chr3.15382_chr3_89761341_89766683_-_2.R 

fitVsDatCorrelation=0.904189002619547
cont.fitVsDatCorrelation=0.273763507453085

fstatistic=13696.4841952201,52,692
cont.fstatistic=2690.58471149765,52,692

residuals=-0.564744651769682,-0.0822732855962293,0.00441216596413152,0.0836035795321267,0.487330404046864
cont.residuals=-0.745442496926423,-0.248973904899691,0.0128694984665846,0.221360764060616,0.843067711913602

predictedValues:
Include	Exclude	Both
chr3.15382_chr3_89761341_89766683_-_2.R.tl.Lung	80.27838080248	95.3252349052448	70.808935790458
chr3.15382_chr3_89761341_89766683_-_2.R.tl.cerebhem	85.5534983239703	88.1572448060566	70.7046270579214
chr3.15382_chr3_89761341_89766683_-_2.R.tl.cortex	101.313332336705	83.1551571738694	101.175803262103
chr3.15382_chr3_89761341_89766683_-_2.R.tl.heart	114.999998043357	91.1123039948074	106.464915942017
chr3.15382_chr3_89761341_89766683_-_2.R.tl.kidney	88.2829135690376	98.4347664268856	86.6094930685495
chr3.15382_chr3_89761341_89766683_-_2.R.tl.liver	78.5851439586282	106.083326734017	68.4311046341537
chr3.15382_chr3_89761341_89766683_-_2.R.tl.stomach	88.0776846460039	92.7636350033814	81.6995532966397
chr3.15382_chr3_89761341_89766683_-_2.R.tl.testicle	86.9877830277664	100.437011945608	88.4558786686374


diffExp=-15.0468541027647,-2.60374648208624,18.1581751628358,23.8876940485498,-10.151852857848,-27.4981827753888,-4.68595035737746,-13.4492289178419
diffExpScore=3.56535585763379
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=0,0,1,1,0,-1,0,0
diffExp1.2Score=1.5

cont.predictedValues:
Include	Exclude	Both
Lung	85.8264591849396	96.0523890968508	72.2364592345524
cerebhem	88.8735275028202	87.2379421625667	82.1166851650346
cortex	90.8221128461904	88.9991591736525	90.3391230673275
heart	90.4041402702933	85.8715270672533	89.795516841812
kidney	92.8570319086871	110.270964187179	98.773097377779
liver	88.1758603404907	102.008691881913	100.064686029945
stomach	90.8634568163052	98.0855050822335	77.3209135028958
testicle	92.4374272126079	103.987403338717	81.1853651983665
cont.diffExp=-10.2259299119112,1.63558534025351,1.82295367253788,4.53261320303997,-17.4139322784923,-13.8328315414222,-7.22204826592832,-11.5499761261096
cont.diffExpScore=1.28133898972206

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=-0.566627700573688
cont.tran.correlation=0.357702844098814

tran.covariance=-0.00567809936915465
cont.tran.covariance=0.000774174977704374

tran.mean=92.4717134811137
cont.tran.mean=93.2983498795438

weightedLogRatios:
wLogRatio
Lung	-0.768160219866565
cerebhem	-0.133835574674842
cortex	0.89263820621206
heart	1.07769940249828
kidney	-0.493620066148775
liver	-1.35445169275562
stomach	-0.233474162509018
testicle	-0.652346522298335

cont.weightedLogRatios:
wLogRatio
Lung	-0.507518154901264
cerebhem	0.0831773431310867
cortex	0.0912163592566366
heart	0.230367659980758
kidney	-0.793568388492928
liver	-0.663367756199135
stomach	-0.347808056060488
testicle	-0.539875087575918

varWeightedLogRatios=0.682532859821372
cont.varWeightedLogRatios=0.151345677429275

