chr8.23105_chr8_21191842_21202799_-_2.R 

fitVsDatCorrelation=0.87832156132856
cont.fitVsDatCorrelation=0.211931306749806

fstatistic=9736.6291894188,69,1083
cont.fstatistic=2318.02920252666,69,1083

residuals=-0.932160948374345,-0.0927487778540749,-0.00888087659785712,0.0850278200836528,1.68998322339555
cont.residuals=-0.583381029667033,-0.239206428496197,-0.0751571263550702,0.167642983421366,2.36104586712446

predictedValues:
Include	Exclude	Both
chr8.23105_chr8_21191842_21202799_-_2.R.tl.Lung	52.2072697802723	43.3222669769219	65.5741683276395
chr8.23105_chr8_21191842_21202799_-_2.R.tl.cerebhem	54.5005051537688	46.874549247827	76.509280123332
chr8.23105_chr8_21191842_21202799_-_2.R.tl.cortex	59.777182964709	45.4168515429913	73.1013091609404
chr8.23105_chr8_21191842_21202799_-_2.R.tl.heart	64.3014888876448	46.28124703048	83.457506219312
chr8.23105_chr8_21191842_21202799_-_2.R.tl.kidney	56.2006347403866	45.1021907118118	68.7470182781262
chr8.23105_chr8_21191842_21202799_-_2.R.tl.liver	50.8901121548372	49.1141660442782	65.7704664448932
chr8.23105_chr8_21191842_21202799_-_2.R.tl.stomach	51.1697529030518	50.7486027790205	66.6725719657644
chr8.23105_chr8_21191842_21202799_-_2.R.tl.testicle	52.5758561693197	45.7029993727117	67.3157706807044


diffExp=8.88500280335036,7.62595590594177,14.3603314217176,18.0202418571647,11.0984440285748,1.77594611055903,0.421150124031293,6.87285679660804
diffExpScore=0.985726505670372
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=0,0,1,1,0,0,0,0
diffExp1.3Score=0.666666666666667
diffExp1.2=1,0,1,1,1,0,0,0
diffExp1.2Score=0.8

cont.predictedValues:
Include	Exclude	Both
Lung	66.2367393064846	55.2721307142703	59.0922660063733
cerebhem	61.2456562994721	61.9290878469694	65.1083560515394
cortex	62.4482261831008	55.4474445365583	61.1564011044645
heart	64.3652952548426	58.3661866085988	63.7211092866862
kidney	64.8485446685338	58.5357504069845	64.797644248843
liver	65.4239377067742	61.9376861588026	63.9828944546075
stomach	64.8634969632958	57.8001364141814	56.2003763056238
testicle	64.9702666502199	54.2595817070062	62.3500026654142
cont.diffExp=10.9646085922143,-0.683431547497285,7.00078164654249,5.99910864624386,6.31279426154935,3.48625154797156,7.0633605491144,10.7106849432137
cont.diffExpScore=1.00707490208348

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=-0.326140870277408
cont.tran.correlation=-0.312038506234215

tran.covariance=-0.00136075496806075
cont.tran.covariance=-0.000401109873259512

tran.mean=50.886604778752
cont.tran.mean=61.121885464131

weightedLogRatios:
wLogRatio
Lung	0.72046501500349
cerebhem	0.591310053406192
cortex	1.08612012979433
heart	1.31510746516331
kidney	0.862153625388235
liver	0.138955423234608
stomach	0.0324879150801965
testicle	0.545271747035622

cont.weightedLogRatios:
wLogRatio
Lung	0.742460544689411
cerebhem	-0.0457247725517869
cortex	0.484513019497976
heart	0.402666977558745
kidney	0.422043799954957
liver	0.22744360839545
stomach	0.474392585233365
testicle	0.735706952379688

varWeightedLogRatios=0.191198342074794
cont.varWeightedLogRatios=0.0663118166067029

