chr15.8680_chr15_9103154_9106427_+_2.R 

fitVsDatCorrelation=0.918343615329077
cont.fitVsDatCorrelation=0.260663288236046

fstatistic=12768.3132609807,59,853
cont.fstatistic=2133.86833091071,59,853

residuals=-0.677953204133903,-0.0866738071364648,0.00415650747417291,0.0907099043654798,0.704416616105492
cont.residuals=-0.693714304525421,-0.230839696598718,-0.0759704261797804,0.187100685059055,1.47652552194756

predictedValues:
Include	Exclude	Both
chr15.8680_chr15_9103154_9106427_+_2.R.tl.Lung	54.8049471844	55.7791679584917	67.0309109478517
chr15.8680_chr15_9103154_9106427_+_2.R.tl.cerebhem	63.5566012536539	54.654080518172	79.6647520850863
chr15.8680_chr15_9103154_9106427_+_2.R.tl.cortex	61.4024557340122	52.8344526789326	81.5802360481268
chr15.8680_chr15_9103154_9106427_+_2.R.tl.heart	67.1317450451578	53.5788806839677	94.6905233326048
chr15.8680_chr15_9103154_9106427_+_2.R.tl.kidney	67.783609880109	57.6496947188047	83.2551385712351
chr15.8680_chr15_9103154_9106427_+_2.R.tl.liver	80.6068804236385	61.465296807118	113.299733876249
chr15.8680_chr15_9103154_9106427_+_2.R.tl.stomach	53.5455503204526	56.6604828432029	71.026032018681
chr15.8680_chr15_9103154_9106427_+_2.R.tl.testicle	53.9104618493226	61.1180840984345	65.425662885728


diffExp=-0.974220774091648,8.90252073548189,8.56800305507958,13.5528643611901,10.1339151613043,19.1415836165206,-3.11493252275026,-7.2076222491119
diffExpScore=1.43185278570017
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=0,0,0,0,0,1,0,0
diffExp1.3Score=0.5
diffExp1.2=0,0,0,1,0,1,0,0
diffExp1.2Score=0.666666666666667

cont.predictedValues:
Include	Exclude	Both
Lung	63.5621323200708	78.7524348034221	65.9674409491297
cerebhem	65.229068774306	70.9956455456042	70.6909011604756
cortex	63.8485880341836	72.5344553201557	63.616925273776
heart	66.2396217663578	67.4990722806947	67.6149678661967
kidney	66.2601471776882	75.9718297127742	67.0584538860589
liver	67.5115343051485	63.6443074653383	62.7112935047285
stomach	65.5149966897097	69.7452578309981	70.737160311344
testicle	68.5738189865586	61.3234391253815	64.7479333279429
cont.diffExp=-15.1903024833514,-5.76657677129825,-8.6858672859721,-1.25945051433699,-9.71168253508606,3.86722683981023,-4.23026114128841,7.25037986117713
cont.diffExpScore=1.61149821008392

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

tran.correlation=0.232962558151654
cont.tran.correlation=-0.834318939320233

tran.covariance=0.00137172377984446
cont.tran.covariance=-0.00183261231260179

tran.mean=59.7801494998669
cont.tran.mean=67.9503968836495

weightedLogRatios:
wLogRatio
Lung	-0.0707018385456136
cerebhem	0.615168925943118
cortex	0.607503470094658
heart	0.923184234185203
kidney	0.669660290412507
liver	1.15331505595449
stomach	-0.226675131117424
testicle	-0.508215431546646

cont.weightedLogRatios:
wLogRatio
Lung	-0.912701718443315
cerebhem	-0.357512458805719
cortex	-0.538286039093941
heart	-0.0791580113490374
kidney	-0.582927417749324
liver	0.246737661167793
stomach	-0.263644218535958
testicle	0.466219557160281

varWeightedLogRatios=0.348892234316331
cont.varWeightedLogRatios=0.204816763491037

