chr10.2569_chr10_77995220_77999449_+_2.R 

fitVsDatCorrelation=0.83141056750399
cont.fitVsDatCorrelation=0.304915506613307

fstatistic=9467.60280584348,51,669
cont.fstatistic=3214.16805436864,51,669

residuals=-0.438238336704237,-0.09523499430205,-0.0089086403104158,0.0802009106085422,1.0117805052676
cont.residuals=-0.490934849189508,-0.179991908135206,-0.0399651969413431,0.122236708210337,1.07056531148161

predictedValues:
Include	Exclude	Both
chr10.2569_chr10_77995220_77999449_+_2.R.tl.Lung	74.3473418403097	52.7002190568774	104.089419735256
chr10.2569_chr10_77995220_77999449_+_2.R.tl.cerebhem	65.0557872684678	59.2215847921259	61.1381003663876
chr10.2569_chr10_77995220_77999449_+_2.R.tl.cortex	59.4164769301762	49.4686029453555	57.2356429060957
chr10.2569_chr10_77995220_77999449_+_2.R.tl.heart	64.1841661814109	51.5953270639417	69.7747298009477
chr10.2569_chr10_77995220_77999449_+_2.R.tl.kidney	62.0784114617808	49.2672411462869	67.563461186962
chr10.2569_chr10_77995220_77999449_+_2.R.tl.liver	63.0753079018767	54.8201118543139	66.3953908026208
chr10.2569_chr10_77995220_77999449_+_2.R.tl.stomach	62.8617967093606	51.7116889150293	57.7097285857627
chr10.2569_chr10_77995220_77999449_+_2.R.tl.testicle	62.8542223344758	55.090603720705	66.0475749276571


diffExp=21.6471227834323,5.83420247634189,9.94787398482065,12.5888391174692,12.8111703154939,8.2551960475628,11.1501077943313,7.76361861377084
diffExpScore=0.989010763325062
diffExp1.5=0,0,0,0,0,0,0,0
diffExp1.5Score=0
diffExp1.4=1,0,0,0,0,0,0,0
diffExp1.4Score=0.5
diffExp1.3=1,0,0,0,0,0,0,0
diffExp1.3Score=0.5
diffExp1.2=1,0,1,1,1,0,1,0
diffExp1.2Score=0.833333333333333

cont.predictedValues:
Include	Exclude	Both
Lung	58.6397650725703	57.5352712480042	67.2086234894736
cerebhem	62.4964204369002	69.6179309449397	66.6482869437206
cortex	58.1052326446562	63.7110975539684	70.0675712965596
heart	63.8997735456969	73.1137294864109	58.2650455776683
kidney	57.8634727793158	61.1889341557682	54.2477233722242
liver	56.9822250217066	57.6033635780831	59.5917543568574
stomach	60.0257029119013	58.5103015665026	53.9750368566005
testicle	59.1666721304306	63.1434911874961	54.7973858230773
cont.diffExp=1.10449382456615,-7.12151050803951,-5.60586490931225,-9.213955940714,-3.32546137645238,-0.621138556376543,1.51540134539864,-3.97681905706553
cont.diffExpScore=1.15010841136239

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=0.235164396578632
cont.tran.correlation=0.855284146377583

tran.covariance=0.00107392718818021
cont.tran.covariance=0.00294915474745484

tran.mean=58.6093056326559
cont.tran.mean=61.350211516522

weightedLogRatios:
wLogRatio
Lung	1.42354998550773
cerebhem	0.387888056894796
cortex	0.731642670518307
heart	0.88478433046462
kidney	0.927520868943708
liver	0.571496233317293
stomach	0.789475790242
testicle	0.537230332594036

cont.weightedLogRatios:
wLogRatio
Lung	0.077236641907684
cerebhem	-0.452054149068811
cortex	-0.378387589568925
heart	-0.569063985677058
kidney	-0.228327317651492
liver	-0.0438884684108288
stomach	0.104376504539043
testicle	-0.267548711249713

varWeightedLogRatios=0.100780942339445
cont.varWeightedLogRatios=0.0610994243247363

