chr6.19592_chr6_130331368_130333564_+_2.R 

fitVsDatCorrelation=0.883201012559091
cont.fitVsDatCorrelation=0.222804172097086

fstatistic=12542.7784445316,62,922
cont.fstatistic=2891.53809140558,62,922

residuals=-0.664905292873021,-0.0812184889439554,-0.00322017536757196,0.0793430418110184,0.542984656445454
cont.residuals=-0.556854781604956,-0.190896307152364,-0.0799272861603928,0.0989596557456025,1.29521367029665

predictedValues:
Include	Exclude	Both
chr6.19592_chr6_130331368_130333564_+_2.R.tl.Lung	55.974454842831	44.0631343866335	49.36176783292
chr6.19592_chr6_130331368_130333564_+_2.R.tl.cerebhem	51.2547958429717	61.1281140924761	47.5519849537448
chr6.19592_chr6_130331368_130333564_+_2.R.tl.cortex	51.144287373654	46.0251809217921	46.2478368984643
chr6.19592_chr6_130331368_130333564_+_2.R.tl.heart	53.0635714385987	46.7879917744324	47.543952536067
chr6.19592_chr6_130331368_130333564_+_2.R.tl.kidney	54.4270169427925	44.1990972244781	45.9895659998794
chr6.19592_chr6_130331368_130333564_+_2.R.tl.liver	57.1663004743618	47.8709942624402	54.4683013273891
chr6.19592_chr6_130331368_130333564_+_2.R.tl.stomach	54.5370473383756	46.6738765182024	48.5164491921426
chr6.19592_chr6_130331368_130333564_+_2.R.tl.testicle	54.1155488455848	53.4832029202259	46.5822608230597


diffExp=11.9113204561975,-9.8733182495044,5.1191064518618,6.2755796641663,10.2279197183144,9.29530621192161,7.86317082017317,0.632345925358926
diffExpScore=1.44160199216078
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=1,0,0,0,1,0,0,0
diffExp1.2Score=0.666666666666667

cont.predictedValues:
Include	Exclude	Both
Lung	54.8625636656286	57.569266897358	53.2568060619601
cerebhem	55.9299806176347	57.6919446023261	51.4715318891001
cortex	54.5559398691851	54.5122508842147	51.3452536021343
heart	56.0008498817342	60.6299677434956	53.9802618648505
kidney	51.1463906337413	56.4206075503757	51.4844955017499
liver	55.6373573371386	55.7703425546204	54.2006527938984
stomach	52.8783420029588	60.2450100471832	54.5921507216644
testicle	52.7362906976213	53.6538316556808	56.6798597122977
cont.diffExp=-2.70670323172939,-1.76196398469139,0.0436889849703874,-4.62911786176142,-5.27421691663433,-0.132985217481853,-7.36666804422438,-0.91754095805954
cont.diffExpScore=0.961566538830506

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=-0.456382283192576
cont.tran.correlation=0.251959914398995

tran.covariance=-0.00195567421792480
cont.tran.covariance=0.000362428929802242

tran.mean=51.3696634499907
cont.tran.mean=55.6400585400561

weightedLogRatios:
wLogRatio
Lung	0.934419025408175
cerebhem	-0.709035592038855
cortex	0.409395578762063
heart	0.491947103147254
kidney	0.810307210704419
liver	0.702230727000413
stomach	0.610487573374719
testicle	0.0468422198999043

cont.weightedLogRatios:
wLogRatio
Lung	-0.194022835663555
cerebhem	-0.125296526721282
cortex	0.00320358591117535
heart	-0.322858342400673
kidney	-0.390976672261573
liver	-0.00959731302834558
stomach	-0.526034654503009
testicle	-0.0685464470707147

varWeightedLogRatios=0.278808677871774
cont.varWeightedLogRatios=0.0368800728244616

