chr4.16975_chr4_131571037_131571646_-_0.R 

fitVsDatCorrelation=0.892249334086774
cont.fitVsDatCorrelation=0.294151937935241

fstatistic=6995.5545083254,37,347
cont.fstatistic=1554.15014675587,37,347

residuals=-0.563758347499614,-0.0814134780181458,-0.00079684041670282,0.0696182916548156,0.824198951217091
cont.residuals=-0.556936290269299,-0.214125267424247,-0.0594127315373011,0.138538324214035,1.26283859133216

predictedValues:
Include	Exclude	Both
chr4.16975_chr4_131571037_131571646_-_0.R.tl.Lung	57.2559868887554	42.6127262856609	77.6254208057757
chr4.16975_chr4_131571037_131571646_-_0.R.tl.cerebhem	94.9959899899494	45.0319391906235	92.5890371708991
chr4.16975_chr4_131571037_131571646_-_0.R.tl.cortex	58.207857399303	50.9299844544997	97.428903762425
chr4.16975_chr4_131571037_131571646_-_0.R.tl.heart	54.2857381033293	47.6042811309754	81.1562213038854
chr4.16975_chr4_131571037_131571646_-_0.R.tl.kidney	56.9819680229478	44.5052863162776	82.7381785720958
chr4.16975_chr4_131571037_131571646_-_0.R.tl.liver	57.711018040593	46.1413611795475	83.1370642915778
chr4.16975_chr4_131571037_131571646_-_0.R.tl.stomach	54.471593645864	49.4209404597565	76.7011011824173
chr4.16975_chr4_131571037_131571646_-_0.R.tl.testicle	67.5353432116045	44.8649840920112	84.9894934141081


diffExp=14.6432606030945,49.964050799326,7.27787294480324,6.68145697235389,12.4766817066702,11.5696568610455,5.0506531861075,22.6703591195933
diffExpScore=0.992385825000046
diffExp1.5=0,1,0,0,0,0,0,1
diffExp1.5Score=0.666666666666667
diffExp1.4=0,1,0,0,0,0,0,1
diffExp1.4Score=0.666666666666667
diffExp1.3=1,1,0,0,0,0,0,1
diffExp1.3Score=0.75
diffExp1.2=1,1,0,0,1,1,0,1
diffExp1.2Score=0.833333333333333

cont.predictedValues:
Include	Exclude	Both
Lung	65.1645180845295	65.561062099604	60.3708250018574
cerebhem	61.6468553660938	61.1661021876197	56.1189816615863
cortex	61.5898439051473	54.819719003442	56.7094819010176
heart	62.5211482245294	60.9299035640097	58.9360155834715
kidney	58.1875774899655	52.2089006394121	58.3471477027705
liver	62.6508204054024	53.0395415124175	57.5833055176247
stomach	54.5688516883936	56.9728280615605	73.4383406257488
testicle	59.3146983093102	56.4569790628554	60.8143650626029
cont.diffExp=-0.396544015074468,0.480753178474131,6.77012490170536,1.59124466051972,5.97867685055339,9.61127889298488,-2.40397637316686,2.85771924645488
cont.diffExpScore=1.18050887495425

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=-0.280510184555916
cont.tran.correlation=0.50318516838831

tran.covariance=-0.00321219944402059
cont.tran.covariance=0.00203053305437096

tran.mean=54.5348124007312
cont.tran.mean=59.1749593502683

weightedLogRatios:
wLogRatio
Lung	1.15193262963549
cerebhem	3.1206643819166
cortex	0.533904896472417
heart	0.51597675340242
kidney	0.968532650929989
liver	0.882329866094127
stomach	0.384260517556994
testicle	1.63930882484941

cont.weightedLogRatios:
wLogRatio
Lung	-0.0253590560820489
cerebhem	0.0322362567856211
cortex	0.473039641498504
heart	0.106284256312850
kidney	0.434701491473706
liver	0.675200575966175
stomach	-0.17335100973158
testicle	0.200385126852303

varWeightedLogRatios=0.799348154618564
cont.varWeightedLogRatios=0.082951545374058

