chr6.20215_chr6_53133480_53135884_+_2.R 

fitVsDatCorrelation=0.943910498425959
cont.fitVsDatCorrelation=0.25986253478853

fstatistic=7706.24426882591,62,922
cont.fstatistic=887.951442132974,62,922

residuals=-0.898452783845415,-0.112644419089752,0.00762607530536241,0.126327031453579,1.20931305301397
cont.residuals=-1.11196592356483,-0.505299337431388,-0.0630344107970614,0.413197732883001,1.93840233568966

predictedValues:
Include	Exclude	Both
chr6.20215_chr6_53133480_53135884_+_2.R.tl.Lung	102.343634550569	51.6800263440891	109.586895190189
chr6.20215_chr6_53133480_53135884_+_2.R.tl.cerebhem	89.6493418658097	52.1869349195554	113.876412325729
chr6.20215_chr6_53133480_53135884_+_2.R.tl.cortex	131.799706290287	50.9131618991032	136.809627895713
chr6.20215_chr6_53133480_53135884_+_2.R.tl.heart	101.816331033092	51.6118976196208	115.438574426511
chr6.20215_chr6_53133480_53135884_+_2.R.tl.kidney	111.565227699713	54.4064084402465	121.620265579839
chr6.20215_chr6_53133480_53135884_+_2.R.tl.liver	93.6651990262338	53.2448491273451	102.542440041115
chr6.20215_chr6_53133480_53135884_+_2.R.tl.stomach	106.483957662462	49.6307053059807	122.353527114596
chr6.20215_chr6_53133480_53135884_+_2.R.tl.testicle	179.031629695842	51.7362147201283	221.374714579078


diffExp=50.6636082064804,37.4624069462543,80.8865443911834,50.204433413471,57.1588192594668,40.4203498988886,56.853252356481,127.295414975714
diffExpScore=0.99800774917614
diffExp1.5=1,1,1,1,1,1,1,1
diffExp1.5Score=0.888888888888889
diffExp1.4=1,1,1,1,1,1,1,1
diffExp1.4Score=0.888888888888889
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	95.8657179631098	123.882047769126	117.885045560414
cerebhem	96.8060228110244	130.943351807949	108.045219573548
cortex	90.272901718726	95.3622497790755	89.0208824962932
heart	107.66822037175	105.381849988339	116.816284149921
kidney	101.789619995485	102.104079752528	97.4014307534041
liver	92.9780620700761	135.201059458363	78.6477385823908
stomach	93.1672617793388	110.017851998506	95.7301149449274
testicle	97.0920897667644	114.547626268258	117.050973418998
cont.diffExp=-28.0163298060166,-34.1373289969249,-5.08934806034952,2.28637038341128,-0.31445975704267,-42.2229973882866,-16.8505902191673,-17.4555365014936
cont.diffExpScore=1.02501915443946

cont.diffExp1.5=0,0,0,0,0,0,0,0
cont.diffExp1.5Score=0
cont.diffExp1.4=0,0,0,0,0,-1,0,0
cont.diffExp1.4Score=0.5
cont.diffExp1.3=0,-1,0,0,0,-1,0,0
cont.diffExp1.3Score=0.666666666666667
cont.diffExp1.2=-1,-1,0,0,0,-1,0,0
cont.diffExp1.2Score=0.75

tran.correlation=-0.156348069177235
cont.tran.correlation=-0.196075352766949

tran.covariance=-0.00105978115694459
cont.tran.covariance=-0.00110489676223005

tran.mean=83.2353266375049
cont.tran.mean=105.817500831151

weightedLogRatios:
wLogRatio
Lung	2.92895355279912
cerebhem	2.28623598104743
cortex	4.19053638573401
heart	2.91026201451654
kidney	3.12783701445181
liver	2.40464005106393
stomach	3.2720971285407
testicle	5.6693207690331

cont.weightedLogRatios:
wLogRatio
Lung	-1.20272103347762
cerebhem	-1.42683116488989
cortex	-0.248464250538887
heart	0.100201083533226
kidney	-0.0142643417300821
liver	-1.76700178646664
stomach	-0.767645313324062
testicle	-0.770164551485844

varWeightedLogRatios=1.21958737544533
cont.varWeightedLogRatios=0.458940116739554

