chr1.576_chr1_133349596_133355954_+_0.R 

fitVsDatCorrelation=0.920033234041157
cont.fitVsDatCorrelation=0.253009124303386

fstatistic=7062.94878035836,52,692
cont.fstatistic=1147.47871283123,52,692

residuals=-0.779814956229466,-0.116732794679532,-0.00463297414285572,0.110544272212864,1.01455942043783
cont.residuals=-0.981843757661541,-0.375607609710161,-0.0810996615122022,0.355324999444147,1.73788575337078

predictedValues:
Include	Exclude	Both
chr1.576_chr1_133349596_133355954_+_0.R.tl.Lung	105.043954702638	91.5733609300454	63.6090126984721
chr1.576_chr1_133349596_133355954_+_0.R.tl.cerebhem	87.265413267363	77.8854643383959	62.4878213444594
chr1.576_chr1_133349596_133355954_+_0.R.tl.cortex	105.855951608741	106.049488841201	69.0000172199482
chr1.576_chr1_133349596_133355954_+_0.R.tl.heart	106.419659620252	100.322904888242	61.4821923585005
chr1.576_chr1_133349596_133355954_+_0.R.tl.kidney	102.158725430059	91.588745890936	59.8293150178728
chr1.576_chr1_133349596_133355954_+_0.R.tl.liver	104.129202163493	96.8405311274372	66.4166392869293
chr1.576_chr1_133349596_133355954_+_0.R.tl.stomach	132.494901195539	140.331621045287	64.4492843863438
chr1.576_chr1_133349596_133355954_+_0.R.tl.testicle	112.034040713525	98.1007313628065	62.5349115843086


diffExp=13.4705937725928,9.37994892896715,-0.193537232460287,6.09675473200902,10.5699795391231,7.28867103605582,-7.83671984974836,13.9333093507184
diffExpScore=1.28040950467653
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=0,0,0,0,0,0,0,0
diffExp1.2Score=0

cont.predictedValues:
Include	Exclude	Both
Lung	78.1630250535879	81.1931723115662	83.4154905238281
cerebhem	80.959729398546	91.0115117863633	81.3778074931773
cortex	76.9984255309712	107.583258878747	75.9148077304427
heart	81.1952947756034	90.2841197953495	95.7672116459223
kidney	76.7190463285419	79.8410902958199	70.2683668173417
liver	80.6065702599037	88.3472645955337	68.1255433136123
stomach	76.9785017868212	84.9197805892681	86.0342444419942
testicle	77.7624254665078	78.9354770097611	78.9053213807832
cont.diffExp=-3.03014725797834,-10.0517823878172,-30.5848333477755,-9.08882501974614,-3.12204396727797,-7.74069433562993,-7.94127880244693,-1.17305154325329
cont.diffExpScore=0.986437488552933

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,-1,0,0,0,0,0
cont.diffExp1.3Score=0.5
cont.diffExp1.2=0,0,-1,0,0,0,0,0
cont.diffExp1.2Score=0.5

tran.correlation=0.949916477876339
cont.tran.correlation=0.107383487114932

tran.covariance=0.0182721873122266
cont.tran.covariance=0.00036316401366939

tran.mean=103.630918570373
cont.tran.mean=83.2186683664307

weightedLogRatios:
wLogRatio
Lung	0.629342632488652
cerebhem	0.501720967731214
cortex	-0.00851760030851537
heart	0.273618469329707
kidney	0.499341840907907
liver	0.334485893780608
stomach	-0.282452320445855
testicle	0.617875491278898

cont.weightedLogRatios:
wLogRatio
Lung	-0.166507738492267
cerebhem	-0.521090865872316
cortex	-1.50884798416784
heart	-0.472154459940411
kidney	-0.173916690778325
liver	-0.406706872176276
stomach	-0.431270911586378
testicle	-0.0652968909855579

varWeightedLogRatios=0.103262673205227
cont.varWeightedLogRatios=0.204408324015009

