chr19.12058_chr19_6876857_6880454_-_2.R 

fitVsDatCorrelation=0.85360950446703
cont.fitVsDatCorrelation=0.243350166535514

fstatistic=10413.5209998770,52,692
cont.fstatistic=2994.11844061962,52,692

residuals=-0.489263839285236,-0.0912983848998581,-0.00482698680689787,0.0869381942158598,0.714409925976651
cont.residuals=-0.633848490934473,-0.214478338277073,-0.0282990632117474,0.179592328452845,0.950099274037394

predictedValues:
Include	Exclude	Both
chr19.12058_chr19_6876857_6880454_-_2.R.tl.Lung	105.894496621818	61.4889151304732	97.0269519501321
chr19.12058_chr19_6876857_6880454_-_2.R.tl.cerebhem	71.2341774646427	61.9453280792022	75.322566978517
chr19.12058_chr19_6876857_6880454_-_2.R.tl.cortex	72.3568766459272	59.4586108044825	68.596944750248
chr19.12058_chr19_6876857_6880454_-_2.R.tl.heart	90.1652542968409	60.4828853669405	81.0015312192027
chr19.12058_chr19_6876857_6880454_-_2.R.tl.kidney	79.8929774378438	65.1010444955002	74.6225038191428
chr19.12058_chr19_6876857_6880454_-_2.R.tl.liver	87.0472587255209	61.4298026331716	74.9666204434035
chr19.12058_chr19_6876857_6880454_-_2.R.tl.stomach	77.6465688840698	63.7258033882218	78.4108422600459
chr19.12058_chr19_6876857_6880454_-_2.R.tl.testicle	82.060545586438	63.650307478726	74.2499720038972


diffExp=44.4055814913446,9.28884938544055,12.8982658414447,29.6823689299004,14.7919329423436,25.6174560923493,13.920765495848,18.4102381077121
diffExpScore=0.994118181898992
diffExp1.5=1,0,0,0,0,0,0,0
diffExp1.5Score=0.5
diffExp1.4=1,0,0,1,0,1,0,0
diffExp1.4Score=0.75
diffExp1.3=1,0,0,1,0,1,0,0
diffExp1.3Score=0.75
diffExp1.2=1,0,1,1,1,1,1,1
diffExp1.2Score=0.875

cont.predictedValues:
Include	Exclude	Both
Lung	80.6057618024783	91.4701616035018	69.2723353442378
cerebhem	79.4825924411201	79.990714397756	79.5717228838108
cortex	77.4605001942814	82.597728408438	85.3331255758573
heart	75.3751661488139	89.2761002880055	72.8139917830213
kidney	77.2685105259448	87.8232682120477	86.8960848643993
liver	74.9292731285467	73.4185068192242	79.8822396388354
stomach	75.2862145743715	79.2040960984052	73.1725963244555
testicle	83.574418919023	76.6058221970666	72.3319996688673
cont.diffExp=-10.8643998010235,-0.508121956635847,-5.13722821415664,-13.9009341391916,-10.5547576861029,1.51076630932255,-3.9178815240337,6.96859672195647
cont.diffExpScore=1.42665872647935

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=-0.122402128827833
cont.tran.correlation=0.0138807847385333

tran.covariance=-0.000364312488953555
cont.tran.covariance=7.29294146630289e-05

tran.mean=72.7238033149887
cont.tran.mean=80.273052234939

weightedLogRatios:
wLogRatio
Lung	2.38669753576967
cerebhem	0.586283068914291
cortex	0.821336024616818
heart	1.71771942261299
kidney	0.875973567894013
liver	1.49606301218646
stomach	0.840373177235517
testicle	1.08745704209277

cont.weightedLogRatios:
wLogRatio
Lung	-0.56302290120651
cerebhem	-0.0279035222940407
cortex	-0.281377939456035
heart	-0.745928924126484
kidney	-0.564823567728241
liver	0.0877145455364636
stomach	-0.220510411782738
testicle	0.381534063878961

varWeightedLogRatios=0.360764324617343
cont.varWeightedLogRatios=0.143795843260897

