chr14.7381_chr14_26337381_26338782_-_2.R 

fitVsDatCorrelation=0.96658639548836
cont.fitVsDatCorrelation=0.283710443590063

fstatistic=8709.90655173744,53,715
cont.fstatistic=609.908731097042,53,715

residuals=-0.791583968147958,-0.0936799927808022,-0.00090846746671128,0.0931468034528657,1.14628413642014
cont.residuals=-1.26351972467951,-0.523434866186682,-0.259529025045352,0.493726160728506,1.76735345127454

predictedValues:
Include	Exclude	Both
chr14.7381_chr14_26337381_26338782_-_2.R.tl.Lung	71.3716064605732	317.302925881527	56.0595888086648
chr14.7381_chr14_26337381_26338782_-_2.R.tl.cerebhem	71.2562215001724	169.76192565441	61.0702871371727
chr14.7381_chr14_26337381_26338782_-_2.R.tl.cortex	62.181691823556	193.965727890183	55.0127919096784
chr14.7381_chr14_26337381_26338782_-_2.R.tl.heart	65.4164492015326	245.856215124515	54.2244069687952
chr14.7381_chr14_26337381_26338782_-_2.R.tl.kidney	70.0154691017247	355.994684287365	58.3840160431668
chr14.7381_chr14_26337381_26338782_-_2.R.tl.liver	72.9371495569842	348.710513160191	56.8816073730852
chr14.7381_chr14_26337381_26338782_-_2.R.tl.stomach	74.6050135469571	250.790680649588	53.834902444924
chr14.7381_chr14_26337381_26338782_-_2.R.tl.testicle	74.0729783169289	384.217547124926	56.6517682207333


diffExp=-245.931319420954,-98.5057041542376,-131.784036066627,-180.439765922983,-285.979215185640,-275.773363603207,-176.185667102631,-310.144568807998
diffExpScore=0.999413745432552
diffExp1.5=-1,-1,-1,-1,-1,-1,-1,-1
diffExp1.5Score=0.888888888888889
diffExp1.4=-1,-1,-1,-1,-1,-1,-1,-1
diffExp1.4Score=0.888888888888889
diffExp1.3=-1,-1,-1,-1,-1,-1,-1,-1
diffExp1.3Score=0.888888888888889
diffExp1.2=-1,-1,-1,-1,-1,-1,-1,-1
diffExp1.2Score=0.888888888888889

cont.predictedValues:
Include	Exclude	Both
Lung	92.6244308087576	78.6524363171574	117.992404826791
cerebhem	107.481147109737	82.228980924771	63.7968456832162
cortex	84.3928532138313	81.3071250484579	102.002967965510
heart	106.950900385266	74.061507631644	105.251730896159
kidney	77.8496372773995	96.696484343503	76.5565068709314
liver	84.7241423080964	77.9809749622475	127.892976696439
stomach	86.9918165721678	121.117333992643	96.6339025331043
testicle	90.4538717793987	96.4144943627726	91.8808510992594
cont.diffExp=13.9719944916002,25.2521661849659,3.08572816537347,32.8893927536218,-18.8468470661035,6.7431673458489,-34.1255174204748,-5.96062258337395
cont.diffExpScore=5.8674966046962

cont.diffExp1.5=0,0,0,0,0,0,0,0
cont.diffExp1.5Score=0
cont.diffExp1.4=0,0,0,1,0,0,0,0
cont.diffExp1.4Score=0.5
cont.diffExp1.3=0,1,0,1,0,0,-1,0
cont.diffExp1.3Score=1.5
cont.diffExp1.2=0,1,0,1,-1,0,-1,0
cont.diffExp1.2Score=4

tran.correlation=0.509248665333585
cont.tran.correlation=-0.410896203419868

tran.covariance=0.00944098073434438
cont.tran.covariance=-0.0080321874172851

tran.mean=176.778549955071
cont.tran.mean=89.9955085648656

weightedLogRatios:
wLogRatio
Lung	-7.48049014375566
cerebhem	-4.08043474405911
cortex	-5.3455337712094
heart	-6.41168452375642
kidney	-8.23152312797849
liver	-7.93574934653189
stomach	-5.96313794160833
testicle	-8.4417126132062

cont.weightedLogRatios:
wLogRatio
Lung	0.727114843604127
cerebhem	1.21676039440427
cortex	0.164523854316789
heart	1.64945553399624
kidney	-0.967607231058765
liver	0.364745665540735
stomach	-1.53270461186253
testicle	-0.289519533307638

