chr11.3475_chr11_70594351_70594597_-_0.R 

fitVsDatCorrelation=0.943800569572368
cont.fitVsDatCorrelation=0.295004429322397

fstatistic=6578.68590466026,37,347
cont.fstatistic=778.90760613311,37,347

residuals=-0.918299824019113,-0.0879651249502658,0.00410929003344807,0.0774362370658941,0.823240671418096
cont.residuals=-0.73186381464892,-0.359197592637724,-0.104701593163256,0.206351751602468,2.34522192055311

predictedValues:
Include	Exclude	Both
chr11.3475_chr11_70594351_70594597_-_0.R.tl.Lung	46.3464981758693	60.7520692496901	88.2876151763161
chr11.3475_chr11_70594351_70594597_-_0.R.tl.cerebhem	55.5483477576027	60.0264525188525	96.7803476168214
chr11.3475_chr11_70594351_70594597_-_0.R.tl.cortex	47.7024381220042	60.2063144525051	71.8283594307664
chr11.3475_chr11_70594351_70594597_-_0.R.tl.heart	51.5557070562633	198.494427959373	237.952314957359
chr11.3475_chr11_70594351_70594597_-_0.R.tl.kidney	46.3223152791508	74.7836706726287	112.314335575295
chr11.3475_chr11_70594351_70594597_-_0.R.tl.liver	51.9157153714421	89.7609016406599	107.926109225426
chr11.3475_chr11_70594351_70594597_-_0.R.tl.stomach	51.0705185862306	72.4454066896381	89.6532920149328
chr11.3475_chr11_70594351_70594597_-_0.R.tl.testicle	51.1171549075269	98.4676498981786	126.206796215221


diffExp=-14.4055710738208,-4.47810476124982,-12.5038763305009,-146.938720903109,-28.4613553934779,-37.8451862692178,-21.3748881034076,-47.3504949906517
diffExpScore=0.99681891546994
diffExp1.5=0,0,0,-1,-1,-1,0,-1
diffExp1.5Score=0.8
diffExp1.4=0,0,0,-1,-1,-1,-1,-1
diffExp1.4Score=0.833333333333333
diffExp1.3=-1,0,0,-1,-1,-1,-1,-1
diffExp1.3Score=0.857142857142857
diffExp1.2=-1,0,-1,-1,-1,-1,-1,-1
diffExp1.2Score=0.875

cont.predictedValues:
Include	Exclude	Both
Lung	79.3176585950306	63.8336025165983	68.154566317676
cerebhem	74.4365002423215	59.9111959531341	69.5249006236169
cortex	66.7784898544937	67.84766493406	74.343146558357
heart	70.3377687191873	71.7116234653682	79.7468726861739
kidney	95.866357487709	59.3816353360253	77.7585471268722
liver	77.7656743456588	69.2595828152455	63.5051108199045
stomach	76.6244682246979	81.760761162109	79.6153509422826
testicle	72.9806580223553	66.3209401127646	79.9383298268321
cont.diffExp=15.4840560784324,14.5253042891874,-1.06917507956625,-1.37385474618097,36.4847221516837,8.50609153041333,-5.1362929374111,6.65971790959067
cont.diffExpScore=1.18857935785392

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

tran.correlation=0.217669868472540
cont.tran.correlation=-0.393612977428515

tran.covariance=0.0061948622998901
cont.tran.covariance=-0.00456597533622395

tran.mean=69.782224271101
cont.tran.mean=72.1334113616724

weightedLogRatios:
wLogRatio
Lung	-1.07490075629468
cerebhem	-0.314469556340148
cortex	-0.926844244051496
heart	-6.22378070833694
kidney	-1.95187962774577
liver	-2.31242157738404
stomach	-1.43627019042889
testicle	-2.79415117312039

cont.weightedLogRatios:
wLogRatio
Lung	0.926248992118531
cerebhem	0.912053656271037
cortex	-0.0668606761945128
heart	-0.0824628538619983
kidney	2.07081289999436
liver	0.497617298897117
stomach	-0.283617930681101
testicle	0.405945222945435

varWeightedLogRatios=3.37190975823413
cont.varWeightedLogRatios=0.583486805874977