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.89578585045226	0.0845446335280288	46.0796349559041	9.49190121555455e-210	***
df.mm.trans1	0.675611552815548	0.0758492144961219	8.90729795033132	4.89795321697663e-18	***
df.mm.trans2	0.112706352093515	0.0698671669347267	1.61315188576074	0.107183089140966	   
df.mm.exp2	0.515278807486975	0.0957346176086041	5.38236659171305	1.01821035677635e-07	***
df.mm.exp3	0.310615732012565	0.095734617608604	3.24454977490451	0.00123492758724538	** 
df.mm.exp4	0.231798550582107	0.095734617608604	2.42126157049876	0.0157317470727109	*  
df.mm.exp5	0.184473147805731	0.095734617608604	1.92692207284851	0.0544125431871208	.  
df.mm.exp6	0.324641671214761	0.095734617608604	3.39105831645985	0.000737190184831631	***
df.mm.exp7	0.403079497557393	0.095734617608604	4.21038395124029	2.89814090408636e-05	***
df.mm.exp8	0.331304771924483	0.095734617608604	3.46065801692519	0.000573105193902702	***
df.mm.trans1:exp2	-0.648781560309331	0.0914775945915717	-7.09224551876342	3.36626521646334e-12	***
df.mm.trans2:exp2	-0.398612336290919	0.0798481907825448	-4.99212734044887	7.6257753558514e-07	***
df.mm.trans1:exp3	-0.53479207499974	0.0914775945915717	-5.84615366623351	7.86450175767539e-09	***
df.mm.trans2:exp3	-0.373897159828957	0.0798481907825448	-4.68260027139767	3.43108010226578e-06	***
df.mm.trans1:exp4	-0.378789923280690	0.0914775945915716	-4.14079452976336	3.90396634221897e-05	***
df.mm.trans2:exp4	-0.252987055187457	0.0798481907825448	-3.16835049996851	0.00160287623492784	** 
df.mm.trans1:exp5	-0.364822781112187	0.0914775945915717	-3.98811077992425	7.39427404495926e-05	***
df.mm.trans2:exp5	-0.251833379628638	0.0798481907825448	-3.15390213805182	0.00168314832233618	** 
df.mm.trans1:exp6	-0.489060215466863	0.0914775945915717	-5.34622950735002	1.23362777590518e-07	***
df.mm.trans2:exp6	-0.285204152165425	0.0798481907825448	-3.57182986076839	0.000379926592474758	***
df.mm.trans1:exp7	-0.57088880417046	0.0914775945915717	-6.24075006256296	7.72927361292465e-10	***
df.mm.trans2:exp7	-0.422015262613649	0.0798481907825448	-5.2852200967577	1.70138345777067e-07	***
df.mm.trans1:exp8	-0.499234578294886	0.0914775945915716	-5.45745196431831	6.80960935814842e-08	***
df.mm.trans2:exp8	-0.286945213908079	0.0798481907825447	-3.59363450938461	0.000350044881397911	***
df.mm.trans1:probe2	-0.369722798562990	0.0457387972957858	-8.08335199922398	2.95354315388246e-15	***
df.mm.trans1:probe3	-0.447352724488126	0.0457387972957858	-9.78059658182886	3.31796382093888e-21	***
