chr7.22125_chr7_106154583_106158770_+_2.R 

fitVsDatCorrelation=0.790637345483553
cont.fitVsDatCorrelation=0.280804151027199

fstatistic=11084.9287879852,52,692
cont.fstatistic=4503.4930267833,52,692

residuals=-0.478302459218023,-0.08805250336714,-0.00576730838181721,0.0786586382609045,0.792985594566877
cont.residuals=-0.537355830754821,-0.160466148924666,-0.0331487427387822,0.125405634303264,1.01626729047788

predictedValues:
Include	Exclude	Both
chr7.22125_chr7_106154583_106158770_+_2.R.tl.Lung	53.9477194754717	48.7484237865531	76.0871874479934
chr7.22125_chr7_106154583_106158770_+_2.R.tl.cerebhem	59.1226033428102	52.3617016849816	70.7776000094167
chr7.22125_chr7_106154583_106158770_+_2.R.tl.cortex	51.2987359335112	45.4903485789418	67.4270812318095
chr7.22125_chr7_106154583_106158770_+_2.R.tl.heart	51.6454056545886	44.3065086167726	61.4754313195238
chr7.22125_chr7_106154583_106158770_+_2.R.tl.kidney	53.9147195559747	44.9024260472014	63.764550992692
chr7.22125_chr7_106154583_106158770_+_2.R.tl.liver	52.9411239617025	43.5215544043158	57.5526591753324
chr7.22125_chr7_106154583_106158770_+_2.R.tl.stomach	52.2069295392415	48.4346621299677	81.1594432391788
chr7.22125_chr7_106154583_106158770_+_2.R.tl.testicle	52.8367139132506	51.183767266977	85.1304474355732


diffExp=5.1992956889186,6.76090165782858,5.80838735456946,7.33889703781596,9.01229350877332,9.41956955738674,3.77226740927382,1.65294664627360
diffExpScore=0.979985813488614
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=0,0,0,0,0,0,0,0
diffExp1.3Score=0
diffExp1.2=0,0,0,0,1,1,0,0
diffExp1.2Score=0.666666666666667

cont.predictedValues:
Include	Exclude	Both
Lung	56.7098750456173	54.4124195456047	67.7153791318878
cerebhem	55.4042577590449	55.3242146156236	54.6681164040933
cortex	54.0105760495295	54.4179045320216	53.7915443833511
heart	54.7564213950965	56.6088384504196	56.9675376522331
kidney	53.3711036811934	50.7836279527695	57.6371957032439
liver	52.2796536208603	52.4509652025595	55.9760410792402
stomach	54.4741911495757	54.9471916585337	44.4139720716743
testicle	55.6457518679361	49.0652363896297	60.4725356212282
cont.diffExp=2.29745550001267,0.0800431434212925,-0.407328482492069,-1.85241705532307,2.58747572842387,-0.171311581699150,-0.47300050895803,6.58051547830641
cont.diffExpScore=1.49869305165337

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=0.625850534230273
cont.tran.correlation=0.174426464930534

tran.covariance=0.00189414157061876
cont.tran.covariance=0.000206638355835988

tran.mean=50.4289589932664
cont.tran.mean=54.041389307251

weightedLogRatios:
wLogRatio
Lung	0.39902051683327
cerebhem	0.488045974051602
cortex	0.465953373037481
heart	0.592811214087335
kidney	0.712614433193914
liver	0.758465008621177
stomach	0.293826775372985
testicle	0.125587991421362

cont.weightedLogRatios:
wLogRatio
Lung	0.166137954609394
cerebhem	0.00580316714077902
cortex	-0.0300003178027653
heart	-0.133731696045364
kidney	0.196417383848631
liver	-0.0129492880209807
stomach	-0.0345998804941660
testicle	0.497892112478671

varWeightedLogRatios=0.0444949973078217
cont.varWeightedLogRatios=0.0400911060325709

