chr19.12085_chr19_55207131_55208439_+_0.R 

fitVsDatCorrelation=0.913043629281303
cont.fitVsDatCorrelation=0.23949017200998

fstatistic=6753.30707388448,64,968
cont.fstatistic=1179.32076955589,64,968

residuals=-0.953075017577259,-0.105429920379022,-0.000487536000092308,0.0987871572731026,1.80053075646604
cont.residuals=-0.826003547786871,-0.318328202430904,-0.135089381315584,0.183285222632046,2.17940376563198

predictedValues:
Include	Exclude	Both
chr19.12085_chr19_55207131_55208439_+_0.R.tl.Lung	67.1816490513192	83.6492629353822	56.4552560081456
chr19.12085_chr19_55207131_55208439_+_0.R.tl.cerebhem	67.9622318236017	89.7147913918432	63.0624488824195
chr19.12085_chr19_55207131_55208439_+_0.R.tl.cortex	65.4913736904197	82.3044393902387	52.682542507422
chr19.12085_chr19_55207131_55208439_+_0.R.tl.heart	68.2294925169043	86.690233924724	53.6825250401283
chr19.12085_chr19_55207131_55208439_+_0.R.tl.kidney	65.9403235683629	81.5301186235257	57.309759343528
chr19.12085_chr19_55207131_55208439_+_0.R.tl.liver	68.9366432644273	91.553874592363	55.5962909091517
chr19.12085_chr19_55207131_55208439_+_0.R.tl.stomach	88.7133649665893	109.002171353213	55.2314466976878
chr19.12085_chr19_55207131_55208439_+_0.R.tl.testicle	68.0394009600556	81.0150984217049	56.4145299824856


diffExp=-16.467613884063,-21.7525595682416,-16.8130656998190,-18.4607414078197,-15.5897950551628,-22.6172313279356,-20.2888063866241,-12.9756974616492
diffExpScore=0.993149066552922
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,-1,0,0,0,-1,0,0
diffExp1.3Score=0.666666666666667
diffExp1.2=-1,-1,-1,-1,-1,-1,-1,0
diffExp1.2Score=0.875

cont.predictedValues:
Include	Exclude	Both
Lung	73.5309951638196	62.8469690710317	78.5908912181279
cerebhem	68.707715353228	72.0432128089359	80.4388870404165
cortex	73.907752781065	69.3666851780896	73.913434981642
heart	64.6250443507121	68.0092232893992	62.8387128937594
kidney	74.8597654481082	84.3581107984889	72.3334460629861
liver	70.905741484919	61.1361627374657	70.7828605609554
stomach	67.2319470411279	72.123883410636	71.1838265655877
testicle	66.9778745266523	78.9512329804951	69.0994580326466
cont.diffExp=10.6840260927879,-3.33549745570789,4.54106760297537,-3.38417893868714,-9.49834535038069,9.7695787474533,-4.8919363695081,-11.9733584538428
cont.diffExpScore=6.39017087842221

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

tran.correlation=0.942455510286823
cont.tran.correlation=0.0407450927568315

tran.covariance=0.00904236879594466
cont.tran.covariance=3.30208991280831e-05

tran.mean=79.1221544046672
cont.tran.mean=70.5988947765109

weightedLogRatios:
wLogRatio
Lung	-0.946430229301096
cerebhem	-1.21008753698524
cortex	-0.981703654309241
heart	-1.03989993899943
kidney	-0.9114656105814
liver	-1.24137766929211
stomach	-0.945012011033438
testicle	-0.751843765311213

cont.weightedLogRatios:
wLogRatio
Lung	0.662433353448927
cerebhem	-0.201638571531483
cortex	0.270835582236779
heart	-0.214073530274843
kidney	-0.522654027398905
liver	0.620747503856193
stomach	-0.298033090917052
testicle	-0.705008030281222

varWeightedLogRatios=0.0256490315818807
cont.varWeightedLogRatios=0.260607319594398

