chr5.18903_chr5_113627565_113634731_-_2.R 

fitVsDatCorrelation=0.923170647744436
cont.fitVsDatCorrelation=0.251834465211552

fstatistic=9565.33825718205,59,853
cont.fstatistic=1496.86312981815,59,853

residuals=-0.979129066680276,-0.090979011290292,0.00183569982288948,0.0865264050619652,1.05139307115227
cont.residuals=-0.877423902745866,-0.328864767554128,-0.059991105021416,0.317688672355396,1.65271909448547

predictedValues:
Include	Exclude	Both
chr5.18903_chr5_113627565_113634731_-_2.R.tl.Lung	67.2157472481214	81.461942418877	90.840549614379
chr5.18903_chr5_113627565_113634731_-_2.R.tl.cerebhem	68.8786489649128	66.6903580256413	100.548658625246
chr5.18903_chr5_113627565_113634731_-_2.R.tl.cortex	75.2324581577197	75.6293514936325	109.288357569811
chr5.18903_chr5_113627565_113634731_-_2.R.tl.heart	66.8142015686418	75.1224748872496	86.8326661231162
chr5.18903_chr5_113627565_113634731_-_2.R.tl.kidney	70.2222387646111	86.7831363756936	100.738706423466
chr5.18903_chr5_113627565_113634731_-_2.R.tl.liver	69.3637344025766	72.6542589728018	93.7449211373895
chr5.18903_chr5_113627565_113634731_-_2.R.tl.stomach	68.5288731867713	86.5671748975807	98.5555901359688
chr5.18903_chr5_113627565_113634731_-_2.R.tl.testicle	73.3549863859544	94.5768665993785	113.956980875031


diffExp=-14.2461951707556,2.18829093927144,-0.396893335912765,-8.30827331860785,-16.5608976110825,-3.29052457022516,-18.0383017108094,-21.2218802134241
diffExpScore=1.0417507937917
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=-1,0,0,0,-1,0,-1,-1
diffExp1.2Score=0.8

cont.predictedValues:
Include	Exclude	Both
Lung	81.0281671489163	90.3816242515582	80.242891801048
cerebhem	78.6049577633539	103.07390410483	87.3067843258635
cortex	90.8854683653206	68.5029176637377	80.1523473572795
heart	83.6148988474654	79.3890363936865	93.8167486590027
kidney	85.3314507355076	90.5614811141813	86.5078201480732
liver	78.266940853461	82.8557053848544	82.8135407801145
stomach	87.001979658147	103.03770646229	86.7946547658673
testicle	84.6938214561593	72.3217698033202	81.9149444426878
cont.diffExp=-9.35345710264195,-24.4689463414761,22.3825507015829,4.22586245377887,-5.23003037867363,-4.58876453139332,-16.0357268041429,12.3720516528392
cont.diffExpScore=4.54716522301074

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

tran.correlation=0.261920912071253
cont.tran.correlation=-0.403799231443218

tran.covariance=0.00118667653780382
cont.tran.covariance=-0.00332425718557795

tran.mean=74.9435282718853
cont.tran.mean=84.9719893754243

weightedLogRatios:
wLogRatio
Lung	-0.827355184000899
cerebhem	0.136123751915659
cortex	-0.0227474220766429
heart	-0.499350246357001
kidney	-0.92269691661015
liver	-0.197559431636731
stomach	-1.01506364426871
testicle	-1.12373282666038

cont.weightedLogRatios:
wLogRatio
Lung	-0.486072934671932
cerebhem	-1.21953550692159
cortex	1.23500485281678
heart	0.228205436676735
kidney	-0.266275793605453
liver	-0.250042552862565
stomach	-0.769783563657584
testicle	0.688533400592529

varWeightedLogRatios=0.233738340315101
cont.varWeightedLogRatios=0.630389216328878

