chr2.13984_chr2_153493616_153498296_+_2.R 

fitVsDatCorrelation=0.909643349316568
cont.fitVsDatCorrelation=0.255046970779423

fstatistic=11224.9791389898,57,807
cont.fstatistic=2060.07006958072,57,807

residuals=-0.655420334401583,-0.0861632493836221,-0.00405388824733712,0.0854970636488767,0.819619221091606
cont.residuals=-0.742286725299508,-0.285286390473913,-0.0382602035235428,0.242315088620408,1.12380197260441

predictedValues:
Include	Exclude	Both
chr2.13984_chr2_153493616_153498296_+_2.R.tl.Lung	98.773232216232	43.4379879118708	76.0634295877318
chr2.13984_chr2_153493616_153498296_+_2.R.tl.cerebhem	90.7323892925643	49.2906605992334	70.8638050915494
chr2.13984_chr2_153493616_153498296_+_2.R.tl.cortex	83.5290244990886	45.7578390734668	70.972252695801
chr2.13984_chr2_153493616_153498296_+_2.R.tl.heart	84.9941886737857	45.6017573691488	72.972452317056
chr2.13984_chr2_153493616_153498296_+_2.R.tl.kidney	100.636608538492	44.0735708759304	71.3177188598922
chr2.13984_chr2_153493616_153498296_+_2.R.tl.liver	90.9682079865938	50.6084968250327	78.0626893035879
chr2.13984_chr2_153493616_153498296_+_2.R.tl.stomach	96.802346251848	45.8285621941205	87.474003285453
chr2.13984_chr2_153493616_153498296_+_2.R.tl.testicle	93.516095830063	49.4344806140204	80.0289013493272


diffExp=55.3352443043613,41.441728693331,37.7711854256218,39.3924313046369,56.5630376625618,40.3597111615611,50.9737840577275,44.0816152160427
diffExpScore=0.997274600894123
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	68.3778472599298	72.6915793902869	65.7486539341292
cerebhem	71.5919737647028	60.8991293550348	73.1627036508189
cortex	70.0891440637873	75.8968317220533	76.9010481920447
heart	66.7023185591451	85.1833997890984	76.8895731542358
kidney	66.6786497741268	66.0311672243958	75.2234253711121
liver	63.3262898997594	62.7765005404185	80.125462893616
stomach	73.065908766435	75.3957563174995	67.1337916564565
testicle	73.0641492248656	74.6153995394094	72.3543454996434
cont.diffExp=-4.31373213035715,10.692844409668,-5.80768765826608,-18.4810812299533,0.647482549731052,0.549789359340892,-2.32984755106459,-1.55125031454385
cont.diffExpScore=2.05495871582724

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,-1,0,0,0,0
cont.diffExp1.2Score=0.5

tran.correlation=-0.317695371489037
cont.tran.correlation=0.183078231978351

tran.covariance=-0.00116586545065777
cont.tran.covariance=0.00118782187463829

tran.mean=69.6240905469682
cont.tran.mean=70.3991278244343

weightedLogRatios:
wLogRatio
Lung	3.43554685674324
cerebhem	2.56447850965647
cortex	2.48211893738624
heart	2.57227665383444
kidney	3.46667122336859
liver	2.47299374208788
stomach	3.13970230949130
testicle	2.68980007824804

cont.weightedLogRatios:
wLogRatio
Lung	-0.260345626188053
cerebhem	0.677807867633493
cortex	-0.341480008279716
heart	-1.05714592742634
kidney	0.0409346450454903
liver	0.0361341556837637
stomach	-0.135194614776108
testicle	-0.0903778461760178

varWeightedLogRatios=0.181256197766280
cont.varWeightedLogRatios=0.233039711181794