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.27342592814728	0.0862475324845238	49.5483848064187	8.66732402227637e-230	***
df.mm.trans1	0.394450555464621	0.0774628969257733	5.0921224369209	4.56976376312596e-07	***
df.mm.trans2	-0.206325221052525	0.0712376541493858	-2.89629443187251	0.00389512745788469	** 
df.mm.exp2	-0.135866274798563	0.097577944128662	-1.39238714252286	0.164252445788501	   
df.mm.exp3	-0.067668452596741	0.097577944128662	-0.693481023821493	0.488240427675697	   
df.mm.exp4	0.00322512030051123	0.097577944128662	0.0330517344806807	0.973642862742361	   
df.mm.exp5	0.0378750237976147	0.097577944128662	0.388151483778694	0.698023310568865	   
df.mm.exp6	0.0609919182086879	0.097577944128662	0.625058446899297	0.532138751589366	   
df.mm.exp7	-0.0615166982451016	0.097577944128662	-0.630436506880985	0.528617162473737	   
df.mm.exp8	0.0471126854644846	0.097577944128662	0.482821050240245	0.629375506079175	   
df.mm.trans1:exp2	-0.260604284954479	0.0934237688279144	-2.78948589019684	0.00542438692749346	** 
df.mm.trans2:exp2	0.143261548864557	0.0813149534405517	1.761810624036	0.0785428100025042	.  
df.mm.trans1:exp3	-0.31316433547373	0.0934237688279145	-3.35208415805377	0.000845689654593326	***
df.mm.trans2:exp3	0.034091989577315	0.0813149534405518	0.419258551285271	0.675157298055113	   
df.mm.trans1:exp4	-0.164024258364218	0.0934237688279145	-1.75570157811069	0.0795817761233164	.  
df.mm.trans2:exp4	-0.0197215985665474	0.0813149534405518	-0.242533479170785	0.808438682811387	   
df.mm.trans1:exp5	-0.319630350348699	0.0934237688279145	-3.42129582609169	0.000659873819600663	***
df.mm.trans2:exp5	0.0192086529798801	0.0813149534405517	0.236225345611533	0.813327714111702	   
df.mm.trans1:exp6	-0.256984026863009	0.0934237688279145	-2.75073495842766	0.00610161945866765	** 
df.mm.trans2:exp6	-0.0619537326977119	0.0813149534405518	-0.761898397236437	0.446380234221159	   
df.mm.trans1:exp7	-0.248759223645755	0.0934237688279145	-2.66269737098667	0.0079318704565578	** 
df.mm.trans2:exp7	0.0972493387539161	0.0813149534405517	1.19595885675583	0.232122247988474	   
df.mm.trans1:exp8	-0.302098633413027	0.0934237688279145	-3.23363783331723	0.00128030057974885	** 
df.mm.trans2:exp8	-0.0125654464853996	0.0813149534405517	-0.154528115109677	0.877238402075736	   
df.mm.trans1:probe2	-0.0629682014870135	0.0467118844139573	-1.34801244430633	0.178095472755031	   
df.mm.trans1:probe3	-0.451045416265603	0.0467118844139572	-9.65590281626132	8.8401877521082e-21	***
df.mm.trans1:probe4	-0.187345298570168	0.0467118844139572	-4.01065598017687	6.71397395408262e-05	***
df.mm.trans1:probe5	0.0306523627873324	0.0467118844139572	0.656200518816441	0.511913243129263	   
df.mm.trans1:probe6	0.476560794737217	0.0467118844139572	10.2021316569884	7.31947570048037e-23	***
df.mm.trans1:probe7	-0.0117757692442931	0.0467118844139572	-0.252093645804076	0.801043534774152	   
df.mm.trans1:probe8	0.0384925552244354	0.0467118844139572	0.824042012163698	0.410199608057976	   
df.mm.trans1:probe9	-0.268835988795416	0.0467118844139572	-5.75519468264246	1.30041294289819e-08	***
df.mm.trans1:probe10	0.160128137541862	0.0467118844139573	3.42799567071236	0.000644068559142996	***
df.mm.trans1:probe11	-0.09389939808095	0.0467118844139572	-2.01018218937220	0.0447994955385158	*  
df.mm.trans1:probe12	-0.134891182119607	0.0467118844139572	-2.88772726281412	0.00400148023374578	** 
