chr6.20233_chr6_38785753_38795844_+_2.R 

fitVsDatCorrelation=0.94083576080105
cont.fitVsDatCorrelation=0.26745007542799

fstatistic=9484.3045323657,49,623
cont.fstatistic=1161.82427349159,49,623

residuals=-0.692975589281832,-0.091772385072502,0.00792986034530373,0.0918066272843287,0.558203451576314
cont.residuals=-0.971777245970971,-0.400547112436021,-0.0340908417454206,0.362429369130234,1.40621956460224

predictedValues:
Include	Exclude	Both
chr6.20233_chr6_38785753_38795844_+_2.R.tl.Lung	94.7860247309566	53.5817289730165	135.740981583538
chr6.20233_chr6_38785753_38795844_+_2.R.tl.cerebhem	77.3525445253036	55.3255167456087	143.459255172747
chr6.20233_chr6_38785753_38795844_+_2.R.tl.cortex	102.063899535706	55.6644998938898	152.107170274621
chr6.20233_chr6_38785753_38795844_+_2.R.tl.heart	90.560640528722	51.5832434314544	139.369167905433
chr6.20233_chr6_38785753_38795844_+_2.R.tl.kidney	71.1610007651439	49.207042768654	94.2369156773324
chr6.20233_chr6_38785753_38795844_+_2.R.tl.liver	72.086777254596	53.5256930979268	98.5702710149094
chr6.20233_chr6_38785753_38795844_+_2.R.tl.stomach	72.2205910947724	50.368420073105	113.226010725621
chr6.20233_chr6_38785753_38795844_+_2.R.tl.testicle	79.401784962959	52.6925599290752	121.666324317175


diffExp=41.2042957579401,22.0270277796949,46.3993996418163,38.9773970972676,21.9539579964900,18.5610841566692,21.8521710216674,26.7092250338838
diffExpScore=0.99581036994456
diffExp1.5=1,0,1,1,0,0,0,1
diffExp1.5Score=0.8
diffExp1.4=1,0,1,1,1,0,1,1
diffExp1.4Score=0.857142857142857
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	82.185371316315	87.4735645773433	74.9611751425765
cerebhem	65.7621690469341	86.2518705137457	100.006610484748
cortex	67.3640210501641	83.9563515390329	79.5245589877465
heart	77.6152004027046	96.358127758714	85.288741269895
kidney	79.6679381408154	81.4964705948272	79.2428062397064
liver	82.7838737918457	87.7495258592706	84.9900747563598
stomach	72.8594334416434	75.8683439711682	67.132200114141
testicle	77.1712507500386	78.6424287681219	73.0260421650115
cont.diffExp=-5.28819326102824,-20.4897014668116,-16.5923304888687,-18.7429273560094,-1.82853245401179,-4.96565206742494,-3.0089105295248,-1.47117801808336
cont.diffExpScore=0.986373687436844

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,-1,0,0,0,0,0,0
cont.diffExp1.3Score=0.5
cont.diffExp1.2=0,-1,-1,-1,0,0,0,0
cont.diffExp1.2Score=0.75

tran.correlation=0.540107661954692
cont.tran.correlation=0.196760624969647

tran.covariance=0.00327006494127366
cont.tran.covariance=0.00118011282805718

tran.mean=67.5988730194306
cont.tran.mean=80.2003713451678

weightedLogRatios:
wLogRatio
Lung	2.43362222663127
cerebhem	1.40115145250813
cortex	2.62052597534037
heart	2.37770589423654
kidney	1.50532639856589
liver	1.22924466491886
stomach	1.47731527378434
testicle	1.70968821771970

cont.weightedLogRatios:
wLogRatio
Lung	-0.276885111486388
cerebhem	-1.17215043495311
cortex	-0.951248346297537
heart	-0.96471788315229
kidney	-0.0996021856431314
liver	-0.258956337854258
stomach	-0.174365006145113
testicle	-0.0822502998579156

varWeightedLogRatios=0.296674888510823
cont.varWeightedLogRatios=0.202868361972609