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.09039832972042	0.0969221892682872	42.2029089582152	1.45678097417317e-217	***
df.mm.trans1	0.598205528580499	0.0832395731030942	7.1865520963161	1.37107818346234e-12	***
df.mm.trans2	-0.163830188021525	0.0730897095278955	-2.24149458357058	0.0252312758720685	*  
df.mm.exp2	-0.161065412897096	0.0929973154634732	-1.73193615422542	0.0836193890068943	.  
df.mm.exp3	0.0161247966488847	0.0929973154634732	0.173389915273609	0.862383009732569	   
df.mm.exp4	-0.0585055199510125	0.0929973154634732	-0.629109772249199	0.529433028959928	   
df.mm.exp5	0.0334980688940958	0.0929973154634732	0.360204686846611	0.718776567422502	   
df.mm.exp6	0.00766133111701705	0.0929973154634732	0.0823822825297168	0.934360605471044	   
df.mm.exp7	-0.11100026374704	0.0929973154634732	-1.1935856771117	0.232947099199306	   
df.mm.exp8	-0.142825988420077	0.0929973154634732	-1.53580764894418	0.124928636913410	   
df.mm.trans1:exp2	0.028635154556771	0.0853724440611421	0.335414487328757	0.73738874335368	   
df.mm.trans2:exp2	0.170826218332528	0.0605116814821713	2.82302877970526	0.00485963638178131	** 
df.mm.trans1:exp3	0.236822479753528	0.0853724440611421	2.77399203405634	0.00564914904199544	** 
df.mm.trans2:exp3	-0.0310746922681807	0.0605116814821713	-0.513532123170901	0.60770218083333	   
df.mm.trans1:exp4	0.0533399167095233	0.0853724440611421	0.62479078930108	0.532262960192393	   
df.mm.trans2:exp4	0.0571863706558214	0.0605116814821713	0.945046795182354	0.34488257371772	   
df.mm.trans1:exp5	0.0527752355369011	0.0853724440611421	0.618176463345766	0.536611692381989	   
df.mm.trans2:exp5	0.0179125110118170	0.0605116814821713	0.296017406442335	0.767283446838472	   
df.mm.trans1:exp6	-0.0962707365466928	0.0853724440611421	-1.12765585670413	0.259758651709007	   
df.mm.trans2:exp6	0.0221683695626983	0.0605116814821713	0.366348596167002	0.714189019914859	   
df.mm.trans1:exp7	0.150658488059499	0.0853724440611421	1.76472033472066	0.0779418232753191	.  
df.mm.trans2:exp7	0.070538595300257	0.0605116814821713	1.16570211854119	0.24403637028606	   
df.mm.trans1:exp8	0.702052363648761	0.0853724440611421	8.22340711185409	6.68420862521265e-16	***
df.mm.trans2:exp8	0.143912633631505	0.0605116814821713	2.37826201663073	0.0175973519421155	*  
df.mm.trans1:probe2	0.064778210979359	0.0611565844019248	1.05921891506616	0.289777501141746	   
df.mm.trans1:probe3	-0.0527206732285052	0.0611565844019248	-0.862060459132606	0.388878401101417	   
df.mm.trans1:probe4	-0.314861148807964	0.0611565844019248	-5.14844234495959	3.210998423924e-07	***
df.mm.trans1:probe5	-0.0735791294456032	0.0611565844019247	-1.2031268614028	0.229236073386657	   
df.mm.trans1:probe6	-0.52832562233703	0.0611565844019247	-8.63890008743528	2.47355887876121e-17	***
df.mm.trans1:probe7	-0.376268579344579	0.0611565844019248	-6.15254404777937	1.13536520673424e-09	***
df.mm.trans1:probe8	-0.80684536556463	0.0611565844019247	-13.1931070620621	1.56405610205928e-36	***
