chr15.8834_chr15_55227864_55230504_-_1.R 

fitVsDatCorrelation=0.90035972125503
cont.fitVsDatCorrelation=0.281617259261924

fstatistic=5475.2364505221,50,646
cont.fstatistic=1115.79162183813,50,646

residuals=-0.632343263802245,-0.114668447962149,-0.00206201179018454,0.110785693368903,1.37870570701793
cont.residuals=-0.80715490109918,-0.290433492510617,-0.117917675100742,0.160236986865143,2.71174720042738

predictedValues:
Include	Exclude	Both
chr15.8834_chr15_55227864_55230504_-_1.R.tl.Lung	53.8836451111949	43.771235135823	59.3837996057431
chr15.8834_chr15_55227864_55230504_-_1.R.tl.cerebhem	89.4877992443927	45.9053605808693	90.470586525208
chr15.8834_chr15_55227864_55230504_-_1.R.tl.cortex	139.276421836883	48.3837391680492	112.138657187011
chr15.8834_chr15_55227864_55230504_-_1.R.tl.heart	56.882720468544	43.3662853329426	63.0326663016513
chr15.8834_chr15_55227864_55230504_-_1.R.tl.kidney	94.5419871848399	48.0841083792679	86.6444943127954
chr15.8834_chr15_55227864_55230504_-_1.R.tl.liver	52.8900353748064	44.9830117357905	62.6857903575704
chr15.8834_chr15_55227864_55230504_-_1.R.tl.stomach	56.0948845511274	44.0148551685006	62.9370963973063
chr15.8834_chr15_55227864_55230504_-_1.R.tl.testicle	44.9597853180928	41.2744169659490	53.2703082445287


diffExp=10.1124099753719,43.5824386635234,90.8926826688337,13.5164351356015,46.457878805572,7.90702363901594,12.0800293826268,3.68536835214376
diffExpScore=0.995637650449329
diffExp1.5=0,1,1,0,1,0,0,0
diffExp1.5Score=0.75
diffExp1.4=0,1,1,0,1,0,0,0
diffExp1.4Score=0.75
diffExp1.3=0,1,1,1,1,0,0,0
diffExp1.3Score=0.8
diffExp1.2=1,1,1,1,1,0,1,0
diffExp1.2Score=0.857142857142857

cont.predictedValues:
Include	Exclude	Both
Lung	65.8110999536572	61.0884764550328	68.3216145778573
cerebhem	71.6673323944435	65.1203727836491	63.9731910836118
cortex	73.4776235677398	71.0018067797431	57.3551633694802
heart	56.0516067735654	75.7689151050469	60.6037100852287
kidney	75.5130816794348	83.93464235798	67.3874216157891
liver	61.4629457501096	60.3757704582762	70.9930775328347
stomach	66.6324359673056	76.681619222793	65.7682264610823
testicle	76.6230082294996	65.0368738641351	71.6165925247451
cont.diffExp=4.72262349862436,6.54695961079443,2.47581678799672,-19.7173083314815,-8.4215606785452,1.08717529183346,-10.0491832554874,11.5861343653646
cont.diffExpScore=5.05952133033252

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

tran.correlation=0.878349354617812
cont.tran.correlation=0.127792171573588

tran.covariance=0.0189351102340406
cont.tran.covariance=0.00140789308717106

tran.mean=59.2375182223171
cont.tran.mean=69.1404757089007

weightedLogRatios:
wLogRatio
Lung	0.807061680136811
cerebhem	2.77711320462851
cortex	4.6603657973307
heart	1.05955427148031
kidney	2.84702328776417
liver	0.629462584504237
stomach	0.947221158845187
testicle	0.321833189778718

cont.weightedLogRatios:
wLogRatio
Lung	0.308997796661712
cerebhem	0.40466203926953
cortex	0.146694166466296
heart	-1.25900582748677
kidney	-0.462809445188934
liver	0.0733408515157958
stomach	-0.599728721137956
testicle	0.697893206657833

varWeightedLogRatios=2.29055844731720
cont.varWeightedLogRatios=0.410377412525065