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.22336530158836	0.0833519808617534	38.6717300328422	8.73823526737791e-190	***
df.mm.trans1	0.67812649065301	0.0719807318141384	9.42094465507799	4.07240514208260e-20	***
df.mm.trans2	1.16893980669736	0.0635946512106865	18.3811025682760	7.99885205587637e-64	***
df.mm.exp2	-0.277172878572811	0.0818030552201618	-3.3882949460364	0.000735511143710842	***
df.mm.exp3	-0.146500387564846	0.0818030552201618	-1.79089139361067	0.0736652018841391	.  
df.mm.exp4	-0.0418851858230858	0.0818030552201618	-0.512024712406616	0.608766249231035	   
df.mm.exp5	0.00360954074596198	0.0818030552201618	0.0441247669325722	0.96481527778902	   
df.mm.exp6	-0.114439039047474	0.0818030552201618	-1.3989580063908	0.162189073560077	   
df.mm.exp7	-0.00138262560025691	0.0818030552201618	-0.0169018821673073	0.986518843660612	   
df.mm.exp8	0.00996464005368966	0.0818030552201618	0.121812565886093	0.903076152121573	   
df.mm.trans1:exp2	0.301611570042793	0.075612265033175	3.98892388570109	7.20702136338837e-05	***
df.mm.trans2:exp2	0.0770973167087282	0.0558433586355478	1.38059956622399	0.167763761812907	   
df.mm.trans1:exp3	0.259175595708775	0.0756122650331749	3.42769252574383	0.000637874469215382	***
df.mm.trans2:exp3	0.0722088956726045	0.0558433586355478	1.29306147475591	0.196339889836310	   
df.mm.trans1:exp4	0.0358932879762282	0.0756122650331749	0.474701927795444	0.635120950279454	   
df.mm.trans2:exp4	-0.0391309810357299	0.0558433586355478	-0.70072757068771	0.483664138933819	   
df.mm.trans1:exp5	0.0401479575100471	0.075612265033175	0.530971496389272	0.595576749577696	   
df.mm.trans2:exp5	0.0596668336597202	0.0558433586355478	1.06846785575928	0.285611798001604	   
df.mm.trans1:exp6	0.145895656811396	0.0756122650331749	1.92952369231875	0.053997252214732	.  
df.mm.trans2:exp6	1.51035090999166e-05	0.0558433586355478	0.000270462047214729	0.999784265721088	   
df.mm.trans1:exp7	0.0207302343092059	0.0756122650331749	0.274164969137091	0.78402422634539	   
df.mm.trans2:exp7	0.062167379561143	0.0558433586355478	1.11324571229442	0.265916523931749	   
df.mm.trans1:exp8	0.0774382888200623	0.0756122650331749	1.02414983582473	0.306054857532790	   
df.mm.trans2:exp8	0.139312319981427	0.0558433586355478	2.49469808738806	0.0127945824465114	*  
df.mm.trans1:probe2	-0.119935678877889	0.0517681789784113	-2.31678380898632	0.0207515706293873	*  
df.mm.trans1:probe3	0.142405997308726	0.0517681789784113	2.75084038339678	0.00607020123273863	** 
df.mm.trans1:probe4	0.336323364381977	0.0517681789784113	6.49672001254347	1.39383148578182e-10	***
df.mm.trans1:probe5	0.382319065929489	0.0517681789784113	7.38521372538381	3.62263161484184e-13	***
df.mm.trans1:probe6	0.513644437154347	0.0517681789784113	9.92201092042568	4.9374320241606e-22	***
df.mm.trans1:probe7	-0.0082128503963124	0.0517681789784113	-0.158646692975957	0.873984790450929	   
df.mm.trans1:probe8	0.0887184205026062	0.0517681789784113	1.71376359480607	0.0869354608209173	.  
df.mm.trans1:probe9	0.342896065730605	0.0517681789784113	6.62368413371469	6.19735433761067e-11	***
df.mm.trans1:probe10	1.08674068465870	0.0517681789784113	20.992445670378	3.34517091697365e-79	***
df.mm.trans1:probe11	0.110610279674451	0.0517681789784113	2.13664613778628	0.0329107377884303	*  
df.mm.trans1:probe12	0.0806227854842695	0.0517681789784113	1.55738113789731	0.119750942601940	   
df.mm.trans1:probe13	-0.0160857534572525	0.0517681789784112	-0.310726662105706	0.756084337337825	   
df.mm.trans1:probe14	0.112473544661927	0.0517681789784113	2.17263861471410	0.0300822028019096	*  
df.mm.trans1:probe15	0.00365212827978815	0.0517681789784113	0.0705477448088563	0.943774236137382	   
df.mm.trans1:probe16	0.0290288317778790	0.0517681789784113	0.560746627575694	0.575117532424954	   
