chr13.6840_chr13_62133350_62139152_-_2.R 

fitVsDatCorrelation=0.849617069993918
cont.fitVsDatCorrelation=0.213416962388790

fstatistic=15108.2119100610,59,853
cont.fstatistic=4392.6554183582,59,853

residuals=-0.514060701048892,-0.0791040779060797,0.000908147677579866,0.0780900307715414,0.77496967404192
cont.residuals=-0.489063769912431,-0.171894910129057,-0.0311746511936647,0.127414503115215,0.928871056946246

predictedValues:
Include	Exclude	Both
chr13.6840_chr13_62133350_62139152_-_2.R.tl.Lung	70.9549392806681	73.8451544579847	64.9201119685642
chr13.6840_chr13_62133350_62139152_-_2.R.tl.cerebhem	67.6821334115759	52.5502605389127	58.325006781384
chr13.6840_chr13_62133350_62139152_-_2.R.tl.cortex	64.0294052680562	63.9694325062219	58.1029139225311
chr13.6840_chr13_62133350_62139152_-_2.R.tl.heart	68.5687968072382	64.2817025716904	58.3604798317614
chr13.6840_chr13_62133350_62139152_-_2.R.tl.kidney	69.8293502092766	69.8062636309728	60.9962098485095
chr13.6840_chr13_62133350_62139152_-_2.R.tl.liver	69.938615847008	62.3528087393208	56.6511596884566
chr13.6840_chr13_62133350_62139152_-_2.R.tl.stomach	73.9184565948113	57.7696490812544	61.6121920820517
chr13.6840_chr13_62133350_62139152_-_2.R.tl.testicle	68.1538490242425	61.9178526311272	54.86507379201


diffExp=-2.89021517731656,15.1318728726632,0.0599727618342953,4.28709423554776,0.0230865783037899,7.58580710768717,16.1488075135569,6.23599639311524
diffExpScore=1.10046630930138
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=0,1,0,0,0,0,1,0
diffExp1.2Score=0.666666666666667

cont.predictedValues:
Include	Exclude	Both
Lung	60.7912407614698	59.9119667160164	59.9764589164482
cerebhem	60.1421250621846	59.9845574034389	66.822828762834
cortex	63.932668830785	60.7013696475068	57.9984316014355
heart	62.4161659492088	61.2634862462625	61.5342462736497
kidney	60.3467051179007	60.4289000824575	63.3786049010221
liver	65.5693886768394	58.3988863584837	56.5272559452694
stomach	62.396039214956	58.0727213890309	62.1538588574955
testicle	63.5955332211186	60.3446554249185	61.7906609489959
cont.diffExp=0.879274045453393,0.157567658745670,3.23129918327828,1.15267970294639,-0.0821949645568125,7.17050231835571,4.32331782592507,3.25087779620005
cont.diffExpScore=0.960366302387915

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=0.0722753444624185
cont.tran.correlation=-0.287103391669285

tran.covariance=0.00028542045626322
cont.tran.covariance=-0.000162757795500024

tran.mean=66.2230419125226
cont.tran.mean=61.1435256314111

weightedLogRatios:
wLogRatio
Lung	-0.170960767615877
cerebhem	1.03455225880212
cortex	0.00389720994522193
heart	0.270875800415669
kidney	0.00140398353748672
liver	0.481075131614754
stomach	1.03029513665814
testicle	0.400512891768751

cont.weightedLogRatios:
wLogRatio
Lung	0.0597370854656736
cerebhem	0.0107437042708256
cortex	0.214297677984548
heart	0.0768820061196359
kidney	-0.00558165841754085
liver	0.477748535228059
stomach	0.294231192447302
testicle	0.216510884488131

varWeightedLogRatios=0.208885217982093
cont.varWeightedLogRatios=0.0273226702214143

