chr11.4879_chr11_30965326_30996231_+_2.R 

fitVsDatCorrelation=0.719652291270198
cont.fitVsDatCorrelation=0.268280037486832

fstatistic=12657.5285487007,63,945
cont.fstatistic=6568.25794149181,63,945

residuals=-0.559514186800182,-0.0748398102240825,-0.00168782229883461,0.0630753800029256,1.6605811968107
cont.residuals=-0.504835507155583,-0.111337664682043,-0.0296205332468350,0.0728738843757219,1.57467930146833

predictedValues:
Include	Exclude	Both
chr11.4879_chr11_30965326_30996231_+_2.R.tl.Lung	49.6999436524897	43.1587443356343	59.6068736982156
chr11.4879_chr11_30965326_30996231_+_2.R.tl.cerebhem	54.739908627969	45.0845856022354	69.0094431121465
chr11.4879_chr11_30965326_30996231_+_2.R.tl.cortex	48.2412347284584	42.2246258517402	73.9852741788157
chr11.4879_chr11_30965326_30996231_+_2.R.tl.heart	47.906355098702	43.5229935353932	61.8224921654566
chr11.4879_chr11_30965326_30996231_+_2.R.tl.kidney	48.1855473666317	40.8436949752738	60.3541703394265
chr11.4879_chr11_30965326_30996231_+_2.R.tl.liver	50.0583528831433	47.1457235468059	60.8477704805353
chr11.4879_chr11_30965326_30996231_+_2.R.tl.stomach	51.0388953313114	48.2561170548371	60.4171190502072
chr11.4879_chr11_30965326_30996231_+_2.R.tl.testicle	50.9097460695806	46.5876930190299	64.3338657382324


diffExp=6.54119931685533,9.6553230257336,6.01660887671819,4.38336156330875,7.34185239135785,2.91262933633737,2.78277827647432,4.32205305055073
diffExpScore=0.977755932045389
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	49.1135654073278	50.8236942003408	48.6872072175318
cerebhem	50.8343777183488	50.5368208819718	48.7179521205903
cortex	48.0096308712097	46.0877161507708	47.9860786852501
heart	49.6211531843768	46.6253399786154	48.2452900103906
kidney	48.3533880224171	52.3153862907476	44.6446047125745
liver	50.2663318996111	50.0996328638452	53.385833512614
stomach	49.9472934125725	47.8190248739081	53.6011125400659
testicle	50.2745324181596	53.9616345385129	48.0715124721477
cont.diffExp=-1.71012879301301,0.297556836377026,1.92191472043894,2.99581320576143,-3.96199826833049,0.166699035765923,2.12826853866433,-3.68710212035337
cont.diffExpScore=5.92124205928557

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=0.534427392507106
cont.tran.correlation=0.284529456054162

tran.covariance=0.00141681009321429
cont.tran.covariance=0.000324081635786782

tran.mean=47.3502601049522
cont.tran.mean=49.668095169546

weightedLogRatios:
wLogRatio
Lung	0.541253132743144
cerebhem	0.757885489652175
cortex	0.507480077455934
heart	0.366684306958015
kidney	0.62690995566619
liver	0.232783584213698
stomach	0.218910444853117
testicle	0.344731015650046

cont.weightedLogRatios:
wLogRatio
Lung	-0.133871841074814
cerebhem	0.0230460654226128
cortex	0.157332239173161
heart	0.241200996913129
kidney	-0.308552247454859
liver	0.0130071938405716
stomach	0.169354055221988
testicle	-0.279764269557189

varWeightedLogRatios=0.0366183864822379
cont.varWeightedLogRatios=0.043136978057661