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.01881748584842	0.0681196021619412	44.3164286055542	1.71267481110733e-223	***
df.mm.trans1	0.935583017095634	0.0588264221655038	15.9041291762304	4.49805702636413e-50	***
df.mm.trans2	0.997743295063136	0.0519728780925369	19.1973839371887	1.51036254750678e-68	***
df.mm.exp2	-0.0448995472868657	0.0668537390427593	-0.671608618003372	0.502014731678393	   
df.mm.exp3	-0.137000768684380	0.0668537390427593	-2.04926112803885	0.0407420005729681	*  
df.mm.exp4	-0.182828980954312	0.0668537390427593	-2.73476074146541	0.00637204707677071	** 
df.mm.exp5	0.0287684611412652	0.0668537390427593	0.430319404018151	0.667072011556366	   
df.mm.exp6	-0.0420071344164874	0.0668537390427593	-0.628343829649078	0.529946923785074	   
df.mm.exp7	-0.0654638044843035	0.0668537390427593	-0.979209322046044	0.327754196213442	   
df.mm.exp8	0.0991907117798541	0.0668537390427593	1.48369729502208	0.138258635096209	   
df.mm.trans1:exp2	0.193049947520018	0.0617943012196193	3.12407363963727	0.00184394192165789	** 
df.mm.trans2:exp2	0.0245229599077193	0.0456381160268937	0.537335062062342	0.591176329566014	   
df.mm.trans1:exp3	0.250670131738792	0.0617943012196193	4.05652506446995	5.43744082331748e-05	***
df.mm.trans2:exp3	0.0827637938576753	0.0456381160268936	1.81347963200112	0.0701091892309394	.  
df.mm.trans1:exp4	0.385705546612311	0.0617943012196193	6.24176564828362	6.81159748128034e-10	***
df.mm.trans2:exp4	0.142583488692244	0.0456381160268936	3.12421942676648	0.00184303894848672	** 
df.mm.trans1:exp5	0.18377149543262	0.0617943012196193	2.97392302858947	0.00302300556886399	** 
df.mm.trans2:exp5	0.00421602453221347	0.0456381160268936	0.0923794603994839	0.926418248873718	   
df.mm.trans1:exp6	0.427810678376401	0.0617943012196193	6.92314129187974	8.6860228834534e-12	***
df.mm.trans2:exp6	0.139079404800736	0.0456381160268936	3.04743966027826	0.00237913970889828	** 
df.mm.trans1:exp7	0.0422160370362864	0.0617943012196193	0.683170392788308	0.494684688131779	   
df.mm.trans2:exp7	0.081140355011789	0.0456381160268936	1.77790763676517	0.0757752067134434	.  
df.mm.trans1:exp8	-0.115646622276163	0.0617943012196193	-1.87147714261143	0.0616210533091785	.  
df.mm.trans2:exp8	-0.00778337957346759	0.0456381160268936	-0.170545593268596	0.864621524162797	   
df.mm.trans1:probe2	-0.186510349944719	0.0423076658790681	-4.40842920708126	1.17410046935290e-05	***
df.mm.trans1:probe3	-0.151477394592735	0.0423076658790681	-3.58037701786046	0.000362485558022389	***
df.mm.trans1:probe4	-0.0834761945932037	0.0423076658790681	-1.97307492291849	0.0488095059328471	*  
df.mm.trans1:probe5	0.335918751043064	0.0423076658790681	7.93990271179817	6.3635360927552e-15	***
df.mm.trans1:probe6	0.613869227030223	0.0423076658790681	14.5096453390953	8.45378213128827e-43	***
df.mm.trans1:probe7	0.526013260999471	0.0423076658790681	12.4330484811671	9.8073654416301e-33	***
df.mm.trans1:probe8	0.243632683891603	0.0423076658790681	5.75859430742411	1.18334320362249e-08	***
df.mm.trans1:probe9	0.625784845747409	0.0423076658790681	14.7912874119822	3.08143141532882e-44	***
df.mm.trans1:probe10	0.151760261965884	0.0423076658790681	3.58706297812965	0.000353455416122147	***
df.mm.trans1:probe11	-0.096971132864024	0.0423076658790681	-2.29204639039189	0.0221457482032809	*  
df.mm.trans1:probe12	0.268891984250485	0.0423076658790681	6.35563268886266	3.37646031385174e-10	***
df.mm.trans1:probe13	-0.126822263208557	0.0423076658790681	-2.99761900292644	0.00279989290910853	** 
df.mm.trans1:probe14	0.340684578987525	0.0423076658790681	8.05254962448968	2.71814824517612e-15	***
df.mm.trans1:probe15	0.186871579671140	0.0423076658790681	4.41696736958481	1.12968164053182e-05	***
df.mm.trans1:probe16	0.0565195433580186	0.0423076658790681	1.33591731388760	0.181932602154960	   