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	5.75185482693484	0.0942714470559073	61.0137534382359	1.14888209900530e-280	***
df.mm.trans1	-0.731391621036004	0.0807055664598843	-9.06246809381546	1.29179199418424e-18	***
df.mm.trans2	-1.20274779088226	0.0728651423631959	-16.5064906466136	7.38502784404665e-52	***
df.mm.exp2	-0.329542255038096	0.0948172496374732	-3.47555171973535	0.000541625331925866	***
df.mm.exp3	0.0731142104579369	0.0948172496374732	0.771106636582306	0.44090693360505	   
df.mm.exp4	0.138272666438551	0.0948172496374732	1.45830707985337	0.145209618488898	   
df.mm.exp5	0.0335762603643271	0.0948172496374732	0.354115527424635	0.723360177808969	   
df.mm.exp6	0.00398633724804283	0.0948172496374732	0.042042321025808	0.966477087952594	   
df.mm.exp7	0.645909761355209	0.0948172496374732	6.81215457972888	2.09117585051247e-11	***
df.mm.exp8	0.150308476520793	0.0948172496374732	1.58524400460345	0.113367748555300	   
df.mm.trans1:exp2	0.144117578100395	0.085668134379197	1.68227753697169	0.0929661648100933	.  
df.mm.trans2:exp2	0.167641186802260	0.0677266068839094	2.47526333468345	0.0135521875683499	*  
df.mm.trans1:exp3	-0.065413866417008	0.085668134379197	-0.76357290713795	0.445382045532738	   
df.mm.trans2:exp3	0.0736512407190026	0.0677266068839094	1.08747867503902	0.277203939816363	   
df.mm.trans1:exp4	-0.125261214509819	0.085668134379197	-1.46216811440493	0.144149121941969	   
df.mm.trans2:exp4	-0.047019043593544	0.0677266068839094	-0.694247737438547	0.487759857733124	   
df.mm.trans1:exp5	-0.0614274037088781	0.085668134379197	-0.717039120251866	0.473591904284522	   
df.mm.trans2:exp5	-0.0334082675278851	0.0677266068839094	-0.493281282866428	0.621970353537445	   
df.mm.trans1:exp6	-0.0127327594408595	0.0856681343791971	-0.148628886728172	0.881889778056266	   
df.mm.trans2:exp6	0.0519388695512139	0.0677266068839094	0.766890177153605	0.443408364045311	   
df.mm.trans1:exp7	-0.413744476990273	0.085668134379197	-4.82961932098224	1.6851652000903e-06	***
df.mm.trans2:exp7	-0.219041827835796	0.0677266068839094	-3.23420643545981	0.00127779248671408	** 
df.mm.trans1:exp8	-0.0858845952401834	0.0856681343791971	-1.00252673718828	0.316439684034173	   
df.mm.trans2:exp8	-0.0814540645418053	0.0677266068839094	-1.20268928696555	0.229507921884474	   
df.mm.trans1:probe2	0.0110013862141712	0.0574679315932414	0.191435221508217	0.848240782518633	   
df.mm.trans1:probe3	-0.433672785339213	0.0574679315932414	-7.54634407949034	1.41413961645186e-13	***
df.mm.trans1:probe4	0.0292758259817603	0.0574679315932414	0.509428914006769	0.610614022674878	   
df.mm.trans1:probe5	0.087379581388159	0.0574679315932414	1.52049288995874	0.128843911785123	   
df.mm.trans1:probe6	0.100999726536296	0.0574679315932414	1.75749715947970	0.0792752459781127	.  
df.mm.trans1:probe7	-1.12365147673414	0.0574679315932414	-19.5526695599096	4.08562948162250e-68	***
df.mm.trans1:probe8	-1.1487708491128	0.0574679315932414	-19.9897719869894	1.61006953014472e-70	***
df.mm.trans1:probe9	-1.25506626555437	0.0574679315932414	-21.8394194946451	7.8249920516591e-81	***
df.mm.trans1:probe10	-1.0897343737344	0.0574679315932414	-18.9624777423268	6.81490943880975e-65	***
df.mm.trans1:probe11	-0.293727304749402	0.0574679315932414	-5.11115149973392	4.14767913054844e-07	***
df.mm.trans1:probe12	-0.902307076598472	0.0574679315932414	-15.7010536412727	9.57276021900487e-48	***
