chr8.23614_chr8_84421237_84426197_-_2.R 

fitVsDatCorrelation=0.939656734727572
cont.fitVsDatCorrelation=0.27421491184619

fstatistic=8156.83811604102,62,922
cont.fstatistic=1019.35600130126,62,922

residuals=-1.16111428617867,-0.121308375450328,0.00358526850008132,0.124517426192406,0.870947365891294
cont.residuals=-1.58666296682534,-0.423595079539303,-0.0191506188958277,0.426270440537178,1.86435135014813

predictedValues:
Include	Exclude	Both
chr8.23614_chr8_84421237_84426197_-_2.R.tl.Lung	86.1259958809141	351.04948336549	170.815500930227
chr8.23614_chr8_84421237_84426197_-_2.R.tl.cerebhem	103.075147765396	251.574198285718	309.206002931734
chr8.23614_chr8_84421237_84426197_-_2.R.tl.cortex	103.806333373698	249.894542578713	221.851874712858
chr8.23614_chr8_84421237_84426197_-_2.R.tl.heart	85.7632786811403	278.373949328821	182.190972965789
chr8.23614_chr8_84421237_84426197_-_2.R.tl.kidney	65.4486673614155	303.756913564923	97.3706980273011
chr8.23614_chr8_84421237_84426197_-_2.R.tl.liver	70.7398309886397	232.662210615721	111.227266464482
chr8.23614_chr8_84421237_84426197_-_2.R.tl.stomach	77.8617675832188	287.331642717889	141.078872707753
chr8.23614_chr8_84421237_84426197_-_2.R.tl.testicle	96.4840118787015	260.347780521004	174.657686887118


diffExp=-264.923487484576,-148.499050520323,-146.088209205015,-192.610670647680,-238.308246203508,-161.922379627081,-209.46987513467,-163.863768642303
diffExpScore=0.99934498632678
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	150.824528602005	143.039502142416	195.401464122704
cerebhem	143.079386585148	159.797731636195	186.650677165729
cortex	148.920468923313	131.217425156758	162.190098098911
heart	154.798295012807	172.045507020012	134.476884547391
kidney	134.313273635056	104.017797671846	175.145522605744
liver	126.925989726228	177.796778960200	143.149732667782
stomach	152.708196107823	187.046274760302	146.334070937548
testicle	141.860090567990	164.255132508025	172.466059164994
cont.diffExp=7.7850264595892,-16.7183450510471,17.7030437665544,-17.2472120072053,30.2954759632105,-50.8707892339721,-34.3380786524785,-22.3950419400342
cont.diffExpScore=2.27402107960342

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

tran.correlation=-0.274901943147570
cont.tran.correlation=0.186168436728854

tran.covariance=-0.00557882774515013
cont.tran.covariance=0.00265108066984823

tran.mean=181.518484655713
cont.tran.mean=149.540398688508

weightedLogRatios:
wLogRatio
Lung	-7.24810663661071
cerebhem	-4.53420664524642
cortex	-4.46440741651448
heart	-5.93429457007351
kidney	-7.59613664507274
liver	-5.77942488581141
stomach	-6.53867655985665
testicle	-5.02841956678909

cont.weightedLogRatios:
wLogRatio
Lung	0.264431183817645
cerebhem	-0.554607519778017
cortex	0.62520714282947
heart	-0.538209545055306
kidney	1.21987903356302
liver	-1.68927103470499
stomach	-1.040491658557
testicle	-0.737021499717565

varWeightedLogRatios=1.40044786052372
cont.varWeightedLogRatios=0.896466859633451

