chr7.21496_chr7_34668826_34669588_-_1.R 

fitVsDatCorrelation=0.917372557320076
cont.fitVsDatCorrelation=0.304231264732822

fstatistic=6332.85523248496,39,393
cont.fstatistic=1097.31504308968,39,393

residuals=-0.54188446302425,-0.106447318777788,-0.00570563187241805,0.0932257801783764,0.75591764134599
cont.residuals=-0.856715791861637,-0.329617702206414,-0.0684768007980017,0.309470415948156,1.17639785581225

predictedValues:
Include	Exclude	Both
chr7.21496_chr7_34668826_34669588_-_1.R.tl.Lung	160.667640289950	57.1204086263029	82.1331931369022
chr7.21496_chr7_34668826_34669588_-_1.R.tl.cerebhem	91.1719653909308	51.3332620010383	60.9592849822042
chr7.21496_chr7_34668826_34669588_-_1.R.tl.cortex	122.221074540264	49.7945192671295	63.4323940117479
chr7.21496_chr7_34668826_34669588_-_1.R.tl.heart	128.246206401563	62.4189596703833	94.220241935668
chr7.21496_chr7_34668826_34669588_-_1.R.tl.kidney	167.946734504596	81.3954223348435	106.707464908307
chr7.21496_chr7_34668826_34669588_-_1.R.tl.liver	149.328380543519	59.5324591165396	89.2499437369097
chr7.21496_chr7_34668826_34669588_-_1.R.tl.stomach	120.778159379817	46.2728444235956	62.4323901536984
chr7.21496_chr7_34668826_34669588_-_1.R.tl.testicle	107.008156005730	49.909892273492	62.441083506347


diffExp=103.547231663647,39.8387033898925,72.4265552731342,65.8272467311795,86.551312169752,89.795921426979,74.5053149562215,57.0982637322377
diffExpScore=0.99830677954276
diffExp1.5=1,1,1,1,1,1,1,1
diffExp1.5Score=0.888888888888889
diffExp1.4=1,1,1,1,1,1,1,1
diffExp1.4Score=0.888888888888889
diffExp1.3=1,1,1,1,1,1,1,1
diffExp1.3Score=0.888888888888889
diffExp1.2=1,1,1,1,1,1,1,1
diffExp1.2Score=0.888888888888889

cont.predictedValues:
Include	Exclude	Both
Lung	80.2510459156995	75.8872061756258	74.0012756980639
cerebhem	80.3390608074637	71.929438853091	67.8678696356034
cortex	92.1941307481355	76.5706269004453	97.3623949617954
heart	83.6619662543172	80.1663753434442	93.92292515741
kidney	91.82807991042	92.5865734303901	75.0099851064654
liver	95.382321257701	110.625724074071	86.0671186090508
stomach	75.5306852323242	85.7558341910812	90.4047335360043
testicle	72.0557094808499	85.959417814165	94.0909880039315
cont.diffExp=4.36383974007369,8.40962195437261,15.6235038476901,3.49559091087292,-0.758493519970045,-15.2434028163701,-10.225148958757,-13.9037083333151
cont.diffExpScore=7.79625166187046

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=0,0,1,0,0,0,0,0
cont.diffExp1.2Score=0.5

tran.correlation=0.722555856758766
cont.tran.correlation=0.47681328490926

tran.covariance=0.0260216863372345
cont.tran.covariance=0.00587974869800326

tran.mean=94.0716302981058
cont.tran.mean=84.4202622743266

weightedLogRatios:
wLogRatio
Lung	4.71817100974011
cerebhem	2.42718804559849
cortex	3.91214771731058
heart	3.2359877983291
kidney	3.44887465282636
liver	4.18092800098715
stomach	4.13909744048501
testicle	3.27311363674312

cont.weightedLogRatios:
wLogRatio
Lung	0.243618621526769
cerebhem	0.478876808154282
cortex	0.822771269206122
heart	0.188025692854871
kidney	-0.0372146961946114
liver	-0.686740939005047
stomach	-0.557125685523838
testicle	-0.770257983576918

varWeightedLogRatios=0.51109802611662
cont.varWeightedLogRatios=0.337859923510933