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.3473443361932	0.0767830337604237	43.5948434472841	1.19768412642787e-200	***
df.mm.trans1	0.494043786784853	0.0689623929925085	7.16395944726747	2.01145146845285e-12	***
df.mm.trans2	0.427499745489455	0.0634202863084481	6.74074133645953	3.32346330503827e-11	***
df.mm.exp2	0.235437786139079	0.0868700861633138	2.71022853248311	0.00689026109811564	** 
df.mm.exp3	0.00131116154469442	0.0868700861633139	0.0150933607022038	0.987962048167904	   
df.mm.exp4	0.0740868254183342	0.0868700861633139	0.85284622924228	0.394039666281035	   
df.mm.exp5	0.0938895493279349	0.0868700861633139	1.0808041464518	0.280160761630467	   
df.mm.exp6	0.146928007847229	0.0868700861633139	1.69135331086247	0.0912195938732222	.  
df.mm.exp7	-0.103793099967859	0.0868700861633139	-1.19480829997947	0.232571274960464	   
df.mm.exp8	-0.0843644292987546	0.0868700861633139	-0.97115627513194	0.331809786752069	   
df.mm.trans1:exp2	-0.143839895311823	0.0831717753458855	-1.72943158557862	0.084177820957855	.  
df.mm.trans2:exp2	-0.163935210249935	0.0723917384694282	-2.26455689165644	0.0238484364492509	*  
df.mm.trans1:exp3	-0.0516604700789554	0.0831717753458855	-0.621129822756766	0.53471874564796	   
df.mm.trans2:exp3	-0.0704838415699954	0.0723917384694283	-0.973644825503968	0.330573136543138	   
df.mm.trans1:exp4	-0.117701005052659	0.0831717753458855	-1.41515561695272	0.157472720211625	   
df.mm.trans2:exp4	-0.169628102124911	0.0723917384694282	-2.34319696848483	0.0194015313390098	*  
df.mm.trans1:exp5	-0.0945014383381035	0.0831717753458855	-1.13622004514274	0.256257813324745	   
df.mm.trans2:exp5	-0.176070588145380	0.0723917384694282	-2.43219173717918	0.0152603088225848	*  
df.mm.trans1:exp6	-0.165763000149237	0.0831717753458855	-1.99301986112333	0.0466515353100627	*  
df.mm.trans2:exp6	-0.260344553264068	0.0723917384694283	-3.59632961949124	0.000345700613449281	***
df.mm.trans1:exp7	0.0709929161047732	0.0831717753458855	0.853569805496346	0.393638756285478	   
df.mm.trans2:exp7	0.0973359527429048	0.0723917384694282	1.34457266534648	0.179203831196659	   
df.mm.trans1:exp8	0.0635552979056356	0.0831717753458855	0.764145019645534	0.445041297162031	   
df.mm.trans2:exp8	0.133114001170168	0.0723917384694282	1.83880100111677	0.0663727920749636	.  
df.mm.trans1:probe2	0.367888915950187	0.0415858876729427	8.84648462583013	7.46519101199521e-18	***
df.mm.trans1:probe3	0.261667706511541	0.0415858876729428	6.29222366417807	5.55102748880293e-10	***
