chr19.11844_chr19_8097449_8097923_+_2.R 

fitVsDatCorrelation=0.888594546404881
cont.fitVsDatCorrelation=0.331427718578901

fstatistic=6706.75203356151,38,370
cont.fstatistic=1577.79162275807,38,370

residuals=-0.649954681471918,-0.0963859291443768,0.00165703611767098,0.086175951703244,0.95338654934868
cont.residuals=-0.636136421685931,-0.220135952504654,-0.058194204218466,0.132406629270575,1.42390584359949

predictedValues:
Include	Exclude	Both
chr19.11844_chr19_8097449_8097923_+_2.R.tl.Lung	76.5768141436802	76.6220319138076	72.8147637688121
chr19.11844_chr19_8097449_8097923_+_2.R.tl.cerebhem	67.6402407511169	77.0865932338235	81.4484231089224
chr19.11844_chr19_8097449_8097923_+_2.R.tl.cortex	76.9906288083215	59.8177787505884	73.4386272307286
chr19.11844_chr19_8097449_8097923_+_2.R.tl.heart	74.3427792362015	60.2134678063619	68.5098878875197
chr19.11844_chr19_8097449_8097923_+_2.R.tl.kidney	84.9915291191054	74.0373534135689	72.0047577251312
chr19.11844_chr19_8097449_8097923_+_2.R.tl.liver	84.6154161310073	73.93746956672	65.7138863558296
chr19.11844_chr19_8097449_8097923_+_2.R.tl.stomach	71.205182976198	63.7260519896659	66.385836962629
chr19.11844_chr19_8097449_8097923_+_2.R.tl.testicle	78.7677558999752	65.8465426542455	69.7869103246533


diffExp=-0.0452177701273939,-9.44635248270664,17.1728500577332,14.1293114298396,10.9541757055365,10.6779465642873,7.4791309865321,12.9212132457297
diffExpScore=1.27733332037881
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=0,0,1,1,0,0,0,0
diffExp1.2Score=0.666666666666667

cont.predictedValues:
Include	Exclude	Both
Lung	75.9865381463962	76.069537488568	78.1632601794681
cerebhem	74.9937407348623	63.2086192432629	81.6831049251163
cortex	67.3967080425711	73.2701486173185	84.9620776697563
heart	83.5410041150272	85.0058105040789	90.3138228263446
kidney	80.3248269756102	65.9291695178322	97.2430923460688
liver	71.4292037622666	72.5160231991782	73.0123014685726
stomach	73.0989214306473	83.0599993194632	73.2880977482644
testicle	82.6577647212778	67.4013872174975	107.954472494938
cont.diffExp=-0.0829993421718314,11.7851214915995,-5.87344057474736,-1.46480638905169,14.3956574577781,-1.08681943691165,-9.96107788881595,15.2563775037803
cont.diffExpScore=2.49942707103445

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=0,0,0,0,1,0,0,1
cont.diffExp1.2Score=0.666666666666667

tran.correlation=0.153946253746367
cont.tran.correlation=0.00886657282633929

tran.covariance=0.0011843156430513
cont.tran.covariance=-0.000154121215733488

tran.mean=72.9011022746492
cont.tran.mean=74.7430876897411

weightedLogRatios:
wLogRatio
Lung	-0.00256113350034059
cerebhem	-0.559451833679161
cortex	1.06441429632707
heart	0.886013893703071
kidney	0.603472002520073
liver	0.589588894537029
stomach	0.467201585936425
testicle	0.766324004051971

cont.weightedLogRatios:
wLogRatio
Lung	-0.00472823798141785
cerebhem	0.723506345281576
cortex	-0.355316108237447
heart	-0.0770724378349726
kidney	0.846738105884601
liver	-0.0645746695149756
stomach	-0.556437532224772
testicle	0.879974352467825

varWeightedLogRatios=0.275576413619006
cont.varWeightedLogRatios=0.316935303413806