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	2.92374368800820	0.0769911133460316	37.9750799922534	2.64667006896334e-201	***
df.mm.trans1	0.95355621850363	0.0656620999735038	14.5221706111808	8.6035402694739e-44	***
df.mm.trans2	0.826576825343378	0.0571948434708919	14.4519466298399	2.02545796604447e-43	***
df.mm.exp2	-0.0324338653998562	0.0717067832646678	-0.452312374411550	0.65113454486104	   
df.mm.exp3	0.0739543103124548	0.0717067832646677	1.03134329759978	0.302610121642627	   
df.mm.exp4	0.033275377019988	0.0717067832646677	0.464047827904502	0.642706738628014	   
df.mm.exp5	0.0667188440891574	0.0717067832646678	0.930439786190101	0.352350776096028	   
df.mm.exp6	0.096938590621153	0.0717067832646678	1.35187476285689	0.176697641465169	   
df.mm.exp7	0.121532364691505	0.0717067832646678	1.69485171637016	0.0903910285034142	.  
df.mm.exp8	0.0343197286541713	0.0717067832646677	0.478612023739764	0.632311270046971	   
df.mm.trans1:exp2	0.0754220828895512	0.0651936366784572	1.15689332168325	0.247571056873052	   
df.mm.trans2:exp2	0.11124198188039	0.0432720493608409	2.57075834224432	0.0102802568753698	*  
df.mm.trans1:exp3	0.0614479690460664	0.0651936366784572	0.942545502548587	0.34612362888365	   
df.mm.trans2:exp3	-0.0267378464915777	0.0432720493608409	-0.617901090577284	0.536770449112202	   
df.mm.trans1:exp4	0.175085656271310	0.0651936366784572	2.68562493506619	0.00735010539035874	** 
df.mm.trans2:exp4	0.032794718568148	0.0432720493608409	0.757873016243728	0.448691879234567	   
df.mm.trans1:exp5	0.00698745404659598	0.0651936366784572	0.107180001033827	0.914666031819202	   
df.mm.trans2:exp5	-0.0264547759363976	0.0432720493608409	-0.611359441652371	0.541089947736726	   
df.mm.trans1:exp6	-0.122491699167984	0.0651936366784572	-1.87889041643937	0.0605278574707193	.  
df.mm.trans2:exp6	0.0285421649897561	0.0432720493608409	0.65959817968745	0.509651957914286	   
df.mm.trans1:exp7	-0.141605523840930	0.0651936366784572	-2.17207585058256	0.0300663478618646	*  
df.mm.trans2:exp7	0.0366849696860726	0.0432720493608409	0.847775185782413	0.396750503638074	   
df.mm.trans1:exp8	-0.0272844754878899	0.0651936366784572	-0.418514396158941	0.675654041528413	   
df.mm.trans2:exp8	0.0191774471628674	0.0432720493608409	0.443183242904646	0.657721711277383	   
df.mm.trans1:probe2	0.264597880145727	0.0495181217607174	5.34345550148938	1.11134166067527e-07	***
df.mm.trans1:probe3	-0.0120655417681626	0.0495181217607174	-0.243659115878142	0.80754098626583	   
df.mm.trans1:probe4	0.246065494183083	0.0495181217607174	4.96920087906657	7.80897317055897e-07	***
df.mm.trans1:probe5	0.35353551234683	0.0495181217607174	7.13951781239184	1.71408571405113e-12	***
df.mm.trans1:probe6	0.295412923697105	0.0495181217607174	5.96575381280829	3.29399153112536e-09	***
df.mm.trans1:probe7	0.379080152610747	0.0495181217607174	7.65538229504234	4.25309832017379e-14	***
df.mm.trans1:probe8	0.253873296616762	0.0495181217607174	5.12687653710968	3.48746483042631e-07	***
df.mm.trans1:probe9	0.236452191936462	0.0495181217607174	4.77506382570509	2.04305043049039e-06	***
df.mm.trans1:probe10	0.454167818846408	0.0495181217607174	9.1717497089459	2.28392740796953e-19	***
df.mm.trans1:probe11	0.0328150377339804	0.0495181217607174	0.662687447891298	0.507671755164469	   
df.mm.trans1:probe12	0.527975969774609	0.0495181217607174	10.6622777884409	2.61407376010704e-25	***