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.43663955755269	0.102823856613262	43.1479590795707	1.87611040204231e-223	***
df.mm.trans1	-0.628804372144407	0.0877983878643828	-7.1619125070461	1.62604763782905e-12	***
df.mm.trans2	1.46788058216796	0.0773039431343469	18.988430895652	4.08199698006623e-68	***
df.mm.exp2	-0.746965901876856	0.0980714839445087	-7.61654531810192	6.44868593852123e-14	***
df.mm.exp3	-0.414598397090134	0.0980714839445087	-4.22751222286719	2.59815955198185e-05	***
df.mm.exp4	-0.300653612355223	0.0980714839445088	-3.06565782695141	0.00223519519039685	** 
df.mm.exp5	0.142814110152108	0.0980714839445088	1.45622462726184	0.145670965585789	   
df.mm.exp6	-0.179133549516965	0.0980714839445088	-1.82656101765854	0.0680890154863358	.  
df.mm.exp7	-0.109901424879901	0.0980714839445088	-1.12062569525395	0.262739027071525	   
df.mm.exp8	-0.207586766335799	0.0980714839445087	-2.11668833779712	0.0345536612713970	*  
df.mm.trans1:exp2	0.926612921569805	0.0889984214939636	10.4115658010030	4.46329184702265e-24	***
df.mm.trans2:exp2	0.413776679132139	0.0629313873532803	6.5750446086514	8.13334693508543e-11	***
df.mm.trans1:exp3	0.601314088650823	0.0889984214939636	6.75645790742039	2.50292604496417e-11	***
df.mm.trans2:exp3	0.0747102044934353	0.0629313873532803	1.18716919546095	0.235466660922778	   
df.mm.trans1:exp4	0.296433247366478	0.0889984214939636	3.33076971917512	0.00090044649400089	***
df.mm.trans2:exp4	0.068691771845509	0.0629313873532803	1.09153436360606	0.275322970294056	   
df.mm.trans1:exp5	-0.417359271644229	0.0889984214939637	-4.68951319178775	3.15221832047064e-06	***
df.mm.trans2:exp5	-0.28751354682743	0.0629313873532803	-4.56868279755862	5.57472423430307e-06	***
df.mm.trans1:exp6	-0.0176689483700150	0.0889984214939637	-0.198531030926357	0.842673375752113	   
df.mm.trans2:exp6	-0.232205980432230	0.0629313873532803	-3.68982776636857	0.000237552785041554	***
df.mm.trans1:exp7	0.00902517640453086	0.0889984214939637	0.101408275034889	0.919248416026062	   
df.mm.trans2:exp7	-0.0903886687329014	0.0629313873532803	-1.4363050384617	0.151254766300888	   
df.mm.trans1:exp8	0.321152788470219	0.0889984214939636	3.60852229825224	0.000324510862775830	***
df.mm.trans2:exp8	-0.091322070851996	0.0629313873532803	-1.45113709855684	0.147081828039045	   
df.mm.trans1:probe2	1.07404254788358	0.0651401745211976	16.4881742454355	1.01073247083179e-53	***
df.mm.trans1:probe3	0.671389201003622	0.0651401745211976	10.3068376150135	1.19001646615432e-23	***
df.mm.trans1:probe4	1.16945200646218	0.0651401745211976	17.9528534434863	4.91065580726392e-62	***
df.mm.trans1:probe5	0.903217331497195	0.0651401745211976	13.8657493342035	7.57040923365054e-40	***
df.mm.trans1:probe6	0.649727007287671	0.0651401745211976	9.97429024505055	2.54482191917682e-22	***
df.mm.trans1:probe7	-0.0312091949987485	0.0651401745211976	-0.479108249680733	0.63197522959215	   
df.mm.trans1:probe8	1.17862370197013	0.0651401745211976	18.0936528130821	7.47631855748051e-63	***
df.mm.trans1:probe9	2.43044660305924	0.0651401745211976	37.311023817849	1.94632813066373e-186	***
df.mm.trans1:probe10	2.01466266761798	0.0651401745211976	30.928112833999	1.18691939381331e-144	***
df.mm.trans1:probe11	1.77119125595334	0.0651401745211976	27.1904591747289	5.08792001332502e-120	***
df.mm.trans1:probe12	1.81488174725556	0.0651401745211976	27.8611741616531	1.99385616924754e-124	***
df.mm.trans1:probe13	1.73808065430038	0.0651401745211976	26.6821614629660	1.09303534242840e-116	***
df.mm.trans1:probe14	1.75716622975994	0.0651401745211976	26.9751538536043	1.31474885704672e-118	***
df.mm.trans1:probe15	0.732815134494911	0.0651401745211976	11.2498184090134	1.32739658435724e-27	***
df.mm.trans1:probe16	0.935908947946558	0.0651401745211976	14.3676149906844	2.17109376894444e-42	***
df.mm.trans1:probe17	0.942354966725701	0.0651401745211976	14.4665711084186	6.74010990822137e-43	***
df.mm.trans1:probe18	1.13988867223301	0.0651401745211976	17.4990116408434	2.01868106385049e-59	***