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.32573208050727	0.0832476828765192	39.9498456364283	5.38815307003487e-174	***
df.mm.trans1	1.29568271641314	0.0727575700716722	17.8082186518432	1.18509149879316e-57	***
df.mm.trans2	0.692500096498554	0.0664724325886536	10.4178539814227	1.54654397074256e-23	***
df.mm.exp2	-0.226524949934455	0.0888348350394425	-2.54995633001264	0.0110119093422318	*  
df.mm.exp3	-0.00172524783681084	0.0888348350394425	-0.0194208480946110	0.984511597227115	   
df.mm.exp4	-0.109991319200099	0.0888348350394424	-1.23815527041012	0.216124859670285	   
df.mm.exp5	-0.00691189567776275	0.0888348350394424	-0.077806140740779	0.938007243520341	   
df.mm.exp6	0.0451811213076986	0.0888348350394424	0.508596895436777	0.611214858128238	   
df.mm.exp7	-0.152377912746087	0.0888348350394424	-1.71529459899860	0.0867884617677047	.  
df.mm.exp8	-0.0843687246120227	0.0888348350394424	-0.949725685589028	0.34261992422415	   
df.mm.trans1:exp2	0.0232764427232093	0.0824658683866734	0.282255473428942	0.777841366620486	   
df.mm.trans2:exp2	0.258551043414898	0.0692851878683603	3.73169289670019	0.000207584962697955	***
df.mm.trans1:exp3	0.0757023510655005	0.0824658683866734	0.917984040506801	0.35898246616167	   
df.mm.trans2:exp3	0.0398597141702703	0.0692851878683603	0.575299214689328	0.56529666793071	   
df.mm.trans1:exp4	0.0643890266621455	0.0824658683866734	0.780796078690791	0.435219014663272	   
df.mm.trans2:exp4	0.0719800666520025	0.0692851878683603	1.03889545322100	0.299256389387449	   
df.mm.trans1:exp5	-0.279765157976361	0.0824658683866734	-3.39249635575985	0.000736467427075464	***
df.mm.trans2:exp5	-0.0782594779597583	0.0692851878683603	-1.12952682048649	0.259110372051965	   
df.mm.trans1:exp6	-0.318932468306714	0.0824658683866733	-3.86744812788819	0.00012154287368205	***
df.mm.trans2:exp6	-0.0462274704610769	0.0692851878683603	-0.66720567387228	0.50488781180138	   
df.mm.trans1:exp7	-0.119518866741087	0.0824658683866733	-1.44931314105221	0.147753319721870	   
df.mm.trans2:exp7	0.0905341729896002	0.0692851878683603	1.30668871334537	0.191800595248848	   
df.mm.trans1:exp8	-0.0927324066897556	0.0824658683866734	-1.12449439391026	0.261236413228957	   
df.mm.trans2:exp8	0.067634859780641	0.0692851878683603	0.976180650749554	0.329353838425431	   
df.mm.trans1:probe2	0.215419761852723	0.0481496936012913	4.47395914159972	9.1280883053625e-06	***
df.mm.trans1:probe3	0.167394985379058	0.0481496936012913	3.47655349097732	0.000543230754115316	***
df.mm.trans1:probe4	0.250990596120457	0.0481496936012913	5.2127142946913	2.53470493708726e-07	***
df.mm.trans1:probe5	-0.0990826194239204	0.0481496936012913	-2.05780373691232	0.0400244901204882	*  
df.mm.trans1:probe6	0.331297706935039	0.0481496936012913	6.88057767674256	1.45530889651835e-11	***
df.mm.trans1:probe7	0.207301131867456	0.0481496936012913	4.30534685400152	1.93624800564893e-05	***
df.mm.trans1:probe8	0.213289698236503	0.0481496936012913	4.42972077875867	1.11455896962482e-05	***
df.mm.trans1:probe9	0.105040863829597	0.0481496936012913	2.18154791802828	0.0295159677730826	*  
df.mm.trans1:probe10	0.291603969088663	0.0481496936012913	6.05619573622464	2.41047804479769e-09	***