df.mm.trans1:probe13	0.0581593998015635	0.0495181217607174	1.17450738706534	0.240450040321464	   
df.mm.trans1:probe14	0.331842763723688	0.0495181217607174	6.70144084477247	3.31258033847128e-11	***
df.mm.trans1:probe15	0.426126348599368	0.0495181217607174	8.60546267603818	2.63682583743796e-17	***
df.mm.trans1:probe16	-0.0764014592785047	0.0495181217607174	-1.54289897439353	0.123147420920640	   
df.mm.trans1:probe17	-0.057963213396606	0.0495181217607174	-1.17054547578959	0.242039027971513	   
df.mm.trans1:probe18	-0.119366051490887	0.0495181217607174	-2.41055288945914	0.0160941506623806	*  
df.mm.trans1:probe19	-0.0218313577929684	0.0495181217607174	-0.440876128106442	0.659390668240107	   
df.mm.trans1:probe20	-0.0903897310938974	0.0495181217607174	-1.82538690644772	0.0682179650030703	.  
df.mm.trans1:probe21	-0.141286707450493	0.0495181217607174	-2.85323236073496	0.00441007651253239	** 
df.mm.trans1:probe22	-0.0680831746938794	0.0495181217607174	-1.37491431970850	0.169442384178464	   
df.mm.trans2:probe2	0.0617662534713436	0.0495181217607174	1.24734645166495	0.212540152253167	   
df.mm.trans2:probe3	0.164234254273923	0.0495181217607174	3.3166495100024	0.000941291239932815	***
df.mm.trans2:probe4	0.103086175505526	0.0495181217607174	2.08178686590056	0.0375963226740257	*  
df.mm.trans2:probe5	0.0130474060207383	0.0495181217607174	0.263487498249353	0.79222498079035	   
df.mm.trans2:probe6	0.134868108241229	0.0495181217607174	2.72361114367265	0.00656109195280878	** 
df.mm.trans3:probe2	-0.330226650977272	0.0495181217607174	-6.66880405062616	4.10314272177974e-11	***
df.mm.trans3:probe3	-0.909869341860209	0.0495181217607174	-18.3744720015210	7.57855099824419e-66	***
df.mm.trans3:probe4	-0.652066749239201	0.0495181217607174	-13.1682447971297	7.67597494472262e-37	***
df.mm.trans3:probe5	-0.749382434239448	0.0495181217607174	-15.1334987595174	4.44362946523032e-47	***
df.mm.trans3:probe6	-0.521626451365316	0.0495181217607174	-10.5340516323687	9.05146050693504e-25	***
df.mm.trans3:probe7	0.235745652830768	0.0495181217607174	4.76079553198611	2.18975133215806e-06	***
df.mm.trans3:probe8	-0.930202739653508	0.0495181217607174	-18.7850973861338	2.29035773776567e-68	***
df.mm.trans3:probe9	-0.33270502125279	0.0495181217607174	-6.71885381397328	2.95400060353772e-11	***
df.mm.trans3:probe10	0.0936448742214356	0.0495181217607174	1.89112330782554	0.058874567975828	.  
df.mm.trans3:probe11	-0.602174523458021	0.0495181217607174	-12.1606899059674	5.50601139483606e-32	***
df.mm.trans3:probe12	-0.806181062166027	0.0495181217607174	-16.2805258660996	1.78089000449829e-53	***
df.mm.trans3:probe13	-0.753959085850272	0.0495181217607174	-15.2259225318272	1.39051014568373e-47	***
df.mm.trans3:probe14	-0.437499688668815	0.0495181217607174	-8.83514303678381	3.96197788001376e-18	***
df.mm.trans3:probe15	-0.873566710663062	0.0495181217607174	-17.6413539044217	2.01895570086728e-61	***
df.mm.trans3:probe16	-0.377353029150026	0.0495181217607174	-7.62050368092472	5.49929816419148e-14	***
df.mm.trans3:probe17	-0.829969210358987	0.0495181217607174	-16.7609186465024	3.07445226340048e-56	***
df.mm.trans3:probe18	-0.787229625258818	0.0495181217607174	-15.8978086661462	2.6132302031117e-51	***
df.mm.trans3:probe19	-0.852614098462895	0.0495181217607174	-17.2182237158129	6.52432830355747e-59	***
