chr13.6582_chr13_89666620_89669700_+_2.R 

fitVsDatCorrelation=0.900139664762003
cont.fitVsDatCorrelation=0.269577564302248

fstatistic=12481.7689989555,55,761
cont.fstatistic=2542.99744741014,55,761

residuals=-0.535428164849571,-0.0900343996996875,-0.00079370961947376,0.0793383686655035,0.645199524729559
cont.residuals=-0.526416721096812,-0.185176115972639,-0.0574955864018909,0.111726797756643,1.59078328252704

predictedValues:
Include	Exclude	Both
chr13.6582_chr13_89666620_89669700_+_2.R.tl.Lung	47.5097727846432	59.1539326080455	76.6651679365187
chr13.6582_chr13_89666620_89669700_+_2.R.tl.cerebhem	48.633709559561	58.9452043374095	68.3311549087867
chr13.6582_chr13_89666620_89669700_+_2.R.tl.cortex	48.6080823800516	57.6555349085298	70.8677622600881
chr13.6582_chr13_89666620_89669700_+_2.R.tl.heart	52.2971714818406	59.934257843834	74.8678568494994
chr13.6582_chr13_89666620_89669700_+_2.R.tl.kidney	60.4253202875245	62.8274977274008	102.573966190003
chr13.6582_chr13_89666620_89669700_+_2.R.tl.liver	56.5047450593447	62.0815079751256	101.221843968331
chr13.6582_chr13_89666620_89669700_+_2.R.tl.stomach	48.580780710258	58.4905984551169	72.3537028299155
chr13.6582_chr13_89666620_89669700_+_2.R.tl.testicle	55.5097948589354	60.4025592523943	86.616360531174


diffExp=-11.6441598234023,-10.3114947778484,-9.04745252847821,-7.63708636199342,-2.40217743987632,-5.5767629157809,-9.90981774485891,-4.89276439345898
diffExpScore=0.983979934158985
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,-1,0,0,0,0,-1,0
diffExp1.2Score=0.75

cont.predictedValues:
Include	Exclude	Both
Lung	62.0374600376	59.2408099020428	58.6808467537231
cerebhem	57.208513362002	60.6079042090358	58.1275916512207
cortex	54.6594567872734	59.262897907729	54.6529142082026
heart	52.5422992185963	66.8139993102371	60.5115915953659
kidney	55.634317882614	54.7378650850772	55.232577176226
liver	54.6918754897427	60.9258141674101	53.891870228744
stomach	57.7707326436646	56.8489968514749	63.659115364234
testicle	57.1086327520313	60.2577799573627	54.9466709619101
cont.diffExp=2.79665013555726,-3.39939084703385,-4.60344112045551,-14.2717000916408,0.896452797536817,-6.23393867766737,0.921735792189722,-3.14914720533134
cont.diffExpScore=1.29346868179257

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=0.935148553647192
cont.tran.correlation=-0.436718901525466

tran.covariance=0.00244091857765410
cont.tran.covariance=-0.00125202652864235

tran.mean=56.097529389376
cont.tran.mean=58.1468347227434

weightedLogRatios:
wLogRatio
Lung	-0.870372542559974
cerebhem	-0.765408602246613
cortex	-0.677517691868257
heart	-0.54864452299212
kidney	-0.16065170997697
liver	-0.384154569784830
stomach	-0.738105562830111
testicle	-0.342854517791372

cont.weightedLogRatios:
wLogRatio
Lung	0.189339342627056
cerebhem	-0.235252130290423
cortex	-0.326804813154693
heart	-0.98082412483696
kidney	0.0651516071085965
liver	-0.437778025794203
stomach	0.0651139713628794
testicle	-0.218559216889918

varWeightedLogRatios=0.0602471654093982
cont.varWeightedLogRatios=0.138042040235135