df.mm.trans1:probe17	-0.258054966158601	0.0423076658790681	-6.09948482849947	1.61200820483042e-09	***
df.mm.trans1:probe18	-0.125134286930318	0.0423076658790681	-2.95772135688130	0.00318478121463887	** 
df.mm.trans1:probe19	-0.221470578686046	0.0423076658790681	-5.2347624026127	2.08137784628274e-07	***
df.mm.trans1:probe20	-0.157853960993151	0.0423076658790681	-3.73109595420271	0.000203269120008415	***
df.mm.trans1:probe21	-0.140021770998187	0.0423076658790681	-3.30960756375508	0.000973448192306978	***
df.mm.trans1:probe22	-0.221994969246577	0.0423076658790681	-5.24715709633156	1.95023975866634e-07	***
df.mm.trans2:probe2	0.0301063041497722	0.0423076658790681	0.711603997153324	0.476904588295791	   
df.mm.trans2:probe3	0.077473217469931	0.0423076658790681	1.83118628409754	0.0674214013231439	.  
df.mm.trans2:probe4	-0.0421242267378989	0.0423076658790681	-0.995664163045687	0.319695703090569	   
df.mm.trans2:probe5	0.0149748004538143	0.0423076658790681	0.353950050012641	0.723463787319198	   
df.mm.trans2:probe6	-0.00299514026396677	0.0423076658790681	-0.0707942686445538	0.943578087224698	   
df.mm.trans3:probe2	-0.868694127630918	0.0423076658790681	-20.5327831158066	1.923279310021e-76	***
df.mm.trans3:probe3	-0.649594587149426	0.0423076658790681	-15.3540634694011	3.69082117396748e-47	***
df.mm.trans3:probe4	-1.1120877782927	0.0423076658790681	-26.2857275433601	5.11988197825007e-112	***
df.mm.trans3:probe5	-1.17669634630851	0.0423076658790681	-27.8128401049579	1.09878533399517e-121	***
df.mm.trans3:probe6	-0.890200132460206	0.0423076658790681	-21.0411071838552	1.70268169333943e-79	***
df.mm.trans3:probe7	-0.678538449358702	0.0423076658790681	-16.0381915489791	8.59853360996831e-51	***
df.mm.trans3:probe8	-0.791587579114197	0.0423076658790681	-18.7102635578352	1.01920035140902e-65	***
df.mm.trans3:probe9	-0.99272103735168	0.0423076658790681	-23.4643300859297	2.46922548174379e-94	***
df.mm.trans3:probe10	-0.309779238115903	0.0423076658790681	-7.32205929302205	5.65032876198469e-13	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.37870252923123	0.166163073746194	26.3518387720697	1.95723383701302e-112	***
df.mm.trans1	-0.247259682776994	0.143494366001635	-1.72313164388752	0.0852271271738278	.  
df.mm.trans2	0.0083779614821795	0.126776623779479	0.0660844344360561	0.947326088254134	   
df.mm.exp2	-0.146958896938986	0.163075273756917	-0.9011721615016	0.36775115536027	   
df.mm.exp3	-0.0414691756626522	0.163075273756917	-0.254294686786588	0.799329191871205	   
df.mm.exp4	-0.137602506137314	0.163075273756917	-0.843797486689654	0.399019146065572	   
df.mm.exp5	-0.0107792403722425	0.163075273756917	-0.0660997840071708	0.947313871400577	   
df.mm.exp6	-0.102098986449177	0.163075273756917	-0.626085022560611	0.531426666312808	   
df.mm.exp7	-0.161008319786981	0.163075273756917	-0.987325154069543	0.323763234123555	   
df.mm.exp8	-0.155594613840564	0.163075273756917	-0.95412756487226	0.340289375447094	   
df.mm.trans1:exp2	0.172846217360757	0.150733866681137	1.14669795956602	0.251828024239616	   
df.mm.trans2:exp2	0.0432682463894355	0.111324338345167	0.388668345418593	0.697618493160457	   
df.mm.trans1:exp3	0.0459657548512096	0.150733866681137	0.304946432167402	0.76048134039089	   
df.mm.trans2:exp3	-0.0407783249414642	0.111324338345167	-0.366301974461586	0.714230589501839	   
df.mm.trans1:exp4	0.178863416898680	0.150733866681137	1.18661731989566	0.235708982475966	   
df.mm.trans2:exp4	-0.0165928354348393	0.111324338345167	-0.149049486226385	0.88154981489755	   
df.mm.trans1:exp5	0.0523499692058692	0.150733866681137	0.347300645558377	0.728451136524883	   
df.mm.trans2:exp5	-0.0251673450939483	0.111324338345167	-0.226072262975556	0.821199374971193	   
df.mm.trans1:exp6	0.162379559073981	0.150733866681137	1.07725995921991	0.281668705676000	   
df.mm.trans2:exp6	-0.110900322864911	0.111324338345167	-0.996191169994285	0.319439774006729	   
