chr1.1527_chr1_91530462_91534575_+_2.R 

fitVsDatCorrelation=0.935662453201798
cont.fitVsDatCorrelation=0.258990813672648

fstatistic=7696.74856698994,56,784
cont.fstatistic=1015.30601742342,56,784

residuals=-0.643276747353282,-0.115579526842862,-0.0161038154931648,0.107763502263571,0.982301903774042
cont.residuals=-0.998491405517355,-0.42433996793737,-0.125252160255701,0.404026040931105,1.69257261677048

predictedValues:
Include	Exclude	Both
chr1.1527_chr1_91530462_91534575_+_2.R.tl.Lung	73.0897019147835	241.246653850113	105.591984580942
chr1.1527_chr1_91530462_91534575_+_2.R.tl.cerebhem	61.6941760595775	115.388738442757	72.1289223243036
chr1.1527_chr1_91530462_91534575_+_2.R.tl.cortex	58.3783885675434	176.190827337030	93.6579349623803
chr1.1527_chr1_91530462_91534575_+_2.R.tl.heart	84.9249966747889	118.166447724948	97.3188106905507
chr1.1527_chr1_91530462_91534575_+_2.R.tl.kidney	66.2011160896618	198.075480165711	70.8032171308288
chr1.1527_chr1_91530462_91534575_+_2.R.tl.liver	67.1536403675419	160.913373743210	65.3448978372175
chr1.1527_chr1_91530462_91534575_+_2.R.tl.stomach	65.0217936673942	151.984614176428	85.986868399511
chr1.1527_chr1_91530462_91534575_+_2.R.tl.testicle	62.9552060352607	225.969899484486	95.4425602693636


diffExp=-168.156951935329,-53.6945623831799,-117.812438769486,-33.241451050159,-131.874364076049,-93.7597333756684,-86.9628205090335,-163.014693449225
diffExpScore=0.99882286054111
diffExp1.5=-1,-1,-1,0,-1,-1,-1,-1
diffExp1.5Score=0.875
diffExp1.4=-1,-1,-1,0,-1,-1,-1,-1
diffExp1.4Score=0.875
diffExp1.3=-1,-1,-1,-1,-1,-1,-1,-1
diffExp1.3Score=0.888888888888889
diffExp1.2=-1,-1,-1,-1,-1,-1,-1,-1
diffExp1.2Score=0.888888888888889

cont.predictedValues:
Include	Exclude	Both
Lung	94.091626217395	75.6376783109939	85.6810941642708
cerebhem	75.94303070858	105.670308144601	97.7821745559016
cortex	89.325131334697	85.673234527432	77.6309378789248
heart	93.252377677801	81.801054619374	107.280463169246
kidney	72.0608841425454	81.1354787383596	92.009893030649
liver	82.79861600442	88.993263003584	86.4401746805604
stomach	82.4893376562394	93.3271040154191	73.2315096428518
testicle	91.1199647637611	83.7172548447545	94.259191861176
cont.diffExp=18.4539479064011,-29.7272774360209,3.65189680726499,11.4513230584271,-9.07459459581422,-6.19464699916401,-10.8377663591797,7.40270991900664
cont.diffExpScore=6.09749761478628

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,-1,0,0,0,0,0,0
cont.diffExp1.3Score=0.5
cont.diffExp1.2=1,-1,0,0,0,0,0,0
cont.diffExp1.2Score=2

tran.correlation=-0.180739156390352
cont.tran.correlation=-0.541133870138945

tran.covariance=-0.00643358411321887
cont.tran.covariance=-0.00522065514181103

tran.mean=120.459690893827
cont.tran.mean=86.0647715443723

weightedLogRatios:
wLogRatio
Lung	-5.83781910978525
cerebhem	-2.77698527172962
cortex	-5.10253208159136
heart	-1.52178795594871
kidney	-5.19554432073167
liver	-4.0582469683642
stomach	-3.90502521367051
testicle	-6.11054179561258

cont.weightedLogRatios:
wLogRatio
Lung	0.968249238188906
cerebhem	-1.48493124735286
cortex	0.186647513801101
heart	0.585630582914669
kidney	-0.514385216982259
liver	-0.321243855391529
stomach	-0.552325501777283
testicle	0.378735245637187