df.mm.trans3:probe20	0.00333811660464288	0.0495181217607174	0.0674120198010216	0.946266143420281	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.15470772674751	0.157387361046167	26.3979756641881	5.6991701315226e-119	***
df.mm.trans1	0.0774874539774998	0.134228278907101	0.577281140817791	0.563869534530467	   
df.mm.trans2	-0.172249091281948	0.116919279227390	-1.47323086851186	0.140979366523940	   
df.mm.exp2	-0.0615740292454581	0.146584987496057	-0.420056857780982	0.674527240038148	   
df.mm.exp3	-0.090065122701321	0.146584987496056	-0.61442255608709	0.539065187618294	   
df.mm.exp4	-0.0496086201571067	0.146584987496056	-0.338429064289011	0.735105472235292	   
df.mm.exp5	-0.0559811403743903	0.146584987496057	-0.381902276151549	0.702608772999979	   
df.mm.exp6	0.0219972091449557	0.146584987496057	0.150064542902441	0.880741636001714	   
df.mm.exp7	0.0739486515440629	0.146584987496057	0.504476296019415	0.614029336299358	   
df.mm.exp8	-0.0914584341522864	0.146584987496056	-0.623927700336618	0.532806461467386	   
df.mm.trans1:exp2	-0.0167683248239225	0.133270633296458	-0.125821603823415	0.89989649314937	   
df.mm.trans2:exp2	0.175295199200890	0.0884579188425682	1.98167898922502	0.0477677005158062	*  
df.mm.trans1:exp3	0.0311676716562820	0.133270633296458	0.233867513685106	0.815132033882587	   
df.mm.trans2:exp3	0.0932319334193876	0.0884579188425682	1.05396932958954	0.292132039138705	   
df.mm.trans1:exp4	0.0209479310339410	0.133270633296457	0.157183398291076	0.875129610160422	   
df.mm.trans2:exp4	0.104076529768872	0.0884579188425682	1.17656543507542	0.239627538210262	   
df.mm.trans1:exp5	0.0348003259622716	0.133270633296458	0.261125238932864	0.794045575300339	   
df.mm.trans2:exp5	0.113350009912555	0.0884579188425682	1.28140036975422	0.200327363053038	   
df.mm.trans1:exp6	-0.0343442810893277	0.133270633296458	-0.257703293214865	0.796684862184073	   
df.mm.trans2:exp6	0.091862792420744	0.0884579188425682	1.03849145020284	0.299273111236253	   
df.mm.trans1:exp7	-0.0948989199769476	0.133270633296458	-0.712076754117669	0.476570612624938	   
df.mm.trans2:exp7	-0.0292263318727241	0.0884579188425682	-0.330398140213306	0.741163050224016	   
df.mm.trans1:exp8	0.0721528798218181	0.133270633296458	0.541401192724248	0.588342436339549	   
df.mm.trans2:exp8	0.0729692161932962	0.0884579188425682	0.824903153364508	0.409608226365153	   
df.mm.trans1:probe2	-0.0740047112714106	0.101226312611620	-0.73108176483073	0.464887350922817	   
df.mm.trans1:probe3	-0.200653829877669	0.101226312611620	-1.98222996275214	0.0477059355741997	*  
df.mm.trans1:probe4	-0.0578352037000347	0.101226312611620	-0.571345554410677	0.567883973460622	   
df.mm.trans1:probe5	-0.0922488775336064	0.101226312611620	-0.911313226310455	0.362333153145243	   
df.mm.trans1:probe6	-0.163239295756624	0.101226312611620	-1.61261722910852	0.107119034102093	   
df.mm.trans1:probe7	-0.125168180144521	0.101226312611620	-1.23651822253725	0.216534083777111	   
df.mm.trans1:probe8	-0.113163123296380	0.101226312611620	-1.11792201431419	0.263848221759155	   
df.mm.trans1:probe9	-0.069745784862638	0.101226312611620	-0.689008451095466	0.49096552929802	   
df.mm.trans1:probe10	-0.119250018358184	0.101226312611620	-1.17805356415298	0.239034043935928	   
df.mm.trans1:probe11	-0.119950555723204	0.101226312611620	-1.1849740707579	0.236287658912720	   
df.mm.trans1:probe12	-0.0175647055593020	0.101226312611620	-0.173519168150412	0.862275788365408	   