varWeightedLogRatios=2.40394683189396
cont.varWeightedLogRatios=1.14817821845141

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	5.73611131068102	0.0925628354518514	61.9699178690868	1.0166813674979e-289	***
df.mm.trans1	-1.86578834026315	0.0814348498894465	-22.9114235833440	1.53096942071772e-87	***
df.mm.trans2	0.067712652535164	0.0736307167222725	0.919625063417069	0.358078867436745	   
df.mm.exp2	-0.712688126662579	0.0981116578313201	-7.26405141260459	9.84499194235674e-13	***
df.mm.exp3	-0.611165473022939	0.09811165783132	-6.22928494464638	7.99509740767192e-10	***
df.mm.exp4	-0.308952333293495	0.09811165783132	-3.14898698200235	0.00170654487849004	** 
df.mm.exp5	0.0552480187861383	0.09811165783132	0.563113701341427	0.573533997391571	   
df.mm.exp6	0.101526333528964	0.0981116578313201	1.03480397511491	0.301110325600009	   
df.mm.exp7	-0.150437471403879	0.09811165783132	-1.53332921621323	0.125637095875314	   
df.mm.exp8	0.217994691287272	0.09811165783132	2.22190406426586	0.0266020531864888	*  
df.mm.trans1:exp2	0.711070139664915	0.0923009881508712	7.70381936217876	4.41510861817391e-14	***
df.mm.trans2:exp2	0.087228225126857	0.0758512355975192	1.14999082664528	0.250532139450685	   
df.mm.trans1:exp3	0.473325964132756	0.0923009881508712	5.1280703881423	3.77307012399866e-07	***
df.mm.trans2:exp3	0.118990036389960	0.0758512355975192	1.56872904511857	0.117153510229043	   
df.mm.trans1:exp4	0.221825955339613	0.0923009881508712	2.40328906313577	0.0165020284648022	*  
df.mm.trans2:exp4	0.0538422872502896	0.0758512355975192	0.709840608740863	0.478034411099409	   
df.mm.trans1:exp5	-0.0744319356183322	0.0923009881508712	-0.806404537042106	0.420277764449118	   
df.mm.trans2:exp5	0.0598108604472042	0.0758512355975192	0.788528492331645	0.430648999249135	   
df.mm.trans1:exp6	-0.0798283498315875	0.0923009881508713	-0.864869937265498	0.387400250353299	   
df.mm.trans2:exp6	-0.00714115044727192	0.0758512355975192	-0.0941467912950581	0.92501892745221	   
df.mm.trans1:exp7	0.194745060443694	0.0923009881508712	2.10989139277006	0.0352145802959196	*  
df.mm.trans2:exp7	-0.0848007987523572	0.0758512355975192	-1.11798836346353	0.263947455571599	   
df.mm.trans1:exp8	-0.180844012215374	0.0923009881508712	-1.95928576538936	0.0504675295876964	.  
df.mm.trans2:exp8	-0.0266426898754791	0.0758512355975192	-0.351249253431416	0.725504838318862	   
df.mm.trans1:probe2	-0.00331976820429891	0.0538921663653889	-0.061600199587281	0.95089843274979	   
df.mm.trans1:probe3	0.399934850216249	0.0538921663653889	7.42102010716532	3.30713016178125e-13	***
df.mm.trans1:probe4	0.231792008427204	0.0538921663653889	4.30103341653876	1.93635390644397e-05	***
df.mm.trans1:probe5	0.0933598727305158	0.0538921663653889	1.73234588673864	0.0836432330963378	.  
df.mm.trans1:probe6	0.0380979044609491	0.0538921663653889	0.706928428199477	0.479841277092488	   
df.mm.trans1:probe7	0.543601923445894	0.0538921663653889	10.0868448998742	1.84656173446219e-22	***
df.mm.trans1:probe8	0.488619219790732	0.0538921663653889	9.0666093561334	1.16492376320005e-18	***
df.mm.trans1:probe9	0.0319743795436508	0.0538921663653889	0.593302917660881	0.553166070889991	   
df.mm.trans1:probe10	1.02931555587879	0.0538921663653889	19.0995394191435	5.0625233664838e-66	***
df.mm.trans1:probe11	0.859406904971095	0.0538921663653889	15.9467871294005	3.30445710589425e-49	***
df.mm.trans1:probe12	1.26717958721404	0.0538921663653889	23.5132426969545	5.23552085361807e-91	***