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.24704163258953	0.0969509854831935	43.8060697518723	2.63190414285458e-153	***
df.mm.trans1	0.804763121763607	0.0791601481646011	10.1662659863929	1.03847383923695e-21	***
df.mm.trans2	-0.262465447119368	0.0791601481646011	-3.31562602148764	0.000999403005363757	***
df.mm.exp2	-0.375276926100719	0.107557461343514	-3.48908315065350	0.000539551424824073	***
df.mm.exp3	-0.152395384168651	0.107557461343514	-1.41687412723452	0.157311939218987	   
df.mm.exp4	-0.273971188082443	0.107557461343514	-2.54720764752379	0.0112390751837613	*  
df.mm.exp5	0.136717668816622	0.107557461343514	1.27111282758876	0.204440341672824	   
df.mm.exp6	-0.114928438928202	0.107557461343514	-1.06853060208578	0.285937118884048	   
df.mm.exp7	-0.221730589899373	0.107557461343514	-2.06150821272377	0.0399117429334574	*  
df.mm.exp8	-0.267256288318330	0.107557461343514	-2.48477683444736	0.0133786329515999	*  
df.mm.trans1:exp2	-0.191313506364501	0.0878202994402449	-2.17846565752916	0.029965058116803	*  
df.mm.trans2:exp2	0.268454378427540	0.087820299440245	3.05686020360478	0.00238952595230179	** 
df.mm.trans1:exp3	-0.121111009810395	0.087820299440245	-1.37907762308192	0.168655147709916	   
df.mm.trans2:exp3	0.0151388354382881	0.087820299440245	0.172384238436683	0.863224200331077	   
df.mm.trans1:exp4	0.0485852067208373	0.087820299440245	0.55323435504676	0.580417517351206	   
df.mm.trans2:exp4	0.362678786351492	0.087820299440245	4.12978307593072	4.43792346657535e-05	***
df.mm.trans1:exp5	-0.0924086814667583	0.0878202994402449	-1.05224739673810	0.293332606196289	   
df.mm.trans2:exp5	0.217439894110277	0.087820299440245	2.47596393426361	0.0137081093318988	*  
df.mm.trans1:exp6	0.0417383308617634	0.0878202994402449	0.475269739773128	0.634858758073005	   
df.mm.trans2:exp6	0.156288662274486	0.0878202994402449	1.77964164630102	0.075907290864463	.  
df.mm.trans1:exp7	-0.0636518260422107	0.087820299440245	-0.724796276577501	0.469008318871554	   
df.mm.trans2:exp7	0.0111243935683957	0.0878202994402449	0.126672234543734	0.899264604920425	   
df.mm.trans1:exp8	-0.139176541032164	0.087820299440245	-1.58478782148612	0.113818854795183	   
df.mm.trans2:exp8	0.13231404155464	0.0878202994402449	1.50664530180371	0.132704953546188	   
df.mm.trans1:probe2	-0.0841044122363546	0.0537787306717568	-1.56389731006656	0.118646531020516	   
df.mm.trans1:probe3	0.0313326163129886	0.0537787306717568	0.582620971555278	0.56048260540919	   
df.mm.trans1:probe4	0.254059783207105	0.0537787306717568	4.72416845904716	3.22196951480728e-06	***
df.mm.trans1:probe5	0.0716963526116112	0.0537787306717568	1.33317301684222	0.183247309487563	   
df.mm.trans1:probe6	0.0574132309880024	0.0537787306717568	1.06758248606552	0.286364234176405	   
df.mm.trans2:probe2	0.118754767998955	0.0537787306717568	2.20821069064991	0.0278063142257974	*  
df.mm.trans2:probe3	0.0091335817966282	0.0537787306717568	0.169836321581776	0.86522625160247	   
df.mm.trans2:probe4	0.297826639972015	0.0537787306717568	5.5380005487639	5.60826721964748e-08	***
df.mm.trans2:probe5	0.170096622692235	0.0537787306717568	3.16289768403859	0.00168344507012308	** 
df.mm.trans2:probe6	0.131211823829016	0.0537787306717568	2.43984605419342	0.0151347668947789	*  
df.mm.trans3:probe2	-0.39425409205656	0.0537787306717568	-7.33104123380904	1.31279227689342e-12	***
df.mm.trans3:probe3	-0.46477933479803	0.0537787306717568	-8.64243780008218	1.40689889851287e-16	***
df.mm.trans3:probe4	-0.618094996499934	0.0537787306717568	-11.4932983500955	1.48653424414781e-26	***
df.mm.trans3:probe5	-0.248042415714730	0.0537787306717568	-4.61227724448683	5.39665976189413e-06	***