df.mm.trans1:probe9	-0.254690320497094	0.0611565844019248	-4.16456090522083	3.41223492651935e-05	***
df.mm.trans1:probe10	-0.447123706282548	0.0611565844019248	-7.31112946635515	5.74409966237152e-13	***
df.mm.trans1:probe11	-0.727656849881521	0.0611565844019248	-11.8982584949368	1.80472651732340e-30	***
df.mm.trans1:probe12	-0.765809361289169	0.0611565844019248	-12.5221081062380	2.45538370847714e-33	***
df.mm.trans1:probe13	-0.739446668800715	0.0611565844019248	-12.0910393546675	2.40873621746198e-31	***
df.mm.trans1:probe14	-0.760260249200447	0.0611565844019248	-12.4313719713967	6.50762120906753e-33	***
df.mm.trans1:probe15	-0.573961731853441	0.0611565844019247	-9.38511752195528	4.7562562783672e-20	***
df.mm.trans1:probe16	-0.514385615552378	0.0611565844019247	-8.41096049726722	1.53471282706839e-16	***
df.mm.trans1:probe17	0.800528315724188	0.0611565844019248	13.0898140168043	4.93863381975932e-36	***
df.mm.trans1:probe18	0.770598595855983	0.0611565844019248	12.6004191272613	1.05452912436531e-33	***
df.mm.trans1:probe19	0.674590226312765	0.0611565844019248	11.0305412395061	1.16258640574520e-26	***
df.mm.trans1:probe20	0.832724060032159	0.0611565844019248	13.6162617349499	1.32235810226587e-38	***
df.mm.trans1:probe21	0.893516849382303	0.0611565844019248	14.6103131514026	1.22149757304586e-43	***
df.mm.trans1:probe22	0.78982782573857	0.0611565844019248	12.9148452854687	3.41507184330927e-35	***
df.mm.trans2:probe2	0.0144180207445542	0.0611565844019248	0.235755820661895	0.813674508583432	   
df.mm.trans2:probe3	0.0522768565049734	0.0611565844019248	0.854803403692507	0.392882049695	   
df.mm.trans2:probe4	0.0335018888627946	0.0611565844019248	0.547805100471573	0.583958325391749	   
df.mm.trans2:probe5	0.252840284634684	0.0611565844019248	4.13431010098606	3.88482162656643e-05	***
df.mm.trans2:probe6	-0.00147572768911772	0.0611565844019248	-0.0241303157059777	0.98075388323264	   
df.mm.trans3:probe2	0.0620896560467328	0.0611565844019248	1.01525709216649	0.310249633151098	   
df.mm.trans3:probe3	0.336828863668497	0.0611565844019248	5.50764675565983	4.71706730294568e-08	***
df.mm.trans3:probe4	-0.124705492129254	0.0611565844019247	-2.03911800092827	0.041722988360534	*  
df.mm.trans3:probe5	0.515158662976161	0.0611565844019248	8.42360095832866	1.38844259146381e-16	***
df.mm.trans3:probe6	0.161186707505724	0.0611565844019247	2.63563946682169	0.00853892756937541	** 
df.mm.trans3:probe7	0.352674090078492	0.0611565844019247	5.76673948565697	1.10229893064690e-08	***
df.mm.trans3:probe8	-0.649175395863686	0.0611565844019248	-10.6149714247818	6.50130277958906e-25	***
df.mm.trans3:probe9	0.815731256799187	0.0611565844019248	13.3384044379940	3.07174866682194e-37	***
df.mm.trans3:probe10	0.25948708653765	0.0611565844019248	4.24299507690431	2.42836898391968e-05	***
df.mm.trans3:probe11	0.0453030852764979	0.0611565844019248	0.740771998952121	0.459020304456751	   
df.mm.trans3:probe12	0.182569994842863	0.0611565844019248	2.98528762893301	0.002907950004392	** 