df.mm.trans1:probe17	1.04766104392391	0.0517681789784113	20.2375487142559	1.11113076710516e-74	***
df.mm.trans1:probe18	1.13631366323948	0.0517681789784113	21.9500412350481	5.19843083778592e-85	***
df.mm.trans1:probe19	1.19630059177878	0.0517681789784113	23.1088018815123	3.93288973758270e-92	***
df.mm.trans1:probe20	1.08521855346128	0.0517681789784113	20.9630428359058	5.02952479997547e-79	***
df.mm.trans1:probe21	1.09880959961775	0.0517681789784113	21.2255795220455	1.31039593427586e-80	***
df.mm.trans1:probe22	1.15579960549276	0.0517681789784113	22.3264489557333	2.58726405523007e-87	***
df.mm.trans2:probe2	0.0136447805399101	0.0517681789784113	0.26357466708652	0.792171338894922	   
df.mm.trans2:probe3	0.0974524652492898	0.0517681789784113	1.88247813951366	0.0601112815555206	.  
df.mm.trans2:probe4	-0.0148150702757378	0.0517681789784113	-0.286181020234768	0.774808967266185	   
df.mm.trans2:probe5	-0.0107717637854739	0.0517681789784113	-0.208076930617281	0.835218569746922	   
df.mm.trans2:probe6	0.0397830076929415	0.0517681789784113	0.768483815309248	0.442412505575628	   
df.mm.trans3:probe2	-0.198116393252295	0.0517681789784113	-3.82699173820495	0.000139191539049600	***
df.mm.trans3:probe3	-0.726938859987667	0.0517681789784113	-14.0421949223058	1.89482759476645e-40	***
df.mm.trans3:probe4	-0.582400972665901	0.0517681789784112	-11.2501730630467	1.78299686872060e-27	***
df.mm.trans3:probe5	-0.710980790353004	0.0517681789784113	-13.7339347140162	6.33432595944605e-39	***
df.mm.trans3:probe6	-0.63428302763032	0.0517681789784113	-12.2523727924607	6.58553774421369e-32	***
df.mm.trans3:probe7	-0.57616622506127	0.0517681789784113	-11.1297371557448	5.82802161384615e-27	***
df.mm.trans3:probe8	-0.792381562043172	0.0517681789784113	-15.3063441225857	6.56527083455621e-47	***
df.mm.trans3:probe9	-1.16103509717654	0.0517681789784113	-22.4275823505540	6.198934102388e-88	***
df.mm.trans3:probe10	-0.230955385462221	0.0517681789784113	-4.46133879962315	9.23545306910316e-06	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.61308526593734	0.209853264532767	21.9824327070073	3.29686076458343e-85	***
df.mm.trans1	-0.264448521919105	0.181224146066884	-1.45923447652227	0.144868724535099	   
df.mm.trans2	-0.0945581197126845	0.160110713931562	-0.590579589527672	0.554958576826149	   
df.mm.exp2	0.0166732176407254	0.205953571939430	0.0809561955333744	0.93549577927013	   
df.mm.exp3	-0.161232332837346	0.205953571939430	-0.78285766699285	0.433927981608635	   
df.mm.exp4	-0.254541028665218	0.205953571939430	-1.23591461060009	0.21683054307276	   
df.mm.exp5	-0.0214423825182932	0.205953571939430	-0.104112700335196	0.917104385885447	   
df.mm.exp6	-0.153145305549212	0.20595357193943	-0.743591403184068	0.457328467450239	   
df.mm.exp7	0.123701208165259	0.205953571939430	0.600626670372286	0.548248218075839	   
df.mm.exp8	-0.199293235215421	0.205953571939430	-0.967660979796124	0.333487987819717	   
df.mm.trans1:exp2	-0.0470352811283369	0.190367169344735	-0.247076642943410	0.804908362760386	   
df.mm.trans2:exp2	0.114732053696436	0.140595472248951	0.816043730720436	0.414702942397707	   
df.mm.trans1:exp3	0.276035620470088	0.190367169344735	1.45001694052726	0.147421370780772	   
df.mm.trans2:exp3	-0.115932304352460	0.140595472248951	-0.824580639034941	0.409840232802341	   
df.mm.trans1:exp4	0.285965911952869	0.190367169344735	1.50218082738318	0.133420504472192	   
df.mm.trans2:exp4	0.124860331518135	0.140595472248951	0.88808216595372	0.374746901099580	   
df.mm.trans1:exp5	0.073188639589898	0.190367169344735	0.384460407967516	0.70073306128297	   
df.mm.trans2:exp5	0.023430376716736	0.140595472248951	0.166651004772387	0.867684153648095	   
df.mm.trans1:exp6	0.118473771264122	0.190367169344735	0.622343504249821	0.533882339953382	   
df.mm.trans2:exp6	0.0662049358982807	0.140595472248951	0.470889530361633	0.637840017974792	   