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.53711885147935	0.0738548789734606	61.432892647617	1.6455660656724e-306	***
df.mm.trans1	0.411898970150627	0.0638478919011592	6.45125403338726	1.91061507973757e-10	***
df.mm.trans2	-0.764340812930975	0.0567037004546053	-13.4795578913386	1.69462458733071e-37	***
df.mm.exp2	0.112295820351079	0.0733534066248613	1.5308875963372	0.126189060317176	   
df.mm.exp3	-0.0463251031792005	0.0733534066248613	-0.631533084974677	0.527870865008326	   
df.mm.exp4	-0.0601462670098097	0.0733534066248613	-0.819951925578664	0.412485620077254	   
df.mm.exp5	0.0976381856867005	0.0733534066248612	1.33106545666018	0.183543390511374	   
df.mm.exp6	0.0445239506357646	0.0733534066248612	0.606978635136413	0.544035819190287	   
df.mm.exp7	-0.106356289130785	0.0733534066248613	-1.44991615283398	0.147470417537398	   
df.mm.exp8	0.0238004991604723	0.0733534066248613	0.324463446969698	0.745671274970168	   
df.mm.trans1:exp2	-0.197208062480329	0.0677738850384719	-2.90979427206192	0.00371609697487525	** 
df.mm.trans2:exp2	0.0141044468082594	0.051232241484708	0.275304113181722	0.783153076932273	   
df.mm.trans1:exp3	-0.121307365631403	0.0677738850384719	-1.78988360431960	0.0738474525060482	.  
df.mm.trans2:exp3	0.098353870325404	0.051232241484708	1.91976512202303	0.055239843641297	.  
df.mm.trans1:exp4	-0.0900974864412362	0.0677738850384719	-1.32938352862747	0.184097144116144	   
df.mm.trans2:exp4	0.108758165819247	0.051232241484708	2.12284613492285	0.0340706002880792	*  
df.mm.trans1:exp5	-0.0789487313046723	0.0677738850384719	-1.16488425091548	0.244410070076168	   
df.mm.trans2:exp5	-0.083112238516797	0.051232241484708	-1.62226434191064	0.105137336554249	   
df.mm.trans1:exp6	-0.126840507005422	0.0677738850384719	-1.8715248053645	0.0616339482686471	.  
df.mm.trans2:exp6	0.108261177238336	0.051232241484708	2.11314543539247	0.0348947497998224	*  
df.mm.trans1:exp7	0.0862008821980757	0.0677738850384719	1.27188934423847	0.203778836621525	   
df.mm.trans2:exp7	0.159929458802521	0.051232241484708	3.12165648364726	0.00186246124245736	** 
df.mm.trans1:exp8	-0.0784935688268989	0.0677738850384719	-1.15816835322841	0.247137973652413	   
df.mm.trans2:exp8	0.105513313925613	0.051232241484708	2.05951000518116	0.0397656807626278	*  
df.mm.trans1:probe2	-0.0381719015003088	0.0454641042135838	-0.83960527014857	0.401378398296516	   
df.mm.trans1:probe3	-0.241825178771627	0.0454641042135838	-5.31903537867076	1.35200935611913e-07	***
df.mm.trans1:probe4	-0.334894958180283	0.0454641042135838	-7.36614003449832	4.34344933050797e-13	***
df.mm.trans1:probe5	-0.145247900416158	0.0454641042135838	-3.19478196983282	0.00145373695109414	** 
df.mm.trans1:probe6	-0.5031740897232	0.0454641042135838	-11.0675025589278	1.32364858082546e-26	***
df.mm.trans1:probe7	-0.181986291601616	0.0454641042135838	-4.00285664370886	6.83473429506451e-05	***
df.mm.trans1:probe8	-0.116008739977739	0.0454641042135838	-2.55165568494975	0.0109045414911412	*  
df.mm.trans1:probe9	0.082193188412696	0.0454641042135838	1.80786996322559	0.0709989367838442	.  
df.mm.trans1:probe10	-0.91259282650026	0.0454641042135838	-20.0728210153010	5.21794215735217e-73	***
df.mm.trans1:probe11	-0.722359136158304	0.0454641042135838	-15.8885597473727	1.15407650898622e-49	***
df.mm.trans1:probe12	-1.00896792345891	0.0454641042135837	-22.1926273685922	1.48320759882402e-85	***
df.mm.trans1:probe13	-0.912808495828294	0.0454641042135838	-20.0775647429465	4.89607385951388e-73	***
df.mm.trans1:probe14	-0.77358047116832	0.0454641042135838	-17.0151921950150	1.03124791963763e-55	***
df.mm.trans1:probe15	-0.903833551450583	0.0454641042135837	-19.8801574799429	6.89768397992432e-72	***
