0.143909976746843	0.703133013218085	0.482146043984854	   
df.mm.trans1:probe25	0.146096869346429	0.143909976746843	1.01519625427661	0.310272130889530	   
df.mm.trans1:probe26	0.041286256393531	0.143909976746843	0.286889466087254	0.774259846097025	   
df.mm.trans1:probe27	0.0334147362276597	0.143909976746843	0.23219193681367	0.816439212957089	   
df.mm.trans1:probe28	0.268345156696178	0.143909976746843	1.8646737548171	0.0625369652143748	.  
df.mm.trans2:probe2	0.208618349936375	0.143909976746843	1.44964480331591	0.147489372523314	   
df.mm.trans2:probe3	0.075202181746098	0.143909976746843	0.522564060158168	0.60140013813523	   
df.mm.trans2:probe4	0.227698279686342	0.143909976746843	1.58222720087637	0.113932315212615	   
df.mm.trans2:probe5	0.190609184327565	0.143909976746843	1.32450291936932	0.185656296390481	   
df.mm.trans2:probe6	-0.000306773523573535	0.143909976746843	-0.00213170435093038	0.998299597210009	   
df.mm.trans3:probe2	0.198899546576775	0.143909976746843	1.3821108937198	0.167264245040708	   
df.mm.trans3:probe3	0.023232431347915	0.143909976746843	0.161437253157117	0.871783534725526	   
df.mm.trans3:probe4	0.00573852949342434	0.143909976746843	0.0398758280916074	0.968200544739634	   
df.mm.trans3:probe5	-0.034298943043907	0.143909976746843	-0.23833610302254	0.811672091740246	   
df.mm.trans3:probe6	0.049253038981547	0.143909976746843	0.342248953789977	0.732239649562176	   
df.mm.trans3:probe7	0.0809626340513717	0.143909976746843	0.562592225233944	0.573846019824312	   
df.mm.trans3:probe8	0.0127115446353349	0.143909976746843	0.0883298359341422	0.92963324051142