varWeightedLogRatios=2.47714587890605
cont.varWeightedLogRatios=0.60937542632639

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.83110810981259	0.0941350266333424	51.3210468259582	7.1086781715634e-253	***
df.mm.trans1	-0.655914777478908	0.0820471143922862	-7.99436741117827	4.65920000188539e-15	***
df.mm.trans2	0.657731982256865	0.0732181956183544	8.98317660933976	1.93005688499919e-18	***
df.mm.exp2	-0.525883693722721	0.0957921365527605	-5.48984199170747	5.43602842931388e-08	***
df.mm.exp3	-0.419060624229349	0.0957921365527606	-4.3746871017804	1.3804135928058e-05	***
df.mm.exp4	-0.482054503283608	0.0957921365527605	-5.03229722846928	6.01395239751889e-07	***
df.mm.exp5	0.103516168379752	0.0957921365527605	1.08063325555681	0.280192585206716	   
df.mm.exp6	-0.0097549451626003	0.0957921365527605	-0.101834508694014	0.918914072657858	   
df.mm.exp7	-0.373617682898963	0.0957921365527605	-3.90029595689393	0.000104311885019095	***
df.mm.exp8	-0.113624228342701	0.0957921365527605	-1.18615402507615	0.235920820075650	   
df.mm.trans1:exp2	0.356385748771174	0.0894490957507912	3.98422975413949	7.40080645691398e-05	***
df.mm.trans2:exp2	-0.211629414187925	0.0697698135161486	-3.03325182514558	0.00249914071304445	** 
df.mm.trans1:exp3	0.194318906647010	0.0894490957507912	2.17239654594598	0.0301247134178696	*  
df.mm.trans2:exp3	0.104808408058649	0.0697698135161486	1.50220278336262	0.133447399970021	   
df.mm.trans1:exp4	0.632135498022642	0.0894490957507912	7.06698589534987	3.50173722905836e-12	***
df.mm.trans2:exp4	-0.231671162306911	0.0697698135161486	-3.32050711663848	0.000940094437656927	***
df.mm.trans1:exp5	-0.202506326371392	0.0894490957507912	-2.26392815569185	0.0238510029295016	*  
df.mm.trans2:exp5	-0.300687867441839	0.0697698135161486	-4.30971293010899	1.84268497798855e-05	***
df.mm.trans1:exp6	-0.0749494010178293	0.0894490957507911	-0.837900041232853	0.402342209960001	   
df.mm.trans2:exp6	-0.395198756010438	0.0697698135161486	-5.66432295134296	2.07248032388942e-08	***
df.mm.trans1:exp7	0.256652703636157	0.0894490957507912	2.86925990119791	0.00422495672797994	** 
df.mm.trans2:exp7	-0.088422893973166	0.0697698135161486	-1.26735173160095	0.205405856090079	   
df.mm.trans1:exp8	-0.0356397936232904	0.0894490957507911	-0.398436600439028	0.690416866312995	   
df.mm.trans2:exp8	0.0482061605513591	0.0697698135161486	0.690931480563604	0.48981311701585	   
df.mm.trans1:probe2	-0.133924567128074	0.0568439082967421	-2.35600561504231	0.0187179031227369	*  
df.mm.trans1:probe3	-0.0398354745001215	0.0568439082967421	-0.700787044623471	0.483643851292929	   
df.mm.trans1:probe4	-0.00570766378461637	0.0568439082967421	-0.10040941862795	0.920044963172413	   
df.mm.trans1:probe5	0.0612436486705679	0.0568439082967421	1.07740038476696	0.281632827814125	   
df.mm.trans1:probe6	-0.225020873503953	0.0568439082967421	-3.95857498624614	8.2248581297208e-05	***
df.mm.trans1:probe7	-0.129157112898954	0.0568439082967421	-2.27213639542016	0.0233483294021885	*  
df.mm.trans1:probe8	-0.0156999752755186	0.0568439082967421	-0.276194507836443	0.782471464640346	   
df.mm.trans1:probe9	0.0707229645290025	0.0568439082967421	1.24416083707347	0.213812209345799	   
df.mm.trans1:probe10	-0.0814712279543334	0.0568439082967421	-1.43324465884769	0.152186581004341	   
df.mm.trans1:probe11	-0.228905115290182	0.0568439082967421	-4.02690670203796	6.20072820057801e-05	***
df.mm.trans1:probe12	-0.215501910534148	0.0568439082967421	-3.79111706058571	0.000161483257695496	***
df.mm.trans1:probe13	-0.227935241016026	0.0568439082967421	-4.00984464027589	6.65650516202108e-05	***
df.mm.trans1:probe14	-0.134426635665757	0.0568439082967421	-2.36483802211506	0.0182806102474194	*  