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.40441775066215	0.095621533874383	46.0609401690647	3.47209398948813e-246	***
df.mm.trans1	-0.435519723070942	0.0821237753940215	-5.30321117095948	1.41008321286071e-07	***
df.mm.trans2	0.0154361790023131	0.0718206168128102	0.214926850914484	0.829869620893733	   
df.mm.exp2	-0.029122048472154	0.0910309492461792	-0.319913707517186	0.749102781583156	   
df.mm.exp3	0.0274749920297365	0.0910309492461792	0.301820339755380	0.762853854438797	   
df.mm.exp4	0.101546266551940	0.0910309492461793	1.11551365104767	0.264907221302944	   
df.mm.exp5	-0.0593326304568261	0.0910309492461793	-0.651785254884799	0.514694432875651	   
df.mm.exp6	0.131414621434945	0.0910309492461793	1.44362573963229	0.149167824648436	   
df.mm.exp7	0.56466152771005	0.0910309492461792	6.20296209570451	8.19861465330155e-10	***
df.mm.exp8	-0.0185885996932627	0.0910309492461792	-0.204200877253215	0.838239449009905	   
df.mm.trans1:exp2	0.0406740543471528	0.0837083029596348	0.485902269058857	0.627146428558318	   
df.mm.trans2:exp2	0.0991250863009281	0.0581521945552621	1.70458031823252	0.0885936121402879	.  
df.mm.trans1:exp3	-0.052956688087178	0.0837083029596348	-0.63263363626801	0.527122322300674	   
df.mm.trans2:exp3	-0.0436825603448304	0.0581521945552621	-0.751176471995718	0.452729031809908	   
df.mm.trans1:exp4	-0.086069484224225	0.0837083029596348	-1.02820725281850	0.304109197460636	   
df.mm.trans2:exp4	-0.0658376473716063	0.0581521945552621	-1.13216101086333	0.257847118771770	   
df.mm.trans1:exp5	0.040682644457627	0.0837083029596348	0.486004888633863	0.627073695494207	   
df.mm.trans2:exp5	0.0336725199968871	0.0581521945552621	0.579041259825337	0.562696045761537	   
df.mm.trans1:exp6	-0.105626882855629	0.0837083029596348	-1.26184475280264	0.207308614010944	   
df.mm.trans2:exp6	-0.0411196451666214	0.0581521945552621	-0.70710392756623	0.479672079741437	   
df.mm.trans1:exp7	-0.286651104326874	0.0837083029596348	-3.42440467900897	0.00064199984789948	***
df.mm.trans2:exp7	-0.299926341109149	0.0581521945552621	-5.15761001631897	3.03316007464525e-07	***
df.mm.trans1:exp8	0.0312754323075625	0.0837083029596348	0.37362401579977	0.708765875391552	   
df.mm.trans2:exp8	-0.0134084788382199	0.0581521945552621	-0.230575629015648	0.817693223172765	   
df.mm.trans1:probe2	-0.119235355202327	0.0606524277486116	-1.96587934940587	0.0495980372308072	*  
df.mm.trans1:probe3	0.0760525617359004	0.0606524277486117	1.25390795651442	0.210178190383988	   
df.mm.trans1:probe4	-0.122583491936940	0.0606524277486116	-2.02108137278555	0.043546194053548	*  
df.mm.trans1:probe5	0.451172487705691	0.0606524277486117	7.4386550456922	2.23990942242811e-13	***
df.mm.trans1:probe6	-0.00452898150216336	0.0606524277486117	-0.074671067099487	0.940491856322147	   
df.mm.trans1:probe7	0.0503250163992091	0.0606524277486117	0.82972798068023	0.406897165084561	   
df.mm.trans1:probe8	0.0786592793698564	0.0606524277486116	1.29688591684868	0.194979479727787	   
df.mm.trans1:probe9	0.0860771560961835	0.0606524277486116	1.41918731518795	0.15616632806415	   