df.mm.trans1:probe13	1.01212143295294	0.0538921663653889	18.7804926246749	2.86244216181494e-64	***
df.mm.trans1:probe14	1.60558352360974	0.0538921663653889	29.7925214719313	1.96076202712598e-127	***
df.mm.trans1:probe15	1.61676888234047	0.0538921663653889	30.0000722067615	1.24003805737239e-128	***
df.mm.trans1:probe16	0.199824139840615	0.0538921663653889	3.70785131341367	0.000225205578371028	***
df.mm.trans1:probe17	0.239439334762869	0.0538921663653889	4.44293393476651	1.02808814697150e-05	***
df.mm.trans1:probe18	0.304672179542516	0.0538921663653889	5.65336671524464	2.27425970583123e-08	***
df.mm.trans1:probe19	0.129402134465543	0.0538921663653889	2.40113068730985	0.0165988846192668	*  
df.mm.trans1:probe20	0.145218518010566	0.0538921663653889	2.69461273881596	0.0072124969544375	** 
df.mm.trans1:probe21	0.104013347644618	0.0538921663653889	1.93002721284960	0.0539987038036426	.  
df.mm.trans2:probe2	0.100282482836907	0.0538921663653889	1.86079888043452	0.0631828679937484	.  
df.mm.trans2:probe3	-0.374840751197405	0.0538921663653889	-6.95538473358047	7.94814988066229e-12	***
df.mm.trans2:probe4	-0.050936179343873	0.0538921663653889	-0.945149968522804	0.344901597121281	   
df.mm.trans2:probe5	-0.235267858254066	0.0538921663653889	-4.36552979998893	1.45535303040477e-05	***
df.mm.trans2:probe6	0.0771248276119522	0.0538921663653889	1.43109533005309	0.152839811180427	   
df.mm.trans3:probe2	0.0643095217066015	0.0538921663653889	1.19329999225830	0.233147706154338	   
df.mm.trans3:probe3	0.232315990902243	0.0538921663653889	4.31075621134138	1.85520261573864e-05	***
df.mm.trans3:probe4	0.114579460949677	0.0538921663653889	2.12608749429051	0.0338379931976790	*  
df.mm.trans3:probe5	0.0306929660067073	0.0538921663653888	0.569525555877806	0.56917841143949	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.32981705209752	0.346255210419132	12.5046986205822	1.37202634450670e-32	***
df.mm.trans1	0.151639794052804	0.304628104209147	0.497786619020199	0.618787507029795	   
df.mm.trans2	-0.0181494959735107	0.275434726988714	-0.0658940002661841	0.947480636990116	   
df.mm.exp2	0.808148226273745	0.367012014715395	2.20196667648724	0.0279862399720413	*  
df.mm.exp3	0.085743173895383	0.367012014715395	0.233624978086545	0.815343006219198	   
df.mm.exp4	0.197939580735305	0.367012014715395	0.539327250332118	0.589828968855346	   
df.mm.exp5	0.465355876738931	0.367012014715395	1.26795815417595	0.205225624847275	   
df.mm.exp6	-0.178299601906327	0.367012014715396	-0.485814073538143	0.627247836962964	   
df.mm.exp7	0.568672904768354	0.367012014715395	1.54946672579463	0.121712053721925	   
df.mm.exp8	0.430032634818627	0.367012014715395	1.17171268943907	0.241702718613045	   
df.mm.trans1:exp2	-0.659385708292266	0.345275702911005	-1.90973677769102	0.0565670037873942	.  
df.mm.trans2:exp2	-0.76367902607435	0.283741151771781	-2.69146375598205	0.0072802378611269	** 
df.mm.trans1:exp3	-0.178813391922800	0.345275702911005	-0.517885824039259	0.604698133073751	   
df.mm.trans2:exp3	-0.0525481279300024	0.283741151771781	-0.185197415326868	0.853126716815035	   
df.mm.trans1:exp4	-0.054122664975506	0.345275702911005	-0.156752023149037	0.875484535598677	   
df.mm.trans2:exp4	-0.258082254282768	0.283741151771781	-0.909569347524003	0.363356171441696	   
df.mm.trans1:exp5	-0.639129576202365	0.345275702911005	-1.85107023405901	0.0645716526728157	.  
df.mm.trans2:exp5	-0.258817436984975	0.283741151771781	-0.912160380575135	0.361991738587205	   