df.mm.trans1:probe19	0.80075691625471	0.0651401745211976	12.2928273088082	2.8549120806117e-32	***
df.mm.trans1:probe20	0.985767350474763	0.0651401745211976	15.1330167246325	2.24907155664993e-46	***
df.mm.trans2:probe2	0.526299017410548	0.0651401745211976	8.07948430103273	2.02880579844676e-15	***
df.mm.trans2:probe3	0.0669002061516959	0.0651401745211976	1.02701914207991	0.304680809088031	   
df.mm.trans2:probe4	-0.464134374909186	0.0651401745211976	-7.12516320873765	2.09508714363445e-12	***
df.mm.trans2:probe5	-0.555929084125045	0.0651401745211976	-8.53435054804985	5.74238898168132e-17	***
df.mm.trans2:probe6	-0.488587671310452	0.0651401745211976	-7.50055821774715	1.49299493692298e-13	***
df.mm.trans3:probe2	0.247436235311242	0.0651401745211976	3.79851968666007	0.000155099756188734	***
df.mm.trans3:probe3	-0.491757298708255	0.0651401745211976	-7.54921678246701	1.05120562076283e-13	***
df.mm.trans3:probe4	-0.406342781171518	0.0651401745211976	-6.23797501554571	6.74515815622721e-10	***
df.mm.trans3:probe5	0.561749566919563	0.0651401745211976	8.6237037442502	2.79714957637441e-17	***
df.mm.trans3:probe6	-0.577152831432195	0.0651401745211976	-8.86016710385664	4.04697895706233e-18	***
df.mm.trans3:probe7	-0.214436824425680	0.0651401745211976	-3.29192892100557	0.00103282879888860	** 
df.mm.trans3:probe8	-0.349625773458435	0.0651401745211976	-5.36728333978691	1.01168145423193e-07	***
df.mm.trans3:probe9	-0.430387311286309	0.0651401745211976	-6.60709484507529	6.61797988478864e-11	***
df.mm.trans3:probe10	0.338723393182200	0.0651401745211976	5.19991534674158	2.45648499491649e-07	***
df.mm.trans3:probe11	-0.760020982217232	0.0651401745211976	-11.6674692354395	1.95036506746428e-29	***
df.mm.trans3:probe12	-0.403180500345021	0.0651401745211976	-6.18942923178414	9.07468305600866e-10	***
df.mm.trans3:probe13	0.344768059502319	0.0651401745211976	5.29271009843744	1.50672133893094e-07	***
df.mm.trans3:probe14	-0.195542075802813	0.0651401745211976	-3.00186601034022	0.00275563814149235	** 
df.mm.trans3:probe15	0.308793091748172	0.0651401745211976	4.74044004361219	2.46920931986257e-06	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.84032925927267	0.289029657509240	16.7468255714137	3.65641773686136e-55	***
df.mm.trans1	0.0478946571077634	0.246794263608985	0.194067140813478	0.846166058540237	   
df.mm.trans2	0.0958159369614246	0.217295216734286	0.440948210464249	0.659353863932094	   
df.mm.exp2	0.103887934830264	0.275671117088291	0.376854622738701	0.706368359553085	   
df.mm.exp3	0.0873172896756562	0.275671117088290	0.316744425741529	0.75150923806892	   
df.mm.exp4	0.584307945114468	0.275671117088291	2.11958347789960	0.0343078680182825	*  
df.mm.exp5	-0.325061933006423	0.275671117088291	-1.17916572631841	0.238636381028116	   
df.mm.exp6	0.356172504116204	0.275671117088291	1.29201966414977	0.196674082495228	   
df.mm.exp7	0.569811068045902	0.275671117088291	2.06699589737363	0.0390131853499469	*  
df.mm.exp8	0.201880043382742	0.275671117088291	0.73232207100639	0.464158124870979	   
df.mm.trans1:exp2	-0.156605406523235	0.250167462401380	-0.6260022987001	0.531468368213927	   
df.mm.trans2:exp2	0.00690007251244708	0.176895109096247	0.0390065759743127	0.968893589922853	   
df.mm.trans1:exp3	-0.100021990707816	0.250167462401380	-0.399820143465884	0.689381598980388	   
df.mm.trans2:exp3	-0.173582439160982	0.176895109096247	-0.981273253103553	0.326715421544313	   
df.mm.trans1:exp4	-0.558302097007343	0.250167462401380	-2.23171347563808	0.0258735517494726	*  
df.mm.trans2:exp4	-0.399669758468409	0.176895109096247	-2.25936014008704	0.0240937627358968	*  
df.mm.trans1:exp5	0.209119768497067	0.250167462401381	0.835919133886187	0.40341697276188	   
df.mm.trans2:exp5	0.00650311809537475	0.176895109096247	0.0367625658425438	0.970682279715888	   
df.mm.trans1:exp6	-0.528685444446975	0.250167462401380	-2.11332616708854	0.0348409942133111	*  
df.mm.trans2:exp6	-0.138652128156020	0.176895109096247	-0.783809845644636	0.433353001509985	   