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.58152294311782	0.0700951444341511	51.0951646084756	3.62682713945781e-274	***
df.mm.trans1	0.572158958282713	0.0627482021329631	9.11833230010816	4.47918991817955e-19	***
df.mm.trans2	0.171612073898432	0.0563758074807858	3.04407300874441	0.00239860658592694	** 
df.mm.exp2	-0.00622786023295765	0.0757573032670052	-0.0822080507671672	0.934498680075884	   
df.mm.exp3	-0.267766274508052	0.0757573032670052	-3.53452753676189	0.000428307371136532	***
df.mm.exp4	-0.0648476419186177	0.0757573032670052	-0.855991952222261	0.392219219133383	   
df.mm.exp5	-0.098536403308644	0.0757573032670052	-1.30068520207688	0.193683313145633	   
df.mm.exp6	0.074939561363167	0.0757573032670053	0.989205768043826	0.322815685439968	   
df.mm.exp7	0.12472015278393	0.0757573032670052	1.64631193832700	0.100032050195786	   
df.mm.exp8	0.0241866639482307	0.0757573032670052	0.319265112473516	0.749596045478717	   
df.mm.trans1:exp2	0.102817095294461	0.0730668314550008	1.40716510141516	0.159707243791596	   
df.mm.trans2:exp2	0.0498832189412832	0.0600305276899979	0.83096419206714	0.406203755092761	   
df.mm.trans1:exp3	0.237976622782094	0.0730668314550008	3.25697198090019	0.00116616614119597	** 
df.mm.trans2:exp3	0.245884829615685	0.0600305276899979	4.09599647175271	4.5637672609543e-05	***
df.mm.trans1:exp4	0.028092012480219	0.0730668314550007	0.384470106624507	0.700716548876499	   
df.mm.trans2:exp4	0.073251980657113	0.0600305276899979	1.22024548968471	0.222676241017204	   
df.mm.trans1:exp5	0.067591732887514	0.0730668314550008	0.925067250646297	0.355167088161541	   
df.mm.trans2:exp5	0.0434038202078218	0.0600305276899979	0.723029129978039	0.469840896307168	   
df.mm.trans1:exp6	-0.0677539781037765	0.0730668314550008	-0.92728775498502	0.354013915567228	   
df.mm.trans2:exp6	0.0134186979778837	0.0600305276899979	0.223531234760735	0.823170387896256	   
df.mm.trans1:exp7	-0.0981359565261393	0.0730668314550008	-1.34309856568199	0.179562529338681	   
df.mm.trans2:exp7	-0.0130826014198059	0.0600305276899979	-0.217932474079945	0.827528773409422	   
df.mm.trans1:exp8	-0.000136083225526632	0.0730668314550008	-0.00186244870369725	0.998514374869776	   
df.mm.trans2:exp8	0.0522646972754223	0.0600305276899979	0.870635313174675	0.384174415540733	   
df.mm.trans1:probe2	-0.25613473578666	0.0400203517933319	-6.40011205072256	2.44096705577401e-10	***
df.mm.trans1:probe3	-0.267602155872252	0.0400203517933319	-6.68665176293724	3.90119267108653e-11	***
df.mm.trans1:probe4	-0.251135524304153	0.0400203517933319	-6.27519532064675	5.31123388400806e-10	***
df.mm.trans1:probe5	-0.237673400113986	0.0400203517933319	-5.93881336529347	4.03037201227891e-09	***
df.mm.trans1:probe6	-0.113312043850085	0.0400203517933319	-2.83136051465108	0.00473342985063778	** 
df.mm.trans1:probe7	-0.357671923990658	0.0400203517933319	-8.93725087269852	2.05406151060859e-18	***
df.mm.trans1:probe8	-0.215134475234750	0.0400203517933319	-5.3756267897324	9.6183503238501e-08	***
df.mm.trans1:probe9	-0.245655640221698	0.0400203517933319	-6.13826788655637	1.22629611674638e-09	***