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	5.11302962823292	0.0775310077769881	65.9481899544005	1.30239627469611e-300	***
df.mm.trans1	-0.636365487540979	0.0696341830423709	-9.13869395371185	6.90175896682803e-19	***
df.mm.trans2	-0.551094594354851	0.064038088496752	-8.60573148404958	5.07535933093034e-17	***
df.mm.exp2	-0.0130567526303489	0.0877163221621363	-0.148852030141147	0.881713760388218	   
df.mm.exp3	-0.260743108692679	0.0877163221621364	-2.97257229060194	0.00305569416138969	** 
df.mm.exp4	-0.0936002561707748	0.0877163221621364	-1.06707912351549	0.286308236017092	   
df.mm.exp5	-0.0742785055962373	0.0877163221621364	-0.846803693603793	0.397397299091328	   
df.mm.exp6	0.119770372715043	0.0877163221621364	1.36542857432687	0.172562068597961	   
df.mm.exp7	-0.077584350195028	0.0877163221621364	-0.884491600680883	0.376738101933957	   
df.mm.exp8	-0.0900151334344085	0.0877163221621364	-1.02620733764946	0.305152439926447	   
df.mm.trans1:exp2	0.0766982899402268	0.0839819846307174	0.913270748214416	0.361418235611745	   
df.mm.trans2:exp2	-0.065115724650337	0.0730969351351137	-0.890813336153916	0.373338927885091	   
df.mm.trans1:exp3	0.493460769344392	0.0839819846307174	5.8757931419961	6.53983524936878e-09	***
df.mm.trans2:exp3	0.124156764947284	0.0730969351351137	1.69852217083781	0.0898587663589561	.  
df.mm.trans1:exp4	0.45303201317119	0.0839819846307174	5.39439518086225	9.44869866532419e-08	***
df.mm.trans2:exp4	0.0483985416360548	0.0730969351351137	0.662114513373154	0.50811826718142	   
df.mm.trans1:exp5	0.169324735818816	0.0839819846307175	2.01620307692613	0.0441646631219883	*  
df.mm.trans2:exp5	0.106377994601941	0.0730969351351137	1.45530034064096	0.146039608366955	   
df.mm.trans1:exp6	-0.141088053652672	0.0839819846307174	-1.67997998943535	0.0934125526861675	.  
df.mm.trans2:exp6	-0.0128400561514613	0.0730969351351137	-0.175657927760275	0.860614077737825	   
df.mm.trans1:exp7	0.170303200971752	0.0839819846307174	2.02785397035570	0.0429578078931212	*  
df.mm.trans2:exp7	0.0503444790036206	0.0730969351351137	0.688735839752556	0.491220355462888	   
df.mm.trans1:exp8	0.170282462911730	0.0839819846307174	2.02760703572904	0.0429830937951799	*  
df.mm.trans2:exp8	0.142251347638759	0.0730969351351137	1.94606446051149	0.052051440101033	.  
df.mm.trans1:probe2	0.165592138617405	0.0419909923153587	3.94351572770137	8.84711565313474e-05	***
df.mm.trans1:probe3	0.0587374231601996	0.0419909923153587	1.39881007619617	0.162317965226759	   
df.mm.trans1:probe4	-0.620240565606016	0.0419909923153587	-14.7708003885194	4.06596551819947e-43	***
df.mm.trans1:probe5	0.247224257505953	0.0419909923153587	5.88755454144217	6.11182789764512e-09	***
df.mm.trans1:probe6	0.229112215739005	0.0419909923153587	5.45622294463387	6.779230178388e-08	***
df.mm.trans1:probe7	-0.342241070117862	0.0419909923153587	-8.15034490129645	1.70034288372126e-15	***
df.mm.trans1:probe8	0.0711441697724474	0.0419909923153587	1.69427217242555	0.090663530792235	.  
df.mm.trans1:probe9	-0.402092974552655	0.0419909923153587	-9.57569593814017	1.75813869919051e-20	***
df.mm.trans1:probe10	-0.155678059490123	0.0419909923153587	-3.70741558858522	0.000226138302840506	***
df.mm.trans1:probe11	-0.217375424549687	0.0419909923153587	-5.17671558979041	2.96315289669794e-07	***
df.mm.trans1:probe12	-0.283370064402763	0.0419909923153587	-6.74835360580694	3.16394171729473e-11	***
