chr13.6754_chr13_81337735_81373365_+_2.R 

fitVsDatCorrelation=0.770934695950751
cont.fitVsDatCorrelation=0.241362629413413

fstatistic=6125.03794714861,58,830
cont.fstatistic=2630.23630320685,58,830

residuals=-0.627210249511869,-0.102653642789163,-0.00527213002780442,0.0853252774229873,1.61874175535063
cont.residuals=-0.62754119029133,-0.185306743216762,-0.0569684019115873,0.119282546124400,2.24609676589376

predictedValues:
Include	Exclude	Both
chr13.6754_chr13_81337735_81373365_+_2.R.tl.Lung	63.248483306855	50.4525976553097	57.511502357082
chr13.6754_chr13_81337735_81373365_+_2.R.tl.cerebhem	110.544973397348	70.3959948465886	67.2292735478309
chr13.6754_chr13_81337735_81373365_+_2.R.tl.cortex	71.8514763274797	51.2564573325015	61.964650251604
chr13.6754_chr13_81337735_81373365_+_2.R.tl.heart	61.6125598759154	48.7248040913132	59.0606196169888
chr13.6754_chr13_81337735_81373365_+_2.R.tl.kidney	63.5388253128639	47.7475298411695	61.0075289471592
chr13.6754_chr13_81337735_81373365_+_2.R.tl.liver	62.371905042762	53.171328073105	62.177409571249
chr13.6754_chr13_81337735_81373365_+_2.R.tl.stomach	71.0332573978946	53.5096840769787	62.049067368508
chr13.6754_chr13_81337735_81373365_+_2.R.tl.testicle	68.6363988428998	54.0341944645214	58.9076712375051


diffExp=12.7958856515452,40.1489785507597,20.5950189949782,12.8877557846022,15.7912954716944,9.20057696965699,17.5235733209159,14.6022043783784
diffExpScore=0.993081753088803
diffExp1.5=0,1,0,0,0,0,0,0
diffExp1.5Score=0.5
diffExp1.4=0,1,1,0,0,0,0,0
diffExp1.4Score=0.666666666666667
diffExp1.3=0,1,1,0,1,0,1,0
diffExp1.3Score=0.8
diffExp1.2=1,1,1,1,1,0,1,1
diffExp1.2Score=0.875

cont.predictedValues:
Include	Exclude	Both
Lung	66.7499939018107	63.3182302761803	62.9786850641666
cerebhem	62.855746607306	60.0286901042928	60.4431915846907
cortex	64.1725385365533	56.9477176112643	63.3607324767839
heart	67.367346737573	58.1284333557598	67.7647675679237
kidney	60.6061370256217	56.7016556628456	67.5842936207133
liver	63.695119722198	59.1018938420837	64.1279414913796
stomach	62.9983436894598	61.264352311586	68.853780571816
testicle	66.222774439551	53.8850057615905	67.2693020721905
cont.diffExp=3.43176362563037,2.82705650301317,7.22482092528908,9.2389133818132,3.90448136277614,4.59322588011425,1.73399137787379,12.3377686779604
cont.diffExpScore=0.97839800547628

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

tran.correlation=0.960501033934802
cont.tran.correlation=0.0511674807727851

tran.covariance=0.0219774474791806
cont.tran.covariance=7.3664573540687e-05

tran.mean=62.6331543678441
cont.tran.mean=61.5027487241048

weightedLogRatios:
wLogRatio
Lung	0.911844816512534
cerebhem	2.02166202841319
cortex	1.38674661855460
heart	0.93953778056344
kidney	1.14540652168395
liver	0.64689169613518
stomach	1.16756285870058
testicle	0.982949727335201

cont.weightedLogRatios:
wLogRatio
Lung	0.22033731590126
cerebhem	0.189501614355577
cortex	0.489932713576004
heart	0.610142883587158
kidney	0.271105723225106
liver	0.308113230733217
stomach	0.115245865676760
testicle	0.843231485678026

varWeightedLogRatios=0.171172622448397
cont.varWeightedLogRatios=0.0612184782120774

