chr13.6451_chr13_54986304_54986632_-_0.R 

fitVsDatCorrelation=0.838693321661307
cont.fitVsDatCorrelation=0.289782622463386

fstatistic=9381.85080773594,39,393
cont.fstatistic=3030.86813259151,39,393

residuals=-0.500300966583375,-0.0752842030128739,-0.00183385172290480,0.0737597424175365,0.601319977859114
cont.residuals=-0.534349090994087,-0.153963384626697,-0.0470982720922197,0.128084982884879,1.19374047690664

predictedValues:
Include	Exclude	Both
chr13.6451_chr13_54986304_54986632_-_0.R.tl.Lung	56.1459001617343	56.1633274167693	90.5133744532792
chr13.6451_chr13_54986304_54986632_-_0.R.tl.cerebhem	51.3254545291277	62.6620903931544	59.6727273134138
chr13.6451_chr13_54986304_54986632_-_0.R.tl.cortex	50.4488901932495	50.5184412642586	63.697253993123
chr13.6451_chr13_54986304_54986632_-_0.R.tl.heart	53.2645596128749	50.6296551021336	72.0269018436596
chr13.6451_chr13_54986304_54986632_-_0.R.tl.kidney	51.2732724632997	52.6604764275395	64.358467235691
chr13.6451_chr13_54986304_54986632_-_0.R.tl.liver	49.6158277416146	50.6387231444199	59.592375676332
chr13.6451_chr13_54986304_54986632_-_0.R.tl.stomach	61.3794804882649	55.6930924537815	112.689475681879
chr13.6451_chr13_54986304_54986632_-_0.R.tl.testicle	50.8707743051874	53.8073650167754	70.1164782707767


diffExp=-0.0174272550349954,-11.3366358640268,-0.0695510710091085,2.63490451074128,-1.38720396423975,-1.02289540280528,5.68638803448339,-2.93659071158805
diffExpScore=2.65547313816746
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=0,-1,0,0,0,0,0,0
diffExp1.2Score=0.5

cont.predictedValues:
Include	Exclude	Both
Lung	56.7505893255226	60.5213887984869	61.0651622398162
cerebhem	56.8313718107395	61.9856364101104	58.3171426936245
cortex	58.1686784849477	63.401060814967	55.1936383781754
heart	58.5807078726404	59.734137329055	56.0369117175187
kidney	58.9416163401699	61.8543810837074	63.4587497600394
liver	62.7415309065113	54.3208346372852	52.9045549091862
stomach	59.6879655343443	58.3788385181233	66.6818074488541
testicle	64.5265454054915	55.7874591262179	62.3300795470203
cont.diffExp=-3.77079947296421,-5.15426459937094,-5.23238233001925,-1.15342945641464,-2.91276474353748,8.4206962692261,1.30912701622101,8.73908627927364
cont.diffExpScore=29.4655622797266

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=0.251150875358358
cont.tran.correlation=-0.848150722529502

tran.covariance=0.00145688231589207
cont.tran.covariance=-0.00209542012416988

tran.mean=53.5685831696366
cont.tran.mean=59.513296399895

weightedLogRatios:
wLogRatio
Lung	-0.00125009996149394
cerebhem	-0.805857320400337
cortex	-0.00540283611964219
heart	0.200393314036717
kidney	-0.105461390888103
liver	-0.0798821899244431
stomach	0.395534051268536
testicle	-0.222093472616311

cont.weightedLogRatios:
wLogRatio
Lung	-0.261879824874306
cerebhem	-0.354505376503601
cortex	-0.353700015756130
heart	-0.0795558585026247
kidney	-0.197797757297193
liver	0.58611383590675
stomach	0.0904385229587958
testicle	0.595835523439878

varWeightedLogRatios=0.123456444094316
cont.varWeightedLogRatios=0.153066087484576