df.mm.trans3:probe13	0.278125143749349	0.0611565844019248	4.54775469345204	6.14515475041622e-06	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.48713237120456	0.283440605583512	15.8309440595747	4.09697573701057e-50	***
df.mm.trans1	-0.0313780971359285	0.243426971542561	-0.128901480953775	0.897463717101005	   
df.mm.trans2	0.378511040476756	0.213744568575157	1.77085688305415	0.0769148507171219	.  
df.mm.exp2	0.152355806128909	0.271962649746217	0.560208566400866	0.575473270770652	   
df.mm.exp3	-0.0409192246219783	0.271962649746217	-0.150458986409208	0.880435415345407	   
df.mm.exp4	-0.0365259614114914	0.271962649746217	-0.134305065219712	0.893190658949138	   
df.mm.exp5	0.05749155018631	0.271962649746217	0.211395021485334	0.832625757254785	   
df.mm.exp6	0.461579330429222	0.271962649746217	1.69721588924047	0.0899933395477899	.  
df.mm.exp7	0.0609377385418489	0.271962649746217	0.224066571636631	0.822755143794472	   
df.mm.exp8	-0.0585272833707893	0.271962649746217	-0.21520338702908	0.829656343215433	   
df.mm.trans1:exp2	-0.142595035716307	0.249664369196747	-0.571146920864527	0.568039240953061	   
df.mm.trans2:exp2	-0.0969208906316271	0.176961207476513	-0.54769568999743	0.584033430651998	   
df.mm.trans1:exp3	-0.0191918927566213	0.249664369196747	-0.0768707718220583	0.938743026773857	   
df.mm.trans2:exp3	-0.220727865089921	0.176961207476513	-1.24732345714366	0.212595650752480	   
df.mm.trans1:exp4	0.152631985502732	0.249664369196747	0.611348691820941	0.541119459467661	   
df.mm.trans2:exp4	-0.125213503791301	0.176961207476513	-0.707576002542363	0.479387412121127	   
df.mm.trans1:exp5	0.00246814299391779	0.249664369196747	0.00988584395065512	0.9921145047969	   
df.mm.trans2:exp5	-0.250828752647661	0.176961207476513	-1.41742224877705	0.156697346706806	   
df.mm.trans1:exp6	-0.492164197878956	0.249664369196747	-1.97130331197203	0.0489878745850298	*  
df.mm.trans2:exp6	-0.374146215853124	0.176961207476513	-2.11428380936416	0.0347589461766235	*  
df.mm.trans1:exp7	-0.089489788078103	0.249664369196747	-0.358440366825356	0.720095840533602	   
df.mm.trans2:exp7	-0.179624980254222	0.176961207476513	-1.01505286280363	0.310346917738565	   
df.mm.trans1:exp8	0.0712387494811784	0.249664369196747	0.285338070908464	0.775449233790665	   
df.mm.trans2:exp8	-0.019811915409551	0.176961207476513	-0.111956262573426	0.910882454225663	   
df.mm.trans1:probe2	0.381123886546302	0.178847170592880	2.13100316478518	0.0333528929612018	*  
df.mm.trans1:probe3	0.283804873069095	0.178847170592880	1.58685693560754	0.112887918863452	   
df.mm.trans1:probe4	0.113834145187151	0.178847170592880	0.636488376135836	0.52461613358234	   
df.mm.trans1:probe5	0.047008366600798	0.178847170592880	0.262840985658117	0.792731864511379	   
df.mm.trans1:probe6	0.091601286941041	0.178847170592880	0.512176327069542	0.608650269418455	   
df.mm.trans1:probe7	-0.038908382313779	0.178847170592880	-0.217551008410127	0.827827094078283	   
df.mm.trans1:probe8	0.33957776736104	0.178847170592880	1.89870360395044	0.0579154411977775	.  
