chr19.12481_chr19_40098666_40103889_-_2.R 

fitVsDatCorrelation=0.893603667826932
cont.fitVsDatCorrelation=0.241475614717370

fstatistic=7691.4873919511,58,830
cont.fstatistic=1634.32880047352,58,830

residuals=-0.69380268148316,-0.106467757272363,0.00459965383919962,0.114283386820196,0.683142804714186
cont.residuals=-0.778441055181769,-0.300778700785870,-0.0866941295752035,0.222871645522085,1.42757777027994

predictedValues:
Include	Exclude	Both
chr19.12481_chr19_40098666_40103889_-_2.R.tl.Lung	62.9535199417174	90.7399424853285	89.6725829706136
chr19.12481_chr19_40098666_40103889_-_2.R.tl.cerebhem	56.2622907857518	66.4068611938343	76.4043736846886
chr19.12481_chr19_40098666_40103889_-_2.R.tl.cortex	57.8683947498818	136.792273408031	103.425718149304
chr19.12481_chr19_40098666_40103889_-_2.R.tl.heart	114.188731527204	88.446165124781	126.771297137791
chr19.12481_chr19_40098666_40103889_-_2.R.tl.kidney	59.968404860012	77.5756307523245	79.950787306602
chr19.12481_chr19_40098666_40103889_-_2.R.tl.liver	60.9403138529481	67.4389154008723	68.2027849834494
chr19.12481_chr19_40098666_40103889_-_2.R.tl.stomach	57.0351871384318	101.262565450967	87.3280367161803
chr19.12481_chr19_40098666_40103889_-_2.R.tl.testicle	57.3926302872729	55.540007768046	68.1917525496407


diffExp=-27.7864225436111,-10.1445704080825,-78.9238786581488,25.7425664024229,-17.6072258923124,-6.49860154792426,-44.227378312535,1.85262251922686
diffExpScore=1.34169487910848
diffExp1.5=0,0,-1,0,0,0,-1,0
diffExp1.5Score=0.666666666666667
diffExp1.4=-1,0,-1,0,0,0,-1,0
diffExp1.4Score=0.75
diffExp1.3=-1,0,-1,0,0,0,-1,0
diffExp1.3Score=0.75
diffExp1.2=-1,0,-1,1,-1,0,-1,0
diffExp1.2Score=1.25

cont.predictedValues:
Include	Exclude	Both
Lung	78.0734999018894	76.0948586181152	75.255139743474
cerebhem	73.8147370859263	77.4777965205138	73.4106783466666
cortex	85.2987102943697	75.0026687880004	78.9205061596035
heart	80.1615896746306	69.9940459520062	84.0117313340302
kidney	79.1289209706047	63.7579387650567	77.9727315010956
liver	73.7227312724994	79.3024382423242	72.7869827291288
stomach	78.0417530224787	63.6434587373098	73.5141076891358
testicle	81.9199205993204	67.9756613133182	81.080300960112
cont.diffExp=1.97864128377421,-3.66305943458754,10.2960415063692,10.1675437226244,15.3709822055480,-5.5797069698248,14.3982942851689,13.9442592860022
cont.diffExpScore=1.30192761644595

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=0,0,0,0,1,0,1,1
cont.diffExp1.2Score=0.75

tran.correlation=0.0428286274071247
cont.tran.correlation=-0.355350995372478

tran.covariance=0.00702100931190352
cont.tran.covariance=-0.00151778820546783

tran.mean=75.6757396704627
cont.tran.mean=75.2131706098977

weightedLogRatios:
wLogRatio
Lung	-1.58129625473886
cerebhem	-0.681821608176404
cortex	-3.86126425214196
heart	1.17769545156745
kidney	-1.08703057473904
liver	-0.421578197903345
stomach	-2.48602718270770
testicle	0.132348656269992

cont.weightedLogRatios:
wLogRatio
Lung	0.111531365518658
cerebhem	-0.209510245433855
cortex	0.563660978975345
heart	0.58542841917261
kidney	0.920761482781671
liver	-0.31640219915307
stomach	0.86785142656744
testicle	0.804669954681392

varWeightedLogRatios=2.44559499076117
cont.varWeightedLogRatios=0.240129307376928