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.6543694707311	0.0729975458636689	50.0615387475634	1.25212535538275e-172	***
df.mm.trans1	0.351473719888957	0.0596022466138005	5.8969877791079	7.98391437196076e-09	***
df.mm.trans2	0.403743242433427	0.0596022466138005	6.77396013357561	4.58946922401543e-11	***
df.mm.exp2	0.43634833178712	0.0809835060290746	5.38811361946299	1.22950483406310e-07	***
df.mm.exp3	0.138437692622026	0.0809835060290746	1.70945541148002	0.0881560152361252	.  
df.mm.exp4	0.0720489293278963	0.0809835060290746	0.889674118357254	0.37418515991003	   
df.mm.exp5	0.185846260962631	0.0809835060290746	2.29486558529473	0.0222671390250830	*  
df.mm.exp6	0.190778766941942	0.0809835060290746	2.35577312339934	0.0189746621172612	*  
df.mm.exp7	-0.138424367799038	0.0809835060290746	-1.70929087398786	0.0881865062915366	.  
df.mm.exp8	0.113821053785922	0.0809835060290746	1.40548439264977	0.160667315631136	   
df.mm.trans1:exp2	-0.526115175719318	0.0661227557842793	-7.95664320821308	1.90844841714530e-14	***
df.mm.trans2:exp2	-0.326855692769444	0.0661227557842793	-4.94316501017875	1.14033433560309e-06	***
df.mm.trans1:exp3	-0.245430606915170	0.0661227557842793	-3.71174195636779	0.000235547397988515	***
df.mm.trans2:exp3	-0.244363256287177	0.0661227557842793	-3.69560000016325	0.000250488516269783	***
df.mm.trans1:exp4	-0.124731404849849	0.0661227557842793	-1.886361259001	0.0599833272283612	.  
df.mm.trans2:exp4	-0.175775462330347	0.0661227557842793	-2.65832027485064	0.00817380637661754	** 
df.mm.trans1:exp5	-0.276630311869167	0.0661227557842793	-4.18358715676723	3.54218357313066e-05	***
df.mm.trans2:exp5	-0.250245066534161	0.0661227557842793	-3.78455289054448	0.000177996521016125	***
df.mm.trans1:exp6	-0.314422539120404	0.0661227557842793	-4.75513362065829	2.78839293349419e-06	***
df.mm.trans2:exp6	-0.294326210628114	0.0661227557842793	-4.45120907525893	1.11384152575407e-05	***
df.mm.trans1:exp7	0.227546290395520	0.0661227557842793	3.4412705232352	0.000641119552142169	***
df.mm.trans2:exp7	0.130016486808371	0.0661227557842793	1.96628959676968	0.0499685847408607	*  
df.mm.trans1:exp8	-0.212486136512316	0.0661227557842793	-3.21350999352683	0.00141943604710916	** 
df.mm.trans2:exp8	-0.156674706601533	0.0661227557842793	-2.36945216126008	0.0182968695137498	*  
df.mm.trans1:probe2	0.136792360631272	0.0404917530145373	3.37827706748485	0.000802296644811232	***
df.mm.trans1:probe3	-0.00787067598259884	0.0404917530145373	-0.194377259482273	0.845980931371208	   
df.mm.trans1:probe4	-0.00377631311968046	0.0404917530145373	-0.093261289979831	0.925743509101156	   
df.mm.trans1:probe5	0.00744400807622715	0.0404917530145373	0.183840103775073	0.854233710146434	   
df.mm.trans1:probe6	0.132736285343935	0.0404917530145373	3.27810666276365	0.00113809133151434	** 
df.mm.trans2:probe2	-0.00742728923379478	0.0404917530145373	-0.183427208773309	0.854557424984671	   
df.mm.trans2:probe3	-0.0287560953696203	0.0404917530145373	-0.710171657900223	0.478018875334605	   
df.mm.trans2:probe4	-0.0872444921838555	0.0404917530145373	-2.15462373665406	0.0317983530240303	*  
df.mm.trans2:probe5	-0.087883579483716	0.0404917530145373	-2.17040688389471	0.0305742547392144	*  
df.mm.trans2:probe6	-0.146873019665250	0.0404917530145373	-3.62723292351704	0.000324227305983461	***
df.mm.trans3:probe2	0.0419175935780203	0.0404917530145373	1.03521311025905	0.301205965946855	   
df.mm.trans3:probe3	0.0849944757931155	0.0404917530145373	2.09905646126511	0.0364493640935253	*  
df.mm.trans3:probe4	0.140683711180167	0.0404917530145373	3.47437936632822	0.000569060997890703	***
df.mm.trans3:probe5	0.192333625236291	0.0404917530145373	4.74994562886027	2.85689057704908e-06	***
df.mm.trans3:probe6	0.115537738697698	0.0404917530145373	2.85336470012099	0.00455470328311787	** 