df.mm.trans1:probe4	0.0940698971206466	0.0415858876729428	2.26206298301170	0.0240028933126512	*  
df.mm.trans1:probe5	0.467828859229362	0.0415858876729428	11.2497023728015	4.42339628228203e-27	***
df.mm.trans1:probe6	0.129517316194559	0.0415858876729427	3.11445356687259	0.00191892236344550	** 
df.mm.trans1:probe7	0.477548653348611	0.0415858876729428	11.483430559529	4.63570436114725e-28	***
df.mm.trans1:probe8	0.209109596071732	0.0415858876729427	5.02837880283571	6.30804952475825e-07	***
df.mm.trans1:probe9	0.26631578728808	0.0415858876729428	6.40399429206737	2.79446505343086e-10	***
df.mm.trans1:probe10	-0.0215993133134426	0.0415858876729428	-0.519390459650953	0.603654561542875	   
df.mm.trans1:probe11	0.36412706911868	0.0415858876729428	8.7560249280333	1.54136413527726e-17	***
df.mm.trans1:probe12	0.213209445527062	0.0415858876729428	5.12696632097584	3.82580508591828e-07	***
df.mm.trans1:probe13	0.312003378549813	0.0415858876729428	7.50262639584854	1.92663985696092e-13	***
df.mm.trans1:probe14	0.164500864822602	0.0415858876729428	3.95568963481889	8.41790823951039e-05	***
df.mm.trans1:probe15	0.137151749284931	0.0415858876729428	3.29803587129311	0.00102344878810736	** 
df.mm.trans1:probe16	0.199755906523970	0.0415858876729427	4.80345419328245	1.91298970473844e-06	***
df.mm.trans1:probe17	-0.0113205672913373	0.0415858876729428	-0.272221369431123	0.785533013885655	   
df.mm.trans1:probe18	-0.097883471684359	0.0415858876729428	-2.35376655788078	0.0188629797024780	*  
df.mm.trans1:probe19	0.140724829622532	0.0415858876729428	3.38395637311579	0.000754782543019623	***
df.mm.trans1:probe20	-0.0134513905662394	0.0415858876729428	-0.323460465050776	0.746444268974936	   
df.mm.trans1:probe21	0.0540107947245191	0.0415858876729428	1.29877700698116	0.194453074767469	   
df.mm.trans1:probe22	-0.049493608107238	0.0415858876729428	-1.1901539410794	0.234394030611196	   
df.mm.trans2:probe2	0.0530264750570242	0.0415858876729428	1.27510744688336	0.202699143727690	   
df.mm.trans2:probe3	0.222444048525775	0.0415858876729428	5.34902730164649	1.20303154890139e-07	***
df.mm.trans2:probe4	0.202735244418401	0.0415858876729428	4.87509719674223	1.34992685468996e-06	***
df.mm.trans2:probe5	0.292934160256535	0.0415858876729428	7.04407616738521	4.51649748970439e-12	***
df.mm.trans2:probe6	0.23531911563695	0.0415858876729428	5.65862913610611	2.23503037946188e-08	***
df.mm.trans3:probe2	0.158946217176672	0.0415858876729428	3.82211913875024	0.000144227522368173	***
df.mm.trans3:probe3	0.0300298354645222	0.0415858876729428	0.722116014468549	0.470467094393955	   