df.mm.trans1:probe9	0.298970471299307	0.178847170592880	1.67165334686715	0.0949320171871169	.  
df.mm.trans1:probe10	-0.161696287118186	0.178847170592880	-0.904103132200311	0.366176880849523	   
df.mm.trans1:probe11	0.240128966496291	0.178847170592880	1.34264895385407	0.179716128793937	   
df.mm.trans1:probe12	0.176619319669599	0.178847170592880	0.987543269955596	0.323635463768221	   
df.mm.trans1:probe13	0.0146036369085807	0.178847170592880	0.0816542797974914	0.934939358096593	   
df.mm.trans1:probe14	0.277200205962843	0.178847170592880	1.54992782409653	0.121502005258628	   
df.mm.trans1:probe15	0.37087305323727	0.178847170592880	2.07368700331027	0.0383855443073118	*  
df.mm.trans1:probe16	0.0791490626005894	0.178847170592880	0.442551382491597	0.658194055712591	   
df.mm.trans1:probe17	0.171668213079359	0.178847170592880	0.95985982059586	0.337377410687668	   
df.mm.trans1:probe18	0.289870164777083	0.178847170592880	1.62077020182182	0.105408854031410	   
df.mm.trans1:probe19	0.260101516173521	0.178847170592880	1.45432279029790	0.146197159351251	   
df.mm.trans1:probe20	0.145756792215902	0.178847170592880	0.814979581352709	0.415294458755185	   
df.mm.trans1:probe21	0.091538284943707	0.178847170592880	0.511824059839789	0.608896712718585	   
df.mm.trans1:probe22	0.278970500939841	0.178847170592880	1.55982619135126	0.119144121318980	   
df.mm.trans2:probe2	-0.0411773185598153	0.178847170592880	-0.230237461533845	0.817958325846391	   
df.mm.trans2:probe3	-0.169707285100702	0.178847170592880	-0.94889555444529	0.342922380801513	   
df.mm.trans2:probe4	-0.260947221942992	0.178847170592880	-1.45905144083605	0.144891537631462	   
df.mm.trans2:probe5	-0.237528041710167	0.178847170592880	-1.32810623127422	0.184471684092875	   
df.mm.trans2:probe6	-0.170597135212668	0.178847170592880	-0.953871032161914	0.340398935647960	   
df.mm.trans3:probe2	-0.0487648685638187	0.178847170592880	-0.272662231122599	0.785173923781311	   
df.mm.trans3:probe3	-0.141546107235318	0.178847170592880	-0.791436100253035	0.428893101021294	   
df.mm.trans3:probe4	-0.192466738857993	0.178847170592880	-1.07615199178139	0.282140795990729	   
df.mm.trans3:probe5	0.0508033174056111	0.178847170592880	0.28405994479643	0.776428221227618	   
df.mm.trans3:probe6	0.111066662519838	0.178847170592880	0.621014367471687	0.534743660039621	   
df.mm.trans3:probe7	-0.252561166043164	0.178847170592880	-1.41216193248080	0.158239704031484	   
df.mm.trans3:probe8	0.167724435973315	0.178847170592880	0.93780871912766	0.348588310226171	   
df.mm.trans3:probe9	-0.0181636807792405	0.178847170592880	-0.101559788276369	0.919128180148592	   
df.mm.trans3:probe10	-0.150049610836471	0.178847170592880	-0.838982301699575	0.401696707916648	   
df.mm.trans3:probe11	-0.0974539927452211	0.178847170592880	-0.544900947675942	0.585953417967353	   
df.mm.trans3:probe12	-0.144020667216695	0.178847170592880	-0.805272270952152	0.420870194880369	   
df.mm.trans3:probe13	-0.123787199626349	0.178847170592880	-0.692139546943872	0.489023964693684