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.90193955982487	0.0679141016193474	57.4540407188908	5.60654206346662e-279	***
df.mm.trans1	-0.132355355679645	0.0594687158806086	-2.22562995887395	0.0263312238468132	*  
df.mm.trans2	0.298533796810610	0.0533297394941956	5.59788590085093	3.02998110324821e-08	***
df.mm.exp2	0.134928329681671	0.0703291777475133	1.91852562482776	0.0554182340642589	.  
df.mm.exp3	0.0758294002164299	0.0703291777475134	1.07820683598296	0.281283103189027	   
df.mm.exp4	0.132834860204679	0.0703291777475134	1.88875889721852	0.0593041785262496	.  
df.mm.exp5	0.0095858721356012	0.0703291777475134	0.136300074060515	0.89162011317483	   
df.mm.exp6	-0.0561728335176417	0.0703291777475134	-0.798713070687475	0.424705999929088	   
df.mm.exp7	0.0688963591760389	0.0703291777475134	0.979626968246118	0.32758160903999	   
df.mm.exp8	0.0544712116281889	0.0703291777475134	0.774517964986655	0.438865114937042	   
df.mm.trans1:exp2	-0.111546859589472	0.065974616736472	-1.69075418861520	0.0912932429159768	.  
df.mm.trans2:exp2	-0.138463130923572	0.0526295374849442	-2.63090153439373	0.0086881596383005	** 
df.mm.trans1:exp3	-0.0529750117337254	0.065974616736472	-0.802960507452858	0.422248266351202	   
df.mm.trans2:exp3	-0.101486222846391	0.0526295374849442	-1.92831302907466	0.0541879155412806	.  
df.mm.trans1:exp4	-0.0368280058745399	0.065974616736472	-0.55821477556505	0.576861920734285	   
df.mm.trans2:exp4	-0.119729674863751	0.0526295374849442	-2.27495206276518	0.0231861841396167	*  
df.mm.trans1:exp5	0.230886922306501	0.065974616736472	3.49963264248661	0.000493002114333483	***
df.mm.trans2:exp5	0.0506638938488283	0.0526295374849442	0.962651322241276	0.336028312815252	   
df.mm.trans1:exp6	0.229562018781833	0.065974616736472	3.47955062321608	0.000530838873094939	***
df.mm.trans2:exp6	0.104477926376556	0.0526295374849442	1.98515760102289	0.0474855290341908	*  
df.mm.trans1:exp7	-0.0466037978336787	0.065974616736472	-0.706389822919808	0.480161957667767	   
df.mm.trans2:exp7	-0.080173401579894	0.0526295374849442	-1.52335371753608	0.128085660923409	   
df.mm.trans1:exp8	0.101152844784488	0.065974616736472	1.53320852455318	0.125640087730419	   
df.mm.trans2:exp8	-0.0335828094141557	0.0526295374849442	-0.638098129282682	0.523601764878797	   
df.mm.trans1:probe2	-0.0181902801214241	0.0404010367450099	-0.450242904315342	0.652663536656314	   
df.mm.trans1:probe3	0.18342283351323	0.0404010367450099	4.54005263951266	6.5356762750307e-06	***
df.mm.trans1:probe4	0.227514374634259	0.0404010367450099	5.63139941358957	2.51550132619658e-08	***
df.mm.trans1:probe5	-0.0601564229273299	0.0404010367450099	-1.48898215922046	0.136906350668359	   
df.mm.trans1:probe6	0.179821229276820	0.0404010367450099	4.45090630747318	9.8294533915965e-06	***
df.mm.trans1:probe7	-0.0716992589846834	0.0404010367450099	-1.77468859121640	0.0763490228404097	.  
df.mm.trans1:probe8	0.203261950255278	0.0404010367450099	5.03110728415612	6.08894793598266e-07	***
df.mm.trans1:probe9	0.151008796633822	0.0404010367450099	3.73774558279061	0.000199586677745142	***
df.mm.trans1:probe10	0.273224524994398	0.0404010367450099	6.76280974468173	2.69756683146362e-11	***
df.mm.trans1:probe11	0.386849205687001	0.0404010367450099	9.5752296686986	1.38846137398511e-20	***
df.mm.trans1:probe12	0.176255995333992	0.0404010367450099	4.36266020712357	1.46208282619630e-05	***
df.mm.trans1:probe13	0.0926231487280255	0.0404010367450099	2.29259336369544	0.0221434471981484	*  
df.mm.trans1:probe14	0.360418148053216	0.0404010367450099	8.92101235738048	3.39902664830657e-18	***