df.mm.trans1:probe11	0.214233683155893	0.0481496936012913	4.44932599010656	1.02037734791909e-05	***
df.mm.trans1:probe12	-0.564187583238737	0.0481496936012913	-11.7173660108941	8.50903905639588e-29	***
df.mm.trans1:probe13	-0.572844476035267	0.0481496936012913	-11.8971572442136	1.48325987773885e-29	***
df.mm.trans1:probe14	-0.617257868193049	0.0481496936012913	-12.8195596280284	1.48050257455723e-33	***
df.mm.trans1:probe15	-0.593092878124887	0.0481496936012913	-12.3176874817949	2.34014407895385e-31	***
df.mm.trans1:probe16	-0.526880099650457	0.0481496936012913	-10.9425431449958	1.30248897494249e-25	***
df.mm.trans1:probe17	-0.558668845280552	0.0481496936012913	-11.6027497476239	2.56895332785950e-28	***
df.mm.trans2:probe2	-0.13218550044341	0.0481496936012913	-2.74530304466704	0.00621991095540778	** 
df.mm.trans2:probe3	-0.0211543212915165	0.0481496936012913	-0.439344878633853	0.66056400577012	   
df.mm.trans2:probe4	-0.0460925879603747	0.0481496936012913	-0.957276869548732	0.338798850682702	   
df.mm.trans2:probe5	-0.101775127981883	0.0481496936012913	-2.11372327360258	0.0349357537813496	*  
df.mm.trans2:probe6	-0.106056950833520	0.0481496936012913	-2.20265058614361	0.0279848407836691	*  
df.mm.trans3:probe2	-0.734090780775267	0.0481496936012913	-15.2460114669469	7.78863220868038e-45	***
df.mm.trans3:probe3	-0.470032872420038	0.0481496936012913	-9.76190785993772	4.82423371172126e-21	***
df.mm.trans3:probe4	-0.85093707701652	0.0481496936012913	-17.6727412652466	5.88037761414265e-57	***
df.mm.trans3:probe5	0.0392288761176115	0.0481496936012913	0.814727429886687	0.415539673166928	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.65434821998711	0.236718480259369	19.6619554792993	2.53144109975862e-67	***
df.mm.trans1	-0.331228101879621	0.206889379014641	-1.60099132907244	0.109885759825609	   
df.mm.trans2	-0.127940599437823	0.189017311687455	-0.676872389600885	0.498738162259849	   
df.mm.exp2	-0.525263446931401	0.252605795356737	-2.0793800323924	0.0379908623639426	*  
df.mm.exp3	-0.299001425272937	0.252605795356737	-1.18366811359446	0.236995906715743	   
df.mm.exp4	-0.0895510541606833	0.252605795356737	-0.354509103934915	0.723077345242413	   
df.mm.exp5	-0.157433334417137	0.252605795356737	-0.623237223020971	0.533356731207755	   
df.mm.exp6	-0.115158377194378	0.252605795356737	-0.455881770375647	0.648633859639044	   
df.mm.exp7	-0.152475909427364	0.252605795356737	-0.6036120794934	0.546321284130049	   
df.mm.exp8	-0.143221407020451	0.252605795356737	-0.566975935046106	0.570934748465205	   
df.mm.trans1:exp2	0.302330859722861	0.234495356065563	1.28928292992860	0.197778210095462	   
df.mm.trans2:exp2	0.511198561123282	0.197015506137399	2.59471232059659	0.00968982999177941	** 
df.mm.trans1:exp3	0.100135166647722	0.234495356065563	0.427024092620944	0.669509313594322	   
df.mm.trans2:exp3	0.257961835928995	0.197015506137399	1.30934788325286	0.190899219517541	   
df.mm.trans1:exp4	0.0323370219428821	0.234495356065563	0.137900479077466	0.890363629313615	   
df.mm.trans2:exp4	0.186286173466079	0.197015506137399	0.945540668946952	0.344749487131454	   