df.mm.trans1:probe10	-0.344388995179753	0.0400203517933319	-8.60534652364386	3.13711139068826e-17	***
df.mm.trans1:probe11	-0.181924424925737	0.0400203517933319	-4.54579774473769	6.18269685397893e-06	***
df.mm.trans1:probe12	-0.358303904271863	0.0400203517933319	-8.9530423451091	1.80038929629634e-18	***
df.mm.trans1:probe13	-0.340236467510813	0.0400203517933319	-8.50158612467524	7.22817607675505e-17	***
df.mm.trans1:probe14	-0.324405925694787	0.0400203517933319	-8.10602383932163	1.61143546631266e-15	***
df.mm.trans1:probe15	-0.284903756463507	0.0400203517933319	-7.11897181550955	2.15063113107917e-12	***
df.mm.trans1:probe16	-0.250537187166096	0.0400203517933320	-6.26024449909607	5.82392085872506e-10	***
df.mm.trans1:probe17	-0.311058963310390	0.0400203517933319	-7.77251946501423	2.00339625994003e-14	***
df.mm.trans1:probe18	-0.353415510199212	0.0400203517933319	-8.83089464141334	4.96604476078279e-18	***
df.mm.trans1:probe19	-0.347037220440911	0.0400203517933319	-8.67151848721962	1.83420049477761e-17	***
df.mm.trans1:probe20	-0.364908026987193	0.0400203517933319	-9.11806145212329	4.48948848412026e-19	***
df.mm.trans1:probe21	-0.338944812437113	0.0400203517933320	-8.46931116916335	9.35489816263383e-17	***
df.mm.trans1:probe22	-0.385183525086241	0.0400203517933319	-9.62469113403492	5.55519671123808e-21	***
df.mm.trans1:probe23	-0.301867370689151	0.0400203517933319	-7.54284650589821	1.07846627015458e-13	***
df.mm.trans1:probe24	-0.350270520471177	0.0400203517933319	-8.75230988173218	9.48127437418627e-18	***
df.mm.trans1:probe25	-0.251296789572306	0.0400203517933319	-6.27922490212034	5.18077633350739e-10	***
df.mm.trans1:probe26	-0.256841256336318	0.0400203517933319	-6.41776608218402	2.18462411819025e-10	***
df.mm.trans1:probe27	-0.288824390862023	0.0400203517933319	-7.21693783087	1.09120283431025e-12	***
df.mm.trans1:probe28	-0.109106826296627	0.0400203517933319	-2.72628353843721	0.00652372536104005	** 
df.mm.trans1:probe29	-0.341945189510454	0.0400203517933319	-8.54428245099603	5.1322359405726e-17	***
df.mm.trans1:probe30	-0.347841418832514	0.0400203517933319	-8.69161322291201	1.55730206637975e-17	***
df.mm.trans1:probe31	-0.280291959148165	0.0400203517933319	-7.00373551426068	4.72848449903091e-12	***
df.mm.trans1:probe32	-0.258557333080873	0.0400203517933319	-6.46064618362382	1.66669748436707e-10	***
df.mm.trans2:probe2	-0.0509158256898664	0.0400203517933319	-1.27224832887026	0.203597863224661	   
df.mm.trans2:probe3	-0.00394470523003979	0.0400203517933319	-0.0985674801263752	0.921502594573653	   
df.mm.trans2:probe4	0.0433090611842757	0.0400203517933319	1.08217592408800	0.279450424949026	   
df.mm.trans2:probe5	-0.000222114378167576	0.0400203517933319	-0.0055500356247389	0.995572906362914	   
df.mm.trans2:probe6	0.129273881188948	0.0400203517933319	3.2302035188628	0.00127972295689307	** 
df.mm.trans3:probe2	-0.47260669190201	0.0400203517933319	-11.8091588585374	4.07650521949245e-30	***
df.mm.trans3:probe3	-0.387056249398159	0.0400203517933319	-9.67148543313527	3.66719157432444e-21	***
df.mm.trans3:probe4	-0.0904293681827992	0.0400203517933319	-2.25958453963081	0.0240740913952267	*  