df.mm.trans1:probe10	0.146537361899777	0.0606524277486117	2.41601807774515	0.0158755071196095	*  
df.mm.trans1:probe11	1.38766887930624	0.0606524277486116	22.8790327249186	5.92210675528128e-93	***
df.mm.trans1:probe12	1.30742897541259	0.0606524277486116	21.5560864411156	1.74641214411454e-84	***
df.mm.trans1:probe13	1.28285700655126	0.0606524277486116	21.1509589009094	6.33374537480735e-82	***
df.mm.trans1:probe14	0.9492885446636	0.0606524277486116	15.6512868470517	2.16774151099070e-49	***
df.mm.trans1:probe15	1.05234887607808	0.0606524277486116	17.3504823325422	6.33339952772507e-59	***
df.mm.trans1:probe16	1.41151850204941	0.0606524277486116	23.2722506657077	1.68086364962601e-95	***
df.mm.trans1:probe17	-0.0813597810018378	0.0606524277486116	-1.34141013017735	0.180101947873827	   
df.mm.trans1:probe18	0.13401752857669	0.0606524277486117	2.20959875064123	0.0273664614063996	*  
df.mm.trans1:probe19	-0.129440382748258	0.0606524277486116	-2.1341335796937	0.0330826016964774	*  
df.mm.trans1:probe20	-0.121608898661929	0.0606524277486116	-2.00501287707667	0.0452397065983457	*  
df.mm.trans1:probe21	0.480756966241125	0.0606524277486116	7.9264257687052	6.18393349298644e-15	***
df.mm.trans1:probe22	0.0171516052079650	0.0606524277486117	0.282785138940422	0.777402004103082	   
df.mm.trans1:probe23	0.014469750559001	0.0606524277486116	0.238568365622137	0.8114907914971	   
df.mm.trans2:probe2	0.0693786136588443	0.0606524277486116	1.14387199711775	0.252959510969281	   
df.mm.trans2:probe3	-0.0912788834361042	0.0606524277486116	-1.50495020272612	0.132663087382042	   
df.mm.trans2:probe4	0.048638432453417	0.0606524277486116	0.801920619814437	0.422795692075761	   
df.mm.trans2:probe5	0.107594731574531	0.0606524277486116	1.77395589209525	0.0763847522831345	.  
df.mm.trans2:probe6	0.00124083449020578	0.0606524277486116	0.0204581174450051	0.983682138558301	   
df.mm.trans3:probe2	-0.081911371239667	0.0606524277486116	-1.35050441145024	0.177169873488405	   
df.mm.trans3:probe3	-0.0841283291528695	0.0606524277486116	-1.38705625274489	0.165743896644351	   
df.mm.trans3:probe4	-0.0622843052650987	0.0606524277486116	-1.02690539483845	0.304721547914715	   
df.mm.trans3:probe5	0.241023523952305	0.0606524277486116	3.97384792165755	7.59725253421417e-05	***
df.mm.trans3:probe6	0.0155013165393564	0.0606524277486116	0.255576192326633	0.798332399020137	   
df.mm.trans3:probe7	0.296266619651828	0.0606524277486116	4.88466217510328	1.21175202631143e-06	***
df.mm.trans3:probe8	-0.146284897777513	0.0606524277486116	-2.41185560426081	0.0160567805508072	*  
df.mm.trans3:probe9	0.185852751073198	0.0606524277486116	3.06422608248277	0.00224277232176372	** 
df.mm.trans3:probe10	0.484304159196132	0.0606524277486116	7.98490970886517	3.96912866073312e-15	***
df.mm.trans3:probe11	-0.0966225376226769	0.0606524277486116	-1.59305309299657	0.111474739523459	   
df.mm.trans3:probe12	-0.103479428433995	0.0606524277486116	-1.70610529990472	0.0883092435623789	.  
df.mm.trans3:probe13	-0.104720308943354	0.0606524277486116	-1.72656417608529	0.0845650136824296	.  
df.mm.trans3:probe14	0.144081450634813	0.0606524277486116	2.37552652025724	0.0177178193160774	*  