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.82409591744347	0.0650580784466905	58.7797243439488	0	***
df.mm.trans1	0.0314459205269660	0.0558737552019168	0.562803062248575	0.573705814934603	   
df.mm.trans2	-0.035146709886735	0.049060757830689	-0.716391499862843	0.473931054146046	   
df.mm.exp2	0.276614844192715	0.062423545015134	4.43125817551138	1.04937938975554e-05	***
df.mm.exp3	0.0184820603280416	0.062423545015134	0.296075147984000	0.76723936502835	   
df.mm.exp4	0.0441199331257742	0.062423545015134	0.706783523990471	0.479879593830446	   
df.mm.exp5	0.0458077779876061	0.062423545015134	0.733822117543956	0.463243715418033	   
df.mm.exp6	0.005512733035984	0.062423545015134	0.088311758562374	0.929648070849031	   
df.mm.exp7	0.0488192512031221	0.062423545015134	0.782064703170676	0.434377340777455	   
df.mm.exp8	0.217926687786272	0.062423545015134	3.4910975935993	0.000503852164143099	***
df.mm.trans1:exp2	-0.364701076268497	0.0573054241226554	-6.36416328562367	3.09018924235020e-10	***
df.mm.trans2:exp2	0.0507335707067908	0.040617878635727	1.24904530740722	0.211965522480227	   
df.mm.trans1:exp3	-0.108726681107081	0.0573054241226554	-1.89731919398004	0.0580980421759343	.  
df.mm.trans2:exp3	0.0250831198334391	0.040617878635727	0.617538893608695	0.53703182046307	   
df.mm.trans1:exp4	-0.0975247003868248	0.0573054241226554	-1.70184065260707	0.0891223630387109	.  
df.mm.trans2:exp4	0.0158831729616121	0.040617878635727	0.391038958584151	0.695858782099008	   
df.mm.trans1:exp5	-0.0738425355702841	0.0573054241226554	-1.28857846706156	0.197867916538247	   
df.mm.trans2:exp5	-0.0427268917940942	0.040617878635727	-1.05192327194833	0.293110366521696	   
df.mm.trans1:exp6	0.0155564160450461	0.0573054241226554	0.271464984043211	0.78609419606405	   
df.mm.trans2:exp6	0.0773735623098153	0.040617878635727	1.90491391743336	0.0571021816196295	.  
df.mm.trans1:exp7	-0.0748344359347476	0.0573054241226554	-1.30588748064360	0.191916543824176	   
df.mm.trans2:exp7	0.0087418897273029	0.040617878635727	0.215222705392931	0.829641286700652	   
df.mm.trans1:exp8	-0.251700557022658	0.0573054241226554	-4.39226409848957	1.25181705731355e-05	***
df.mm.trans2:exp8	-0.0241825251852763	0.040617878635727	-0.595366523253276	0.551744597601011	   
df.mm.trans1:probe2	0.192840322244397	0.0410507634587027	4.69760623181578	3.03269883564533e-06	***
df.mm.trans1:probe3	0.105319622119458	0.0410507634587027	2.56559472335783	0.0104569982639668	*  
df.mm.trans1:probe4	0.0575070595131691	0.0410507634587027	1.40087673572799	0.161587406275861	   
df.mm.trans1:probe5	0.507870259307632	0.0410507634587027	12.3717616072732	1.23124117173921e-32	***
df.mm.trans1:probe6	0.0248877604524982	0.0410507634587027	0.606267907234794	0.544486098824694	   
df.mm.trans1:probe7	0.0127791607279703	0.0410507634587027	0.311301414426218	0.755641863110906	   
df.mm.trans1:probe8	0.433072489922311	0.0410507634587027	10.5496817460651	1.21033862900036e-24	***
df.mm.trans1:probe9	1.08982798947184	0.0410507634587027	26.5483001447271	8.22005703177687e-116	***
