chr10.2584_chr10_45795166_45817894_+_2.R 

fitVsDatCorrelation=0.64361835286771
cont.fitVsDatCorrelation=0.292329747562444

fstatistic=8591.70122684912,42,462
cont.fstatistic=5498.94002317996,42,462

residuals=-0.472187442430298,-0.0802706868505615,-0.00346054915935068,0.0660599185664966,1.09208926632721
cont.residuals=-0.369012114673246,-0.110791121394341,-0.0197793902586547,0.0755132896309896,1.42234370606276

predictedValues:
Include	Exclude	Both
chr10.2584_chr10_45795166_45817894_+_2.R.tl.Lung	48.5473055590507	41.0441764804029	53.2328736012982
chr10.2584_chr10_45795166_45817894_+_2.R.tl.cerebhem	59.2461687860163	46.1929136271013	67.5810142021884
chr10.2584_chr10_45795166_45817894_+_2.R.tl.cortex	54.4021674928182	46.269486367618	61.2780049372371
chr10.2584_chr10_45795166_45817894_+_2.R.tl.heart	49.1536892792614	46.1858290818447	49.2569992455599
chr10.2584_chr10_45795166_45817894_+_2.R.tl.kidney	47.5945276307119	44.6478100370662	51.7061931417255
chr10.2584_chr10_45795166_45817894_+_2.R.tl.liver	49.8476593811525	50.2108296819103	49.3204394707642
chr10.2584_chr10_45795166_45817894_+_2.R.tl.stomach	48.5727122107637	43.8697395370907	52.0925654623189
chr10.2584_chr10_45795166_45817894_+_2.R.tl.testicle	52.9395774841203	47.2485132970094	51.2091364141621


diffExp=7.50312907864779,13.0532551589150,8.13268112520024,2.96786019741664,2.94671759364569,-0.363170300757794,4.70297267367305,5.69106418711083
diffExpScore=0.994003235704725
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=0,1,0,0,0,0,0,0
diffExp1.2Score=0.5

cont.predictedValues:
Include	Exclude	Both
Lung	50.2557902659888	49.3176912751763	53.5148357228457
cerebhem	50.2394333723172	52.8051237962053	52.2497408079878
cortex	51.083923741778	50.7694691649781	49.2978992841225
heart	48.7950686460818	56.8291222714891	52.5132370118786
kidney	51.3147088256321	56.7162221313283	47.135467173514
liver	51.659554525968	50.6255457996364	55.2129269624394
stomach	50.8837601428127	50.6731577338467	46.542962100581
testicle	49.2658289760462	48.1031919196425	51.1028999115752
cont.diffExp=0.938098990812477,-2.56569042388804,0.314454576799911,-8.0340536254073,-5.40151330569625,1.03400872633152,0.210602408966068,1.16263705640360
cont.diffExpScore=1.47368171136247

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=0.300890199575525
cont.tran.correlation=-0.0864722430064166

tran.covariance=0.00143450216623167
cont.tran.covariance=-9.40525518826628e-05

tran.mean=48.4983191208711
cont.tran.mean=51.208599536808

weightedLogRatios:
wLogRatio
Lung	0.637744904195234
cerebhem	0.984862888016133
cortex	0.633993656040774
heart	0.240633928984079
kidney	0.244833661158101
liver	-0.0284023231847702
stomach	0.390254433463954
testicle	0.444944415038125

cont.weightedLogRatios:
wLogRatio
Lung	0.0736324949836363
cerebhem	-0.196328341184888
cortex	0.0242688173640390
heart	-0.604166985340062
kidney	-0.399132259206961
liver	0.079552425283651
stomach	0.0162891088562413
testicle	0.0927891921121322

varWeightedLogRatios=0.096177790706387
cont.varWeightedLogRatios=0.0685522381021865