df.mm.trans1:probe13	-0.0210980214365288	0.101226312611620	-0.208424281120231	0.834936889699239	   
df.mm.trans1:probe14	-0.0547543291670166	0.101226312611620	-0.540910043588123	0.588680821755104	   
df.mm.trans1:probe15	-0.0489955312165058	0.101226312611620	-0.484019717328727	0.628469733192613	   
df.mm.trans1:probe16	-0.00740770466240916	0.101226312611620	-0.0731796355245166	0.941676684316197	   
df.mm.trans1:probe17	-0.103568118246938	0.101226312611620	-1.02313435681790	0.306472804554433	   
df.mm.trans1:probe18	0.0512268528348736	0.101226312611620	0.506062618633734	0.612915684166362	   
df.mm.trans1:probe19	-0.108159048493260	0.101226312611620	-1.06848748811229	0.285538771021365	   
df.mm.trans1:probe20	0.0137465578164007	0.101226312611620	0.135800242661636	0.892004435944736	   
df.mm.trans1:probe21	-0.148095151903938	0.101226312611620	-1.46301043753457	0.143754667890740	   
df.mm.trans1:probe22	-0.0563869062596838	0.101226312611620	-0.557038034923054	0.577616538569982	   
df.mm.trans2:probe2	0.115235026267551	0.101226312611620	1.13839004202078	0.255209410240948	   
df.mm.trans2:probe3	0.143953342305801	0.101226312611620	1.42209410371504	0.155286861825027	   
df.mm.trans2:probe4	0.200284863543427	0.101226312611620	1.97858499807129	0.0481157929814636	*  
df.mm.trans2:probe5	0.176596677333278	0.101226312611620	1.74457285637613	0.081342918713694	.  
df.mm.trans2:probe6	0.138994787335203	0.101226312611620	1.37310926130927	0.170002600448564	   
df.mm.trans3:probe2	0.0390441971587166	0.101226312611620	0.385711937453646	0.699785771626204	   
df.mm.trans3:probe3	-0.0464369031612749	0.101226312611620	-0.458743403401855	0.64651048852871	   
df.mm.trans3:probe4	0.136882550126272	0.101226312611620	1.35224277754199	0.176579958239784	   
df.mm.trans3:probe5	-0.0498841000301741	0.101226312611620	-0.492797759230514	0.622255389029502	   
df.mm.trans3:probe6	0.0797112967845913	0.101226312611620	0.787456292025803	0.43118710409183	   
df.mm.trans3:probe7	-0.0473311643278733	0.101226312611620	-0.467577679229224	0.640180698037295	   
df.mm.trans3:probe8	0.099758819783331	0.101226312611620	0.98550285207049	0.324597245126197	   
df.mm.trans3:probe9	0.034369996901407	0.101226312611620	0.339536193847898	0.734271667610742	   
df.mm.trans3:probe10	-0.0882740591370115	0.101226312611620	-0.872046574250873	0.383376253798653	   
df.mm.trans3:probe11	0.0328194412983804	0.101226312611620	0.324218480863768	0.745835237645266	   
df.mm.trans3:probe12	-0.0250538229642704	0.101226312611620	-0.247503068301969	0.804565830777826	   
df.mm.trans3:probe13	-0.0194730068742564	0.101226312611620	-0.192370998921688	0.847487672578614	   
df.mm.trans3:probe14	-0.0299612804095187	0.101226312611620	-0.295983125696502	0.767299711191872	   
df.mm.trans3:probe15	0.0550861303547715	0.101226312611620	0.544187859199446	0.586424221984648	   
df.mm.trans3:probe16	0.119172399543096	0.101226312611620	1.17728677918290	0.239339722607402	   
df.mm.trans3:probe17	0.0770077249808152	0.101226312611620	0.760748099916217	0.44697313526819	   
df.mm.trans3:probe18	0.0397967522507648	0.101226312611620	0.393146319608171	0.694288790232672	   
df.mm.trans3:probe19	-0.0662024991147089	0.101226312611620	-0.65400484722496	0.513247526118128	   
df.mm.trans3:probe20	0.0420467982244615	0.101226312611620	0.415374196092516	0.677950273325155