df.mm.trans1:probe13	-1.21370927918558	0.0574679315932414	-21.1197661989339	8.50671924045141e-77	***
df.mm.trans1:probe14	-0.487821216103008	0.0574679315932414	-8.48858141538504	1.27066795443103e-16	***
df.mm.trans1:probe15	-1.01378171680999	0.0574679315932414	-17.640824868825	8.53776280003222e-58	***
df.mm.trans1:probe16	-0.0524380271038395	0.0574679315932414	-0.912474586261367	0.361836716267568	   
df.mm.trans2:probe2	-0.230923575676288	0.0574679315932414	-4.01830323928774	6.50462105893569e-05	***
df.mm.trans2:probe3	-0.47497309710843	0.0574679315932414	-8.26501117997937	7.12365606077603e-16	***
df.mm.trans2:probe4	0.133039190571555	0.0574679315932414	2.31501616437508	0.0209037399508879	*  
df.mm.trans2:probe5	0.157563959534266	0.0574679315932414	2.74177189200937	0.00626874812077084	** 
df.mm.trans2:probe6	-0.0642058704663706	0.0574679315932414	-1.11724693557479	0.264276503415502	   
df.mm.trans3:probe2	0.297602006490514	0.0574679315932414	5.17857521994952	2.93486504618605e-07	***
df.mm.trans3:probe3	0.467617545070972	0.0574679315932414	8.13701715211839	1.8800948459668e-15	***
df.mm.trans3:probe4	0.187400098858894	0.0574679315932414	3.26095082358825	0.00116483175810889	** 
df.mm.trans3:probe5	0.284540481134415	0.0574679315932414	4.9512914985073	9.2718966760795e-07	***
df.mm.trans3:probe6	0.208734559882941	0.0574679315932414	3.63219197378403	0.000301796538908811	***
df.mm.trans3:probe7	0.90344413111432	0.0574679315932414	15.7208395372380	7.60553870392438e-48	***
df.mm.trans3:probe8	0.412051004903824	0.0574679315932414	7.17010328160625	1.92918696207588e-12	***
df.mm.trans3:probe9	0.253967962010848	0.0574679315932414	4.41929881535386	1.14922764245629e-05	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.08348254579424	0.232758633869036	17.5438499441093	2.78568047022850e-57	***
df.mm.trans1	0.234209452033649	0.199264124838235	1.17537189508540	0.24025020527127	   
df.mm.trans2	0.310696333211899	0.179905915553330	1.72699342462588	0.0846150897311044	.  
df.mm.exp2	0.174041424850952	0.234106234518171	0.743429260690804	0.457474158387052	   
df.mm.exp3	0.360644423034853	0.234106234518171	1.54051609850168	0.123891731152229	   
df.mm.exp4	0.00610467649833268	0.234106234518171	0.0260765225278903	0.979203820834524	   
df.mm.exp5	0.136072725154555	0.234106234518171	0.581243491590962	0.561265624583202	   
df.mm.exp6	0.317709332831911	0.234106234518171	1.35711606948789	0.175186806040316	   
df.mm.exp7	-0.00130600910654370	0.234106234518171	-0.00557870280230547	0.995550470065935	   
df.mm.exp8	0.0222466138811641	0.234106234518171	0.095027857446647	0.924320209905787	   
df.mm.trans1:exp2	-0.138886272059042	0.211516833006558	-0.656620421575317	0.511643306023181	   
df.mm.trans2:exp2	-0.0598865819874767	0.167218738941551	-0.358133199464022	0.720352851755674	   
df.mm.trans1:exp3	-0.375656159372348	0.211516833006558	-1.77601070341622	0.0761705073379624	.  
df.mm.trans2:exp3	-0.0792105328401484	0.167218738941551	-0.473694116709224	0.635867456211469	   
df.mm.trans1:exp4	0.0319559125447032	0.211516833006558	0.151079760842072	0.8799568274045	   
df.mm.trans2:exp4	0.100025749143341	0.167218738941551	0.598173086201203	0.549920167771295	   
df.mm.trans1:exp5	-0.154719435534624	0.211516833006558	-0.731475756966478	0.464736229057279	   