df.mm.trans1:exp6	0.0891472576208036	0.345275702911005	0.258191517298225	0.796333404047711	   
df.mm.trans2:exp6	0.169725882383705	0.283741151771781	0.598171542350752	0.549914902834234	   
df.mm.trans1:exp7	-0.631411791409531	0.345275702911005	-1.82871770612911	0.0678583247700145	.  
df.mm.trans2:exp7	-0.136951732331481	0.283741151771781	-0.482664327949278	0.62948183279231	   
df.mm.trans1:exp8	-0.45374555663382	0.345275702911005	-1.31415432018039	0.189215715295807	   
df.mm.trans2:exp8	-0.226414693764964	0.283741151771781	-0.797962129748013	0.425157403684059	   
df.mm.trans1:probe2	-0.0079858636409675	0.201597577620634	-0.0396128948334651	0.968412804869355	   
df.mm.trans1:probe3	0.130372994959693	0.201597577620634	0.64669921384189	0.518034169109976	   
df.mm.trans1:probe4	0.128465983487912	0.201597577620634	0.637239717878251	0.524172695798738	   
df.mm.trans1:probe5	0.101341836639248	0.201597577620634	0.50269372199478	0.615334419384004	   
df.mm.trans1:probe6	-0.0225775163874327	0.201597577620634	-0.111992994429323	0.910860393683799	   
df.mm.trans1:probe7	-0.008640240758018	0.201597577620634	-0.0428588520754807	0.965826015534199	   
df.mm.trans1:probe8	-0.0937772589212224	0.201597577620634	-0.46517056419047	0.641950954134937	   
df.mm.trans1:probe9	0.07570824896605	0.201597577620634	0.375541461656438	0.707369200212946	   
df.mm.trans1:probe10	0.0565913311919287	0.201597577620634	0.280714341213078	0.779010714098828	   
df.mm.trans1:probe11	0.427440325319134	0.201597577620634	2.12026518554449	0.0343274568597503	*  
df.mm.trans1:probe12	-0.0133472756294208	0.201597577620634	-0.066207519886661	0.947231117621954	   
df.mm.trans1:probe13	-0.0233429446136643	0.201597577620634	-0.115789807046149	0.90785164071836	   
df.mm.trans1:probe14	0.0575110139231097	0.201597577620634	0.285276314338131	0.775515074038801	   
df.mm.trans1:probe15	0.0438979807550615	0.201597577620634	0.217750536852524	0.82768561216457	   
df.mm.trans1:probe16	-0.128432116386247	0.201597577620634	-0.63707172428396	0.524282048115188	   
df.mm.trans1:probe17	-0.0646338494990495	0.201597577620634	-0.320608264553046	0.748600951987772	   
df.mm.trans1:probe18	0.398816761974033	0.201597577620634	1.97828151846411	0.0482803912765831	*  
df.mm.trans1:probe19	-0.0820809064498731	0.201597577620634	-0.407152245669999	0.684018032700223	   
df.mm.trans1:probe20	0.26394125984926	0.201597577620634	1.30924817135424	0.190870880131255	   
df.mm.trans1:probe21	-0.0147713641366497	0.201597577620634	-0.073271535853702	0.941610534284836	   
df.mm.trans2:probe2	0.0728044808184885	0.201597577620634	0.361137676740798	0.718103208897329	   
df.mm.trans2:probe3	-0.0365811367892403	0.201597577620634	-0.181456231870398	0.856060911279634	   
df.mm.trans2:probe4	0.184481499740988	0.201597577620634	0.915097799876071	0.360448796035892	   
df.mm.trans2:probe5	0.218256751545813	0.201597577620634	1.08263578422816	0.279335088828147	   
df.mm.trans2:probe6	0.148119950247936	0.201597577620634	0.734730803793029	0.462744354091295	   
df.mm.trans3:probe2	0.318838681202311	0.201597577620634	1.58156008105564	0.114192260902507	   
df.mm.trans3:probe3	0.545476009109637	0.201597577620634	2.70576668404277	0.00697708987047915	** 
df.mm.trans3:probe4	0.436457524825561	0.201597577620634	2.16499389514931	0.0307182842475556	*  
df.mm.trans3:probe5	0.235792316575639	0.201597577620634	1.16961879879010	0.24254415255217