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.24662203685526	0.0968745353352097	43.8363087075557	3.22162872031069e-218	***
df.mm.trans1	-0.0160454020195016	0.0835365101043221	-0.192076518392542	0.847729250072832	   
df.mm.trans2	-0.353931795773396	0.0739891485145455	-4.78356357491824	2.03769444246378e-06	***
df.mm.exp2	0.735329622078482	0.0952643201132562	7.71883556408397	3.37181661953795e-14	***
df.mm.exp3	0.0687582869068077	0.0952643201132562	0.721763266929985	0.470643313374998	   
df.mm.exp4	-0.0876308134094527	0.0952643201132561	-0.9198702442349	0.357907829756	   
df.mm.exp5	-0.109539220464923	0.0952643201132562	-1.14984519214220	0.250538838201741	   
df.mm.exp6	-0.0394779186096301	0.0952643201132562	-0.414404034613340	0.678685309501253	   
df.mm.exp7	0.098964934150888	0.0952643201132562	1.03884575078300	0.299179010874887	   
df.mm.exp8	0.126348328111639	0.0952643201132562	1.32629223576495	0.185107749250987	   
df.mm.trans1:exp2	-0.176978332833164	0.0877510492427897	-2.01682298229278	0.0440355600092168	*  
df.mm.trans2:exp2	-0.402227487089519	0.0652888699139017	-6.1607359358486	1.12790575508551e-09	***
df.mm.trans1:exp3	0.0587717247805924	0.0877510492427897	0.669755236977084	0.503200108688013	   
df.mm.trans2:exp3	-0.0529509152664495	0.0652888699139017	-0.811025146189195	0.417583726360145	   
df.mm.trans1:exp4	0.0614254092730279	0.0877510492427897	0.699996294096451	0.484125766057767	   
df.mm.trans2:exp4	0.0527848029203921	0.0652888699139017	0.808480878747035	0.41904547692534	   
df.mm.trans1:exp5	0.114119213789107	0.0877510492427897	1.30048831066808	0.193794632138227	   
df.mm.trans2:exp5	0.0544323198056064	0.0652888699139017	0.833715147426932	0.404681382247652	   
df.mm.trans1:exp6	0.0255217049154977	0.0877510492427897	0.290842162409754	0.77124469606162	   
df.mm.trans2:exp6	0.0919629885063926	0.0652888699139017	1.40855537287851	0.159341162091187	   
df.mm.trans1:exp7	0.0171120992918046	0.0877510492427897	0.195007346800593	0.845434920141672	   
df.mm.trans2:exp7	-0.0401365210177282	0.0652888699139017	-0.614752883158451	0.538886418768986	   
df.mm.trans1:exp8	-0.0445964867000638	0.0877510492427897	-0.508215993824464	0.611436915383364	   
df.mm.trans2:exp8	-0.0577654863019077	0.0652888699139017	-0.88476774644874	0.376538139675269	   
df.mm.trans1:probe2	-0.235734448960657	0.0600790363937782	-3.92373884653499	9.4401052225772e-05	***
df.mm.trans1:probe3	-0.466729957410249	0.0600790363937782	-7.76859925567289	2.34026816445420e-14	***
df.mm.trans1:probe4	-0.017785825679186	0.0600790363937782	-0.296040461811200	0.76727323358616	   
df.mm.trans1:probe5	-0.169834922115500	0.0600790363937782	-2.82685829050827	0.00481373946954947	** 
df.mm.trans1:probe6	-0.117995848114862	0.0600790363937782	-1.96401033035013	0.0498622729292829	*  
df.mm.trans1:probe7	-0.272932439821674	0.0600790363937782	-4.54288976994876	6.37161412580838e-06	***
df.mm.trans1:probe8	-0.36399893744444	0.0600790363937782	-6.058668036196	2.07990203676597e-09	***
df.mm.trans1:probe9	-0.105877988194417	0.0600790363937782	-1.76231169056136	0.0783846879124114	.  
df.mm.trans1:probe10	0.0717255672945437	0.0600790363937782	1.19385349033281	0.232876380719389	   
df.mm.trans1:probe11	0.163227288412043	0.0600790363937782	2.71687593892479	0.00672733528054277	** 
df.mm.trans1:probe12	-0.0222453524014189	0.0600790363937782	-0.370268129062779	0.711277183633019	   
df.mm.trans1:probe13	0.156703337015703	0.0600790363937782	2.60828645766914	0.00926326976896803	** 
df.mm.trans1:probe14	0.318284610128260	0.0600790363937782	5.29776489826029	1.50290360076959e-07	***
df.mm.trans1:probe15	-0.0151128359536624	0.0600790363937782	-0.251549240147725	0.80145176518603	   
df.mm.trans1:probe16	-0.219844399857630	0.0600790363937782	-3.65925309481823	0.000268928336022801	***