df.mm.trans1:probe13	-0.24816552112266	0.0467118844139573	-5.31268486031169	1.45801507042344e-07	***
df.mm.trans1:probe14	-0.196847711198479	0.0467118844139572	-4.21408199793504	2.84030767089701e-05	***
df.mm.trans1:probe15	-0.0712920523990841	0.0467118844139572	-1.52620801523011	0.127414969753245	   
df.mm.trans1:probe16	-0.207156765202274	0.0467118844139572	-4.43477645574017	1.07180711559027e-05	***
df.mm.trans1:probe17	0.552923473052249	0.0467118844139573	11.8368907610809	1.44331054990871e-29	***
df.mm.trans1:probe18	0.0793014010708384	0.0467118844139573	1.69767077620066	0.090019520124756	.  
df.mm.trans1:probe19	0.0603637999239145	0.0467118844139573	1.29225786288078	0.196699216070962	   
df.mm.trans1:probe20	0.158603390655422	0.0467118844139573	3.39535415120252	0.000724543529883791	***
df.mm.trans1:probe21	0.166945774766637	0.0467118844139572	3.57394647767100	0.000376065780002223	***
df.mm.trans1:probe22	0.0744216136474081	0.0467118844139573	1.59320512501464	0.111570815906504	   
df.mm.trans2:probe2	0.0336733109559189	0.0467118844139573	0.72087245844138	0.471231441919626	   
df.mm.trans2:probe3	0.0512521205784056	0.0467118844139573	1.09719659614271	0.272937108480992	   
df.mm.trans2:probe4	-0.0191126018512360	0.0467118844139572	-0.409159298346039	0.682549365614574	   
df.mm.trans2:probe5	0.435587154598645	0.0467118844139573	9.32497500504378	1.46687029463636e-19	***
df.mm.trans2:probe6	-0.0355940970601165	0.0467118844139573	-0.761992317515694	0.446324213830934	   
df.mm.trans3:probe2	-0.00545854360367052	0.0467118844139573	-0.116855564106498	0.90700841694757	   
df.mm.trans3:probe3	0.345771141119902	0.0467118844139573	7.40220921202202	3.89835776351446e-13	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.75106852676891	0.16059252015203	29.5846190237948	5.84298260492396e-125	***
df.mm.trans1	-0.365233369028556	0.144235567989369	-2.53220044209535	0.0115549548247841	*  
df.mm.trans2	-0.152087931120544	0.13264419375269	-1.14658566513741	0.251949204663384	   
df.mm.exp2	-0.286747521628877	0.181689696011740	-1.57822665744538	0.114970535307667	   
df.mm.exp3	-0.350349735225095	0.181689696011740	-1.92828620948574	0.0542283366575301	.  
df.mm.exp4	-0.141233778740348	0.181689696011740	-0.777335103974318	0.437226741828423	   
df.mm.exp5	-0.309637317676999	0.181689696011740	-1.70420956429467	0.0887908487497154	.  
df.mm.exp6	-0.435370186332593	0.181689696011740	-2.39622937287792	0.0168292194971249	*  
df.mm.exp7	-0.267033247793749	0.181689696011740	-1.46972147378404	0.142091686885008	   
df.mm.exp8	-0.184393390451856	0.181689696011740	-1.01488083528931	0.310517337811104	   
df.mm.trans1:exp2	0.272715422967828	0.173954640161649	1.56773870886344	0.117399258265864	   
df.mm.trans2:exp2	0.1526452631336	0.151408080009784	1.00817118296287	0.313724675532468	   
df.mm.trans1:exp3	0.310547733402832	0.173954640161649	1.78522247589517	0.0746631249653663	.  
df.mm.trans2:exp3	0.248319097860906	0.151408080009784	1.64006503381365	0.101446101644758	   
df.mm.trans1:exp4	0.0741415047406487	0.173954640161649	0.426211710545646	0.670086126932911	   
df.mm.trans2:exp4	0.116954780445078	0.151408080009784	0.772447417849304	0.440113211723819	   
df.mm.trans1:exp5	0.267353689869109	0.173954640161649	1.53691611572229	0.124770939247281	   
df.mm.trans2:exp5	0.268950980608297	0.151408080009784	1.7763317558146	0.076117556174342	.  