df.mm.trans1:exp7	-0.0525671718814287	0.190367169344735	-0.276135701667313	0.782510727356032	   
df.mm.trans2:exp7	0.00735282004869822	0.140595472248951	0.0522977015623848	0.958303729228503	   
df.mm.trans1:exp8	0.243539051201238	0.190367169344735	1.27931224716702	0.201135003168467	   
df.mm.trans2:exp8	-0.0236225523442533	0.140595472248951	-0.168017874021043	0.866609044915669	   
df.mm.trans1:probe2	0.104918169227896	0.130335491073147	0.804985413903987	0.421052411356947	   
df.mm.trans1:probe3	-0.0455248390548972	0.130335491073147	-0.349289657637057	0.72695807019375	   
df.mm.trans1:probe4	-0.00863348035273728	0.130335491073147	-0.0662404405864555	0.947201922214594	   
df.mm.trans1:probe5	0.114516851932813	0.130335491073147	0.878631376533839	0.379848605076341	   
df.mm.trans1:probe6	-0.04304187103357	0.130335491073147	-0.330239067495546	0.741300418654844	   
df.mm.trans1:probe7	0.128594744232760	0.130335491073147	0.986644107249273	0.324096914813055	   
df.mm.trans1:probe8	0.0573167127251613	0.130335491073147	0.439762893845960	0.66022023946694	   
df.mm.trans1:probe9	0.0625178276377692	0.130335491073147	0.479668485713405	0.631586100949689	   
df.mm.trans1:probe10	0.0677961909961564	0.130335491073147	0.520166766841028	0.60308231663104	   
df.mm.trans1:probe11	0.178140070753929	0.130335491073147	1.36678098411394	0.172054082865093	   
df.mm.trans1:probe12	-0.154493738378684	0.130335491073147	-1.18535432756362	0.236207495073102	   
df.mm.trans1:probe13	0.203621543541868	0.130335491073147	1.56228776878274	0.118591116200129	   
df.mm.trans1:probe14	0.083525674278962	0.130335491073147	0.640851341344054	0.521791399345638	   
df.mm.trans1:probe15	0.122667850687422	0.130335491073147	0.941169973561373	0.346884216364696	   
df.mm.trans1:probe16	0.214064033988524	0.130335491073147	1.64240785242745	0.100874075266855	   
df.mm.trans1:probe17	0.110447901948162	0.130335491073147	0.847412328282684	0.397003035037934	   
df.mm.trans1:probe18	0.120805311682579	0.130335491073147	0.926879629546034	0.354251206253268	   
df.mm.trans1:probe19	0.154463862621137	0.130335491073147	1.18512510559729	0.236298050740895	   
df.mm.trans1:probe20	-0.0946369004353512	0.130335491073147	-0.726102304569054	0.467975236993729	   
df.mm.trans1:probe21	0.0228962153828231	0.130335491073147	0.175671378488714	0.8605938154675	   
df.mm.trans1:probe22	0.0771608367365554	0.130335491073147	0.592017079164195	0.553996029603301	   
df.mm.trans2:probe2	0.0355745512376609	0.130335491073147	0.272946002234309	0.784960788568313	   
df.mm.trans2:probe3	-0.0438545321975448	0.130335491073147	-0.336474216166745	0.736596049397411	   
df.mm.trans2:probe4	0.00508208337252742	0.130335491073147	0.0389923215133724	0.968905634308668	   
df.mm.trans2:probe5	-0.00640330690684388	0.130335491073147	-0.0491294186573496	0.96082765990665	   
df.mm.trans2:probe6	-0.222177532186568	0.130335491073147	-1.70465872616291	0.0886222321151497	.  
df.mm.trans3:probe2	0.0862368090647354	0.130335491073147	0.661652542639654	0.508372614932503	   
df.mm.trans3:probe3	0.0925157390851648	0.130335491073147	0.709827678734438	0.478004993709943	   
df.mm.trans3:probe4	0.128397264971098	0.130335491073147	0.985128946182736	0.324840076569323	   
df.mm.trans3:probe5	0.237092099295648	0.130335491073147	1.81909085041608	0.0692480578734581	.  
df.mm.trans3:probe6	0.292544414742488	0.130335491073147	2.24454914262998	0.0250527064130588	*  
df.mm.trans3:probe7	0.157266520731309	0.130335491073147	1.20662852026274	0.227909765345642	   
df.mm.trans3:probe8	0.1160679220183	0.130335491073147	0.890531973007724	0.373431408645623	   
df.mm.trans3:probe9	0.0915980512582653	0.130335491073147	0.70278671223066	0.482380427332764	   
df.mm.trans3:probe10	0.108076759769391	0.130335491073147	0.829219722728755	0.407212066161015