df.mm.trans1:exp7	-0.557399281543989	0.250167462401381	-2.22810463116770	0.0261140773128751	*  
df.mm.trans2:exp7	-0.301575854064068	0.176895109096247	-1.70482867279266	0.0885632583113369	.  
df.mm.trans1:exp8	-0.263155848035505	0.250167462401380	-1.05191876477240	0.293112433466116	   
df.mm.trans2:exp8	-0.0635799692311265	0.176895109096247	-0.359421860536197	0.719361823719327	   
df.mm.trans1:probe2	0.5056055090804	0.183103833605142	2.7613048789067	0.00587145907664173	** 
df.mm.trans1:probe3	0.0452973057995978	0.183103833605142	0.247385895247174	0.804664665964027	   
df.mm.trans1:probe4	-0.0152413964406334	0.183103833605142	-0.0832390897587706	0.933679499494871	   
df.mm.trans1:probe5	0.216808754311154	0.183103833605142	1.18407545075596	0.236688360842684	   
df.mm.trans1:probe6	0.115441180959848	0.183103833605142	0.63046839974303	0.528544401426835	   
df.mm.trans1:probe7	0.392200267930846	0.183103833605142	2.14195552440815	0.0324584912498826	*  
df.mm.trans1:probe8	-0.0312778096289466	0.183103833605142	-0.170820069755591	0.864402726179625	   
df.mm.trans1:probe9	0.322385539056336	0.183103833605142	1.76067061354679	0.0786256634719069	.  
df.mm.trans1:probe10	0.288116394408122	0.183103833605142	1.57351372025031	0.115942978379655	   
df.mm.trans1:probe11	0.384997096959349	0.183103833605142	2.10261625537335	0.0357699305941676	*  
df.mm.trans1:probe12	0.234897618880434	0.183103833605142	1.28286565199384	0.199861540578062	   
df.mm.trans1:probe13	0.321820753189536	0.183103833605142	1.75758610212134	0.0791497915120053	.  
df.mm.trans1:probe14	0.221247739222149	0.183103833605142	1.20831844350819	0.22723461193214	   
df.mm.trans1:probe15	0.205162618100024	0.183103833605142	1.12047145087333	0.262804681681693	   
df.mm.trans1:probe16	0.223783312797027	0.183103833605142	1.22216617965306	0.221957142769360	   
df.mm.trans1:probe17	0.150138826442166	0.183103833605142	0.819965499826373	0.412447694854672	   
df.mm.trans1:probe18	0.316190940432722	0.183103833605142	1.72683954348317	0.0845314258492601	.  
df.mm.trans1:probe19	0.232302232846496	0.183103833605142	1.26869125715548	0.204871411651934	   
df.mm.trans1:probe20	0.346384502392493	0.183103833605142	1.89173812242216	0.0588390409123303	.  
df.mm.trans2:probe2	-0.0870143741982939	0.183103833605142	-0.47521874602548	0.634743621629031	   
df.mm.trans2:probe3	0.196562509775031	0.183103833605142	1.07350297317593	0.283326379652990	   
df.mm.trans2:probe4	0.0894790202380293	0.183103833605142	0.48867911979925	0.625185099859984	   
df.mm.trans2:probe5	0.234047399832879	0.183103833605142	1.27822228090316	0.20149275054059	   
df.mm.trans2:probe6	0.133413771730774	0.183103833605142	0.728623585339433	0.466416969152082	   
df.mm.trans3:probe2	0.40720046784016	0.183103833605142	2.22387734774726	0.0263982809529431	*  
df.mm.trans3:probe3	0.214282923842779	0.183103833605142	1.17028092543859	0.242190337220286	   
df.mm.trans3:probe4	0.338272675635108	0.183103833605143	1.84743633693974	0.0650041145603693	.  
df.mm.trans3:probe5	0.169601134482345	0.183103833605142	0.926256600656895	0.354555026844135	   
df.mm.trans3:probe6	0.217799500837717	0.183103833605142	1.18948629610560	0.234554585147185	   
df.mm.trans3:probe7	0.3652262170987	0.183103833605142	1.99463992592475	0.0463761995127858	*  
df.mm.trans3:probe8	0.278734477020896	0.183103833605142	1.52227548453179	0.128282947979285	   
df.mm.trans3:probe9	0.543612740792142	0.183103833605142	2.96887689399461	0.00306626498642446	** 
df.mm.trans3:probe10	0.349367124542556	0.183103833605142	1.90802736165511	0.0566980608648264	.  
df.mm.trans3:probe11	0.345272531470611	0.183103833605142	1.88566522432938	0.0596542514067713	.  
df.mm.trans3:probe12	0.487523807439823	0.183103833605142	2.66255379715944	0.00789009825276004	** 
df.mm.trans3:probe13	0.203132018980445	0.183103833605142	1.10938157318155	0.267554877828948	   
df.mm.trans3:probe14	0.199448151057381	0.183103833605142	1.08926256283353	0.276322734884239	   
df.mm.trans3:probe15	0.245771916811692	0.183103833605142	1.34225434810770	0.179843950910240