df.mm.trans3:probe6	-0.560811588017002	0.0537787306717568	-10.4281298761022	1.21809295494649e-22	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.45245539989685	0.232031301881326	19.1890290826971	2.20048145821774e-58	***
df.mm.trans1	-0.062671151676746	0.189452764654312	-0.330800934951252	0.740971149883326	   
df.mm.trans2	-0.142916385335378	0.189452764654312	-0.75436421102723	0.451082324556747	   
df.mm.exp2	0.0340532683385145	0.257415617367934	0.132289053347687	0.894823368078957	   
df.mm.exp3	-0.126655605856772	0.257415617367934	-0.492027667753113	0.622974504955698	   
df.mm.exp4	-0.141911436768933	0.257415617367934	-0.551293034276522	0.581746102559642	   
df.mm.exp5	0.320115457059437	0.257415617367934	1.24357434227420	0.214397556437362	   
df.mm.exp6	0.398592885791162	0.257415617367934	1.54844096044661	0.122321038589549	   
df.mm.exp7	-0.138579078133249	0.257415617367934	-0.538347593476322	0.590641866534386	   
df.mm.exp8	-0.223272981501903	0.257415617367934	-0.867363774524875	0.386272008693637	   
df.mm.trans1:exp2	-0.0329571248415983	0.210178971458318	-0.156805053392957	0.875479012471296	   
df.mm.trans2:exp2	-0.0876157543888641	0.210178971458318	-0.416862608951532	0.67700650346681	   
df.mm.trans1:exp3	0.265392281421108	0.210178971458318	1.26269664172250	0.207446923138382	   
df.mm.trans2:exp3	0.135621039626192	0.210178971458318	0.645264550897697	0.519132282773978	   
df.mm.trans1:exp4	0.183536110284520	0.210178971458318	0.87323726541748	0.383067010289678	   
df.mm.trans2:exp4	0.196767495062999	0.210178971458318	0.93619020826744	0.349750182118113	   
df.mm.trans1:exp5	-0.185357119970671	0.210178971458318	-0.881901356185058	0.378369217417979	   
df.mm.trans2:exp5	-0.121219429879830	0.210178971458318	-0.57674385329205	0.564442695255701	   
df.mm.trans1:exp6	-0.225859431416041	0.210178971458318	-1.07460527496602	0.283210805413975	   
df.mm.trans2:exp6	-0.0216883457896773	0.210178971458318	-0.103189894018387	0.917864895284842	   
df.mm.trans1:exp7	0.077958283594748	0.210178971458318	0.370913812422992	0.710901580694668	   
df.mm.trans2:exp7	0.260835090471121	0.210178971458318	1.24101421118073	0.215340767803600	   
df.mm.trans1:exp8	0.115552748980272	0.210178971458318	0.549782636095868	0.582780762436208	   
df.mm.trans2:exp8	0.347900171892901	0.210178971458318	1.65525680080652	0.0986707056961611	.  
df.mm.trans1:probe2	0.101422688339745	0.128707808683967	0.788007265268429	0.431167485184752	   
df.mm.trans1:probe3	-0.0603260853814986	0.128707808683967	-0.4687057141158	0.639539877185229	   
df.mm.trans1:probe4	-0.0154307044133374	0.128707808683967	-0.119889419073449	0.904632010343634	   
df.mm.trans1:probe5	-0.0703418365745933	0.128707808683967	-0.546523457231042	0.58501631152727	   
df.mm.trans1:probe6	-0.0108174988999138	0.128707808683967	-0.0840469510787447	0.933061897265238	   
df.mm.trans2:probe2	0.00105007194092385	0.128707808683967	0.00815857213063292	0.993494613256673	   
df.mm.trans2:probe3	0.0278592758072216	0.128707808683967	0.216453656480377	0.828746456170826	   
df.mm.trans2:probe4	0.148301523274985	0.128707808683967	1.15223407803585	0.249925311229844	   
df.mm.trans2:probe5	-0.0178123960260617	0.128707808683967	-0.138394058668179	0.889999875786204	   
df.mm.trans2:probe6	0.0771106535556374	0.128707808683967	0.59911402691174	0.549442044279264	   
df.mm.trans3:probe2	0.0647722600108731	0.128707808683967	0.503250429582845	0.615070146538127	   
df.mm.trans3:probe3	-0.0771863369426525	0.128707808683967	-0.599702051739363	0.549050412584775	   
df.mm.trans3:probe4	0.077861911292598	0.128707808683967	0.60495095121837	0.545560719027207	   
df.mm.trans3:probe5	0.200433041773298	0.128707808683967	1.55727180675919	0.120210861655356	   
df.mm.trans3:probe6	0.0774059398691731	0.128707808683967	0.601408264662775	0.547914837183358