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.89466413127634	0.0904899216889595	43.0397557936169	1.26236991708326e-213	***
df.mm.trans1	0.0477310097194699	0.078030952420596	0.61169328630252	0.540908212663893	   
df.mm.trans2	0.58197192548471	0.0691128192950472	8.42060751421865	1.63551876030580e-16	***
df.mm.exp2	-0.264444285214404	0.0889858293200748	-2.97175727006172	0.00304650939935706	** 
df.mm.exp3	0.183551997014412	0.0889858293200748	2.06271041599433	0.0394507576862187	*  
df.mm.exp4	0.223632783397161	0.0889858293200748	2.51312804640807	0.0121550104334495	*  
df.mm.exp5	-0.0905693536347924	0.0889858293200748	-1.01779524140885	0.309071855137557	   
df.mm.exp6	-0.0555974906254908	0.0889858293200748	-0.624790385731094	0.532280355911932	   
df.mm.exp7	0.0374843861809579	0.0889858293200748	0.421239948735316	0.673688935483752	   
df.mm.exp8	-0.309533348511493	0.0889858293200748	-3.47845663603501	0.000530554731431615	***
df.mm.trans1:exp2	0.152072129892481	0.0819677281199615	1.85526832791949	0.0639122891333536	.  
df.mm.trans2:exp2	-0.0477529728043545	0.0609859413025988	-0.783016081811622	0.433841022212762	   
df.mm.trans1:exp3	-0.267777296108957	0.0819677281199615	-3.26686248662472	0.00113211327644366	** 
df.mm.trans2:exp3	0.226913885248194	0.0609859413025988	3.72075728276944	0.000212003384024060	***
df.mm.trans1:exp4	0.371823160418421	0.0819677281199615	4.53621405578364	6.57149764791023e-06	***
df.mm.trans2:exp4	-0.249236360545101	0.0609859413025988	-4.08678385906098	4.7986534167301e-05	***
df.mm.trans1:exp5	0.0419905160995107	0.0819677281199615	0.512281077719474	0.608590591978202	   
df.mm.trans2:exp5	-0.0661749455880214	0.0609859413025988	-1.08508525365995	0.278198961001157	   
df.mm.trans1:exp6	0.0230957389698637	0.0819677281199615	0.281766245077119	0.778192991340065	   
df.mm.trans2:exp6	-0.241177918636239	0.0609859413025988	-3.9546478005409	8.31886759990836e-05	***
df.mm.trans1:exp7	-0.136212665986809	0.0819677281199615	-1.66178408394409	0.0969336832664968	.  
df.mm.trans2:exp7	0.0722347749296604	0.0609859413025988	1.18444961882686	0.236574188738682	   
df.mm.trans1:exp8	0.217052575990247	0.0819677281199615	2.64802478937304	0.00825002906868435	** 
df.mm.trans2:exp8	-0.181360670141161	0.0609859413025988	-2.97381111560268	0.00302640943568961	** 
df.mm.trans1:probe2	-0.0432315798546223	0.0561194670984418	-0.770349080093505	0.441312056863809	   
df.mm.trans1:probe3	0.174226224586069	0.0561194670984418	3.10455949769534	0.00197030966246317	** 
df.mm.trans1:probe4	-0.113257080854351	0.0561194670984418	-2.01814248620147	0.0438976876550321	*  
df.mm.trans1:probe5	0.170360475387837	0.0561194670984418	3.03567521567872	0.00247494056520415	** 
df.mm.trans1:probe6	0.0925601185308567	0.0561194670984418	1.64934065336887	0.0994562514434268	.  
df.mm.trans1:probe7	0.064971693370336	0.0561194670984418	1.15773895814738	0.247303622890668	   
df.mm.trans1:probe8	-0.101231810565360	0.0561194670984418	-1.80386264872730	0.0716153062081363	.  
df.mm.trans1:probe9	0.264601253536051	0.0561194670984418	4.71496375886645	2.83487642488314e-06	***
df.mm.trans1:probe10	0.366400791946332	0.0561194670984418	6.52894282306015	1.15269063172777e-10	***
df.mm.trans1:probe11	0.178221415708394	0.0561194670984418	3.17575032200088	0.00154969167406155	** 
df.mm.trans1:probe12	0.225033093275925	0.0561194670984418	4.00989362356531	6.62198698522442e-05	***
df.mm.trans1:probe13	0.455706797970594	0.0561194670984418	8.12029802726419	1.67611931612483e-15	***
df.mm.trans1:probe14	0.129352724876675	0.0561194670984418	2.30495283659361	0.0214151334911976	*  
df.mm.trans1:probe15	0.283998755002878	0.0561194670984418	5.060610331611	5.14823399771959e-07	***
df.mm.trans1:probe16	0.613502746975572	0.0561194670984418	10.9320843317952	4.40325271653058e-26	***