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.9782512947239	0.0972521336503688	40.9065708421998	2.42496723820895e-211	***
df.mm.trans1	-0.0290920214067152	0.0870587626206835	-0.334165344544002	0.738328936895132	   
df.mm.trans2	-0.0453969694710438	0.0782175086167256	-0.580393958768157	0.561787344885325	   
df.mm.exp2	0.0281458257007055	0.105107984893812	0.267780090438805	0.788927031452538	   
df.mm.exp3	-0.106044488812899	0.105107984893812	-1.00890992173461	0.313276092491522	   
df.mm.exp4	-0.0668184534952854	0.105107984893812	-0.63571243957146	0.52511778133689	   
df.mm.exp5	0.100011713272980	0.105107984893812	0.951513944197667	0.341586838417259	   
df.mm.exp6	-0.0832778685375644	0.105107984893812	-0.792307726398695	0.428380114971050	   
df.mm.exp7	-0.140259571138531	0.105107984893812	-1.33443307166655	0.182383412172824	   
df.mm.exp8	0.0960005774682075	0.105107984893812	0.913351897719233	0.361290455693051	   
df.mm.trans1:exp2	0.00629174889643797	0.101375142535674	0.0620640202229449	0.950524973364093	   
df.mm.trans2:exp2	-0.0338062958376111	0.083288178505635	-0.405895487741083	0.684911280722529	   
df.mm.trans1:exp3	0.0833108448946913	0.101375142535674	0.821807425477842	0.411393795517036	   
df.mm.trans2:exp3	0.0082282752603508	0.083288178505635	0.0987928348054112	0.921323709135349	   
df.mm.trans1:exp4	0.0771003939526545	0.101375142535674	0.760545356821797	0.447118383057524	   
df.mm.trans2:exp4	-0.0194000439111702	0.083288178505635	-0.232926740135848	0.815868733485008	   
df.mm.trans1:exp5	-0.115610698826346	0.101375142535674	-1.14042452552571	0.254398423108834	   
df.mm.trans2:exp5	-0.0710838596390356	0.083288178505635	-0.853468774493927	0.393615672721063	   
df.mm.trans1:exp6	0.106478097748918	0.101375142535674	1.05033734193221	0.293831565920638	   
df.mm.trans2:exp6	0.0689288814241709	0.083288178505635	0.827595016014277	0.408108829680858	   
df.mm.trans1:exp7	0.157092610980342	0.101375142535674	1.54961667180947	0.121568362354340	   
df.mm.trans2:exp7	0.0793204742550014	0.0832881785056349	0.952361735821067	0.34115707966229	   
df.mm.trans1:exp8	-0.0726372201870425	0.101375142535674	-0.716519043723974	0.473847947177182	   
df.mm.trans2:exp8	-0.0360899220278402	0.0832881785056349	-0.43331385888573	0.664885658568075	   
df.mm.trans1:probe2	0.036403384053345	0.05552545233709	0.65561616377915	0.512230697089109	   
df.mm.trans1:probe3	-0.0889712050664855	0.05552545233709	-1.60234993722067	0.109412429380681	   
df.mm.trans1:probe4	-0.0409754210449434	0.05552545233709	-0.737957446905347	0.460723516392737	   
df.mm.trans1:probe5	-0.132781834008740	0.05552545233709	-2.39136879430776	0.0169804165348892	*  
df.mm.trans1:probe6	-0.0344905193395413	0.05552545233709	-0.621165931799214	0.534640250177896	   
df.mm.trans1:probe7	-0.0123694300357977	0.05552545233709	-0.222770450580105	0.823762306985618	   
df.mm.trans1:probe8	-0.0152505076479901	0.05552545233709	-0.274657963259906	0.783639062014437	   
df.mm.trans1:probe9	-0.0895954614016555	0.05552545233709	-1.61359264320315	0.106949662777170	   