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.9363630995923	0.0965836276264136	40.7560079935928	7.07739852181444e-139	***
df.mm.trans1	0.201339669002085	0.0834072583031262	2.41393462749199	0.0162661386661149	*  
df.mm.trans2	0.286993201894913	0.081165578155489	3.53589795596749	0.000457980458995939	***
df.mm.exp2	-0.230097782001229	0.112466324152808	-2.04592604705917	0.0414701813776550	*  
df.mm.exp3	-0.250723690925123	0.112466324152808	-2.22932235772608	0.0263922295020041	*  
df.mm.exp4	-0.209655757052289	0.112466324152808	-1.86416475004047	0.0630903102910003	.  
df.mm.exp5	0.0811288713290424	0.112466324152808	0.721361455886233	0.471142724801037	   
df.mm.exp6	0.166765672566117	0.112466324152808	1.48280539816997	0.138977355560636	   
df.mm.exp7	-0.164584934329873	0.112466324152808	-1.46341525402975	0.144202773211863	   
df.mm.exp8	-0.080876081652623	0.112466324152808	-0.719113763714167	0.472524745760335	   
df.mm.trans1:exp2	0.106006521818089	0.100592938394082	1.05381673416079	0.292654505457583	   
df.mm.trans2:exp2	0.236142501145714	0.0963104060673571	2.45188978832217	0.0146722387596507	*  
df.mm.trans1:exp3	0.256113058076123	0.100592938394082	2.54603416666066	0.0113001437933247	*  
df.mm.trans2:exp3	0.00314195293064802	0.0963104060673571	0.0326231926428657	0.973992665527892	   
df.mm.trans1:exp4	0.180047963189296	0.100592938394082	1.78986682428882	0.0742929458312826	.  
df.mm.trans2:exp4	-0.0313328562270297	0.0963104060673571	-0.325331991696892	0.745113709378637	   
df.mm.trans1:exp5	0.0231283792647096	0.100592938394082	0.229920505692976	0.818280598120257	   
df.mm.trans2:exp5	-0.115443787908983	0.0963104060673572	-1.19866370232355	0.23142589146147	   
df.mm.trans1:exp6	-0.0669435422920458	0.100592938394082	-0.665489480283284	0.506152103352078	   
df.mm.trans2:exp6	-0.202430600722450	0.0963104060673571	-2.10185595709019	0.0362414470811793	*  
df.mm.trans1:exp7	0.0918562011997824	0.100592938394082	0.913147609228072	0.36175953417976	   
df.mm.trans2:exp7	-0.0197062655583644	0.0963104060673572	-0.204612007809233	0.837987779754096	   
df.mm.trans1:exp8	0.109085462181005	0.100592938394082	1.08442465169526	0.278882655130508	   
df.mm.trans2:exp8	-0.0706816531754899	0.0963104060673571	-0.733894249454798	0.463477976096445	   
df.mm.trans1:probe2	0.260117160301125	0.0502964691970409	5.17167833952903	3.80837131787044e-07	***
df.mm.trans1:probe3	1.24877387661190	0.0502964691970408	24.8282612387704	8.56985313045156e-81	***
df.mm.trans1:probe4	0.132276353204226	0.0502964691970408	2.62993318051853	0.00889665380789342	** 
df.mm.trans1:probe5	-0.0276510091590713	0.0502964691970409	-0.549760442442711	0.582815375393611	   
df.mm.trans1:probe6	0.185871087527953	0.0502964691970409	3.69550965495781	0.00025260102784024	***
df.mm.trans1:probe7	0.195223899779671	0.0502964691970408	3.88146330937990	0.000122927602514904	***
df.mm.trans1:probe8	0.211895955785492	0.0502964691970408	4.21293898296063	3.17015384627609e-05	***
df.mm.trans2:probe2	0.0198328753098433	0.0502964691970409	0.394319434872183	0.693572391632519	   
df.mm.trans2:probe3	0.0798757259660453	0.0502964691970408	1.58809807609208	0.113118298698543	   
df.mm.trans2:probe4	0.284326868684134	0.0502964691970409	5.65301845682762	3.15443628543576e-08	***
df.mm.trans2:probe5	0.097350284898808	0.0502964691970408	1.93552920220761	0.0536869808048999	.  
df.mm.trans2:probe6	0.558369456336256	0.0502964691970409	11.1015636932444	6.54670516387136e-25	***
df.mm.trans3:probe2	0.0685844054174006	0.0502964691970408	1.36360278389951	0.173521667928597	   