df.mm.trans1:exp7	0.191269504065928	0.150733866681137	1.26892189709789	0.204815064624519	   
df.mm.trans2:exp7	0.0395485547246322	0.111324338345167	0.355255241688569	0.722486207344996	   
df.mm.trans1:exp8	0.231487539049842	0.150733866681137	1.53573675343665	0.124973775723197	   
df.mm.trans2:exp8	-0.0945524442061977	0.111324338345167	-0.849342072108554	0.395929281086265	   
df.mm.trans1:probe2	-0.0770629341317938	0.103200423701544	-0.746730792062057	0.455431842509362	   
df.mm.trans1:probe3	0.0768071830423708	0.103200423701544	0.744252594005791	0.456928647826589	   
df.mm.trans1:probe4	0.0346793130608502	0.103200423701544	0.336038475589431	0.736924493257763	   
df.mm.trans1:probe5	-0.104443382764906	0.103200423701544	-1.01204412752177	0.311803936102810	   
df.mm.trans1:probe6	0.215246846409622	0.103200423701544	2.08571669271550	0.0373009643441822	*  
df.mm.trans1:probe7	0.114035139569427	0.103200423701544	1.10498712582050	0.269476744807603	   
df.mm.trans1:probe8	-0.0654380650071191	0.103200423701544	-0.6340871738702	0.526193933581611	   
df.mm.trans1:probe9	-0.130198914173095	0.103200423701544	-1.26161220567883	0.207433246916391	   
df.mm.trans1:probe10	0.0184113700633309	0.103200423701544	0.178404016213893	0.858448056441292	   
df.mm.trans1:probe11	0.166117786782977	0.103200423701544	1.60966186789495	0.107841681907789	   
df.mm.trans1:probe12	-0.0108330892099729	0.103200423701544	-0.104971363696163	0.916423209288231	   
df.mm.trans1:probe13	-0.0965705950987183	0.103200423701544	-0.935757738534106	0.349662772869979	   
df.mm.trans1:probe14	0.0220294380538696	0.103200423701544	0.213462670633784	0.831017111292813	   
df.mm.trans1:probe15	0.0862658816277983	0.103200423701544	0.83590627376957	0.403441718466476	   
df.mm.trans1:probe16	0.0697739167843034	0.103200423701544	0.676101068984851	0.499159743585272	   
df.mm.trans1:probe17	0.0498962940260015	0.103200423701544	0.483489236151799	0.628872483255103	   
df.mm.trans1:probe18	-0.0560238255553498	0.103200423701544	-0.542864297896401	0.587365052105568	   
df.mm.trans1:probe19	0.090918398212949	0.103200423701544	0.880988613727841	0.378572139578646	   
df.mm.trans1:probe20	0.0301692687439118	0.103200423701544	0.292336675197783	0.770100309224883	   
df.mm.trans1:probe21	0.168425902806751	0.103200423701544	1.63202724141753	0.103042833676661	   
df.mm.trans1:probe22	0.056195436233719	0.103200423701544	0.544527185239437	0.58622106368765	   
df.mm.trans2:probe2	0.0638086486403166	0.103200423701544	0.6182983204105	0.536543763120386	   
df.mm.trans2:probe3	-0.0519193325526287	0.103200423701544	-0.503092242167335	0.615029295780096	   
df.mm.trans2:probe4	-0.192768822014212	0.103200423701544	-1.86790727305249	0.0621176874596496	.  
df.mm.trans2:probe5	-0.0321108878740791	0.103200423701544	-0.311150736812321	0.755762054407667	   
df.mm.trans2:probe6	-0.119350331750216	0.103200423701544	-1.15649071456701	0.247804279033135	   
df.mm.trans3:probe2	0.0614105671751336	0.103200423701544	0.595061192313834	0.551960389169735	   
df.mm.trans3:probe3	0.0170607767378020	0.103200423701544	0.165316925317496	0.868733708091237	   
df.mm.trans3:probe4	0.0987046319098536	0.103200423701544	0.956436304906149	0.339122832110267	   
df.mm.trans3:probe5	-0.0653286982584438	0.103200423701544	-0.633027422904529	0.526885403265968	   
df.mm.trans3:probe6	0.0675310626030792	0.103200423701544	0.654368075061197	0.513051084657819	   
df.mm.trans3:probe7	-0.00743204648117716	0.103200423701544	-0.0720156586049557	0.942606328072336	   
df.mm.trans3:probe8	0.132115776658618	0.103200423701544	1.28018637831078	0.200827620672548	   
df.mm.trans3:probe9	0.0382491613004107	0.103200423701544	0.37062988627864	0.711005236795055	   
df.mm.trans3:probe10	0.151093702510767	0.103200423701544	1.46408025365991	0.143540440443108