df.mm.trans1:probe15	-0.119423512850438	0.0568439082967421	-2.10090256685047	0.0359682614563420	*  
df.mm.trans1:probe16	0.310777481002765	0.0568439082967421	5.46720819019716	6.1485595022487e-08	***
df.mm.trans1:probe17	1.14227399999967	0.0568439082967421	20.0949236994166	9.11012732667913e-73	***
df.mm.trans1:probe18	0.864861867503393	0.0568439082967421	15.2146798736737	5.36410171470995e-46	***
df.mm.trans1:probe19	0.774889749883319	0.0568439082967421	13.6318872699281	3.96862114872579e-38	***
df.mm.trans1:probe20	0.611451768725371	0.0568439082967421	10.7566806549157	2.88914922663801e-25	***
df.mm.trans1:probe21	1.01265669421973	0.0568439082967421	17.8146915749240	7.22082971298989e-60	***
df.mm.trans1:probe22	0.0864614226265966	0.0568439082967421	1.52103233604632	0.128654915008189	   
df.mm.trans2:probe2	0.0389466961233617	0.0568439082967421	0.685151624692101	0.493450763155989	   
df.mm.trans2:probe3	0.0348227623011849	0.0568439082967421	0.612603238317107	0.540316359397765	   
df.mm.trans2:probe4	-0.0424864289118252	0.0568439082967421	-0.747422726284642	0.455032539991124	   
df.mm.trans2:probe5	0.207166317210254	0.0568439082967421	3.64447701464832	0.000285596733108123	***
df.mm.trans2:probe6	-0.277712232695631	0.0568439082967421	-4.88552319882529	1.25091371082212e-06	***
df.mm.trans3:probe2	-0.0967427538918879	0.0568439082967421	-1.70190187111804	0.0891702158782392	.  
df.mm.trans3:probe3	-0.540212128783731	0.0568439082967421	-9.50343044612033	2.40412669737506e-20	***
df.mm.trans3:probe4	-0.145683753264043	0.0568439082967421	-2.56287362409232	0.0105665722194185	*  
df.mm.trans3:probe5	-0.504964952653098	0.0568439082967421	-8.88336090504247	4.37859175299326e-18	***
df.mm.trans3:probe6	0.0847111724819893	0.0568439082967421	1.49024187499163	0.136562837517605	   
df.mm.trans3:probe7	-0.0105075324106596	0.0568439082967421	-0.184848873441411	0.853395378790719	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.5467172014923	0.257648290273380	17.6469915506443	6.07059485531025e-59	***
df.mm.trans1	0.0711591602472292	0.224563581708804	0.316877561827914	0.751420867415713	   
df.mm.trans2	-0.190160356900965	0.200398763272768	-0.94890983255287	0.342958876016314	   
df.mm.exp2	-0.0120262938409076	0.262183812839238	-0.045869703818373	0.96342578250329	   
df.mm.exp3	0.171265895913564	0.262183812839238	0.653228336482307	0.513800600979698	   
df.mm.exp4	-0.155438271561314	0.262183812839238	-0.592859909534627	0.553445875771422	   
df.mm.exp5	-0.267855802419572	0.262183812839238	-1.02163363755722	0.307269467720893	   
df.mm.exp6	0.0259280566626924	0.262183812839238	0.0988926676361618	0.92124876982876	   
df.mm.exp7	0.235562418614219	0.262183812839238	0.898462861086918	0.369214679406801	   
df.mm.exp8	-0.02601771566994	0.262183812839238	-0.0992346376696152	0.92097734103235	   
df.mm.trans1:exp2	-0.202259297406216	0.244822861488715	-0.826145467691706	0.408972913449662	   
df.mm.trans2:exp2	0.346395691005240	0.190960514996670	1.81396500219577	0.0700652724311767	.  
df.mm.trans1:exp3	-0.223252076209702	0.244822861488715	-0.911892275305316	0.362105731498015	   
df.mm.trans2:exp3	-0.0466799843771998	0.190960514996670	-0.244448358227427	0.806947553027668	   
df.mm.trans1:exp4	0.146478773139235	0.244822861488715	0.598305126606762	0.549809159083224	   
df.mm.trans2:exp4	0.233773858356964	0.190960514996670	1.22419997851933	0.22124454035439	   
df.mm.trans1:exp5	0.00109812269100914	0.244822861488715	0.00448537642412842	0.996422340434618	   
df.mm.trans2:exp5	0.338021587522264	0.190960514996670	1.77011246292543	0.0770970065195325	.  
df.mm.trans1:exp6	-0.153785764839842	0.244822861488715	-0.628151161638683	0.530087853126663	   