df.mm.trans1:probe10	-0.105174496567216	0.05552545233709	-1.89416730779088	0.0585079436855528	.  
df.mm.trans1:probe11	-0.0700231686543785	0.05552545233709	-1.26110037301946	0.207583924089131	   
df.mm.trans1:probe12	-0.0259439770984109	0.05552545233709	-0.46724476805533	0.640432482638335	   
df.mm.trans1:probe13	-0.0601849281271155	0.05552545233709	-1.08391603478957	0.278678492315020	   
df.mm.trans1:probe14	-0.056484477028218	0.05552545233709	-1.01727180330393	0.309284513744082	   
df.mm.trans1:probe15	-0.0895531706840133	0.05552545233709	-1.61283099758187	0.107115103459655	   
df.mm.trans1:probe16	-0.0226704097999383	0.05552545233709	-0.408288610821364	0.683154293110202	   
df.mm.trans1:probe17	-0.0166589207080848	0.05552545233709	-0.300023142665278	0.764225485275019	   
df.mm.trans1:probe18	-0.0199247595665852	0.05552545233709	-0.358840112559980	0.719794857484679	   
df.mm.trans1:probe19	-0.0887227646081481	0.05552545233709	-1.59787558450709	0.110404962331625	   
df.mm.trans1:probe20	-0.0884836924330916	0.05552545233709	-1.59356995231511	0.111366780803079	   
df.mm.trans1:probe21	-0.0841683885929064	0.05552545233709	-1.51585237130402	0.129891096801115	   
df.mm.trans1:probe22	-0.0716437934172897	0.05552545233709	-1.29028743399238	0.197266501495829	   
df.mm.trans1:probe23	-0.0729427119321233	0.05552545233709	-1.31368064305527	0.189272529722512	   
df.mm.trans1:probe24	-0.0351875089983928	0.05552545233709	-0.633718547392871	0.526417867485955	   
df.mm.trans1:probe25	0.000501480508753559	0.0555254523370899	0.0090315429707644	0.992795875474387	   
df.mm.trans1:probe26	-0.0598357282173817	0.05552545233709	-1.0776270286665	0.281475239107622	   
df.mm.trans1:probe27	-0.0735504287473675	0.05552545233709	-1.32462547627437	0.185615639420429	   
df.mm.trans1:probe28	-0.124147694311363	0.05552545233709	-2.23587002151147	0.025593087454441	*  
df.mm.trans1:probe29	-0.113955835333011	0.05552545233709	-2.05231710029475	0.0404138662128565	*  
df.mm.trans1:probe30	-0.109365174022335	0.05552545233709	-1.96964039767545	0.0491713243639708	*  
df.mm.trans1:probe31	-0.0821449723406742	0.05552545233709	-1.47941113278969	0.139363730038352	   
df.mm.trans1:probe32	-0.132567321641903	0.05552545233709	-2.38750547833630	0.0171588294373193	*  
df.mm.trans2:probe2	0.00968593680587089	0.05552545233709	0.174441384953849	0.861555956069168	   
df.mm.trans2:probe3	-0.0505301923218948	0.05552545233709	-0.91003657232958	0.363035272698598	   
df.mm.trans2:probe4	0.0380933292937694	0.05552545233709	0.686051669827168	0.492848805017877	   
df.mm.trans2:probe5	1.51895496692521e-05	0.05552545233709	0.000273560124770128	0.999781788300094	   
df.mm.trans2:probe6	-0.0421808447519704	0.05552545233709	-0.759666837037083	0.447643218381817	   
df.mm.trans3:probe2	0.055142103284286	0.05552545233709	0.993095976049385	0.320917397653457	   
df.mm.trans3:probe3	-0.0433233641049265	0.05552545233709	-0.780243334928896	0.435443041696857	   
df.mm.trans3:probe4	-0.0852027141277323	0.05552545233709	-1.53448032463517	0.125246241337339