df.mm.trans1:probe13	-0.438507439970007	0.0419909923153587	-10.4428930061178	8.32878043190992e-24	***
df.mm.trans1:probe14	-0.440339122087201	0.0419909923153587	-10.4865138404015	5.59615930416614e-24	***
df.mm.trans1:probe15	-0.467929016687148	0.0419909923153587	-11.1435570079633	1.21943526647201e-26	***
df.mm.trans1:probe16	-0.565869028697361	0.0419909923153587	-13.4759622837107	6.34959891309452e-37	***
df.mm.trans1:probe17	0.0379208742755753	0.0419909923153587	0.90307163952649	0.366802116571621	   
df.mm.trans1:probe18	0.0967497303279239	0.0419909923153587	2.30405915633807	0.0215146856658942	*  
df.mm.trans1:probe19	-0.0907485402652878	0.0419909923153587	-2.16114302762251	0.0310266409582216	*  
df.mm.trans1:probe20	0.150367094503783	0.0419909923153587	3.58093691557712	0.00036632408289475	***
df.mm.trans1:probe21	0.287734213212876	0.0419909923153587	6.85228420066734	1.60898480525361e-11	***
df.mm.trans1:probe22	0.400714530726233	0.0419909923153587	9.54286880664324	2.32662120515158e-20	***
df.mm.trans2:probe2	0.133375752555967	0.0419909923153587	3.17629437176181	0.00155795402879649	** 
df.mm.trans2:probe3	-0.106816558786556	0.0419909923153587	-2.54379696446200	0.0111818407743190	*  
df.mm.trans2:probe4	0.29366762237495	0.0419909923153587	6.99358615222669	6.32819735303301e-12	***
df.mm.trans2:probe5	-0.166676236264687	0.0419909923153587	-3.96933311346688	7.96034291571272e-05	***
df.mm.trans2:probe6	-0.195314754809021	0.0419909923153587	-4.65134887363885	3.95118997764988e-06	***
df.mm.trans3:probe2	0.439950134017107	0.0419909923153587	10.4772502329313	6.08985042904443e-24	***
df.mm.trans3:probe3	0.563296840367461	0.0419909923153587	13.4147065669946	1.22431459313981e-36	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.92270555724101	0.174580670625373	28.1973115328701	4.62733403491869e-117	***
df.mm.trans1	-0.391929848222538	0.156798972727855	-2.49956897933753	0.0126649477246478	*  
df.mm.trans2	-0.254242172735524	0.144197950676557	-1.76314692090043	0.0783170267370464	.  
df.mm.exp2	-0.189563762413957	0.197515481701274	-0.959741286005401	0.337520644560848	   
df.mm.exp3	-0.243317120896638	0.197515481701274	-1.23188885651321	0.218409035013661	   
df.mm.exp4	-0.277668885896857	0.197515481701274	-1.40580821060300	0.160229910168654	   
df.mm.exp5	-0.096099816764976	0.197515481701274	-0.486543211383901	0.626736128229795	   
df.mm.exp6	-0.238701789163073	0.197515481701274	-1.20852191993785	0.227259368277721	   
df.mm.exp7	0.00995682593954159	0.197515481701274	0.0504103569693867	0.95980992994489	   
df.mm.exp8	0.0367905142843659	0.197515481701274	0.186266483859774	0.852290378667424	   
df.mm.trans1:exp2	0.224450741155277	0.189106676382350	1.18690014254952	0.235674302767405	   
df.mm.trans2:exp2	0.0933093528605122	0.164596234751062	0.566898465214803	0.570966996773143	   
df.mm.trans1:exp3	0.299892569339977	0.189106676382351	1.58583808396923	0.113232872713522	   
df.mm.trans2:exp3	0.167050280721277	0.164596234751062	1.01490949032903	0.310503686851212	   
df.mm.trans1:exp4	0.329631610633592	0.189106676382351	1.74309874690578	0.0817605218183721	.  
df.mm.trans2:exp4	0.165627431525274	0.164596234751062	1.00626500828389	0.314639832808798	   
df.mm.trans1:exp5	0.174833494706329	0.189106676382351	0.924523121292857	0.35553629073975	   
df.mm.trans2:exp5	0.234146701997267	0.164596234751062	1.42255199428708	0.155316674623153	   
