chr3.15594_chr3_88948371_88950268_+_2.R 

fitVsDatCorrelation=0.869590387278777
cont.fitVsDatCorrelation=0.289902469211955

fstatistic=5109.24273034394,43,485
cont.fstatistic=1351.71954497051,43,485

residuals=-0.806698508483388,-0.104396588799672,0.00082661597587891,0.111433923612463,1.60998629502702
cont.residuals=-0.792722457539845,-0.278837087657158,-0.085909653413266,0.214361843484965,1.48594730113788

predictedValues:
Include	Exclude	Both
chr3.15594_chr3_88948371_88950268_+_2.R.tl.Lung	56.1104677756425	71.1554394469862	77.6447118506465
chr3.15594_chr3_88948371_88950268_+_2.R.tl.cerebhem	111.715377789077	52.6272691509434	103.956686139227
chr3.15594_chr3_88948371_88950268_+_2.R.tl.cortex	147.624332699424	52.3682308558732	111.743655340115
chr3.15594_chr3_88948371_88950268_+_2.R.tl.heart	108.441328238505	68.4507755701735	101.858774872730
chr3.15594_chr3_88948371_88950268_+_2.R.tl.kidney	54.3947647859355	55.0255502004879	65.3790505869454
chr3.15594_chr3_88948371_88950268_+_2.R.tl.liver	56.9856847112437	57.3033272080811	57.8405718312743
chr3.15594_chr3_88948371_88950268_+_2.R.tl.stomach	53.1252668978424	66.3588096278956	74.9057461651303
chr3.15594_chr3_88948371_88950268_+_2.R.tl.testicle	56.7549291447972	66.2730854540084	63.6453377190442


diffExp=-15.0449716713437,59.0881086381333,95.2561018435508,39.9905526683318,-0.630785414552392,-0.317642496837472,-13.2335427300533,-9.51815630921114
diffExpScore=1.48847538868256
diffExp1.5=0,1,1,1,0,0,0,0
diffExp1.5Score=0.75
diffExp1.4=0,1,1,1,0,0,0,0
diffExp1.4Score=0.75
diffExp1.3=0,1,1,1,0,0,0,0
diffExp1.3Score=0.75
diffExp1.2=-1,1,1,1,0,0,-1,0
diffExp1.2Score=2.5

cont.predictedValues:
Include	Exclude	Both
Lung	69.1037342936263	71.7331967803047	68.2681636271347
cerebhem	76.0566496100843	86.3547657009307	82.300660539789
cortex	69.6890726160364	83.0038813627803	64.1033703957564
heart	72.6010990719822	76.6269924184283	64.779062012169
kidney	74.4459731145434	81.239127655675	64.3260564011533
liver	72.0027317172702	67.1583470434469	74.1984060843518
stomach	65.6554329263599	71.1992771295797	57.950882317954
testicle	76.1282601506426	77.8797007685123	73.2375881409775
cont.diffExp=-2.62946248667839,-10.2981160908463,-13.3148087467438,-4.02589334644618,-6.79315454113167,4.84438467382333,-5.54384420321982,-1.75144061786966
cont.diffExpScore=1.21447219150975

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=-0.463869367857965
cont.tran.correlation=0.535036640966362

tran.covariance=-0.0237780296172016
cont.tran.covariance=0.00232658073989917

tran.mean=70.9196649723073
cont.tran.mean=74.4298901475127

weightedLogRatios:
wLogRatio
Lung	-0.984881489217677
cerebhem	3.26649930042349
cortex	4.63929802766886
heart	2.05025517742497
kidney	-0.046142288392753
liver	-0.0224877479592537
stomach	-0.908348990455137
testicle	-0.638191018252345

cont.weightedLogRatios:
wLogRatio
Lung	-0.158875556403759
cerebhem	-0.558097799986733
cortex	-0.757330060709801
heart	-0.232713871808018
kidney	-0.380182665453123
liver	0.295450406691978
stomach	-0.342484339321397
testicle	-0.0988029772461627

varWeightedLogRatios=4.54825977103934
cont.varWeightedLogRatios=0.099999973149665