df.mm.trans1:probe10	0.286899344532796	0.0410507634587027	6.98889181004925	5.31001385411864e-12	***
df.mm.trans1:probe11	0.0314981491120868	0.0410507634587027	0.767297522828635	0.44310107957268	   
df.mm.trans1:probe12	0.0400901307856815	0.0410507634587027	0.976598908471274	0.329023921451660	   
df.mm.trans1:probe13	-0.0698502765050573	0.0410507634587027	-1.70155852461373	0.0891753003641196	.  
df.mm.trans1:probe14	0.0692036949618538	0.0410507634587027	1.68580774463484	0.0921711826018735	.  
df.mm.trans1:probe15	0.0539840115128522	0.0410507634587027	1.31505499446217	0.188818388237395	   
df.mm.trans1:probe16	0.022666149639656	0.0410507634587027	0.552149283714499	0.580979890210448	   
df.mm.trans1:probe17	0.135774174664430	0.0410507634587027	3.30747014732185	0.000977830528258506	***
df.mm.trans1:probe18	0.596704161094373	0.0410507634587027	14.5357628170463	2.96600500078654e-43	***
df.mm.trans1:probe19	0.395675626507677	0.0410507634587027	9.63869105396126	5.16511129924815e-21	***
df.mm.trans1:probe20	0.697683309173831	0.0410507634587027	16.9956232330662	1.46312930722292e-56	***
df.mm.trans1:probe21	0.431026260302938	0.0410507634587027	10.4998354229527	1.94137854990598e-24	***
df.mm.trans1:probe22	0.811916081393963	0.0410507634587027	19.7783430315676	7.48797845904647e-73	***
df.mm.trans2:probe2	-0.0186873150491307	0.0410507634587027	-0.455224543337184	0.649054880554332	   
df.mm.trans2:probe3	-0.0678213693578134	0.0410507634587027	-1.65213417835803	0.0988476840711455	.  
df.mm.trans2:probe4	-0.0172597595455307	0.0410507634587027	-0.420449172958601	0.674255324441362	   
df.mm.trans2:probe5	0.0512882969124851	0.0410507634587027	1.24938716338568	0.211840577878812	   
df.mm.trans2:probe6	-0.0107087165141471	0.0410507634587027	-0.260865221786195	0.79425469841397	   
df.mm.trans3:probe2	-0.0829203543054605	0.0410507634587027	-2.01994670303462	0.0436777269278305	*  
df.mm.trans3:probe3	0.0861164587639631	0.0410507634587027	2.09780407252588	0.0361941614826384	*  
df.mm.trans3:probe4	0.230095294243966	0.0410507634587027	5.60514043728914	2.74844147962107e-08	***
df.mm.trans3:probe5	0.0460766041238715	0.0410507634587027	1.12242989512789	0.261971905973373	   
df.mm.trans3:probe6	-0.00272666121170004	0.0410507634587027	-0.0664216930933106	0.947056499457456	   
df.mm.trans3:probe7	0.122549524727683	0.0410507634587027	2.98531657884923	0.00290767745112654	** 
df.mm.trans3:probe8	0.00925179962140932	0.0410507634587027	0.225374605534844	0.821737809027848	   
df.mm.trans3:probe9	0.234097788796697	0.0410507634587027	5.70264153630664	1.58806857657035e-08	***
df.mm.trans3:probe10	0.175951135553186	0.0410507634587027	4.2861842443002	2.00883921587336e-05	***
df.mm.trans3:probe11	0.0808112025958429	0.0410507634587027	1.9685675925891	0.0493019826665192	*  
df.mm.trans3:probe12	0.0061198126059387	0.0410507634587027	0.149079142269675	0.881523784683965	   
df.mm.trans3:probe13	0.118731252012197	0.0410507634587027	2.89230313905469	0.00391422550850671	** 