df.mm.trans1:exp6	0.362344696647763	0.173954640161649	2.08298379572428	0.0376192848275465	*  
df.mm.trans2:exp6	0.215533410269229	0.151408080009784	1.42352647398542	0.155034296130489	   
df.mm.trans1:exp7	0.198760159117441	0.173954640161649	1.14259762736275	0.253600855788178	   
df.mm.trans2:exp7	0.123048447286525	0.151408080009784	0.812694060175479	0.41667298587058	   
df.mm.trans1:exp8	0.22056073658461	0.173954640161649	1.26792097284471	0.20525260860385	   
df.mm.trans2:exp8	0.00705365570009873	0.151408080009784	0.0465870493810036	0.96285579489414	   
df.mm.trans1:probe2	0.0670101980705915	0.0869773200808245	0.77043300492958	0.441306023274446	   
df.mm.trans1:probe3	0.0626788105007914	0.0869773200808245	0.720633958859005	0.471378113299928	   
df.mm.trans1:probe4	-0.00719821844463854	0.0869773200808245	-0.0827597175671719	0.934066532596597	   
df.mm.trans1:probe5	-0.056916168696269	0.0869773200808245	-0.654379424928006	0.513084805949182	   
df.mm.trans1:probe6	0.0269922005839245	0.0869773200808245	0.310336080243008	0.756398838350048	   
df.mm.trans1:probe7	0.0143463705315001	0.0869773200808245	0.164943809698535	0.869036379827845	   
df.mm.trans1:probe8	0.0750900569019293	0.0869773200808245	0.863329162500652	0.388255631752755	   
df.mm.trans1:probe9	-0.0234874184400626	0.0869773200808245	-0.270040723469482	0.787209434870509	   
df.mm.trans1:probe10	-0.0539867341586493	0.0869773200808245	-0.620698983464674	0.535002069433436	   
df.mm.trans1:probe11	0.0300093051162778	0.0869773200808245	0.345024485560045	0.730180804665387	   
df.mm.trans1:probe12	-0.0109503122493087	0.0869773200808245	-0.125898478351977	0.899848855333571	   
df.mm.trans1:probe13	0.0165638156885113	0.0869773200808245	0.190438331200814	0.849021515962126	   
df.mm.trans1:probe14	-0.00816160265967787	0.0869773200808245	-0.093835986807752	0.92526660632188	   
df.mm.trans1:probe15	-0.0130809970778799	0.0869773200808245	-0.150395494661416	0.880496421512278	   
df.mm.trans1:probe16	-0.0945660755895467	0.0869773200808245	-1.08724981985730	0.277304968773410	   
df.mm.trans1:probe17	0.0166976742184596	0.0869773200808245	0.191977336194575	0.847816277755177	   
df.mm.trans1:probe18	-0.0942002960129131	0.0869773200808245	-1.08304436059167	0.279165959851320	   
df.mm.trans1:probe19	0.00493574927627447	0.0869773200808245	0.0567475437468972	0.954762681533486	   
df.mm.trans1:probe20	0.0559101476781463	0.0869773200808245	0.64281294969989	0.520558403893474	   
df.mm.trans1:probe21	0.0723424343064152	0.0869773200808245	0.8317390584027	0.405843162428617	   
df.mm.trans1:probe22	0.0133454504638037	0.0869773200808245	0.153435981373102	0.878099203445961	   
df.mm.trans2:probe2	-0.0844448563010217	0.0869773200808245	-0.97088363061256	0.331945455522070	   
df.mm.trans2:probe3	-0.106017427085860	0.0869773200808245	-1.21890887173049	0.223294125912356	   
df.mm.trans2:probe4	-0.173983607585185	0.0869773200808245	-2.00033304571248	0.0458545968844801	*  
df.mm.trans2:probe5	-0.231967947955574	0.0869773200808245	-2.66699350750306	0.0078322255350188	** 
df.mm.trans2:probe6	-0.150296174267498	0.0869773200808245	-1.72799270117582	0.0844356535838226	.  
df.mm.trans3:probe2	0.0472505790805213	0.0869773200808245	0.543251723973713	0.587131442386734	   
df.mm.trans3:probe3	-0.0343553836041733	0.0869773200808245	-0.394992436789824	0.692970188959014