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.67892771088205	0.0613959852402566	76.2090174556582	0	***
df.mm.trans1	-0.16616913502064	0.0530200710571421	-3.13407982500725	0.00178290208623013	** 
df.mm.trans2	-0.41699398980769	0.0468429931325383	-8.9019501513885	3.24757119986322e-18	***
df.mm.exp2	-0.280296585810080	0.0602550667540225	-4.65183429228163	3.81199000138954e-06	***
df.mm.exp3	-0.135325972551594	0.0602550667540225	-2.24588536436333	0.0249666081471662	*  
df.mm.exp4	-0.0663842877207212	0.0602550667540224	-1.10172125427593	0.270893639943393	   
df.mm.exp5	-0.00989151825320893	0.0602550667540225	-0.164160771634173	0.869643471302796	   
df.mm.exp6	-0.047343742166615	0.0602550667540224	-0.785722176026873	0.43224846255975	   
df.mm.exp7	-0.152291634993845	0.0602550667540224	-2.52744944446815	0.0116690435172752	*  
df.mm.exp8	-0.0481587269141298	0.0602550667540224	-0.799247756387472	0.424369259134731	   
df.mm.trans1:exp2	0.233073805107986	0.0556950112038588	4.18482374040419	3.14972617299987e-05	***
df.mm.trans2:exp2	-0.0599037524824387	0.0411334918151617	-1.45632548657973	0.145670631992003	   
df.mm.trans1:exp3	0.0326233901645487	0.0556950112038588	0.585750670650522	0.558198017732837	   
df.mm.trans2:exp3	-0.00823906880170043	0.0411334918151617	-0.200300738841324	0.841293128829542	   
df.mm.trans1:exp4	0.0321768443944701	0.0556950112038588	0.577732972827568	0.563596881787093	   
df.mm.trans2:exp4	-0.0723110784851475	0.0411334918151617	-1.75796109919591	0.0791127593503247	.  
df.mm.trans1:exp5	-0.00609908779730917	0.0556950112038588	-0.109508691451463	0.912824785043706	   
df.mm.trans2:exp5	-0.0463551326984626	0.0411334918151617	-1.12694377872817	0.260083169865869	   
df.mm.trans1:exp6	0.0329166654865797	0.0556950112038588	0.591016408383434	0.554665995064554	   
df.mm.trans2:exp6	-0.121817932305080	0.0411334918151617	-2.96152665211317	0.00314609017052777	** 
df.mm.trans1:exp7	0.193209165168194	0.0556950112038588	3.46905694050399	0.000548454411181221	***
df.mm.trans2:exp7	-0.0932152231701237	0.0411334918151617	-2.26616363106243	0.0236911580663837	*  
df.mm.trans1:exp8	0.00788134463219288	0.0556950112038588	0.14150898728335	0.887501273459251	   
df.mm.trans2:exp8	-0.128003117662922	0.0411334918151617	-3.11189524677651	0.00192082600832410	** 
df.mm.trans1:probe2	-0.595543514712399	0.0381317674710705	-15.6180411821776	1.49845140837234e-48	***
df.mm.trans1:probe3	-0.712726179479631	0.0381317674710705	-18.6911393504210	1.31440408729497e-65	***
df.mm.trans1:probe4	-0.296865717523472	0.0381317674710705	-7.7852598295816	2.01268510781303e-14	***
df.mm.trans1:probe5	-0.52100906363273	0.0381317674710705	-13.6633861524516	1.40455271603475e-38	***
df.mm.trans1:probe6	0.321457404374941	0.0381317674710705	8.43017320450254	1.46058947528278e-16	***
df.mm.trans1:probe7	-0.62248180002147	0.0381317674710705	-16.3244937569109	2.45011003472988e-52	***
df.mm.trans1:probe8	-0.446950596783496	0.0381317674710705	-11.7212137392421	1.58911749061247e-29	***
df.mm.trans1:probe9	-0.51977208022128	0.0381317674710705	-13.6309464442113	2.02387949515480e-38	***
df.mm.trans1:probe10	-0.239542682945146	0.0381317674710705	-6.28197166907828	5.32322607019742e-10	***
df.mm.trans1:probe11	-0.526827148126074	0.0381317674710705	-13.8159645635562	2.50136254064429e-39	***
df.mm.trans1:probe12	-0.369702050889299	0.0381317674710705	-9.69538197173213	3.71421019789938e-21	***
df.mm.trans1:probe13	-0.466280021999632	0.0381317674710705	-12.2281250758540	8.49086897832445e-32	***
df.mm.trans1:probe14	-0.456943350196194	0.0381317674710705	-11.9832722294571	1.08363272501015e-30	***
df.mm.trans1:probe15	-0.150291749434125	0.0381317674710705	-3.94137904958502	8.76490093300234e-05	***
df.mm.trans1:probe16	-0.225013928085984	0.0381317674710705	-5.90095720731266	5.20991944299929e-09	***