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.58384902538662	0.0796975282361229	44.9681326975237	7.25708285364231e-171	***
df.mm.trans1	0.275148051451324	0.0702275240543647	3.91795175974488	0.000102801026438433	***
df.mm.trans2	0.0621880643283363	0.0663989780582156	0.936581648497852	0.349463109949438	   
df.mm.exp2	0.0786889027511493	0.0914838431751513	0.860139889406424	0.390158055710779	   
df.mm.exp3	0.0929542040258536	0.0914838431751513	1.01607235550749	0.310126736054082	   
df.mm.exp4	0.208061926076099	0.0914838431751513	2.27430242166097	0.0234055448288396	*  
df.mm.exp5	0.0934339570112124	0.0914838431751512	1.02131648352734	0.307639014079731	   
df.mm.exp6	0.304352161001709	0.0914838431751513	3.32684057029621	0.000948461361720192	***
df.mm.exp7	0.088752906607138	0.0914838431751513	0.970148427599563	0.332480131156765	   
df.mm.exp8	0.266142916492610	0.0914838431751513	2.90917944913030	0.00379856645588927	** 
df.mm.trans1:exp2	0.120473518405569	0.084697580815995	1.42239621539246	0.155586057848222	   
df.mm.trans2:exp2	0.0394885371007461	0.0773179592983955	0.510729168993543	0.60978466322037	   
df.mm.trans1:exp3	0.0209110977318219	0.084697580815995	0.246891322400945	0.805102000598324	   
df.mm.trans2:exp3	0.0268795362903692	0.0773179592983955	0.347649324093413	0.728261886480664	   
df.mm.trans1:exp4	-0.195648715595385	0.084697580815995	-2.30996816804521	0.0213298232396620	*  
df.mm.trans2:exp4	-0.0900378666462075	0.0773179592983955	-1.16451426632617	0.244816632956323	   
df.mm.trans1:exp5	-0.113254863052720	0.084697580815995	-1.33716762582353	0.181825910324198	   
df.mm.trans2:exp5	-0.00927765999009547	0.0773179592983955	-0.119993596239263	0.90454038335788	   
df.mm.trans1:exp6	-0.277919313861327	0.084697580815995	-3.28131348243706	0.00111148673672394	** 
df.mm.trans2:exp6	-0.102770388631591	0.0773179592983955	-1.32919168540089	0.184440743639716	   
df.mm.trans1:exp7	-0.0882297054612565	0.084697580815995	-1.04170278077877	0.298094303879300	   
df.mm.trans2:exp7	-0.0221770903761901	0.0773179592983955	-0.286829742758748	0.774371278190849	   
df.mm.trans1:exp8	-0.179530395686832	0.084697580815995	-2.11966379626428	0.0345670326003982	*  
df.mm.trans2:exp8	-0.125370689437821	0.0773179592983955	-1.62149506499486	0.105593732805724	   
df.mm.trans1:probe2	0.081637015837124	0.0423487904079975	1.92772957741213	0.054501424593222	.  
df.mm.trans1:probe3	0.0284500426364926	0.0423487904079975	0.67180295735483	0.502044935266154	   
df.mm.trans1:probe4	0.0261170236602875	0.0423487904079975	0.616712387973077	0.537728224504082	   
df.mm.trans1:probe5	0.0380653831782647	0.0423487904079975	0.898854083234362	0.369198610349545	   
df.mm.trans1:probe6	-0.0112181085071613	0.0423487904079975	-0.264897967547209	0.791206207159473	   
df.mm.trans1:probe7	-0.0261056104781660	0.0423487904079975	-0.616442883649304	0.537905877975053	   
df.mm.trans1:probe8	0.0374231722177453	0.0423487904079975	0.883689282673773	0.377323580660667	   
df.mm.trans1:probe9	0.052990679561834	0.0423487904079975	1.25129145487534	0.211461392605371	   
df.mm.trans1:probe10	-0.0272594688754852	0.0423487904079975	-0.64368943275266	0.52009623792721	   
df.mm.trans1:probe11	0.0529442072702332	0.0423487904079975	1.25019408488784	0.211861523443443	   
df.mm.trans1:probe12	0.100079934856718	0.0423487904079975	2.36323006849843	0.0185296266759142	*  
df.mm.trans2:probe2	0.198111299625271	0.0423487904079975	4.6780863801923	3.80841129729024e-06	***
df.mm.trans2:probe3	0.0135378603545181	0.0423487904079975	0.319675254572596	0.749359026288647	   
df.mm.trans2:probe4	0.285376762674943	0.0423487904079975	6.73872287556647	4.77221971338202e-11	***
df.mm.trans2:probe5	0.046389890932096	0.0423487904079975	1.09542422546584	0.273901541364603	   
df.mm.trans2:probe6	0.0740910349660536	0.0423487904079975	1.74954312159201	0.08086113613263	.  
df.mm.trans3:probe2	0.237879752707285	0.0423487904079975	5.61715577742599	3.35792983799505e-08	***
df.mm.trans3:probe3	-0.0774067851648488	0.0423487904079975	-1.82783934131518	0.0682184328998024	.  