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.15928362490237	0.227623200300423	18.2726700064530	2.58658776382871e-64	***
df.mm.trans1	0.106521361294370	0.195492331261883	0.544887672098366	0.58595628454113	   
df.mm.trans2	-0.0387117705995317	0.170966078289002	-0.226429540801031	0.820915157860161	   
df.mm.exp2	0.0454759614949884	0.216695498955510	0.209861126392501	0.83382022361542	   
df.mm.exp3	0.165175907820076	0.216695498955510	0.76224890972003	0.44609714696489	   
df.mm.exp4	0.173520096396555	0.216695498955510	0.800755425160814	0.423469737402197	   
df.mm.exp5	0.395246982365238	0.216695498955510	1.82397412161471	0.0684641845548247	.  
df.mm.exp6	0.0406841495780778	0.216695498955510	0.187748014029727	0.851113536863992	   
df.mm.exp7	0.147114218326915	0.216695498955510	0.678898357538653	0.497364546047263	   
df.mm.exp8	0.263491879813291	0.216695498955510	1.21595455873953	0.224298672354897	   
df.mm.trans1:exp2	-0.113321483812597	0.199264235150425	-0.568699564811768	0.569691954278388	   
df.mm.trans2:exp2	0.0910874463194132	0.138428951020077	0.658008643771364	0.510689026434746	   
df.mm.trans1:exp3	-0.160065196523996	0.199264235150425	-0.803281112655074	0.422009467025084	   
df.mm.trans2:exp3	-0.0664719052940717	0.138428951020077	-0.480187885584939	0.631202289696704	   
df.mm.trans1:exp4	-0.302625097526473	0.199264235150425	-1.51871256423924	0.129161386619252	   
df.mm.trans2:exp4	-0.094579472878265	0.138428951020077	-0.683234772649168	0.494621996058353	   
df.mm.trans1:exp5	-0.377337433337295	0.199264235150425	-1.89365358541357	0.0585689739421976	.  
df.mm.trans2:exp5	-0.100878730591917	0.138428951020077	-0.728740121546443	0.46633690950025	   
df.mm.trans1:exp6	-0.0770397595137518	0.199264235150425	-0.386621108678104	0.69912169902414	   
df.mm.trans2:exp6	-0.0682833060532972	0.138428951020077	-0.493273304103806	0.621931373013165	   
df.mm.trans1:exp7	-0.236672701604212	0.199264235150425	-1.18773296886693	0.235229981115399	   
df.mm.trans2:exp7	-0.00943168399564472	0.138428951020077	-0.0681337532802428	0.945693232190927	   
df.mm.trans1:exp8	-0.356836566142278	0.199264235150425	-1.79077076161159	0.0736424644051017	.  
df.mm.trans2:exp8	-0.03536423107004	0.138428951020077	-0.255468460964579	0.79841557117968	   
df.mm.trans1:probe2	0.0105503428435661	0.144380655180305	0.0730731054682542	0.941763039063996	   
df.mm.trans1:probe3	0.0504763545333496	0.144380655180305	0.349606077561526	0.726710392484842	   
df.mm.trans1:probe4	-0.066865892058138	0.144380655180305	-0.463122237356762	0.643380851206827	   
df.mm.trans1:probe5	-0.0726556636143445	0.144380655180305	-0.50322298041667	0.614921991993507	   
df.mm.trans1:probe6	0.0216687777604949	0.144380655180305	0.150080893686447	0.880732058669637	   
df.mm.trans1:probe7	0.0308823163100012	0.144380655180305	0.213895111304453	0.830673897063468	   
df.mm.trans1:probe8	0.147604756651599	0.144380655180305	1.02233056407223	0.306879892643645	   
df.mm.trans1:probe9	-0.0350273398206211	0.144380655180305	-0.242604106324898	0.808363492482212	   