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.68114843632744	0.104206611754346	35.325478627069	5.08696739284462e-153	***
df.mm.trans1	0.254353718109123	0.082241855366763	3.09275267410756	0.00206858553697923	** 
df.mm.trans2	0.0854868203044846	0.082241855366763	1.03945636833277	0.298981425727573	   
df.mm.exp2	0.133876990118404	0.108902150065788	1.22933284639035	0.219394608168200	   
df.mm.exp3	0.414105862207705	0.108902150065788	3.80254992171911	0.000156787075429170	***
df.mm.exp4	-0.0147616045800225	0.108902150065788	-0.135549248303225	0.8922198546925	   
df.mm.exp5	0.278399889318378	0.108902150065788	2.55642234014844	0.0108030390953014	*  
df.mm.exp6	-0.04541735343574	0.108902150065788	-0.41704735313585	0.676782322819012	   
df.mm.exp7	-0.0123463553733336	0.108902150065788	-0.113371089238139	0.909771581871417	   
df.mm.exp8	-0.131150228611712	0.108902150065788	-1.20429420844753	0.228916935400734	   
df.mm.trans1:exp2	0.373398302926444	0.082579143953828	4.52170227309719	7.29845250701492e-06	***
df.mm.trans2:exp2	-0.0862719611974916	0.082579143953828	-1.04471852173387	0.296543847483916	   
df.mm.trans1:exp3	0.535527740840363	0.082579143953828	6.48502412594383	1.76409773656536e-10	***
df.mm.trans2:exp3	-0.313918942117771	0.082579143953828	-3.80143129472607	0.000157481081507622	***
df.mm.trans1:exp4	0.0689262154888896	0.082579143953828	0.834668563861935	0.404212901155826	   
df.mm.trans2:exp4	0.00546703856612439	0.082579143953828	0.0662036236314238	0.947236194812342	   
df.mm.trans1:exp5	0.283817153687992	0.082579143953828	3.43691082395672	0.000626138972728471	***
df.mm.trans2:exp5	-0.184425023502524	0.082579143953828	-2.23331236765594	0.0258700061067840	*  
df.mm.trans1:exp6	0.0268053056990658	0.082579143953828	0.32460139952593	0.745587850933525	   
df.mm.trans2:exp6	0.0727253853655461	0.082579143953828	0.88067497292305	0.378821284839735	   
df.mm.trans1:exp7	0.0525639776208753	0.082579143953828	0.636528487753096	0.524657491507649	   
df.mm.trans2:exp7	0.0178966801969611	0.082579143953828	0.216721551472701	0.828493773693028	   
df.mm.trans1:exp8	-0.0499083424193743	0.082579143953828	-0.604369820632669	0.545809990899278	   
df.mm.trans2:exp8	0.0724162231396894	0.082579143953828	0.876931143536425	0.380850027742055	   
df.mm.trans1:probe2	0.420795455119457	0.0614839202930592	6.84399194315787	1.79258083949135e-11	***
df.mm.trans1:probe3	0.0812164666471935	0.0614839202930592	1.32093832436319	0.186989646725571	   
df.mm.trans1:probe4	0.360013361204516	0.0614839202930592	5.85540673868119	7.5753712064937e-09	***
df.mm.trans1:probe5	0.145569031105048	0.0614839202930592	2.36759514375795	0.0181977532190802	*  
df.mm.trans1:probe6	0.172877171871219	0.0614839202930592	2.81174608006794	0.00507685518818966	** 
df.mm.trans2:probe2	0.0467340561488487	0.0614839202930591	0.760102087278981	0.447470874937126	   
df.mm.trans2:probe3	0.0118701339951117	0.0614839202930592	0.193060786276045	0.846972044105238	   
df.mm.trans2:probe4	0.07408062894369	0.0614839202930592	1.20487809805538	0.22869157261973	   
df.mm.trans2:probe5	-0.0180691641006282	0.0614839202930592	-0.293884384966065	0.768940647130354	   
df.mm.trans2:probe6	0.169241442832584	0.0614839202930592	2.75261307388836	0.00607821701120802	** 