df.mm.trans1:exp5	0.126323235776879	0.234495356065563	0.538702505228118	0.590284573598118	   
df.mm.trans2:exp5	0.0866564195409799	0.197015506137399	0.439845681387867	0.660201421258124	   
df.mm.trans1:exp6	0.122414336946310	0.234495356065563	0.522033096945784	0.601832839451045	   
df.mm.trans2:exp6	0.118308207612282	0.197015506137399	0.600502010891335	0.548390102124271	   
df.mm.trans1:exp7	0.0320306032884663	0.234495356065563	0.136593763842005	0.891396033729992	   
df.mm.trans2:exp7	0.0101388027497829	0.197015506137399	0.0514619531658185	0.958973914091415	   
df.mm.trans1:exp8	0.0802710733794728	0.234495356065563	0.342314128204013	0.732229955631201	   
df.mm.trans2:exp8	0.0367961384225359	0.197015506137399	0.186767727799426	0.851903553520744	   
df.mm.trans1:probe2	0.0732137030516891	0.136915790330866	0.534735276879046	0.593023711301594	   
df.mm.trans1:probe3	0.147715107552590	0.136915790330866	1.07887561541022	0.281060702626744	   
df.mm.trans1:probe4	0.0610065069550048	0.136915790330866	0.445576852805498	0.65605772703755	   
df.mm.trans1:probe5	0.139968945793928	0.136915790330866	1.02229951312178	0.307035959630543	   
df.mm.trans1:probe6	0.0920598045510378	0.136915790330866	0.672382669146992	0.501589402700885	   
df.mm.trans1:probe7	-0.0319809772681887	0.136915790330866	-0.233581365530627	0.815386725381971	   
df.mm.trans1:probe8	-0.00448199860833806	0.136915790330866	-0.0327354397729218	0.97389604685722	   
df.mm.trans1:probe9	0.188882657038691	0.136915790330866	1.37955349475939	0.168219116483536	   
df.mm.trans1:probe10	0.266963545777775	0.136915790330866	1.94983752518712	0.0516437020699681	.  
df.mm.trans1:probe11	0.207130268948282	0.136915790330866	1.51282966301942	0.130830029359181	   
df.mm.trans1:probe12	0.218614876320357	0.136915790330866	1.59671047285386	0.110837338624409	   
df.mm.trans1:probe13	0.0883202664547789	0.136915790330866	0.645069982369068	0.519119308496689	   
df.mm.trans1:probe14	0.10233001863576	0.136915790330866	0.747393842510587	0.455107854287815	   
df.mm.trans1:probe15	0.0085878759991219	0.136915790330866	0.0627237806418729	0.950006578594945	   
df.mm.trans1:probe16	0.162509632583028	0.136915790330866	1.18693126768149	0.235707123278592	   
df.mm.trans1:probe17	0.168018245312430	0.136915790330866	1.22716485006150	0.220224156986267	   
df.mm.trans2:probe2	0.0337802800546229	0.136915790330866	0.246723040293531	0.805203848787214	   
df.mm.trans2:probe3	-0.089045537335951	0.136915790330866	-0.65036718643457	0.515694826719226	   
df.mm.trans2:probe4	-0.110092616297877	0.136915790330866	-0.804089988684507	0.42165171612461	   
df.mm.trans2:probe5	-0.212286677497334	0.136915790330866	-1.55049083078240	0.121531571487245	   
df.mm.trans2:probe6	-0.228136360362172	0.136915790330866	-1.66625310207731	0.0961656705304993	.  
df.mm.trans3:probe2	0.240327019781375	0.136915790330866	1.75529074623613	0.0797010525879592	.  
df.mm.trans3:probe3	0.161262595584584	0.136915790330866	1.17782320939668	0.239316816190293	   
df.mm.trans3:probe4	-0.00998967342176908	0.136915790330866	-0.072962171840285	0.94185963786197	   
df.mm.trans3:probe5	0.217354038387455	0.136915790330866	1.58750161586333	0.112906449178982