df.mm.trans1:probe16	-0.573262899728249	0.0454641042135838	-12.6091321855841	2.11087424143154e-33	***
df.mm.trans1:probe17	-0.651070817323296	0.0454641042135838	-14.3205464747454	1.29583093728905e-41	***
df.mm.trans1:probe18	-0.745668149661549	0.0454641042135838	-16.4012502293789	2.16201010379952e-52	***
df.mm.trans1:probe19	-0.757960668282054	0.0454641042135838	-16.6716287803949	7.57345668787203e-54	***
df.mm.trans1:probe20	-0.517115278707096	0.0454641042135838	-11.3741442320685	6.59294587910996e-28	***
df.mm.trans1:probe21	-0.727399387061209	0.0454641042135838	-15.9994219537240	2.99363883088691e-50	***
df.mm.trans2:probe2	-0.0097502735913162	0.0454641042135838	-0.21446091944341	0.830241818171981	   
df.mm.trans2:probe3	-0.089765090115747	0.0454641042135838	-1.97441677711374	0.0486749411594692	*  
df.mm.trans2:probe4	0.0857111986963345	0.0454641042135838	1.88524991702631	0.0597551350591668	.  
df.mm.trans2:probe5	-0.0344274704062728	0.0454641042135838	-0.757245105821012	0.449124067418216	   
df.mm.trans2:probe6	0.0265763936728352	0.0454641042135838	0.584557732579161	0.559008515874106	   
df.mm.trans3:probe2	0.0949697946340275	0.0454641042135838	2.08889620232862	0.0370298419042287	*  
df.mm.trans3:probe3	0.187193890554208	0.0454641042135838	4.1173997330905	4.22620732413106e-05	***
df.mm.trans3:probe4	0.381024224165955	0.0454641042135838	8.38077051680064	2.32489121226441e-16	***
df.mm.trans3:probe5	0.246637153476222	0.0454641042135838	5.42487656454324	7.67052205353052e-08	***
df.mm.trans3:probe6	0.0812123283070894	0.0454641042135838	1.78629557783797	0.0744267446303187	.  
df.mm.trans3:probe7	0.113517747766833	0.0454641042135838	2.49686537831127	0.0127279546430735	*  
df.mm.trans3:probe8	0.00039582740082018	0.0454641042135838	0.00870637193159334	0.99305555977166	   
df.mm.trans3:probe9	0.217064283764973	0.0454641042135838	4.77441021921903	2.13996713350984e-06	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.10503111704266	0.171916448771511	23.8780590593663	9.59742304960984e-96	***
df.mm.trans1	0.046876430631809	0.148622582417865	0.31540584122009	0.752535075825582	   
df.mm.trans2	0.18280447914974	0.131992617818279	1.38495987253935	0.166447475003157	   
df.mm.exp2	-0.237919184771992	0.170749141390786	-1.39338436980762	0.163887228748501	   
df.mm.exp3	-0.0888119021391114	0.170749141390786	-0.520130885670762	0.603115003944754	   
df.mm.exp4	-0.0227592419779327	0.170749141390786	-0.133290520775415	0.893996853837211	   
df.mm.exp5	-0.255886274820444	0.170749141390786	-1.49860943801064	0.134366037422860	   
df.mm.exp6	-0.421147573290494	0.170749141390786	-2.46646963996518	0.0138520180889945	*  
df.mm.exp7	0.0819901117969257	0.170749141390786	0.480178764760396	0.631230411841766	   
df.mm.exp8	-0.00332604199614058	0.170749141390786	-0.0194791140327225	0.984463713408862	   
df.mm.trans1:exp2	0.283853252494497	0.157761353037348	1.79925721369351	0.0723514795499687	.  
df.mm.trans2:exp2	0.0609125120683852	0.119256373323968	0.510769448798449	0.609652196537784	   
df.mm.trans1:exp3	0.113530918915412	0.157761353037348	0.719637076696058	0.471956829170741	   
df.mm.trans2:exp3	0.131961291864578	0.119256373323968	1.10653450366209	0.268824974522445	   
df.mm.trans1:exp4	-0.00204994640024163	0.157761353037348	-0.0129939707081260	0.989635814706819	   
df.mm.trans2:exp4	0.181340267661243	0.119256373323968	1.52059183594842	0.128753990827170	   
df.mm.trans1:exp5	0.230722181457513	0.157761353037348	1.46247592972211	0.144000153718073	   
df.mm.trans2:exp5	0.159787585041301	0.119256373323968	1.33986621081648	0.180665998160998	   
df.mm.trans1:exp6	0.344399236787008	0.157761353037348	2.18303931955677	0.0293203928408793	*  