df.mm.trans1:probe17	-0.404623643545977	0.0381317674710705	-10.6111956088307	8.57871065406584e-25	***
df.mm.trans1:probe18	-0.438801591522497	0.0381317674710705	-11.5075072734408	1.37622722379853e-28	***
df.mm.trans1:probe19	-0.472179756070515	0.0381317674710705	-12.3828447351344	1.66797310069505e-32	***
df.mm.trans1:probe20	-0.455047175562476	0.0381317674710705	-11.9335453282544	1.80958881453044e-30	***
df.mm.trans1:probe21	-0.224551013627377	0.0381317674710705	-5.88881734364234	5.59123894447238e-09	***
df.mm.trans1:probe22	-0.199138206219289	0.0381317674710705	-5.22237020275469	2.22100560123507e-07	***
df.mm.trans2:probe2	0.169285734104185	0.0381317674710705	4.43949350715561	1.02007290990683e-05	***
df.mm.trans2:probe3	0.130616007355790	0.0381317674710705	3.42538560413924	0.000643241113878814	***
df.mm.trans2:probe4	0.290343615271956	0.0381317674710705	7.61421865619607	7.0352100671517e-14	***
df.mm.trans2:probe5	0.0257730840073331	0.0381317674710705	0.675895341774714	0.499290295796819	   
df.mm.trans2:probe6	0.0245683185079956	0.0381317674710705	0.644300543546398	0.519553776011691	   
df.mm.trans3:probe2	-0.0536753137058434	0.0381317674710705	-1.40762721650827	0.159605785489736	   
df.mm.trans3:probe3	0.0462791250305985	0.0381317674710705	1.21366325507227	0.225212279574548	   
df.mm.trans3:probe4	0.161370588900827	0.0381317674710705	4.23191998700964	2.56816015652352e-05	***
df.mm.trans3:probe5	0.0471093779987767	0.0381317674710705	1.23543651719048	0.217008237063588	   
df.mm.trans3:probe6	-0.0169087338879353	0.0381317674710705	-0.443429062153058	0.657567864326131	   
df.mm.trans3:probe7	0.225832135028688	0.0381317674710705	5.92241456418248	4.59699886260265e-09	***
df.mm.trans3:probe8	-0.137055773325418	0.0381317674710705	-3.59426752062825	0.00034396102650617	***
df.mm.trans3:probe9	0.0337787952751787	0.0381317674710705	0.88584394365684	0.375951282500475	   
df.mm.trans3:probe10	0.467198611757201	0.0381317674710705	12.2522149572965	6.59644733612628e-32	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.08935868831093	0.113730541963863	35.9565567674011	4.64080047481672e-173	***
df.mm.trans1	0.0192058000534797	0.0982149140973063	0.195548713044249	0.845009977059205	   
df.mm.trans2	-0.0083071784767077	0.0867724326814764	-0.0957352262694032	0.923753348788346	   
df.mm.exp2	-0.117616947160512	0.111617093058886	-1.05375390038568	0.292293993749852	   
df.mm.exp3	0.0970109315123463	0.111617093058886	0.869140459169334	0.385014792858097	   
df.mm.exp4	0.0230446087850234	0.111617093058886	0.206461287903867	0.836479870358781	   
df.mm.exp5	-0.0539223655684281	0.111617093058886	-0.483101325170512	0.629147761771189	   
df.mm.exp6	0.109313001793372	0.111617093058886	0.979357182646759	0.327681200903899	   
df.mm.exp7	-0.0407849057117231	0.111617093058886	-0.365400178359835	0.714903294754035	   
df.mm.exp8	0.0224935420319445	0.111617093058886	0.201524169959144	0.840336778790072	   
df.mm.trans1:exp2	0.106881747180406	0.103170000189931	1.03597699896910	0.300506468723842	   
df.mm.trans2:exp2	0.118827836247170	0.0761960948862999	1.55950034479438	0.119248918472592	   
df.mm.trans1:exp3	-0.0466261636345625	0.103170000189931	-0.451935286892759	0.651430496166155	   
df.mm.trans2:exp3	-0.0839209328911736	0.0761960948862998	-1.10138102243167	0.271041542810083	   
df.mm.trans1:exp4	0.00333399056609491	0.103170000189931	0.0323155041189996	0.974228004866192	   
df.mm.trans2:exp4	-0.000736863383642132	0.0761960948862998	-0.0096706187468227	0.992286344089986	   
df.mm.trans1:exp5	0.0465830032274927	0.103170000189931	0.451516944283567	0.65173178839615	   
df.mm.trans2:exp5	0.0625135708623448	0.0761960948862999	0.820430114635504	0.412200158525626	   
df.mm.trans1:exp6	-0.0336497629459531	0.103170000189931	-0.326158407327765	0.744384509110239	   
df.mm.trans2:exp6	-0.134892444744105	0.0761960948862998	-1.77033278339779	0.0770288553880445	.  