df.mm.trans1:probe17	0.57188894286973	0.0561194670984418	10.1905626057809	4.65591992809813e-23	***
df.mm.trans1:probe18	0.580897073426581	0.0561194670984418	10.3510796424279	1.06378171771017e-23	***
df.mm.trans1:probe19	0.717325771478445	0.0561194670984418	12.7821201548502	2.79032287142726e-34	***
df.mm.trans1:probe20	0.784001228662179	0.0561194670984418	13.9702186994564	5.46905252977945e-40	***
df.mm.trans1:probe21	0.784718930075514	0.0561194670984418	13.9830075132218	4.72885609757749e-40	***
df.mm.trans2:probe2	0.110820377764872	0.0561194670984418	1.97472256054173	0.0486307016034707	*  
df.mm.trans2:probe3	0.0734964238552064	0.0561194670984418	1.30964222675677	0.190679281854525	   
df.mm.trans2:probe4	0.109821097873388	0.0561194670984418	1.95691626366918	0.05069220589992	.  
df.mm.trans2:probe5	0.172387782237182	0.0561194670984418	3.07180005709585	0.00219715669254160	** 
df.mm.trans2:probe6	0.0352596564171490	0.0561194670984418	0.628296351340941	0.529982664717283	   
df.mm.trans3:probe2	-0.279093206713547	0.0561194670984418	-4.97319773589398	8.00471235175546e-07	***
df.mm.trans3:probe3	-0.294096815826877	0.0561194670984418	-5.24054897583022	2.03187474727149e-07	***
df.mm.trans3:probe4	-0.307793319819188	0.0561194670984418	-5.48460874154905	5.50318650223659e-08	***
df.mm.trans3:probe5	-0.0125566887646767	0.0561194670984418	-0.223749251621553	0.823007480589444	   
df.mm.trans3:probe6	0.127415860367321	0.0561194670984418	2.27043959886175	0.0234364608574115	*  
df.mm.trans3:probe7	-0.330723436043534	0.0561194670984418	-5.89320343087714	5.50419623570855e-09	***
df.mm.trans3:probe8	-0.0535941916029448	0.0561194670984418	-0.955001791248885	0.339854845253782	   
df.mm.trans3:probe9	0.953829752471065	0.0561194670984418	16.9964150015521	8.07924686027203e-56	***
df.mm.trans3:probe10	-0.0854079204529999	0.0561194670984418	-1.52189471619860	0.128416332828414	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.43675468394774	0.195634845319305	22.6787547826989	5.47111648285212e-89	***
df.mm.trans1	-0.0604952287589081	0.168699154800836	-0.358598291913957	0.71998681563731	   
df.mm.trans2	-0.113022734767923	0.149418581207782	-0.756416864986509	0.449613940220058	   
df.mm.exp2	-0.0132667942333603	0.192383070177493	-0.0689602999947989	0.94503783000238	   
df.mm.exp3	0.0264947491541351	0.192383070177493	0.137718714696106	0.890496129954923	   
df.mm.exp4	-0.167248986433138	0.192383070177492	-0.86935397318919	0.384904874625498	   
df.mm.exp5	-0.198934217742319	0.192383070177493	-1.03405261990456	0.301412753439010	   
df.mm.exp6	0.0172957384586792	0.192383070177492	0.089902601318932	0.928386303461984	   
df.mm.exp7	-0.15568398766179	0.192383070177493	-0.809239542326443	0.418609288926611	   
df.mm.exp8	-0.139295309796068	0.192383070177492	-0.724051808028398	0.469237955854557	   
df.mm.trans1:exp2	-0.0428254940163842	0.177210273946784	-0.241664848558638	0.80909956105204	   
df.mm.trans2:exp2	0.031277491315661	0.131848663041133	0.237222665700473	0.812542592622877	   
df.mm.trans1:exp3	0.0620138961531581	0.177210273946784	0.349945264300991	0.726468554916646	   
df.mm.trans2:exp3	-0.040951754130445	0.131848663041133	-0.310596658213131	0.756185246830088	   
df.mm.trans1:exp4	0.193642765411326	0.177210273946783	1.09272877411993	0.274829960073838	   
df.mm.trans2:exp4	0.0836784653168554	0.131848663041133	0.63465539495649	0.525828085082805	   
df.mm.trans1:exp5	0.212361961677689	0.177210273946784	1.19836145471713	0.231118389756153	   
df.mm.trans2:exp5	0.0220472219560939	0.131848663041133	0.167216120721799	0.867240730870139	   
df.mm.trans1:exp6	-0.0746352465011626	0.177210273946784	-0.421167716966431	0.673741654893014	   