df.mm.trans2:exp6	0.136678064228047	0.190960514996670	0.715739922624478	0.474365065134605	   
df.mm.trans1:exp7	-0.367162428662495	0.244822861488715	-1.49970646707526	0.134093019109496	   
df.mm.trans2:exp7	-0.0254063984197349	0.190960514996670	-0.133045296930509	0.894191697627125	   
df.mm.trans1:exp8	-0.00607440639889211	0.244822861488714	-0.0248114345284381	0.98021168407665	   
df.mm.trans2:exp8	0.127508273604168	0.190960514996670	0.667720620707331	0.504508446017935	   
df.mm.trans1:probe2	-0.208968284864655	0.155582213219717	-1.34313737116944	0.179616171167528	   
df.mm.trans1:probe3	-0.162441361229366	0.155582213219717	-1.04408696770474	0.296766974864773	   
df.mm.trans1:probe4	-0.132990972865466	0.155582213219717	-0.854795481522383	0.39292550883299	   
df.mm.trans1:probe5	0.0663938149001292	0.155582213219717	0.426744250040756	0.669682772599067	   
df.mm.trans1:probe6	-0.0464591483233099	0.155582213219717	-0.298614779683710	0.76531311582558	   
df.mm.trans1:probe7	-0.230065532001932	0.155582213219717	-1.47873929314161	0.139611655616516	   
df.mm.trans1:probe8	-0.168737286125544	0.155582213219717	-1.0845538357733	0.278452705762915	   
df.mm.trans1:probe9	-0.182930453409896	0.155582213219717	-1.17577999196834	0.240039722526434	   
df.mm.trans1:probe10	-0.0329640505612095	0.155582213219717	-0.211875444364947	0.832259275828374	   
df.mm.trans1:probe11	-0.170040891544071	0.155582213219717	-1.09293272042566	0.274759051197585	   
df.mm.trans1:probe12	0.000284512597004589	0.155582213219717	0.00182869616723342	0.998541377567018	   
df.mm.trans1:probe13	-0.0638873563366333	0.155582213219717	-0.410634062946578	0.681453083859579	   
df.mm.trans1:probe14	-0.0413275848755659	0.155582213219717	-0.265631809834213	0.790592617642107	   
df.mm.trans1:probe15	-0.076248588620446	0.155582213219717	-0.49008551197794	0.62421050366477	   
df.mm.trans1:probe16	-0.173718539280437	0.155582213219717	-1.11657069073254	0.264520011187955	   
df.mm.trans1:probe17	-0.237690648905265	0.155582213219717	-1.52774950289203	0.126978070775881	   
df.mm.trans1:probe18	-0.166618235797617	0.155582213219717	-1.07093370347107	0.284528810386133	   
df.mm.trans1:probe19	-0.0317638333092528	0.155582213219717	-0.204161084046253	0.83828060583032	   
df.mm.trans1:probe20	-0.0380342541423637	0.155582213219717	-0.244464025515891	0.806935424644978	   
df.mm.trans1:probe21	0.0319778223239561	0.155582213219717	0.205536492007581	0.8372063454917	   
df.mm.trans1:probe22	-0.068381037394546	0.155582213219717	-0.43951706290472	0.66040804098459	   
df.mm.trans2:probe2	0.00273967455888369	0.155582213219717	0.017609175896056	0.985955116742836	   
df.mm.trans2:probe3	-0.0577743489497769	0.155582213219717	-0.371342891672241	0.71048248276162	   
df.mm.trans2:probe4	-0.0480298722262064	0.155582213219717	-0.308710560367061	0.757623722476874	   
df.mm.trans2:probe5	-0.295059170937206	0.155582213219717	-1.89648395424556	0.0582634396791543	.  
df.mm.trans2:probe6	0.000293879902124864	0.155582213219717	0.00188890423939296	0.998493353879921	   
df.mm.trans3:probe2	0.1578068294864	0.155582213219717	1.01429865420118	0.310753182323003	   
df.mm.trans3:probe3	0.120050204841587	0.155582213219717	0.771619083937631	0.440572573614306	   
df.mm.trans3:probe4	0.154180312275341	0.155582213219717	0.990989323809163	0.321996539220347	   
df.mm.trans3:probe5	-0.0519687445328517	0.155582213219717	-0.334027543749234	0.738448100939109	   
df.mm.trans3:probe6	-0.0680887635650319	0.155582213219717	-0.437638481648768	0.661768905811134	   
df.mm.trans3:probe7	-0.151566497463951	0.155582213219717	-0.974189107657856	0.330263128471925