df.mm.trans1:probe17	-0.332728076889990	0.0600790363937782	-5.53817266157829	4.10298953419119e-08	***
df.mm.trans1:probe18	-0.260691030568013	0.0600790363937782	-4.33913468350851	1.60669945568688e-05	***
df.mm.trans1:probe19	-0.263625298297084	0.0600790363937782	-4.38797480986871	1.29155943844975e-05	***
df.mm.trans1:probe20	-0.18866359807261	0.0600790363937782	-3.14025672509202	0.00174778368532592	** 
df.mm.trans1:probe21	-0.244809935540070	0.0600790363937782	-4.07479797005238	5.04747154551969e-05	***
df.mm.trans2:probe2	0.086947693021413	0.0600790363937782	1.44722183044896	0.148212375810059	   
df.mm.trans2:probe3	0.204477469732564	0.0600790363937782	3.40347452299916	0.000697224270988156	***
df.mm.trans2:probe4	0.0316225477759306	0.0600790363937782	0.526349117330475	0.598786279542158	   
df.mm.trans2:probe5	0.0852576532792022	0.0600790363937782	1.41909155666870	0.156247740044181	   
df.mm.trans2:probe6	0.0451985416486435	0.0600790363937782	0.752318019090671	0.452073130817499	   
df.mm.trans3:probe2	0.374694638171168	0.0600790363937782	6.23669520455178	7.1120199693436e-10	***
df.mm.trans3:probe3	0.0673656877652396	0.0600790363937782	1.12128442479840	0.262491114925101	   
df.mm.trans3:probe4	0.164404412498445	0.0600790363937782	2.73646886446186	0.00634294698555635	** 
df.mm.trans3:probe5	-0.085154545877305	0.0600790363937782	-1.41737536066946	0.156748479734700	   
df.mm.trans3:probe6	0.144436183178475	0.0600790363937782	2.4041028593034	0.0164304447407877	*  
df.mm.trans3:probe7	0.552811683037764	0.0600790363937782	9.20140728314033	2.80252030569935e-19	***
df.mm.trans3:probe8	-0.0707147858551529	0.0600790363937782	-1.17702929507165	0.239521236311487	   
df.mm.trans3:probe9	0.149694284475473	0.0600790363937782	2.49162259351709	0.0129103156125391	*  
df.mm.trans3:probe10	0.455863739887299	0.0600790363937782	7.5877338794087	8.74191094649657e-14	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.29393901746886	0.147602989081901	29.0911386292203	7.98391976684213e-129	***
df.mm.trans1	-0.0833869125437611	0.127280492713619	-0.655142911265923	0.512557271861965	   
df.mm.trans2	-0.167029771325895	0.112733645044925	-1.48163195875848	0.138817781290607	   
df.mm.exp2	-0.0723701157830142	0.145149582941648	-0.498589898202517	0.618200423484663	   
df.mm.exp3	-0.151466480256843	0.145149582941648	-1.04351991364477	0.297011395196273	   
df.mm.exp4	-0.149558200907454	0.145149582941648	-1.03037292892242	0.303135129652299	   
df.mm.exp5	-0.277507198279265	0.145149582941648	-1.91187044878266	0.0562368646940071	.  
df.mm.exp6	-0.133840413691524	0.145149582941648	-0.922086105788742	0.356751611964975	   
df.mm.exp7	-0.180009707923757	0.145149582941648	-1.24016689731808	0.215264147074507	   
df.mm.exp8	-0.235158470264114	0.145149582941648	-1.62011123627307	0.105588228491642	   
df.mm.trans1:exp2	0.0122582744059949	0.133701979766825	0.0916835668953685	0.92697157678744	   
df.mm.trans2:exp2	0.0190194463933373	0.099477456276053	0.191193533744548	0.848420728198615	   
df.mm.trans1:exp3	0.112087644868677	0.133701979766825	0.838339455138636	0.402081440038839	   
df.mm.trans2:exp3	0.0454268065533876	0.099477456276053	0.456654283834187	0.648039032964643	   
df.mm.trans1:exp4	0.158764425741660	0.133701979766825	1.18745007380252	0.235389853521652	   
df.mm.trans2:exp4	0.064039845826113	0.099477456276053	0.643762398270423	0.51990735776776	   
df.mm.trans1:exp5	0.180949151355118	0.133701979766825	1.35337675381241	0.176303760823009	   
df.mm.trans2:exp5	0.167137323258992	0.099477456276053	1.68015276541833	0.0933038898576495	.  
df.mm.trans1:exp6	0.0869941539466885	0.133701979766825	0.650657186216728	0.515447876954457	   
df.mm.trans2:exp6	0.0649300965648877	0.099477456276053	0.652711669513389	0.51412291471771	   