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	2.99704645757491	0.093338930620299	32.1092864216201	6.04117042601182e-106	***
df.mm.trans1	0.845664368183594	0.0777641382788266	10.8747346386252	6.71884028497536e-24	***
df.mm.trans2	1.07858932163457	0.0777641382788266	13.8700093064395	4.13925134144585e-35	***
df.mm.exp2	0.0772481180349909	0.107142646453287	0.720983852761844	0.471404903086651	   
df.mm.exp3	0.226133330626902	0.107142646453287	2.11058190284196	0.0355233759220081	*  
df.mm.exp4	0.299006604734939	0.107142646453287	2.79073379865881	0.00554965261575344	** 
df.mm.exp5	-0.0334251782550205	0.107142646453287	-0.31196894384715	0.755251492902315	   
df.mm.exp6	0.302977171469948	0.107142646453287	2.82779249439245	0.00495907176135739	** 
df.mm.exp7	0.257743700465905	0.107142646453287	2.40561260149831	0.0166680424799025	*  
df.mm.exp8	0.223579377292106	0.107142646453287	2.08674495817671	0.0376407200594704	*  
df.mm.trans1:exp2	0.103859916874314	0.0905520635128687	1.14696355715355	0.252186910317819	   
df.mm.trans2:exp2	-0.0892639210195118	0.0905520635128686	-0.985774565002887	0.324930592148557	   
df.mm.trans1:exp3	-0.197296557766521	0.0905520635128686	-2.17881901430642	0.030017481595466	*  
df.mm.trans2:exp3	-0.235157235939066	0.0905520635128686	-2.59692851621926	0.00980636825873524	** 
df.mm.trans1:exp4	-0.192489428654414	0.0905520635128686	-2.12573210578530	0.0342313703574926	*  
df.mm.trans2:exp4	0.884953280900811	0.0905520635128686	9.77286708408415	4.36195879426221e-20	***
df.mm.trans1:exp5	0.0329032573116975	0.0905520635128686	0.363362865905552	0.716555098609494	   
df.mm.trans2:exp5	0.241223589523593	0.0905520635128686	2.66392150731398	0.00808391393499369	** 
df.mm.trans1:exp6	-0.189501363538402	0.0905520635128686	-2.09273379519918	0.0370988573669755	*  
df.mm.trans2:exp6	0.0873711719063862	0.0905520635128686	0.964872235009527	0.335280753478342	   
df.mm.trans1:exp7	-0.160682042834392	0.0905520635128686	-1.77447135494109	0.076861936740955	.  
df.mm.trans2:exp7	-0.0817115768018678	0.0905520635128686	-0.90237122857234	0.367485636983424	   
df.mm.trans1:exp8	-0.125604961341714	0.0905520635128686	-1.38710214288893	0.166300915832685	   
df.mm.trans2:exp8	0.259347546148315	0.0905520635128686	2.86407107786625	0.00443680167945265	** 
df.mm.trans1:probe2	0.252449127421435	0.0495974078146387	5.08996616042754	5.88235118751348e-07	***
df.mm.trans1:probe3	-0.0619417623268437	0.0495974078146387	-1.24889112266391	0.212546765123181	   
df.mm.trans1:probe4	-0.0572169180778133	0.0495974078146387	-1.15362718736534	0.249447017770147	   
df.mm.trans1:probe5	-0.0778027303186525	0.0495974078146387	-1.56868541616986	0.117632666089258	   
df.mm.trans1:probe6	-0.121138600318086	0.0495974078146387	-2.4424381365014	0.0150868159295347	*  
df.mm.trans2:probe2	0.0447051722218961	0.0495974078146387	0.901361062839687	0.368021555355350	   
df.mm.trans2:probe3	-0.0178448826104	0.0495974078146387	-0.359794662597933	0.719219566255634	   
df.mm.trans2:probe4	0.07547595423941	0.0495974078146387	1.52177215634913	0.128976901254593	   
df.mm.trans2:probe5	0.113138358547905	0.0495974078146387	2.28113450950378	0.0231459708288066	*  
df.mm.trans2:probe6	0.0961790391450585	0.0495974078146387	1.93919487696837	0.0532879479884232	.  
df.mm.trans3:probe2	-0.255632249594271	0.0495974078146387	-5.15414536480718	4.28659864072552e-07	***
df.mm.trans3:probe3	-0.723313394464126	0.0495974078146387	-14.5836935100999	6.58590823170304e-38	***