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.89472989309849	0.0995838325878986	39.1100622649843	1.10452064350282e-148	***
df.mm.trans1	0.0396088827994906	0.0877508519181736	0.451378897568144	0.651928292349034	   
df.mm.trans2	0.0309654749891552	0.0829669986171527	0.373226409358785	0.709151127971256	   
df.mm.exp2	0.0919238242018394	0.114311095022425	0.804154873888718	0.421721119705387	   
df.mm.exp3	0.127433830926958	0.114311095022425	1.11479844456007	0.265516372907329	   
df.mm.exp4	0.131163177566133	0.114311095022425	1.14742298234832	0.251800682093536	   
df.mm.exp5	0.287562254201475	0.114311095022425	2.51561105372198	0.0122207467452359	*  
df.mm.exp6	0.0224846442112936	0.114311095022425	0.196696954104785	0.844151190408306	   
df.mm.exp7	0.179114636576443	0.114311095022425	1.56690508949551	0.117821523881094	   
df.mm.exp8	0.00128828930175323	0.114311095022425	0.0112700285261067	0.991012873479172	   
df.mm.trans1:exp2	-0.0922493499974704	0.105831509398771	-0.871662423804962	0.383845305292962	   
df.mm.trans2:exp2	-0.0235984626757146	0.0966105083208782	-0.244263932421674	0.807134854603402	   
df.mm.trans1:exp3	-0.111089756569302	0.105831509398771	-1.04968508150742	0.294411698272098	   
df.mm.trans2:exp3	-0.098421523777894	0.0966105083208782	-1.01874553284619	0.308856967346320	   
df.mm.trans1:exp4	-0.160659691622271	0.105831509398771	-1.51807049275758	0.129680601403601	   
df.mm.trans2:exp4	0.0106028667416977	0.0966105083208782	0.109748586628711	0.912656420898302	   
df.mm.trans1:exp5	-0.266710590849082	0.105831509398771	-2.52014350323704	0.0120666509866203	*  
df.mm.trans2:exp5	-0.147784845851579	0.0966105083208782	-1.52969742546776	0.126776019485359	   
df.mm.trans1:exp6	0.00506475075379178	0.105831509398771	0.0478567373985748	0.961851098832692	   
df.mm.trans2:exp6	0.00368879631202283	0.0966105083208782	0.0381821437039852	0.969558950656172	   
df.mm.trans1:exp7	-0.166696587572004	0.105831509398771	-1.57511301236284	0.115914855624757	   
df.mm.trans2:exp7	-0.152001165508697	0.0966105083208782	-1.57333987938297	0.116324673624472	   
df.mm.trans1:exp8	-0.0211833422676054	0.105831509398771	-0.200161014313677	0.84144273202675	   
df.mm.trans2:exp8	-0.0262226203886977	0.0966105083208782	-0.271426171380892	0.786184513575982	   
df.mm.trans1:probe2	-0.0410332478876157	0.0529157546993855	-0.775444820181167	0.438473592836015	   
df.mm.trans1:probe3	-0.04479206150665	0.0529157546993855	-0.84647874269419	0.397723961132859	   
df.mm.trans1:probe4	-0.0662757893756835	0.0529157546993855	-1.25247744744824	0.211029564166219	   
df.mm.trans1:probe5	0.00699190498239001	0.0529157546993855	0.132132765035877	0.89493680516079	   
df.mm.trans1:probe6	-0.0287111577064155	0.0529157546993855	-0.542582409898972	0.587678985435019	   
df.mm.trans1:probe7	-0.0615069077990477	0.0529157546993855	-1.16235529755681	0.245691253428360	   
df.mm.trans1:probe8	-0.0298974141542718	0.0529157546993855	-0.565000240932386	0.572347840930701	   
df.mm.trans1:probe9	-0.0245339707428247	0.0529157546993855	-0.463642083198136	0.64312255395566	   
df.mm.trans1:probe10	-0.0460827926607585	0.0529157546993855	-0.870870932911284	0.384276915847198	   
df.mm.trans1:probe11	0.100585669152583	0.0529157546993855	1.90086430258833	0.0579418439460759	.  
df.mm.trans1:probe12	-0.0229393286505999	0.0529157546993855	-0.433506595170346	0.664849114167279	   
df.mm.trans2:probe2	-0.0365943722438422	0.0529157546993855	-0.691559110358246	0.489561614282091	   
df.mm.trans2:probe3	-0.0588754854859537	0.0529157546993855	-1.11262677477484	0.266447347294941	   
df.mm.trans2:probe4	-0.0492127663325713	0.0529157546993855	-0.930021061064878	0.352845863303655	   
df.mm.trans2:probe5	-0.0407558619572744	0.0529157546993855	-0.770202790998797	0.441573258689271	   
df.mm.trans2:probe6	-0.061274032115248	0.0529157546993855	-1.15795442138822	0.247480895544919	   
df.mm.trans3:probe2	0.000618178797136962	0.0529157546993855	0.0116823203344417	0.990684111869422	   
df.mm.trans3:probe3	0.0433458246153226	0.0529157546993855	0.81914781073369	0.413124433693633