df.mm.trans1:probe4	-0.558215653917937	0.0457387972957858	-12.2044235292861	4.51180033959005e-31	***
df.mm.trans1:probe5	-0.13879612017496	0.0457387972957858	-3.03453803731189	0.00250245544173496	** 
df.mm.trans1:probe6	-0.367488298741643	0.0457387972957858	-8.03449851042546	4.25130267729842e-15	***
df.mm.trans1:probe7	0.484919330335306	0.0457387972957858	10.6019256955841	2.21347188112514e-24	***
df.mm.trans1:probe8	-0.103375167666735	0.0457387972957858	-2.26011993709026	0.024134513994684	*  
df.mm.trans1:probe9	-0.436615327586726	0.0457387972957858	-9.54584189792313	2.47985150159873e-20	***
df.mm.trans1:probe10	-0.257385193810546	0.0457387972957858	-5.62728381653927	2.69344981662694e-08	***
df.mm.trans1:probe11	-0.271266833307266	0.0457387972957858	-5.93078194761057	4.83387830185046e-09	***
df.mm.trans1:probe12	-0.478450061264553	0.0457387972957858	-10.4604862731849	8.03297594293255e-24	***
df.mm.trans1:probe13	-0.232505289815268	0.0457387972957858	-5.08332758099633	4.81938687870797e-07	***
df.mm.trans1:probe14	-0.300990777616185	0.0457387972957858	-6.58064477886735	9.46091136522013e-11	***
df.mm.trans1:probe15	-0.340688991727184	0.0457387972957858	-7.44857783478652	2.92055087709822e-13	***
df.mm.trans1:probe16	-0.504328862806202	0.0457387972957858	-11.0262816825896	4.3100230289966e-26	***
df.mm.trans1:probe17	-0.557729316880072	0.0457387972957858	-12.1937906078579	5.02038394378115e-31	***
df.mm.trans1:probe18	-0.515031193107887	0.0457387972957858	-11.2602696957084	4.69721762835302e-27	***
df.mm.trans1:probe19	-0.481648929152699	0.0457387972957858	-10.5304240082648	4.25330458394515e-24	***
df.mm.trans1:probe20	-0.323086816940277	0.0457387972957858	-7.06373660966474	4.07606679317107e-12	***
df.mm.trans1:probe21	-0.103828564298986	0.0457387972957858	-2.27003267330233	0.0235228954585178	*  
df.mm.trans2:probe2	0.0121920515114310	0.0457387972957858	0.266558200745571	0.789891480041246	   
df.mm.trans2:probe3	-0.120890383661414	0.0457387972957858	-2.64305995804031	0.00840840422205648	** 
df.mm.trans2:probe4	-0.139574274150111	0.0457387972957858	-3.05155103330561	0.00236675048670870	** 
df.mm.trans2:probe5	-0.0176109029490129	0.0457387972957858	-0.385032051348572	0.700336047210371	   
df.mm.trans2:probe6	-0.128969803721855	0.0457387972957858	-2.81970255771762	0.00494908769618791	** 
df.mm.trans3:probe2	-0.0327187212826075	0.0457387972957858	-0.715338470118059	0.474649492713294	   
df.mm.trans3:probe3	-0.0838415401992849	0.0457387972957858	-1.83305082678704	0.0672392177144467	.  