df.mm.trans3:probe4	-0.783855588338263	0.0495974078146387	-15.8043660521086	9.17326104905642e-43	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.27696583678021	0.269835964044683	15.8502438765797	6.0070687318422e-43	***
df.mm.trans1	0.126268464977578	0.224810388131957	0.56166650494577	0.574705836881904	   
df.mm.trans2	-0.23621973830582	0.224810388131956	-1.05075099184103	0.294104179317002	   
df.mm.exp2	-0.146837518007988	0.309741488400274	-0.474064739490865	0.635751895856731	   
df.mm.exp3	-0.198007861305300	0.309741488400273	-0.639268127521288	0.523070291226388	   
df.mm.exp4	-0.160858136632498	0.309741488400273	-0.51933028882661	0.603861515550111	   
df.mm.exp5	-0.0146307165258893	0.309741488400273	-0.0472352496317261	0.962352907057522	   
df.mm.exp6	0.132478895691583	0.309741488400273	0.427707945667204	0.669129073440439	   
df.mm.exp7	0.0575446032599582	0.309741488400273	0.18578267818483	0.852723740618112	   
df.mm.exp8	-0.204517688492863	0.309741488400273	-0.660285096288324	0.509508949253963	   
df.mm.trans1:exp2	0.0833231494528676	0.261779336787435	0.318295364620494	0.750452379409376	   
df.mm.trans2:exp2	0.083421179486645	0.261779336787435	0.318669840448038	0.750168610238033	   
df.mm.trans1:exp3	0.0259280970790643	0.261779336787435	0.0990456213895829	0.921159239788929	   
df.mm.trans2:exp3	0.258993094959349	0.261779336787435	0.989356524994379	0.323178104788637	   
df.mm.trans1:exp4	0.0407062570634090	0.261779336787435	0.155498358132302	0.87651886360133	   
df.mm.trans2:exp4	0.277231246673058	0.261779336787435	1.05902646891558	0.290324348131544	   
df.mm.trans1:exp5	0.204125043859219	0.261779336787434	0.779759954946213	0.43606369579106	   
df.mm.trans2:exp5	-0.0576640112493228	0.261779336787435	-0.220277169149321	0.825784838282591	   
df.mm.trans1:exp6	-0.152239550396381	0.261779336787435	-0.581556788494733	0.561242841990088	   
df.mm.trans2:exp6	-0.0508971171081267	0.261779336787435	-0.194427557700841	0.845954890306011	   
df.mm.trans1:exp7	-0.092088933745793	0.261779336787435	-0.351780758847935	0.725216213840896	   
df.mm.trans2:exp7	0.189973095950877	0.261779336787435	0.725699355351089	0.468512246264047	   
df.mm.trans1:exp8	0.121251351188839	0.261779336787435	0.463181520271387	0.643524622271519	   
df.mm.trans2:exp8	0.242743637709094	0.261779336787435	0.927283416208675	0.354423913540631	   
df.mm.trans1:probe2	-0.120893659265468	0.14338244784722	-0.843155219349339	0.399722454663746	   
df.mm.trans1:probe3	-0.215491930978971	0.14338244784722	-1.50291708793106	0.133769934476865	   
df.mm.trans1:probe4	0.218779897858948	0.14338244784722	1.5258485340693	0.127958502572539	   
df.mm.trans1:probe5	-0.00999268683111902	0.14338244784722	-0.0696925389484678	0.944478525165368	   
df.mm.trans1:probe6	-0.170136790893174	0.14338244784722	-1.18659426901724	0.236199459999517	   
df.mm.trans2:probe2	0.227905963808564	0.14338244784722	1.58949695189614	0.112858896974197	   
df.mm.trans2:probe3	0.313220149548697	0.14338244784722	2.18450831500970	0.0295936357718169	*  
df.mm.trans2:probe4	0.242004769360053	0.14338244784722	1.68782701783638	0.0923429715799694	.  
df.mm.trans2:probe5	0.251484917111269	0.14338244784722	1.75394492761929	0.0803227239360178	.  
df.mm.trans2:probe6	0.120720584566583	0.14338244784722	0.841948135068917	0.400396869412088	   
df.mm.trans3:probe2	0.0848985494214816	0.14338244784722	0.592112568143241	0.554160811645135	   
df.mm.trans3:probe3	0.0991195265632584	0.14338244784722	0.691294702046616	0.489842579599658	   
df.mm.trans3:probe4	0.0350363095098878	0.14338244784722	0.244355637917554	0.807099817171156