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.05991639313959	0.128286614448876	31.6472331161058	3.91666848823026e-110	***
df.mm.trans1	-0.0257701154745260	0.104745582076301	-0.246025798546367	0.805790702327758	   
df.mm.trans2	0.0701395950436971	0.104745582076301	0.669618647902539	0.50349413898976	   
df.mm.exp2	0.0713737385013585	0.142321220415724	0.501497515921195	0.61630182947995	   
df.mm.exp3	0.172258583182617	0.142321220415724	1.21035066084625	0.226871809748822	   
df.mm.exp4	0.104577135450102	0.142321220415724	0.734796505711723	0.46290165671032	   
df.mm.exp5	0.0212188961699551	0.142321220415724	0.14909158386904	0.881557842032771	   
df.mm.exp6	0.135720662436011	0.142321220415724	0.953622109475783	0.340861124687683	   
df.mm.exp7	-0.073569625920056	0.142321220415724	-0.516926609434328	0.605498173508862	   
df.mm.exp8	0.0264603161937031	0.142321220415724	0.185919683069129	0.85260366954574	   
df.mm.trans1:exp2	-0.0699512855338309	0.1162047898629	-0.60196559553492	0.547544156516453	   
df.mm.trans2:exp2	-0.0474678875184768	0.1162047898629	-0.408484775666132	0.68314028498784	   
df.mm.trans1:exp3	-0.147577584570895	0.1162047898629	-1.26997849869191	0.204843701677213	   
df.mm.trans2:exp3	-0.125774826199860	0.1162047898629	-1.08235492141288	0.279758501587904	   
df.mm.trans1:exp4	-0.0728377511597485	0.1162047898629	-0.626805067550859	0.531150959144723	   
df.mm.trans2:exp4	-0.117670300335872	0.1162047898629	-1.01261144635002	0.311868807010729	   
df.mm.trans1:exp5	0.0166624633496667	0.1162047898629	0.143388782590849	0.88605663297041	   
df.mm.trans2:exp5	0.000567197755272408	0.1162047898629	0.00488101872514546	0.996108002630579	   
df.mm.trans1:exp6	-0.0353631000643837	0.1162047898629	-0.304317060476643	0.76104742074356	   
df.mm.trans2:exp6	-0.243809650528299	0.1162047898629	-2.09810327797976	0.0365339726925546	*  
df.mm.trans1:exp7	0.124034002760571	0.1162047898629	1.06737427008738	0.286458090967622	   
df.mm.trans2:exp7	0.0375262595286756	0.1162047898629	0.322932123305326	0.746918392849339	   
df.mm.trans1:exp8	0.101950338717792	0.1162047898629	0.877333359821691	0.38084159570529	   
df.mm.trans2:exp8	-0.107908055325481	0.1162047898629	-0.928602473725841	0.353665118385813	   
df.mm.trans1:probe2	0.0342048404463786	0.0711606102078621	0.480670982815708	0.631017824398139	   
df.mm.trans1:probe3	0.0410048655140075	0.0711606102078621	0.576229818634651	0.564789701314472	   
df.mm.trans1:probe4	0.0407433005717147	0.0711606102078621	0.572554120217665	0.56727402846801	   
df.mm.trans1:probe5	0.0247555702613617	0.0711606102078621	0.347883052000960	0.728114266637472	   
df.mm.trans1:probe6	-0.0864714179945719	0.0711606102078621	-1.21515846676956	0.225035180593789	   
df.mm.trans2:probe2	-0.0838698121764493	0.0711606102078621	-1.17859883342011	0.239271058296075	   
df.mm.trans2:probe3	-0.0969264053405602	0.0711606102078621	-1.36207945740538	0.173952987560704	   
df.mm.trans2:probe4	-0.0484762368393234	0.0711606102078621	-0.681222894206823	0.496131663775886	   
df.mm.trans2:probe5	-0.0772496334055479	0.0711606102078621	-1.08556732692285	0.278335895308862	   
df.mm.trans2:probe6	-0.0181877334249531	0.0711606102078621	-0.255587091957562	0.798403400863074	   
df.mm.trans3:probe2	-0.0409479191926837	0.0711606102078621	-0.575429568030314	0.565330126243137	   
df.mm.trans3:probe3	0.0629458893992631	0.0711606102078621	0.884560843638024	0.37693437879773	   
df.mm.trans3:probe4	0.00760923633030516	0.0711606102078621	0.106930453632682	0.914898716908279	   
df.mm.trans3:probe5	0.0524586536453463	0.0711606102078621	0.737186675214183	0.461448711501917	   
df.mm.trans3:probe6	-0.0361319316892698	0.0711606102078621	-0.507751852938408	0.611912217785163