df.mm.trans1:exp7	0.122163937404477	0.133701979766825	0.913703279618817	0.361138118536491	   
df.mm.trans2:exp7	0.147034567623031	0.099477456276053	1.47806923424947	0.139768610564145	   
df.mm.trans1:exp8	0.227228692889044	0.133701979766825	1.69951629201997	0.0895966396525506	.  
df.mm.trans2:exp8	0.0738374375061554	0.099477456276053	0.742252971379307	0.458144075189668	   
df.mm.trans1:probe2	0.0150988928020579	0.091539487876737	0.164944038384718	0.869028192072375	   
df.mm.trans1:probe3	0.0758539638358467	0.091539487876737	0.828647456909398	0.407542146480254	   
df.mm.trans1:probe4	-0.00124977830802154	0.091539487876737	-0.0136528872622102	0.989110191422717	   
df.mm.trans1:probe5	-0.126769449728575	0.091539487876737	-1.38486081437639	0.166467154925668	   
df.mm.trans1:probe6	-0.00786459206862766	0.091539487876737	-0.0859147483894358	0.93155490758972	   
df.mm.trans1:probe7	-0.0328268961887222	0.091539487876737	-0.358609130880495	0.719978708990701	   
df.mm.trans1:probe8	0.0416144179782449	0.091539487876737	0.45460619174843	0.649511448763106	   
df.mm.trans1:probe9	-0.00116033319078020	0.091539487876737	-0.0126757666848940	0.989889518408677	   
df.mm.trans1:probe10	-0.0598166444433517	0.091539487876737	-0.653451814411483	0.513646021106877	   
df.mm.trans1:probe11	0.0758493093228454	0.091539487876737	0.828596609858478	0.407570911233732	   
df.mm.trans1:probe12	0.00384256503075133	0.091539487876737	0.0419771305245399	0.96652702481754	   
df.mm.trans1:probe13	-0.0138269125096044	0.091539487876737	-0.151048611154817	0.879974072078727	   
df.mm.trans1:probe14	0.0690814390588411	0.0915394878767369	0.754662721642743	0.450665444888923	   
df.mm.trans1:probe15	-0.00622369092670067	0.091539487876737	-0.0679891385789837	0.945810655196116	   
df.mm.trans1:probe16	0.0457366731560287	0.091539487876737	0.499638726596501	0.617461903984748	   
df.mm.trans1:probe17	-0.0569768377719197	0.091539487876737	-0.622429064150351	0.533830728890281	   
df.mm.trans1:probe18	-0.0493398031642138	0.091539487876737	-0.539000209730828	0.590031249201425	   
df.mm.trans1:probe19	-0.103963476775093	0.091539487876737	-1.13572272673281	0.256400459918349	   
df.mm.trans1:probe20	-0.0486473448193209	0.091539487876737	-0.531435623551087	0.595259132389543	   
df.mm.trans1:probe21	-0.115946370394573	0.091539487876737	-1.26662681957213	0.205644087057282	   
df.mm.trans2:probe2	0.0520938576824125	0.091539487876737	0.569086182266606	0.569451615855408	   
df.mm.trans2:probe3	-0.0450844277798984	0.091539487876737	-0.492513436830749	0.622486678169664	   
df.mm.trans2:probe4	0.0337917524471815	0.0915394878767369	0.369149459222275	0.712110475541228	   
df.mm.trans2:probe5	0.103102871550024	0.091539487876737	1.12632126245733	0.260355105242534	   
df.mm.trans2:probe6	0.196320579502145	0.091539487876737	2.14465455352451	0.0322702052170132	*  
df.mm.trans3:probe2	0.180925474394636	0.091539487876737	1.97647461867235	0.0484317249099751	*  
df.mm.trans3:probe3	0.0733599441187299	0.091539487876737	0.801402168837925	0.423128220366138	   
df.mm.trans3:probe4	0.0628419774889789	0.0915394878767369	0.686501300658347	0.4925887805623	   
df.mm.trans3:probe5	0.133892351754953	0.091539487876737	1.46267315735092	0.143935378542780	   
df.mm.trans3:probe6	0.058590517717624	0.091539487876737	0.640057302882439	0.522311985122158	   
df.mm.trans3:probe7	0.122360890868986	0.091539487876737	1.33670062731563	0.181686655058697	   
df.mm.trans3:probe8	0.0814190025317405	0.091539487876737	0.889441315657957	0.374023660578233	   
df.mm.trans3:probe9	0.208031797690466	0.091539487876737	2.27259079677825	0.0233057895526112	*  
df.mm.trans3:probe10	0.0713180757361614	0.091539487876737	0.779096293745877	0.436145064448798