df.mm.trans1:exp7	0.0668409927828777	0.103170000189931	0.647872372393396	0.517241839302109	   
df.mm.trans2:exp7	0.00960468453915662	0.0761960948862999	0.126052188809529	0.899720317170348	   
df.mm.trans1:exp8	0.0226039813050094	0.103170000189931	0.219094516462117	0.826628834781847	   
df.mm.trans2:exp8	-0.0152974214624707	0.0761960948862998	-0.200763851287886	0.840931088451305	   
df.mm.trans1:probe2	-0.113892699230866	0.0706356704522968	-1.61239637850939	0.107245606228772	   
df.mm.trans1:probe3	-0.0379516872705637	0.0706356704522969	-0.537287846601443	0.591208923962551	   
df.mm.trans1:probe4	-0.0110876295265922	0.0706356704522968	-0.156969268580528	0.875306213038073	   
df.mm.trans1:probe5	0.00934275270024032	0.0706356704522968	0.132266780231807	0.894804474541264	   
df.mm.trans1:probe6	-0.00763133434257737	0.0706356704522968	-0.108037968546375	0.913990980628702	   
df.mm.trans1:probe7	0.0444292464908641	0.0706356704522968	0.628991644113706	0.529522928438496	   
df.mm.trans1:probe8	-0.0157433837399141	0.0706356704522968	-0.222881493714231	0.82368109894687	   
df.mm.trans1:probe9	-0.0149805076592032	0.0706356704522968	-0.212081340253154	0.832094241908751	   
df.mm.trans1:probe10	0.036284352334048	0.0706356704522968	0.513683130657793	0.607606578263104	   
df.mm.trans1:probe11	0.0120772186642269	0.0706356704522968	0.17097903349531	0.86428080017447	   
df.mm.trans1:probe12	0.0143275709444435	0.0706356704522968	0.202837615226141	0.839310327886083	   
df.mm.trans1:probe13	0.0290705977038461	0.0706356704522968	0.411556902025567	0.680767612468717	   
df.mm.trans1:probe14	-0.0329882283371907	0.0706356704522968	-0.467019398640366	0.640605264404205	   
df.mm.trans1:probe15	-0.0134520186374658	0.0706356704522968	-0.190442287180533	0.849007876884259	   
df.mm.trans1:probe16	0.0430031381101379	0.0706356704522968	0.608802009449032	0.542817772691258	   
df.mm.trans1:probe17	0.000743069869659764	0.0706356704522968	0.0105197538991520	0.991609065372195	   
df.mm.trans1:probe18	0.0297724312482755	0.0706356704522968	0.421492866955684	0.673501409957437	   
df.mm.trans1:probe19	-0.0576011721838621	0.0706356704522969	-0.815468612600803	0.415031759521574	   
df.mm.trans1:probe20	-0.0189399935273685	0.0706356704522968	-0.268136387834804	0.788659165233981	   
df.mm.trans1:probe21	0.0284210874229144	0.0706356704522968	0.402361685546799	0.687518669298315	   
df.mm.trans1:probe22	0.0409963507575367	0.0706356704522968	0.580391613685089	0.561803845793944	   
df.mm.trans2:probe2	0.046800005224227	0.0706356704522968	0.662554838434399	0.507794676871764	   
df.mm.trans2:probe3	0.0352039693317454	0.0706356704522968	0.498387983101542	0.618339084294651	   
df.mm.trans2:probe4	0.0864129640122191	0.0706356704522968	1.22336156022724	0.221531008203447	   
df.mm.trans2:probe5	-0.00708472086687118	0.0706356704522968	-0.100299477891355	0.920130140282988	   
df.mm.trans2:probe6	0.0278638393358952	0.0706356704522968	0.3944726390714	0.693330728235364	   
df.mm.trans3:probe2	-0.0193007749159589	0.0706356704522968	-0.273244025184039	0.78473178134897	   
df.mm.trans3:probe3	0.0112485813467281	0.0706356704522968	0.159247888137831	0.873511273165477	   
df.mm.trans3:probe4	-0.0466232004132634	0.0706356704522968	-0.660051785659059	0.509398780694441	   
df.mm.trans3:probe5	-0.0617230444142478	0.0706356704522968	-0.87382258877166	0.382460814351547	   
df.mm.trans3:probe6	0.0662833391129633	0.0706356704522968	0.938383378943464	0.348313047520295	   
df.mm.trans3:probe7	0.010967865708589	0.0706356704522968	0.155273753874766	0.876642240629454	   
df.mm.trans3:probe8	0.0235756713365037	0.0706356704522968	0.333764388241	0.738639389608106	   
df.mm.trans3:probe9	0.0345650540399511	0.0706356704522968	0.48934276150595	0.624724857544865	   
df.mm.trans3:probe10	-0.0820452522820405	0.0706356704522968	-1.16152719662297	0.245752485290779