df.mm.trans2:exp5	-0.152865596034196	0.167218738941551	-0.914165463761978	0.360948316035840	   
df.mm.trans1:exp6	-0.286925880101791	0.211516833006558	-1.35651558329116	0.175377564165859	   
df.mm.trans2:exp6	-0.2332652543462	0.167218738941551	-1.39497077793258	0.163472215719273	   
df.mm.trans1:exp7	-0.0139645159288191	0.211516833006558	-0.0660208255311108	0.947380313834431	   
df.mm.trans2:exp7	0.0461819034044072	0.167218738941551	0.276176603751027	0.78249488509424	   
df.mm.trans1:exp8	-0.0273849728489113	0.211516833006558	-0.129469472758522	0.89702380078884	   
df.mm.trans2:exp8	-0.0504470006447211	0.167218738941551	-0.301682699941627	0.762984594876432	   
df.mm.trans1:probe2	0.0479098029664342	0.141889805096440	0.337655005825617	0.735725583867969	   
df.mm.trans1:probe3	0.159998615188409	0.141889805096440	1.12762587191983	0.259868779338830	   
df.mm.trans1:probe4	0.0526547852398025	0.141889805096440	0.371096325095477	0.710679367973418	   
df.mm.trans1:probe5	0.0561499776732432	0.141889805096440	0.395729472142688	0.692426583365722	   
df.mm.trans1:probe6	0.0346722631754859	0.141889805096440	0.244360496174617	0.807024068306324	   
df.mm.trans1:probe7	-0.0950047263414864	0.141889805096440	-0.669566966258873	0.503357217734475	   
df.mm.trans1:probe8	-0.0224989124845483	0.141889805096440	-0.158566096198780	0.87405700459162	   
df.mm.trans1:probe9	6.87891370414625e-05	0.141889805096440	0.000484806762506351	0.99961331987981	   
df.mm.trans1:probe10	0.236584975645774	0.141889805096440	1.66738530287621	0.0958902627303337	.  
df.mm.trans1:probe11	0.0995794599778633	0.141889805096440	0.701808420345497	0.483034610550189	   
df.mm.trans1:probe12	0.241059205158196	0.141889805096440	1.69891843176718	0.0897840264462359	.  
df.mm.trans1:probe13	0.0455385572720812	0.141889805096440	0.320943123722873	0.748350393898762	   
df.mm.trans1:probe14	0.136389265209271	0.141889805096440	0.961233720185668	0.336770411385891	   
df.mm.trans1:probe15	-0.0242331808260705	0.141889805096440	-0.170788738553835	0.864439807878367	   
df.mm.trans1:probe16	0.0176442231166595	0.141889805096440	0.124351591748731	0.901073012016204	   
df.mm.trans2:probe2	0.00456560134538681	0.141889805096440	0.0321770922321279	0.974340102732158	   
df.mm.trans2:probe3	0.170964050443219	0.141889805096440	1.20490721885915	0.228651019118593	   
df.mm.trans2:probe4	0.0503695725194216	0.141889805096440	0.354990779536177	0.722704663430553	   
df.mm.trans2:probe5	-0.0667636372790767	0.141889805096440	-0.470531601856091	0.638123530469166	   
df.mm.trans2:probe6	-0.119351390130459	0.141889805096440	-0.841155501266191	0.4005513907196	   
df.mm.trans3:probe2	-0.0953279868060235	0.141889805096440	-0.671845216372173	0.501906469091557	   
df.mm.trans3:probe3	-0.273654341764389	0.141889805096440	-1.92863991587267	0.0541842953257177	.  
df.mm.trans3:probe4	-0.289990728825626	0.141889805096440	-2.04377424176828	0.0413539701504578	*  
df.mm.trans3:probe5	-0.263220113365951	0.141889805096440	-1.85510236755237	0.0640067013860849	.  
df.mm.trans3:probe6	-0.316658200132171	0.141889805096440	-2.231719184595	0.0259529578353907	*  
df.mm.trans3:probe7	-0.18588533953566	0.141889805096440	-1.31006832668010	0.190607425500091	   
df.mm.trans3:probe8	-0.298580867356353	0.141889805096440	-2.10431515607067	0.0357110848616258	*  
df.mm.trans3:probe9	-0.117671133251609	0.141889805096440	-0.829313516722567	0.407212995445733