df.mm.trans2:exp6	0.274502830507463	0.119256373323968	2.30178750918207	0.0216010074042304	*  
df.mm.trans1:exp7	-0.0156771198693962	0.157761353037348	-0.0993723720516315	0.920867297079755	   
df.mm.trans2:exp7	-0.0454646716406182	0.119256373323968	-0.381234732982449	0.703129423897834	   
df.mm.trans1:exp8	0.0696149520668132	0.157761353037348	0.441267463333258	0.659137576626212	   
df.mm.trans2:exp8	0.0294474050322973	0.119256373323968	0.2469252100456	0.805028906372721	   
df.mm.trans1:probe2	0.131193516072564	0.105829532884156	1.23966829009982	0.215458475802301	   
df.mm.trans1:probe3	0.136657600161575	0.105829532884156	1.29129928515478	0.196969665981134	   
df.mm.trans1:probe4	0.157425650439869	0.105829532884156	1.48753987804322	0.137262892160961	   
df.mm.trans1:probe5	0.124472969039946	0.105829532884156	1.17616477789992	0.239875874481025	   
df.mm.trans1:probe6	0.143857449272152	0.105829532884156	1.35933179852190	0.174421191068286	   
df.mm.trans1:probe7	0.129774509446273	0.105829532884156	1.22625987198042	0.220458582834755	   
df.mm.trans1:probe8	0.200830063698860	0.105829532884156	1.89767504613947	0.0580955578135886	.  
df.mm.trans1:probe9	0.132182639461638	0.105829532884156	1.24901467349694	0.212021881988787	   
df.mm.trans1:probe10	0.137058167519208	0.105829532884156	1.29508430949266	0.195661522172222	   
df.mm.trans1:probe11	-0.0414395880138897	0.105829532884156	-0.391569223491241	0.695479902165548	   
df.mm.trans1:probe12	0.0725424284311445	0.105829532884156	0.685464883517453	0.4932474642485	   
df.mm.trans1:probe13	0.103378453410150	0.105829532884156	0.976839362253552	0.328941413669303	   
df.mm.trans1:probe14	0.0764307687697372	0.105829532884156	0.722206426569041	0.470376790575221	   
df.mm.trans1:probe15	0.178055505794664	0.105829532884156	1.68247464523507	0.092863668754501	.  
df.mm.trans1:probe16	0.0554142518247081	0.105829532884156	0.523618032835561	0.60068799346975	   
df.mm.trans1:probe17	0.0901028345438415	0.105829532884156	0.851395939189022	0.394802011079423	   
df.mm.trans1:probe18	0.0215785067487944	0.105829532884156	0.203898724304253	0.838484048043906	   
df.mm.trans1:probe19	0.15776498661527	0.105829532884156	1.49074631925253	0.136418859419176	   
df.mm.trans1:probe20	0.0724983116318772	0.105829532884156	0.685048016901254	0.493510332874415	   
df.mm.trans1:probe21	0.114461595965749	0.105829532884156	1.08156572977641	0.279768626389158	   
df.mm.trans2:probe2	0.0426069190059311	0.105829532884156	0.40259951872385	0.687349485241516	   
df.mm.trans2:probe3	0.0990683252386252	0.105829532884156	0.93611227923559	0.349495422915619	   
df.mm.trans2:probe4	-0.106274212588671	0.105829532884156	-1.00420184888278	0.315582334607671	   
df.mm.trans2:probe5	0.0319752475154423	0.105829532884156	0.302139172724529	0.762623821350419	   
df.mm.trans2:probe6	-0.09152695687107	0.105829532884156	-0.864852696375954	0.387376649133131	   
df.mm.trans3:probe2	-0.285672066911796	0.105829532884156	-2.69936055774243	0.00709263355842677	** 
df.mm.trans3:probe3	-0.181665661254057	0.105829532884156	-1.71658757535019	0.08643828919751	.  
df.mm.trans3:probe4	-0.203540386350182	0.105829532884156	-1.92328531368444	0.0547957793284668	.  
df.mm.trans3:probe5	-0.163946637497541	0.105829532884156	-1.54915771646656	0.121735865371918	   
df.mm.trans3:probe6	-0.178590069378044	0.105829532884156	-1.68752582111020	0.0918887056246875	.  
df.mm.trans3:probe7	-0.107301583959065	0.105829532884156	-1.01390964350679	0.310929755265186	   
df.mm.trans3:probe8	-0.156743431401537	0.105829532884156	-1.48109348241301	0.138971983607351	   
df.mm.trans3:probe9	-0.0623956193934259	0.105829532884156	-0.589586079546679	0.555633209674197