df.mm.trans1:exp6	0.265707681367784	0.189106676382351	1.40506769221916	0.160449893469693	   
df.mm.trans2:exp6	0.298866050969528	0.164596234751062	1.81575265935784	0.0698409738159334	.  
df.mm.trans1:exp7	0.0470737381291634	0.189106676382351	0.248926896869501	0.80349119083301	   
df.mm.trans2:exp7	0.0109890107867228	0.164596234751062	0.0667634396579166	0.946789313381958	   
df.mm.trans1:exp8	0.0374140977007938	0.189106676382351	0.197846519311391	0.843223251151246	   
df.mm.trans2:exp8	0.0425854934022523	0.164596234751062	0.258727020497519	0.795922807246998	   
df.mm.trans1:probe2	-0.0925414543560413	0.0945533381911753	-0.97872223367655	0.328059273032262	   
df.mm.trans1:probe3	-0.0769916995734185	0.0945533381911753	-0.814267386496188	0.415771901026062	   
df.mm.trans1:probe4	-0.106877388306187	0.0945533381911753	-1.13033966172717	0.258724747611956	   
df.mm.trans1:probe5	-0.0999502847952435	0.0945533381911753	-1.05707832962128	0.290844717026592	   
df.mm.trans1:probe6	-0.120932923717515	0.0945533381911753	-1.27899158327973	0.201328743141982	   
df.mm.trans1:probe7	-0.045076056578434	0.0945533381911753	-0.476726231360502	0.633707581354374	   
df.mm.trans1:probe8	-0.0872558633956367	0.0945533381911753	-0.922821605930148	0.35642181800208	   
df.mm.trans1:probe9	-0.0282771906048494	0.0945533381911753	-0.299060732765208	0.764983497121458	   
df.mm.trans1:probe10	-0.111993507959284	0.0945533381911753	-1.18444795394581	0.236642436768060	   
df.mm.trans1:probe11	-0.114729166024842	0.0945533381911753	-1.21338038634738	0.225398419104295	   
df.mm.trans1:probe12	-0.165188896068311	0.0945533381911753	-1.74704457006393	0.0810732230854083	.  
df.mm.trans1:probe13	-0.220868274321475	0.0945533381911753	-2.33591196827876	0.0197805175395743	*  
df.mm.trans1:probe14	-0.109673971824429	0.0945533381911753	-1.15991644422624	0.246482862983914	   
df.mm.trans1:probe15	-0.166113401981590	0.0945533381911753	-1.75682218268941	0.0793903606305964	.  
df.mm.trans1:probe16	-0.121835868708877	0.0945533381911753	-1.28854116670677	0.197988279396566	   
df.mm.trans1:probe17	-0.075067893254345	0.0945533381911753	-0.7939211316111	0.427513504249752	   
df.mm.trans1:probe18	-0.0167833938110524	0.0945533381911753	-0.177501864366951	0.859166143933754	   
df.mm.trans1:probe19	0.0119126593672092	0.0945533381911753	0.125988776230441	0.899777403820918	   
df.mm.trans1:probe20	-0.0755036045121412	0.0945533381911753	-0.79852923182344	0.424837398377861	   
df.mm.trans1:probe21	-0.00636562690141126	0.0945533381911753	-0.0673231323524585	0.946343908108722	   
df.mm.trans1:probe22	-0.131095391564524	0.0945533381911753	-1.38647026189034	0.166049867123096	   
df.mm.trans2:probe2	-0.356119448609041	0.0945533381911753	-3.76633395945271	0.000179753448285598	***
df.mm.trans2:probe3	-0.137789719364693	0.0945533381911753	-1.45726974848946	0.145495556686926	   
df.mm.trans2:probe4	-0.195925396995260	0.0945533381911753	-2.07211507011125	0.0386245393536427	*  
df.mm.trans2:probe5	-0.197495183049164	0.0945533381911753	-2.08871719208742	0.0370980475116798	*  
df.mm.trans2:probe6	-0.0447968511488612	0.0945533381911753	-0.473773343234984	0.635810980945103	   
df.mm.trans3:probe2	0.0196273927423722	0.0945533381911753	0.207580114228099	0.835617904882874	   
df.mm.trans3:probe3	-0.00939331962317595	0.0945533381911753	-0.0993441353089387	0.920893808082093