df.mm.trans3:probe2	0.0873927076881734	0.0614839202930592	1.42139127224845	0.155685598234394	   
df.mm.trans3:probe3	-0.150147770280065	0.0614839202930592	-2.44206565821430	0.0148705849824974	*  
df.mm.trans3:probe4	-0.242980865928643	0.0614839202930592	-3.95194165841232	8.6066779662589e-05	***
df.mm.trans3:probe5	0.0417118659735712	0.0614839202930592	0.678419101689585	0.49774894521754	   
df.mm.trans3:probe6	-0.0430085298636875	0.0614839202930592	-0.699508581409417	0.484486046408635	   
df.mm.trans3:probe7	-0.0266654794162005	0.0614839202930592	-0.433698425362293	0.664652241947093	   
df.mm.trans3:probe8	-0.257018886071677	0.0614839202930592	-4.18026184483053	3.31320833822579e-05	***
df.mm.trans3:probe9	-0.259938191242492	0.0614839202930592	-4.22774263585524	2.70106237436604e-05	***
df.mm.trans3:probe10	-0.194127706756359	0.0614839202930592	-3.15737359997642	0.00166611093706327	** 
df.mm.trans3:probe11	-0.075253612816524	0.0614839202930592	-1.22395599463783	0.221415034573064	   
df.mm.trans3:probe12	0.0810584353561494	0.0614839202930592	1.31836803785103	0.187847709905824	   
df.mm.trans3:probe13	0.243572776468127	0.0614839202930592	3.96156873711295	8.27478820624104e-05	***
df.mm.trans3:probe14	0.232408411120625	0.0614839202930592	3.77998686506758	0.00017135891424036	***
df.mm.trans3:probe15	1.20266014844789	0.0614839202930592	19.5605638468641	2.86826055906967e-67	***
df.mm.trans3:probe16	-0.215954712123169	0.0614839202930592	-3.51237707507645	0.000475077418920137	***
df.mm.trans3:probe17	0.647843578264651	0.0614839202930592	10.5367968596789	4.59575179521646e-24	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.99940093595993	0.229782536097769	17.4051562136917	6.31313016018333e-56	***
df.mm.trans1	0.185764612306969	0.181348781823074	1.0243499318799	0.306053444472608	   
df.mm.trans2	0.114768420379204	0.181348781823074	0.632860167162155	0.527048912874069	   
df.mm.exp2	0.214922786973628	0.240136511564227	0.895002536572387	0.371119078887276	   
df.mm.exp3	0.435537789183382	0.240136511564227	1.81370915379060	0.0701863741412338	.  
df.mm.exp4	0.174719238115208	0.240136511564227	0.72758297760346	0.46713251311225	   
df.mm.exp5	0.469000378129728	0.240136511564227	1.95305734673458	0.0512441805571191	.  
df.mm.exp6	-0.118445596169820	0.240136511564227	-0.493242761786937	0.622008694733645	   
df.mm.exp7	0.277831097298965	0.240136511564227	1.15697148879693	0.247711644018538	   
df.mm.exp8	0.167639431521824	0.240136511564227	0.698100553013934	0.485365514971395	   
df.mm.trans1:exp2	-0.129676274741571	0.182092525676058	-0.712144961799609	0.476632123462256	   
df.mm.trans2:exp2	-0.151008587730538	0.182092525676058	-0.829295915194133	0.407243302004949	   
df.mm.trans1:exp3	-0.325345386980623	0.182092525676058	-1.78670368689054	0.0744542063836432	.  
df.mm.trans2:exp3	-0.285155711863281	0.182092525676058	-1.56599350140583	0.117839833798950	   
df.mm.trans1:exp4	-0.33523493862732	0.182092525676058	-1.84101427218216	0.0660778441952123	.  
df.mm.trans2:exp4	0.0406456324609358	0.182092525676058	0.223214172630260	0.82343938542707	   
df.mm.trans1:exp5	-0.331482986015653	0.182092525676058	-1.82040962299221	0.069159205091159	.  