df.mm.trans3:probe3	-0.478916115893779	0.0502964691970409	-9.52186353315543	2.27392071180502e-19	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.27592880770317	0.198661587955257	21.5236818134475	3.28214882795176e-67	***
df.mm.trans1	0.101116035890750	0.171559287932170	0.589394122052601	0.555956621412947	   
df.mm.trans2	-0.0277093676367054	0.166948405645371	-0.16597563498489	0.868266779863993	   
df.mm.exp2	-0.242406226331969	0.231330496656321	-1.04787838108567	0.295378656764962	   
df.mm.exp3	-0.240859926111227	0.231330496656321	-1.04119400421754	0.298465375827215	   
df.mm.exp4	0.0613623007990659	0.231330496656321	0.265258155262726	0.790958318908108	   
df.mm.exp5	-0.305958587930272	0.231330496656321	-1.32260377404897	0.186784082674102	   
df.mm.exp6	-0.0415179565182716	0.231330496656321	-0.179474635287510	0.857663275778117	   
df.mm.exp7	0.113574258094678	0.231330496656321	0.490961026480703	0.623745077794656	   
df.mm.exp8	-0.359739586213584	0.231330496656321	-1.55508932636770	0.120779707846387	   
df.mm.trans1:exp2	0.22925468457272	0.206908286316929	1.10800146602907	0.268580919818676	   
df.mm.trans2:exp2	0.0571990097031295	0.198099602139237	0.288738639984377	0.772943087162523	   
df.mm.trans1:exp3	0.120899905793983	0.206908286316929	0.58431640388146	0.559363544646692	   
df.mm.trans2:exp3	0.203365313718538	0.198099602139237	1.02658113152393	0.305288400323549	   
df.mm.trans1:exp4	0.0334190828251779	0.206908286316929	0.161516406230289	0.871774849287296	   
df.mm.trans2:exp4	0.049709423312346	0.198099602139237	0.250931464654871	0.802006389116821	   
df.mm.trans1:exp5	0.361481143931507	0.206908286316929	1.74705977399965	0.0814566645866945	.  
df.mm.trans2:exp5	0.162891675639093	0.198099602139237	0.822271594087314	0.411451916399551	   
df.mm.trans1:exp6	-0.0203314364266423	0.206908286316929	-0.09826303619131	0.921776639384826	   
df.mm.trans2:exp6	-0.00632238531035549	0.198099602139237	-0.0319151842915449	0.974556898244805	   
df.mm.trans1:exp7	-0.152316841102844	0.206908286316929	-0.736156312606714	0.462102023120748	   
df.mm.trans2:exp7	-0.0256589169994459	0.198099602139237	-0.129525333329095	0.897012363521841	   
df.mm.trans1:exp8	0.443892158144439	0.206908286316928	2.14535708572113	0.0325746677480228	*  
df.mm.trans2:exp8	0.238757296867964	0.198099602139237	1.20523864909203	0.22888144015778	   
df.mm.trans1:probe2	-0.126941714116046	0.103454143158464	-1.22703364254446	0.220590124312341	   
df.mm.trans1:probe3	-0.0318635346667086	0.103454143158464	-0.307996699734897	0.75825815468788	   
df.mm.trans1:probe4	-0.109522490345179	0.103454143158464	-1.05865736259030	0.290446491976744	   
df.mm.trans1:probe5	-0.130170684481189	0.103454143158464	-1.25824525250576	0.209096490746572	   
df.mm.trans1:probe6	-0.0207996240201532	0.103454143158464	-0.20105162910966	0.840768679592281	   
df.mm.trans1:probe7	-0.00705055590888172	0.103454143158464	-0.0681515084232261	0.945701841588632	   
df.mm.trans1:probe8	-0.0850265316071837	0.103454143158464	-0.821876524335479	0.411676464114678	   
df.mm.trans2:probe2	0.145245906089209	0.103454143158464	1.40396412995012	0.161168315193292	   
df.mm.trans2:probe3	0.249726696670574	0.103454143158464	2.41388782552729	0.0162681948773107	*  
df.mm.trans2:probe4	0.084481354915296	0.103454143158464	0.816606781865593	0.41467862850525	   
df.mm.trans2:probe5	0.15946674877509	0.103454143158464	1.54142447954771	0.1240682937292	   
df.mm.trans2:probe6	0.111935333178231	0.103454143158464	1.0819801871712	0.279965986112119	   
df.mm.trans3:probe2	-0.0173374556186372	0.103454143158464	-0.167585899310778	0.867000622984676	   
df.mm.trans3:probe3	0.0457301831720424	0.103454143158464	0.44203336643556	0.65872331207027