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.18472527767619	0.135231242904149	30.9449590775580	9.18857903765802e-145	***
df.mm.trans1	-0.183357813169765	0.116140493879923	-1.57875868307688	0.114734418271542	   
df.mm.trans2	-0.110195465070480	0.101978838257573	-1.08057188092449	0.280170160359475	   
df.mm.exp2	0.0554947716198827	0.129755040118451	0.427688755436571	0.668977609370409	   
df.mm.exp3	-0.0236149118405907	0.129755040118451	-0.181996104498392	0.855625787638983	   
df.mm.exp4	0.0588432262396254	0.129755040118451	0.453494725028858	0.650299253882353	   
df.mm.exp5	-0.0564487748717368	0.129755040118451	-0.435041096054578	0.663634407806902	   
df.mm.exp6	-0.0352903198723775	0.129755040118451	-0.271976486155463	0.785700989703566	   
df.mm.exp7	-0.0161709936712447	0.129755040118451	-0.124627094689212	0.900845942989317	   
df.mm.exp8	-0.172256677306361	0.129755040118451	-1.32755288079069	0.184654458021911	   
df.mm.trans1:exp2	-0.0362254248050023	0.119116394370703	-0.304117875598761	0.761106710288115	   
df.mm.trans2:exp2	-0.0533660806284156	0.0844292721700983	-0.632080311208887	0.527491097856806	   
df.mm.trans1:exp3	0.0180102912477198	0.119116394370703	0.151199096840271	0.879851737039271	   
df.mm.trans2:exp3	-0.0309484893825353	0.0844292721700983	-0.366561129653988	0.714030508827195	   
df.mm.trans1:exp4	-0.0383075746318049	0.119116394370703	-0.321597835748686	0.747830276113478	   
df.mm.trans2:exp4	-0.0070428026761678	0.0844292721700983	-0.0834165982383312	0.933538397871859	   
df.mm.trans1:exp5	-0.0136905150373479	0.119116394370703	-0.114933927522533	0.908522517699765	   
df.mm.trans2:exp5	0.0362943842409596	0.0844292721700983	0.429879155748706	0.667383997140973	   
df.mm.trans1:exp6	0.0493139745899712	0.119116394370703	0.413998214523695	0.678971700863249	   
df.mm.trans2:exp6	0.00354368803110014	0.0844292721700983	0.0419722679115452	0.9665298929202	   
df.mm.trans1:exp7	-0.0206663807017003	0.119116394370703	-0.173497366259966	0.862298580399962	   
df.mm.trans2:exp7	0.0616018773206718	0.0844292721700983	0.729627008942626	0.46580352633542	   
df.mm.trans1:exp8	0.132729308424832	0.119116394370703	1.11428245562710	0.265448411421509	   
df.mm.trans2:exp8	0.101820698825739	0.0844292721700983	1.20598811536125	0.228131452409197	   
df.mm.trans1:probe2	0.00420295238634188	0.0853290766838962	0.0492558052855983	0.960726106767385	   
df.mm.trans1:probe3	-0.147910203730905	0.0853290766838962	-1.73340916694601	0.0833572857343485	.  
df.mm.trans1:probe4	-0.0131793779231491	0.0853290766838962	-0.154453539582673	0.877285943847923	   
df.mm.trans1:probe5	-0.0166940591704374	0.0853290766838962	-0.195643265100371	0.844932501652727	   
df.mm.trans1:probe6	0.0044486610057924	0.0853290766838962	0.0521353468088326	0.958432141614256	   
df.mm.trans1:probe7	0.0536151544486238	0.0853290766838962	0.628333934131768	0.529940816850093	   
df.mm.trans1:probe8	0.0794524131220525	0.0853290766838962	0.931129413439994	0.352030364247464	   
df.mm.trans1:probe9	-0.0395211999842065	0.0853290766838962	-0.46316216605289	0.643357436286306	   
df.mm.trans1:probe10	-0.0183699772015804	0.0853290766838962	-0.215283909254432	0.829593585515407	   
df.mm.trans1:probe11	0.0171296031637432	0.0853290766838962	0.200747550887024	0.840940249992187	   
df.mm.trans1:probe12	0.0329623405225602	0.0853290766838962	0.386296697486486	0.69936607217413	   
df.mm.trans1:probe13	-0.0193412211604874	0.0853290766838962	-0.226666242178355	0.820733521913625	   
df.mm.trans1:probe14	0.0249306468478753	0.0853290766838962	0.292170591980405	0.77022192499505	   
df.mm.trans1:probe15	0.0544161872540192	0.0853290766838962	0.637721505596567	0.523813321080263	   
df.mm.trans1:probe16	0.106392599112091	0.0853290766838962	1.24685046700112	0.212768983218383	   
df.mm.trans1:probe17	0.0648971084980957	0.0853290766838962	0.76055092847786	0.447119787205282	   
df.mm.trans1:probe18	0.0280061569476511	0.0853290766838962	0.328213523877689	0.742824744565738	   
df.mm.trans1:probe19	-0.0813304208932518	0.0853290766838962	-0.953138414875183	0.340769751838411	   
df.mm.trans1:probe20	0.105853284207635	0.0853290766838962	1.24053005518589	0.215094982940466	   
df.mm.trans1:probe21	-0.0473057637802584	0.0853290766838962	-0.554392073823837	0.579444993279836	   
df.mm.trans1:probe22	-0.0714235998874521	0.0853290766838962	-0.837037064775033	0.402788634979414	   
df.mm.trans2:probe2	-0.145500885342425	0.0853290766838962	-1.70517355861515	0.0884989075252988	.  
df.mm.trans2:probe3	-0.0688706641694848	0.0853290766838962	-0.807118356906849	0.419806453976716	   
df.mm.trans2:probe4	-0.0377178935823669	0.0853290766838962	-0.442028614959632	0.658572159392738	   
df.mm.trans2:probe5	-0.0662841753759546	0.0853290766838962	-0.776806429319587	0.437472225431321	   
df.mm.trans2:probe6	-0.09090439557882	0.0853290766838962	-1.06533902758116	0.287001439375925	   
df.mm.trans3:probe2	0.0580854935345723	0.0853290766838962	0.680723333615241	0.496217479200025	   
df.mm.trans3:probe3	0.136078645689074	0.0853290766838962	1.59475117952092	0.111110593892078	   
df.mm.trans3:probe4	0.151640152944717	0.0853290766838962	1.77712168979013	0.0758778368051372	.  
df.mm.trans3:probe5	0.00772903324496919	0.0853290766838962	0.0905791266627857	0.927846691904844	   
df.mm.trans3:probe6	0.0585931529527662	0.0853290766838962	0.686672764195329	0.492461622102957	   
df.mm.trans3:probe7	0.158666148243977	0.0853290766838962	1.85946167953698	0.0632800850835036	.  
df.mm.trans3:probe8	0.0189186697093009	0.0853290766838962	0.221714220339986	0.824585455571403	   
df.mm.trans3:probe9	0.111075190147831	0.0853290766838962	1.30172731810180	0.193334755720925	   
df.mm.trans3:probe10	0.0673536222835398	0.0853290766838962	0.789339635456892	0.430116460249074	   
df.mm.trans3:probe11	0.134775480391977	0.0853290766838962	1.57947894937685	0.114569230478949	   
df.mm.trans3:probe12	0.111086924150122	0.0853290766838962	1.30186483280074	0.193287753662839	   
df.mm.trans3:probe13	0.0773944213390002	0.0853290766838962	0.907011119148867	0.364637901595655