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.66704764630405	0.109239838844741	33.5687756873746	1.41746189092628e-128	***
df.mm.trans1	0.446545428442537	0.0950079079744168	4.70008695026503	3.39316274250233e-06	***
df.mm.trans2	0.511644136787652	0.0891939549178265	5.73630956558687	1.70503336893627e-08	***
df.mm.exp2	0.0951687308038521	0.12119072008558	0.785280677733804	0.432672455939518	   
df.mm.exp3	0.296717710336582	0.12119072008558	2.44835338982268	0.0147042705123130	*  
df.mm.exp4	0.348691147851906	0.12119072008558	2.87720996793875	0.00418895917873821	** 
df.mm.exp5	-0.116182053205063	0.12119072008558	-0.958671201252204	0.338202058497225	   
df.mm.exp6	0.0934226015191258	0.12119072008558	0.770872567248998	0.441157834254102	   
df.mm.exp7	-0.088547140765585	0.12119072008558	-0.730642913112956	0.465350091074293	   
df.mm.exp8	0.139154586401002	0.12119072008558	1.14822806814529	0.251440439412349	   
df.mm.trans1:exp2	0.593463249755088	0.110631485251944	5.36432506897631	1.26045820223470e-07	***
df.mm.trans2:exp2	-0.396801092501184	0.0989518085900452	-4.01004386029082	7.02773367942755e-05	***
df.mm.trans1:exp3	0.670630657440916	0.110631485251944	6.06184266543714	2.70676437845319e-09	***
df.mm.trans2:exp3	-0.603284356277024	0.0989518085900452	-6.0967491637916	2.21114821028810e-09	***
df.mm.trans1:exp4	0.310195738817685	0.110631485251944	2.80386490438293	0.00525188503094474	** 
df.mm.trans2:exp4	-0.387443037747012	0.0989518085900452	-3.91547201883068	0.000103153601956513	***
df.mm.trans1:exp5	0.085127580394542	0.110631485251944	0.76946974182511	0.44198907966249	   
df.mm.trans2:exp5	-0.140887092360314	0.0989518085900452	-1.42379502070554	0.155148827826222	   
df.mm.trans1:exp6	-0.0779448971324671	0.110631485251944	-0.704545337658271	0.481431393083146	   
df.mm.trans2:exp6	-0.309930685053664	0.0989518085900452	-3.13213764831423	0.00184028003119273	** 
df.mm.trans1:exp7	0.0338774054681073	0.110631485251944	0.306218481935384	0.75956970672957	   
df.mm.trans2:exp7	0.0187568958020292	0.0989518085900452	0.189555866328209	0.849736476544454	   
df.mm.trans1:exp8	-0.127734463123135	0.110631485251944	-1.15459412690919	0.248825240938541	   
df.mm.trans2:exp8	-0.2102374945776	0.0989518085900452	-2.12464529525285	0.034121343548921	*  
df.mm.trans1:probe2	-0.0394605528412141	0.06059536004279	-0.65121409978171	0.515216713233334	   
df.mm.trans1:probe3	-0.194379477086286	0.06059536004279	-3.2078277437253	0.00142586204813077	** 
df.mm.trans1:probe4	-0.173107595956013	0.06059536004279	-2.85677972428534	0.00446341548349551	** 
df.mm.trans1:probe5	0.0026290340802484	0.06059536004279	0.0433867226532177	0.965411117795589	   
df.mm.trans1:probe6	0.00359021327518838	0.06059536004279	0.059248979998685	0.952778202035591	   
df.mm.trans1:probe7	-0.336130105140275	0.06059536004279	-5.54712613148785	4.78170518385814e-08	***
df.mm.trans1:probe8	-0.361798346462259	0.06059536004279	-5.9707269039539	4.56864423638175e-09	***
df.mm.trans1:probe9	-0.255287519462652	0.06059536004279	-4.21298791330522	3.00557603944893e-05	***
df.mm.trans1:probe10	0.0609430629710359	0.06059536004279	1.00573811143296	0.315043068486387	   
df.mm.trans1:probe11	0.0391793122264576	0.06059536004279	0.646572810175412	0.518214310349257	   
df.mm.trans1:probe12	-0.126509037728421	0.06059536004279	-2.08776773731660	0.0373400060041323	*  
df.mm.trans2:probe2	-0.0491159102782724	0.06059536004279	-0.810555630721373	0.418018451615675	   
df.mm.trans2:probe3	0.187514378604118	0.06059536004279	3.09453361563827	0.00208510038223499	** 
df.mm.trans2:probe4	0.283260655615715	0.06059536004279	4.67462616635478	3.82180466916825e-06	***
df.mm.trans2:probe5	0.0431406267937521	0.06059536004279	0.711946042787565	0.476840502160251	   
df.mm.trans2:probe6	0.396950138628678	0.06059536004279	6.55083389798108	1.46282243967892e-10	***
df.mm.trans3:probe2	-0.272492102534509	0.06059536004279	-4.49691366372088	8.63584133999954e-06	***
df.mm.trans3:probe3	-0.31906544875617	0.06059536004279	-5.26550957913046	2.10477041719510e-07	***