df.mm.trans1:probe10	0.109123340941167	0.144380655180305	0.755803059661227	0.449951156885165	   
df.mm.trans1:probe11	-0.083956320976622	0.144380655180305	-0.581492866006017	0.561043703122982	   
df.mm.trans1:probe12	0.0675007167919734	0.144380655180305	0.467519119564026	0.64023374280493	   
df.mm.trans1:probe13	0.0533087707356355	0.144380655180305	0.369223776336675	0.71204168306493	   
df.mm.trans1:probe14	-0.0403624821227580	0.144380655180305	-0.279556025510154	0.779877869362597	   
df.mm.trans1:probe15	0.0288002914905702	0.144380655180305	0.199474725021880	0.841933305444618	   
df.mm.trans1:probe16	0.0020597604147694	0.144380655180305	0.0142661799961853	0.988620561021447	   
df.mm.trans1:probe17	0.09337178103637	0.144380655180305	0.646705619390394	0.517975791804168	   
df.mm.trans1:probe18	0.113306449985473	0.144380655180305	0.784775840253489	0.432777020102528	   
df.mm.trans1:probe19	0.0623751481375316	0.144380655180305	0.432018735886996	0.665824008666768	   
df.mm.trans1:probe20	0.170682388708069	0.144380655180305	1.18216937369427	0.237428809631180	   
df.mm.trans1:probe21	0.115257434813650	0.144380655180305	0.7982886257838	0.424898815401058	   
df.mm.trans1:probe22	0.213125729020616	0.144380655180305	1.47613770525187	0.140232139401680	   
df.mm.trans1:probe23	0.125344529799389	0.144380655180305	0.868153213758845	0.385525637718294	   
df.mm.trans2:probe2	0.200680202188258	0.144380655180305	1.38993829843510	0.164867158976854	   
df.mm.trans2:probe3	0.167317337612915	0.144380655180305	1.15886257341031	0.246798005919569	   
df.mm.trans2:probe4	-0.0388621941710167	0.144380655180305	-0.269164827673659	0.78786020509913	   
df.mm.trans2:probe5	-0.0461450604716022	0.144380655180305	-0.319606947440262	0.749335270573086	   
df.mm.trans2:probe6	0.119626810160982	0.144380655180305	0.82855151205395	0.407562475402735	   
df.mm.trans3:probe2	0.0390553250444386	0.144380655180305	0.270502478297149	0.786831373504066	   
df.mm.trans3:probe3	0.305447170647838	0.144380655180305	2.11556853143789	0.0346364070738066	*  
df.mm.trans3:probe4	0.182519553896113	0.144380655180305	1.26415518525096	0.206478644285687	   
df.mm.trans3:probe5	0.33003063625298	0.144380655180305	2.28583694845291	0.0224791811122314	*  
df.mm.trans3:probe6	-0.108021268521220	0.144380655180305	-0.748169956607565	0.454539378406064	   
df.mm.trans3:probe7	0.0210965857110867	0.144380655180305	0.146117813946342	0.88385880597072	   
df.mm.trans3:probe8	0.282744048103988	0.144380655180305	1.95832362549465	0.0504789246064431	.  
df.mm.trans3:probe9	0.201026113817194	0.144380655180305	1.39233412929280	0.164140996824459	   
df.mm.trans3:probe10	0.096681619919138	0.144380655180305	0.66963001240298	0.50325336683881	   
df.mm.trans3:probe11	0.107369383390290	0.144380655180305	0.743654911776135	0.457265732053268	   
df.mm.trans3:probe12	0.0572864654313983	0.144380655180305	0.396773829290759	0.691621707892694	   
df.mm.trans3:probe13	0.168959554418806	0.144380655180305	1.17023678974033	0.242193718353721	   
df.mm.trans3:probe14	0.23608106226102	0.144380655180305	1.63512945668655	0.102347024093705