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.80871957328543	0.144906547651353	26.2839715321165	3.87340322495868e-105	***
df.mm.trans1	0.217301593475996	0.130002903271869	1.67151338937072	0.0950879562394018	.  
df.mm.trans2	0.316207974923429	0.119749882780384	2.64057022505267	0.00846978281948404	** 
df.mm.exp2	0.262692441723586	0.164085789357477	1.60094571718996	0.109861015848911	   
df.mm.exp3	0.0511447461525048	0.164085789357477	0.311695158689708	0.755369318329905	   
df.mm.exp4	0.468319973186942	0.164085789357477	2.85411658755324	0.0044491913314175	** 
df.mm.exp5	0.26248199177572	0.164085789357477	1.59966315671540	0.110145448336934	   
df.mm.exp6	0.0927934651206944	0.164085789357477	0.565517985951452	0.571911103192352	   
df.mm.exp7	0.259444367976711	0.164085789357477	1.58115074433098	0.1143162114876	   
df.mm.exp8	0.306116039114452	0.164085789357477	1.86558531554215	0.0625368804137993	.  
df.mm.trans1:exp2	-0.198996210935505	0.156789400658057	-1.26919428290626	0.204813146033158	   
df.mm.trans2:exp2	-0.0720684517957066	0.136857008891867	-0.52659671856959	0.598648216254688	   
df.mm.trans1:exp3	-0.0603020749238179	0.156789400658057	-0.384605557969643	0.700651903258047	   
df.mm.trans2:exp3	0.0508158444184387	0.136857008891867	0.371306115995776	0.710527100423068	   
df.mm.trans1:exp4	-0.382417207000058	0.156789400658057	-2.43905012325466	0.014984838270673	*  
df.mm.trans2:exp4	-0.228701978946435	0.136857008891867	-1.67110169072258	0.0951692700971496	.  
df.mm.trans1:exp5	-0.275808724951168	0.156789400658057	-1.75910312682859	0.0790170947009043	.  
df.mm.trans2:exp5	-0.200913805805789	0.136857008891867	-1.46805638551207	0.142558897935906	   
df.mm.trans1:exp6	-0.121467138947848	0.156789400658057	-0.774715245023205	0.438781659344274	   
df.mm.trans2:exp6	-0.0916106764221795	0.136857008891867	-0.669389731398867	0.503477844531922	   
df.mm.trans1:exp7	-0.236084566923421	0.156789400658057	-1.50574315567606	0.132605109731553	   
df.mm.trans2:exp7	-0.242639706839156	0.136857008891867	-1.77294322595395	0.0766930684411597	.  
df.mm.trans1:exp8	-0.297170677826307	0.156789400658057	-1.89534928113163	0.0584769395003992	.  
df.mm.trans2:exp8	-0.213104437462763	0.136857008891867	-1.55713206936402	0.119912045857829	   
df.mm.trans1:probe2	0.153951986763784	0.0783947003290284	1.96380604961351	0.0499662983452056	*  
df.mm.trans1:probe3	0.104060603551448	0.0783947003290284	1.32739334565599	0.184831390555771	   
df.mm.trans1:probe4	-0.0103584651848790	0.0783947003290284	-0.132132212272051	0.894919446428883	   
df.mm.trans1:probe5	0.0750813131714375	0.0783947003290284	0.957734551651013	0.338542602103017	   
df.mm.trans1:probe6	0.064598158718269	0.0783947003290284	0.82401180752201	0.410226515802034	   
df.mm.trans1:probe7	0.0426214425169456	0.0783947003290284	0.543677599864025	0.586844471491698	   
df.mm.trans1:probe8	0.00800027734032447	0.0783947003290284	0.102051252275303	0.918746573333987	   
df.mm.trans1:probe9	0.053533799430577	0.0783947003290284	0.682875235263247	0.494922081335839	   
df.mm.trans1:probe10	-0.0327392316231992	0.0783947003290284	-0.417620470335243	0.676358622673904	   
df.mm.trans1:probe11	0.0054462997695772	0.0783947003290284	0.0694728055177031	0.944634038530474	   
df.mm.trans1:probe12	0.0134840142031233	0.0783947003290284	0.172001604018255	0.863488284483367	   
df.mm.trans1:probe13	0.143411861342976	0.0783947003290284	1.82935658585422	0.0677911366989044	.  
df.mm.trans1:probe14	-0.0198791754415483	0.0783947003290284	-0.253578052573884	0.79989946206172	   
df.mm.trans1:probe15	0.161604689029353	0.0783947003290284	2.06142364663793	0.0396484602229105	*  
df.mm.trans1:probe16	0.00904460526718415	0.0783947003290284	0.115372662045052	0.908184366774052	   
df.mm.trans1:probe17	0.0655198459256923	0.0783947003290284	0.835768816650879	0.403583364428484	   
df.mm.trans1:probe18	0.024442482899449	0.0783947003290284	0.311787439672096	0.75529921203308	   
df.mm.trans1:probe19	0.062478001577977	0.0783947003290284	0.796967158695068	0.425752849927451	   
df.mm.trans1:probe20	0.109870365474379	0.0783947003290284	1.40150246143228	0.161527615651012	   
df.mm.trans1:probe21	0.0552323543012129	0.0783947003290284	0.7045419405827	0.481340524430969	   
df.mm.trans2:probe2	-0.137503566982546	0.0783947003290284	-1.75399059382118	0.0798899807188307	.  
df.mm.trans2:probe3	-0.101738627334390	0.0783947003290284	-1.29777429988743	0.194812180603274	   
df.mm.trans2:probe4	-0.146708348577453	0.0783947003290284	-1.87140645938702	0.0617249710714811	.  
df.mm.trans2:probe5	-0.094115667249377	0.0783947003290284	-1.20053609305688	0.230356118542124	   
df.mm.trans2:probe6	-0.172698168975047	0.0783947003290284	-2.20293168097104	0.0279397564301268	*  
df.mm.trans3:probe2	-0.213936828218491	0.0783947003290284	-2.72897054674082	0.006520191335513	** 
df.mm.trans3:probe3	-0.189345901739258	0.0783947003290284	-2.41528956606199	0.0159897590603332	*