df.mm.trans2:exp6	0.0239924350557839	0.131848663041133	0.181969498229186	0.855651094605616	   
df.mm.trans1:exp7	0.155277276859948	0.177210273946784	0.87623179741022	0.381157552012187	   
df.mm.trans2:exp7	-0.0230001635843155	0.131848663041133	-0.174443661799893	0.861559343508306	   
df.mm.trans1:exp8	0.187386812408147	0.177210273946784	1.05742634574573	0.290624712390456	   
df.mm.trans2:exp8	0.0264643273203523	0.131848663041133	0.200717449156812	0.840968687699589	   
df.mm.trans1:probe2	0.0425995923440198	0.121327580577904	0.351112188515674	0.725593287531501	   
df.mm.trans1:probe3	-0.0362864503459453	0.121327580577904	-0.299078331349778	0.764955147736412	   
df.mm.trans1:probe4	-0.187586766642395	0.121327580577904	-1.54611808583742	0.122457231192231	   
df.mm.trans1:probe5	-0.158940924655824	0.121327580577904	-1.31001478722942	0.190553275245134	   
df.mm.trans1:probe6	-0.057716510916119	0.121327580577904	-0.47570808418997	0.63440753621921	   
df.mm.trans1:probe7	0.0989880083677405	0.121327580577904	0.815873916682782	0.414806325452726	   
df.mm.trans1:probe8	0.0226496795766465	0.121327580577904	0.186682034445608	0.851955562051657	   
df.mm.trans1:probe9	0.0265902346552923	0.121327580577904	0.219160676646138	0.826578768006026	   
df.mm.trans1:probe10	-0.0941099956275139	0.121327580577904	-0.77566860873061	0.438165628394429	   
df.mm.trans1:probe11	-0.122912587751722	0.121327580577904	-1.01306386533275	0.311324881082977	   
df.mm.trans1:probe12	0.00350739990785678	0.121327580577904	0.028908512731816	0.976944505621454	   
df.mm.trans1:probe13	-0.109806430348604	0.121327580577904	-0.905040962867447	0.365706313795875	   
df.mm.trans1:probe14	-0.111849096214913	0.121327580577904	-0.921876919346418	0.356860662793669	   
df.mm.trans1:probe15	-0.0149903849897688	0.121327580577904	-0.123552987032025	0.901699130654008	   
df.mm.trans1:probe16	0.20772960754549	0.121327580577904	1.71213838235328	0.0872447016129151	.  
df.mm.trans1:probe17	0.01701599000142	0.121327580577904	0.140248325404413	0.888497817866775	   
df.mm.trans1:probe18	-0.0265893609047112	0.121327580577904	-0.219153475063638	0.826584375843091	   
df.mm.trans1:probe19	0.047410177221156	0.121327580577904	0.390761745971799	0.696073629478847	   
df.mm.trans1:probe20	-0.0992895859835398	0.121327580577904	-0.818359564334889	0.413386785456425	   
df.mm.trans1:probe21	-0.0232843336980393	0.121327580577904	-0.191912948293636	0.847857335353132	   
df.mm.trans2:probe2	-0.0501479643200517	0.121327580577904	-0.413326995240392	0.679473817040276	   
df.mm.trans2:probe3	-0.0241995748224055	0.121327580577904	-0.199456502034729	0.841954518509721	   
df.mm.trans2:probe4	0.108530936352064	0.121327580577904	0.894528151267111	0.371298693697483	   
df.mm.trans2:probe5	-0.016573209478927	0.121327580577904	-0.136598862352533	0.891381001084346	   
df.mm.trans2:probe6	0.114369852904877	0.121327580577904	0.942653371641578	0.346132521765799	   
df.mm.trans3:probe2	0.119715849708037	0.121327580577904	0.986715873981906	0.324069493008630	   
df.mm.trans3:probe3	0.173541338329882	0.121327580577904	1.43035357256178	0.152991904138311	   
df.mm.trans3:probe4	-0.0468309477818932	0.121327580577904	-0.385987650613564	0.699604730338985	   
df.mm.trans3:probe5	0.0973939469159152	0.121327580577904	0.80273542464138	0.422357468380559	   
df.mm.trans3:probe6	0.107180674190648	0.121327580577904	0.883399089309521	0.37727647958177	   
df.mm.trans3:probe7	-0.064620568668594	0.121327580577904	-0.532612357065022	0.594444502446953	   
df.mm.trans3:probe8	0.0760349794584195	0.121327580577904	0.626691631830552	0.531033716694856	   
df.mm.trans3:probe9	0.0438498717874952	0.121327580577904	0.361417178012045	0.717879588004733	   
df.mm.trans3:probe10	0.070209687204569	0.121327580577904	0.578678704958494	0.562962978452943