df.mm.trans1:probe15	0.109392087877412	0.0404010367450099	2.70765546359211	0.00692808419903146	** 
df.mm.trans1:probe16	0.107680808509625	0.0404010367450099	2.66529815037296	0.0078550717964322	** 
df.mm.trans1:probe17	0.0300073753970523	0.0404010367450099	0.742737756618551	0.457869670272959	   
df.mm.trans1:probe18	0.026384073745651	0.0404010367450099	0.653054373633365	0.513918466949279	   
df.mm.trans1:probe19	0.0452247871762695	0.0404010367450099	1.11939669919128	0.263324123647814	   
df.mm.trans1:probe20	0.0842980129527986	0.0404010367450099	2.08653093446199	0.0372629023180250	*  
df.mm.trans1:probe21	-0.0129164193789094	0.0404010367450099	-0.319705146687970	0.749279605991324	   
df.mm.trans1:probe22	0.0834094285420463	0.0404010367450099	2.06453683524219	0.0393051504349097	*  
df.mm.trans2:probe2	-0.198053564148586	0.0404010367450099	-4.90219014424297	1.15886883207608e-06	***
df.mm.trans2:probe3	-0.323420016157287	0.0404010367450099	-8.00524051396365	4.4545054217598e-15	***
df.mm.trans2:probe4	-0.414219062216264	0.0404010367450099	-10.2526839801314	3.41906388198529e-23	***
df.mm.trans2:probe5	-0.185638412397876	0.0404010367450099	-4.59489229371831	5.06693686139978e-06	***
df.mm.trans2:probe6	-0.322632342016252	0.0404010367450099	-7.98574412960088	5.15464226707384e-15	***
df.mm.trans3:probe2	0.210470358810743	0.0404010367450099	5.20952865984903	2.43976384923200e-07	***
df.mm.trans3:probe3	-0.128261422834069	0.0404010367450099	-3.17470622458497	0.00156028345161812	** 
df.mm.trans3:probe4	0.389957768082063	0.0404010367450099	9.65217230793535	7.12930587368884e-21	***
df.mm.trans3:probe5	1.1417274743694	0.0404010367450099	28.25985584418	1.06947803501597e-120	***
df.mm.trans3:probe6	0.0140826442962617	0.0404010367450099	0.34857135932288	0.727507543202495	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.17809828844454	0.150136870895912	27.8285957574083	4.12505846134153e-118	***
df.mm.trans1	-0.104495093001379	0.131466760298999	-0.794840405009768	0.426954159206941	   
df.mm.trans2	-0.0656671720364638	0.117895400549210	-0.556995198545124	0.577694480747477	   
df.mm.exp2	-0.0487480854897007	0.155475850050647	-0.313541205748807	0.7539554391522	   
df.mm.exp3	-0.0551325275944914	0.155475850050647	-0.354605088677962	0.722983705166677	   
df.mm.exp4	-0.0765394440072213	0.155475850050647	-0.49229152940658	0.622655254344266	   
df.mm.exp5	-0.127432679037880	0.155475850050647	-0.819630051846429	0.412683659339599	   
df.mm.exp6	-0.0128431775728582	0.155475850050647	-0.0826056108950324	0.934186861929416	   
df.mm.exp7	-0.193897333601563	0.155475850050647	-1.24712187480177	0.212736488360534	   
df.mm.exp8	-1.17866325254403e-05	0.155475850050647	-7.58100535973959e-05	0.999939532401199	   
df.mm.trans1:exp2	-0.0322875889474730	0.145849275469900	-0.221376409608126	0.824858745911121	   
df.mm.trans2:exp2	0.071562741705366	0.116347472561392	0.615077750551091	0.538687251062452	   
df.mm.trans1:exp3	-0.0714836267332222	0.145849275469900	-0.490119861774526	0.624190352690494	   
df.mm.trans2:exp3	0.0555053092795579	0.116347472561393	0.477065019614154	0.633452790834037	   
df.mm.trans1:exp4	-0.0895804081430244	0.145849275469900	-0.614198513187072	0.539267724309348	   
df.mm.trans2:exp4	0.196841412259155	0.116347472561393	1.69184089628839	0.0910856975651443	.  
df.mm.trans1:exp5	0.0184945212439355	0.145849275469900	0.126805712159690	0.899127670985169	   
df.mm.trans2:exp5	0.0483777200401496	0.116347472561393	0.415803789932973	0.67767080937694	   
df.mm.trans1:exp6	-0.113180049302689	0.145849275469900	-0.776006935502718	0.437985988909481	   