df.mm.trans3:probe4	-0.500817515240417	0.06059536004279	-8.26494825489542	1.34771473821502e-15	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.48529402865927	0.211733927432541	21.1836340214692	5.35623869552986e-71	***
df.mm.trans1	-0.138747595271273	0.184148912203757	-0.753453243958085	0.45154319497213	   
df.mm.trans2	-0.234868905282789	0.172880027815069	-1.35856586935554	0.174915726014735	   
df.mm.exp2	0.0944444373633714	0.234897702188738	0.402066246214218	0.687812399100156	   
df.mm.exp3	0.217315080578130	0.234897702188738	0.925147749651119	0.355349140758959	   
df.mm.exp4	0.167828147718536	0.234897702188738	0.714473347992512	0.475278260468255	   
df.mm.exp5	0.258387012298178	0.234897702188738	1.09999804123485	0.271878655593726	   
df.mm.exp6	-0.108104264895173	0.234897702188738	-0.460218486123429	0.645565659800441	   
df.mm.exp7	0.105188348968017	0.234897702188738	0.447804929498624	0.654493936169586	   
df.mm.exp8	0.108757226515030	0.234897702188738	0.462998256269209	0.643573291957477	   
df.mm.trans1:exp2	0.00142524367513154	0.214431283658171	0.0066466219425499	0.994699534999407	   
df.mm.trans2:exp2	0.091065920223497	0.191793170704884	0.474813153611304	0.635133886364173	   
df.mm.trans1:exp3	-0.208880323680135	0.214431283658171	-0.974113105684313	0.330485969051586	   
df.mm.trans2:exp3	-0.0713813464653345	0.191793170704884	-0.372178770510919	0.709922315667616	   
df.mm.trans1:exp4	-0.118456858459177	0.214431283658171	-0.552423398481404	0.58091278986683	   
df.mm.trans2:exp4	-0.101832387599546	0.191793170704884	-0.530948976052114	0.595697184142521	   
df.mm.trans1:exp5	-0.183922114275088	0.214431283658171	-0.857720530033677	0.391470447311005	   
df.mm.trans2:exp5	-0.133943649508187	0.191793170704884	-0.698375489679395	0.485277113428096	   
df.mm.trans1:exp6	0.149199552519809	0.214431283658171	0.695791910464196	0.486892423377984	   
df.mm.trans2:exp6	0.0422038485863224	0.191793170704884	0.220048755809258	0.825925773140495	   
df.mm.trans1:exp7	-0.156376766909404	0.214431283658171	-0.72926284001866	0.466192922120574	   
df.mm.trans2:exp7	-0.112659319273487	0.191793170704884	-0.58740005631816	0.557208414078868	   
df.mm.trans1:exp8	-0.0119464463103059	0.214431283658171	-0.0557122361369152	0.955593994518546	   
df.mm.trans2:exp8	-0.0265455242280522	0.191793170704884	-0.138407035717128	0.889976183375802	   
df.mm.trans1:probe2	-0.223665070857701	0.117448851094369	-1.9043615052308	0.0574545214583695	.  
df.mm.trans1:probe3	-0.0717841653757047	0.117448851094369	-0.611195126276943	0.541356757117172	   
df.mm.trans1:probe4	-0.158645070287372	0.117448851094369	-1.35075880955108	0.177402563809781	   
df.mm.trans1:probe5	-0.227267899052052	0.117448851094369	-1.93503722628538	0.0535667863233924	.  
df.mm.trans1:probe6	-0.293422822000371	0.117448851094369	-2.49830304227164	0.0128088954858931	*  
df.mm.trans1:probe7	-0.191104364851324	0.117448851094369	-1.6271284314035	0.104359286648160	   
df.mm.trans1:probe8	-0.229843878445163	0.117448851094369	-1.95697000271620	0.0509242722419296	.  
df.mm.trans1:probe9	-0.184412296250313	0.117448851094369	-1.57014985274006	0.117032393233200	   
df.mm.trans1:probe10	-0.0116154610517594	0.117448851094369	-0.0988980389635868	0.921260087639568	   
df.mm.trans1:probe11	-0.00823294103211832	0.117448851094369	-0.0700980976434007	0.944144473913665	   
df.mm.trans1:probe12	-0.175008625974584	0.117448851094369	-1.49008376279446	0.136852232134338	   
df.mm.trans2:probe2	0.0378063807635711	0.117448851094369	0.321896556767457	0.747669753749236	   
df.mm.trans2:probe3	0.0291010027042223	0.117448851094369	0.247775967436581	0.804412614063055	   
df.mm.trans2:probe4	0.082239410921274	0.117448851094369	0.700214690522561	0.484128980879122	   
df.mm.trans2:probe5	0.0865174948353967	0.117448851094369	0.73663977151961	0.461697604950119	   
df.mm.trans2:probe6	-0.0103791630150345	0.117448851094369	-0.0883717713568347	0.92961767390975	   
df.mm.trans3:probe2	0.169146185565501	0.117448851094369	1.44016892450990	0.150464795200422	   
df.mm.trans3:probe3	0.135648286244767	0.117448851094369	1.15495626377626	0.248677049548416	   
df.mm.trans3:probe4	0.142269545323639	0.117448851094369	1.21133194576188	0.226358086770362