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.39569259500880	0.086032326463049	39.4699612879497	2.31776444405742e-130	***
df.mm.trans1	0.661590514516514	0.0716767343171888	9.23019890371677	2.72657889967690e-18	***
df.mm.trans2	0.313117929999802	0.0716767343171888	4.36847371720608	1.65448454432357e-05	***
df.mm.exp2	0.385245734361427	0.0987554825893792	3.90100604300889	0.000115044002639116	***
df.mm.exp3	-0.0324409296414314	0.0987554825893791	-0.328497505058218	0.742733675842133	   
df.mm.exp4	0.0130180861006869	0.0987554825893791	0.131821401296933	0.895201957210235	   
df.mm.exp5	-0.0251285018230047	0.0987554825893791	-0.254451714113817	0.799297325570513	   
df.mm.exp6	0.018877041841656	0.0987554825893791	0.191149304795015	0.848520412745568	   
df.mm.exp7	0.110347315368751	0.0987554825893791	1.11737913152195	0.264605295157288	   
df.mm.exp8	0.125990850241670	0.0987554825893791	1.27578587981322	0.202884565317649	   
df.mm.trans1:exp2	0.121056734273212	0.0834636162881818	1.45041324180382	0.147846613784679	   
df.mm.trans2:exp2	-0.330026684321541	0.0834636162881817	-3.95413832995243	9.31227020855762e-05	***
df.mm.trans1:exp3	0.0489290706841971	0.0834636162881817	0.586232335240012	0.558100526526834	   
df.mm.trans2:exp3	0.210739817543516	0.0834636162881817	2.52493034588721	0.0120171756830140	*  
df.mm.trans1:exp4	-0.0662887551330218	0.0834636162881817	-0.794223376376853	0.427608220815329	   
df.mm.trans2:exp4	0.0977516630570225	0.0834636162881817	1.17118892523788	0.242326447203453	   
df.mm.trans1:exp5	0.0203311576906920	0.0834636162881817	0.243593060004649	0.807689950149217	   
df.mm.trans2:exp5	0.0685835298023066	0.0834636162881817	0.821717687926468	0.411801816414163	   
df.mm.trans1:exp6	-0.0109611440901186	0.0834636162881817	-0.131328410840385	0.8955916260645	   
df.mm.trans2:exp6	0.0606797637809501	0.0834636162881817	0.72702054475373	0.467703555070432	   
df.mm.trans1:exp7	-0.160200178530595	0.0834636162881817	-1.91940135900005	0.0557533803416735	.  
df.mm.trans2:exp7	0.0378739671914040	0.0834636162881817	0.453778171564402	0.650272164264279	   
df.mm.trans1:exp8	0.0391280022965091	0.0834636162881817	0.468803102916229	0.63950476203778	   
df.mm.trans2:exp8	-0.0744861718280025	0.0834636162881817	-0.892438827126996	0.372776224305673	   
df.mm.trans1:probe2	0.111103527632815	0.0457149053719927	2.43035672345245	0.0155902961082138	*  
df.mm.trans1:probe3	-0.163654959504775	0.0457149053719927	-3.57990371352794	0.000392690917147110	***
df.mm.trans1:probe4	0.0734145601785749	0.0457149053719927	1.60592173561738	0.109200714566108	   
df.mm.trans1:probe5	0.0124030351848369	0.0457149053719927	0.271312717021081	0.78631185718632	   
df.mm.trans1:probe6	-0.130775144315577	0.0457149053719927	-2.86066750551992	0.00448358093578494	** 
df.mm.trans2:probe2	0.0188223484278858	0.0457149053719927	0.411733290810164	0.680789126055538	   
df.mm.trans2:probe3	0.0604410836277976	0.0457149053719928	1.32213078285899	0.186995451540689	   
df.mm.trans2:probe4	-0.0109237743618394	0.0457149053719927	-0.238954325136411	0.811282064852244	   
df.mm.trans2:probe5	0.194165234018813	0.0457149053719927	4.2473069218638	2.78217787820613e-05	***
df.mm.trans2:probe6	0.170919335818417	0.0457149053719927	3.73880979141501	0.000216196230392374	***
df.mm.trans3:probe2	-0.370444423019903	0.0457149053719927	-8.10336191238964	9.23252579797708e-15	***
df.mm.trans3:probe3	0.401479827409704	0.0457149053719927	8.78225218105057	7.45808877237373e-17	***
df.mm.trans3:probe4	-0.105059717500913	0.0457149053719927	-2.29815016887858	0.0221474223418173	*  