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.74286375521754	0.120358506410496	31.0976254761097	1.59478810183202e-133	***
df.mm.trans1	0.21392563434451	0.108099539866711	1.97896896331182	0.0482155060850011	*  
df.mm.trans2	0.256007135340839	0.099412208171243	2.5752082168807	0.0102244963489146	*  
df.mm.exp2	0.207359010389436	0.136170105690153	1.52279392997806	0.128267093593273	   
df.mm.exp3	0.181529353194617	0.136170105690154	1.33310723579576	0.182935319640565	   
df.mm.exp4	0.177350719353573	0.136170105690153	1.30242036939535	0.193206016242768	   
df.mm.exp5	0.0314479032757575	0.136170105690154	0.230945721282726	0.817425233546012	   
df.mm.exp6	0.0723347720859312	0.136170105690154	0.531208900215767	0.595444482750495	   
df.mm.exp7	0.391318031831601	0.136170105690153	2.87374405599729	0.00418075530906416	** 
df.mm.exp8	-0.0092602664369531	0.136170105690154	-0.0680051351213919	0.945801190809516	   
df.mm.trans1:exp2	-0.230650923364091	0.130372950453799	-1.76916241107720	0.0773071854844619	.  
df.mm.trans2:exp2	-0.190740748660544	0.113475088075128	-1.68090416932976	0.09323278808008	.  
df.mm.trans1:exp3	-0.230297831669041	0.130372950453799	-1.76645409087872	0.077760517009896	.  
df.mm.trans2:exp3	-0.181428554332386	0.113475088075128	-1.59884039228300	0.110312529291568	   
df.mm.trans1:exp4	-0.212404430410326	0.130372950453799	-1.62920628605086	0.103724460853514	   
df.mm.trans2:exp4	-0.137778018243718	0.113475088075128	-1.21416974052049	0.225097103810046	   
df.mm.trans1:exp5	-0.0921267919698335	0.130372950453799	-0.706640385518323	0.480027845571889	   
df.mm.trans2:exp5	-0.100466313306383	0.113475088075128	-0.885360082204723	0.376269992226111	   
df.mm.trans1:exp6	-0.153675867444712	0.130372950453799	-1.17874042820847	0.238906693631288	   
df.mm.trans2:exp6	-0.109048463352239	0.113475088075128	-0.960990338954765	0.336892683533080	   
df.mm.trans1:exp7	-0.431539357845513	0.130372950453799	-3.31003752192018	0.000981217733678852	***
df.mm.trans2:exp7	-0.38153788777901	0.113475088075128	-3.36230527996072	0.000815483480986946	***
df.mm.trans1:exp8	-0.00968235399131728	0.130372950453799	-0.0742665864170076	0.940819726228333	   
df.mm.trans2:exp8	-0.0941813943050971	0.113475088075128	-0.829974189953859	0.406839604407218	   
df.mm.trans1:probe2	0.123567978156925	0.0651864752268993	1.89560760459609	0.0584283655709776	.  
df.mm.trans1:probe3	0.0569372210169711	0.0651864752268993	0.873451445545807	0.382720056823898	   
df.mm.trans1:probe4	0.115898049762683	0.0651864752268993	1.77794625893283	0.0758517321903172	.  
df.mm.trans1:probe5	0.142624416952769	0.0651864752268993	2.18794491428361	0.0290073509296413	*  
df.mm.trans1:probe6	0.0952774072506514	0.0651864752268993	1.46161311712303	0.144301193833826	   
df.mm.trans1:probe7	0.0735584075304161	0.0651864752268993	1.12843051069069	0.259529208459535	   
df.mm.trans1:probe8	0.0606176217229767	0.0651864752268993	0.929911020836463	0.352741427777421	   
df.mm.trans1:probe9	0.0668680076426682	0.0651864752268993	1.02579572541568	0.305346317992141	   
df.mm.trans1:probe10	0.194368301176725	0.0651864752268993	2.98172742889032	0.00296692740660484	** 
df.mm.trans1:probe11	0.109895392789322	0.0651864752268993	1.68586186638871	0.0922731976638888	.  
df.mm.trans1:probe12	0.0519864285837887	0.0651864752268993	0.797503291945694	0.425432351911212	   
df.mm.trans1:probe13	0.0928274872289303	0.0651864752268993	1.42402986057796	0.154888581105930	   
df.mm.trans1:probe14	0.128864981775826	0.0651864752268993	1.97686684741393	0.0484532413538935	*  
df.mm.trans1:probe15	0.12233274855498	0.0651864752268993	1.87665843457815	0.0609855054782991	.  
df.mm.trans1:probe16	0.129427182742192	0.0651864752268993	1.98549135064729	0.0474841096131521	*  
df.mm.trans1:probe17	0.0186380506932372	0.0651864752268993	0.285918982862048	0.775025741597365	   
df.mm.trans1:probe18	0.0934272389443996	0.0651864752268993	1.43323041503933	0.152243630994082	   
df.mm.trans1:probe19	0.103782763068948	0.0651864752268993	1.59209042531757	0.111821054203373	   
df.mm.trans1:probe20	0.0385750102647529	0.0651864752268993	0.591764014398417	0.554201895007088	   
df.mm.trans1:probe21	0.111370822610984	0.0651864752268993	1.70849585321690	0.0879928073837146	.  
df.mm.trans1:probe22	0.0981287082565463	0.0651864752268993	1.50535380099910	0.132689431372208	   
df.mm.trans2:probe2	0.055075035094662	0.0651864752268993	0.844884385955189	0.398467401018803	   
df.mm.trans2:probe3	-0.0459759085499992	0.0651864752268993	-0.705298275293572	0.48086196713743	   
df.mm.trans2:probe4	-0.0717665457866264	0.0651864752268993	-1.10094226657943	0.271304586879720	   
df.mm.trans2:probe5	0.0564295129134908	0.0651864752268993	0.86566289582421	0.386975066183281	   
df.mm.trans2:probe6	-0.0142682542130611	0.0651864752268993	-0.218883658970616	0.826805215700614	   
df.mm.trans3:probe2	0.0434087956583603	0.0651864752268993	0.665917209164388	0.505685935187119	   
df.mm.trans3:probe3	-0.0358584102868514	0.0651864752268993	-0.550089725852433	0.58243533707854