df.mm.trans2:exp6	0.0408894795856505	0.116347472561393	0.351442783289293	0.725353471503462	   
df.mm.trans1:exp7	0.122641228644511	0.145849275469900	0.840876502467243	0.400681252136399	   
df.mm.trans2:exp7	0.152685247263514	0.116347472561393	1.31232113514926	0.189807476866574	   
df.mm.trans1:exp8	-0.0827713183307141	0.145849275469900	-0.567512715192035	0.570533266856984	   
df.mm.trans2:exp8	0.0170328177436632	0.116347472561393	0.146396113028373	0.88364746669275	   
df.mm.trans1:probe2	-0.0685590053215818	0.0893140760639697	-0.76761702458275	0.442952846008416	   
df.mm.trans1:probe3	0.0920407554615832	0.0893140760639697	1.03052911162246	0.303089101138102	   
df.mm.trans1:probe4	0.0656895190449146	0.0893140760639697	0.735488983817798	0.462268357917578	   
df.mm.trans1:probe5	0.0245965828893692	0.0893140760639697	0.275394248850006	0.783088119489156	   
df.mm.trans1:probe6	0.0822543026554575	0.0893140760639697	0.920955646415065	0.357365436771896	   
df.mm.trans1:probe7	0.072407189694811	0.0893140760639697	0.81070300321923	0.417789704685482	   
df.mm.trans1:probe8	0.0727809146077046	0.0893140760639697	0.814887393064186	0.415391711556416	   
df.mm.trans1:probe9	0.0500431324779658	0.0893140760639697	0.560305101763839	0.575436252032695	   
df.mm.trans1:probe10	0.194809792684147	0.0893140760639697	2.18117682306446	0.0294757652300158	*  
df.mm.trans1:probe11	0.0265491312586794	0.0893140760639697	0.297255846207982	0.766352309784426	   
df.mm.trans1:probe12	0.119526238743169	0.0893140760639697	1.33826877028387	0.181208547130969	   
df.mm.trans1:probe13	0.0759205877187103	0.0893140760639697	0.850040565434876	0.395569884373805	   
df.mm.trans1:probe14	-0.0356313592154635	0.0893140760639697	-0.398944497728926	0.690046020849643	   
df.mm.trans1:probe15	0.138575662002541	0.0893140760639697	1.55155456014893	0.121184596677123	   
df.mm.trans1:probe16	0.0812687130529935	0.0893140760639697	0.909920548187569	0.363152512137680	   
df.mm.trans1:probe17	0.0919365710972743	0.0893140760639697	1.02936261728136	0.303636357288641	   
df.mm.trans1:probe18	0.159444022875136	0.0893140760639697	1.78520598210004	0.0746260948501557	.  
df.mm.trans1:probe19	0.0614830842356974	0.0893140760639697	0.688391874441619	0.491415829400757	   
df.mm.trans1:probe20	0.087279737845396	0.0893140760639697	0.977222647221737	0.328769479699221	   
df.mm.trans1:probe21	0.0361745541695706	0.0893140760639697	0.405026349303117	0.685571969674118	   
df.mm.trans1:probe22	0.0871955085609692	0.0893140760639697	0.976279578803647	0.329236171888919	   
df.mm.trans2:probe2	0.0184393909037674	0.0893140760639697	0.20645559710611	0.836490268958573	   
df.mm.trans2:probe3	-0.0985356119861817	0.0893140760639697	-1.10324840527497	0.270268054102761	   
df.mm.trans2:probe4	-0.166723253739754	0.0893140760639697	-1.86670747867718	0.0623268084130503	.  
df.mm.trans2:probe5	-0.0335837456515371	0.0893140760639697	-0.376018508297431	0.707007935188919	   
df.mm.trans2:probe6	-0.0894422462668493	0.0893140760639697	-1.00143505042573	0.316934841183935	   
df.mm.trans3:probe2	0.162542791190896	0.0893140760639697	1.81990116624481	0.0691667878438533	.  
df.mm.trans3:probe3	0.212274094399758	0.0893140760639697	2.37671488923784	0.0177139704157139	*  
df.mm.trans3:probe4	-0.00988545476978548	0.0893140760639697	-0.110681935092798	0.911897754525038	   
df.mm.trans3:probe5	0.0801488168424577	0.0893140760639697	0.897381693620751	0.369799083438612	   
df.mm.trans3:probe6	-0.0600160889442236	0.0893140760639697	-0.671966744651069	0.50180881412493