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.24737058474111	0.182100338051393	23.3243421192464	4.77618710070449e-73	***
df.mm.trans1	-0.075672136374487	0.151714571559168	-0.498779620156494	0.618250677254512	   
df.mm.trans2	-0.131589175306853	0.151714571559168	-0.867346978965258	0.386351314613507	   
df.mm.exp2	-0.051849853970597	0.209030808572616	-0.248048860953359	0.804243323970587	   
df.mm.exp3	-0.172785591048121	0.209030808572616	-0.826603466866927	0.409029868031097	   
df.mm.exp4	-0.0906145365044488	0.209030808572616	-0.433498473852815	0.664922036205186	   
df.mm.exp5	-0.306876712863837	0.209030808572616	-1.46809322013042	0.142984757204992	   
df.mm.exp6	-0.204009328294087	0.209030808572616	-0.97597731974144	0.329755597107289	   
df.mm.exp7	-0.513799574858399	0.209030808572616	-2.45800883786903	0.0144591666596349	*  
df.mm.exp8	-0.250881089424410	0.209030808572616	-1.20021106523757	0.230876124946614	   
df.mm.trans1:exp2	-0.00364304521313376	0.176663277234488	-0.0206214062716514	0.983559516700348	   
df.mm.trans2:exp2	-0.0175389499512026	0.176663277234488	-0.0992789799088965	0.920974095865697	   
df.mm.trans1:exp3	0.116367456681190	0.176663277234488	0.6586963544593	0.510527597383966	   
df.mm.trans2:exp3	-0.00614639805951583	0.176663277234488	-0.0347915999053816	0.97226592350497	   
df.mm.trans1:exp4	0.0492042879606273	0.176663277234488	0.278520181052215	0.78077897407136	   
df.mm.trans2:exp4	0.0173566638640188	0.176663277234488	0.0982471520721369	0.92179276842033	   
df.mm.trans1:exp5	0.193633479985077	0.176663277234488	1.09605959436643	0.273812801912321	   
df.mm.trans2:exp5	0.0791477493853075	0.176663277234488	0.448014723966959	0.654422154664959	   
df.mm.trans1:exp6	0.164670984964834	0.176663277234488	0.932117798008827	0.351923732448618	   
df.mm.trans2:exp6	-0.00793492421631021	0.176663277234488	-0.0449155271006212	0.964200476603108	   
df.mm.trans1:exp7	0.336347693281103	0.176663277234488	1.90389139467090	0.0577513221172697	.  
df.mm.trans2:exp7	0.373392074195230	0.176663277234488	2.11358059264133	0.0352643819194051	*  
df.mm.trans1:exp8	0.156823108634512	0.176663277234488	0.887695004244474	0.375319703799691	   
df.mm.trans2:exp8	0.101378050858540	0.176663277234488	0.573849033288222	0.566441719499028	   
df.mm.trans1:probe2	0.0561899439369406	0.0967624620241181	0.580699816452947	0.561819721917283	   
df.mm.trans1:probe3	0.0364728627789022	0.0967624620241181	0.376931942573053	0.70645458194008	   
df.mm.trans1:probe4	-0.0296052103794418	0.0967624620241181	-0.305957597193659	0.759820406714152	   
df.mm.trans1:probe5	-0.102836437019234	0.0967624620241181	-1.06277201786786	0.288624405687272	   
df.mm.trans1:probe6	0.0919455534555562	0.0967624620241181	0.950219243415268	0.342662204855012	   
df.mm.trans2:probe2	0.182011966305313	0.0967624620241181	1.88101834634950	0.0608065500673972	.  
df.mm.trans2:probe3	0.124720677921267	0.0967624620241181	1.28893659082569	0.198278740590250	   
df.mm.trans2:probe4	0.246897343344363	0.0967624620241181	2.55158186531905	0.0111517543359147	*  
df.mm.trans2:probe5	0.121316041574175	0.0967624620241181	1.25375108318282	0.210776504509230	   
df.mm.trans2:probe6	-0.00294058183311040	0.0967624620241181	-0.0303896962892227	0.975773733329308	   
df.mm.trans3:probe2	0.0639589360822728	0.0967624620241181	0.660989135087643	0.509057885098947	   
df.mm.trans3:probe3	0.114397823019867	0.0967624620241181	1.18225415751982	0.237914360258079	   
df.mm.trans3:probe4	0.063229982553742	0.0967624620241181	0.65345570204675	0.513895294594432