df.mm.trans2:exp5	-0.151285196304125	0.182092525676058	-0.830814970260014	0.4063851167898	   
df.mm.trans1:exp6	0.0500915648638875	0.182092525676058	0.27508852808709	0.783336183728404	   
df.mm.trans2:exp6	0.106710222275372	0.182092525676058	0.586021979096545	0.55806543060702	   
df.mm.trans1:exp7	-0.265428128184578	0.182092525676058	-1.45765526179132	0.145421532691476	   
df.mm.trans2:exp7	-0.0504923097190773	0.182092525676058	-0.277289304059097	0.781646680509116	   
df.mm.trans1:exp8	-0.0155305477546920	0.182092525676058	-0.085289320344322	0.932057807380343	   
df.mm.trans2:exp8	-0.105008279256436	0.182092525676058	-0.576675395470354	0.564359637419217	   
df.mm.trans1:probe2	0.0440061927847772	0.135576149116881	0.324586537318146	0.745599095503927	   
df.mm.trans1:probe3	0.0680541193987582	0.135576149116881	0.501962327754922	0.615865059074417	   
df.mm.trans1:probe4	0.0627054432280991	0.135576149116881	0.462510874047914	0.643870748302487	   
df.mm.trans1:probe5	-0.0902159704873762	0.135576149116881	-0.665426559723275	0.506015209437069	   
df.mm.trans1:probe6	-0.0472215176526342	0.135576149116881	-0.348302544070079	0.727726457304953	   
df.mm.trans2:probe2	0.220400088775084	0.135576149116881	1.62565532514923	0.104510711138103	   
df.mm.trans2:probe3	0.0260730631126103	0.135576149116881	0.192313052719416	0.847557432768185	   
df.mm.trans2:probe4	-0.0537183486040813	0.135576149116881	-0.396222705497929	0.692071579760406	   
df.mm.trans2:probe5	-0.0610154101371418	0.135576149116881	-0.450045310584386	0.652828750676188	   
df.mm.trans2:probe6	-0.174199907959322	0.135576149116881	-1.28488608869649	0.199292601186382	   
df.mm.trans3:probe2	-0.0109572257226284	0.135576149116881	-0.0808197149277497	0.935610360759432	   
df.mm.trans3:probe3	-0.198378510629413	0.135576149116881	-1.46322573639696	0.143891990163348	   
df.mm.trans3:probe4	-0.112203292934854	0.135576149116881	-0.827603480890454	0.408200711871787	   
df.mm.trans3:probe5	-0.0266791979886967	0.135576149116881	-0.196783860306405	0.844058574808312	   
df.mm.trans3:probe6	-0.0595553555277655	0.135576149116881	-0.439276051987745	0.66060842109525	   
df.mm.trans3:probe7	-0.0117691737323006	0.135576149116881	-0.0868085854994621	0.930850562986886	   
df.mm.trans3:probe8	0.0068671007946163	0.135576149116881	0.050651245365408	0.959619084320468	   
df.mm.trans3:probe9	-0.183192998399963	0.135576149116881	-1.35121848196198	0.177098473166702	   
df.mm.trans3:probe10	-0.195182946314183	0.135576149116881	-1.43965548207092	0.150449289149959	   
df.mm.trans3:probe11	-0.114489537738820	0.135576149116881	-0.844466659398308	0.39872130751502	   
df.mm.trans3:probe12	-0.0153527968028761	0.135576149116881	-0.113241133509703	0.909874567194359	   
df.mm.trans3:probe13	-0.128403769860549	0.135576149116881	-0.947097042488282	0.343943464652051	   
df.mm.trans3:probe14	-0.174001815343036	0.135576149116881	-1.28342497169637	0.199803425825679	   
df.mm.trans3:probe15	0.164627037942017	0.135576149116881	1.21427728265161	0.225085557795759	   
df.mm.trans3:probe16	-0.217774001061885	0.135576149116881	-1.60628548959700	0.108699863563059	   
df.mm.trans3:probe17	-0.0105858933872958	0.135576149116881	-0.078080794123822	0.937787962764117