chr4.16814_chr4_132412542_132415305_-_2.R 

fitVsDatCorrelation=0.863463636690988
cont.fitVsDatCorrelation=0.246273298933624

fstatistic=11741.7291483915,59,853
cont.fstatistic=3169.80250743883,59,853

residuals=-0.466737594369145,-0.0849982157218043,0.00163250617550548,0.0745269368611042,0.912559042957613
cont.residuals=-0.621150050572267,-0.197998030080059,-0.0451747306793124,0.131053360477419,1.23792176697394

predictedValues:
Include	Exclude	Both
chr4.16814_chr4_132412542_132415305_-_2.R.tl.Lung	46.7958700740667	63.9504547312497	58.03345276606
chr4.16814_chr4_132412542_132415305_-_2.R.tl.cerebhem	51.5038913007312	76.3238211304249	66.1503380180887
chr4.16814_chr4_132412542_132415305_-_2.R.tl.cortex	45.8400491014948	79.3497859641096	67.2353294180625
chr4.16814_chr4_132412542_132415305_-_2.R.tl.heart	46.4560710991374	59.5640081648514	59.0088462885875
chr4.16814_chr4_132412542_132415305_-_2.R.tl.kidney	46.1573037351421	54.695885537703	56.3718290138781
chr4.16814_chr4_132412542_132415305_-_2.R.tl.liver	47.7115866276469	57.1148561500912	57.6600061961907
chr4.16814_chr4_132412542_132415305_-_2.R.tl.stomach	47.8266208792273	63.5955940475258	59.853474179319
chr4.16814_chr4_132412542_132415305_-_2.R.tl.testicle	50.1891150090216	54.950159395835	56.577320340388


diffExp=-17.1545846571830,-24.8199298296937,-33.5097368626148,-13.1079370657139,-8.53858180256087,-9.4032695224443,-15.7689731682985,-4.76104438681335
diffExpScore=0.992191407791384
diffExp1.5=0,0,-1,0,0,0,0,0
diffExp1.5Score=0.5
diffExp1.4=0,-1,-1,0,0,0,0,0
diffExp1.4Score=0.666666666666667
diffExp1.3=-1,-1,-1,0,0,0,-1,0
diffExp1.3Score=0.8
diffExp1.2=-1,-1,-1,-1,0,0,-1,0
diffExp1.2Score=0.833333333333333

cont.predictedValues:
Include	Exclude	Both
Lung	58.6373030053209	61.0602799392143	57.1332426935752
cerebhem	54.79791842696	59.8433952890295	62.236643451509
cortex	55.1666786687093	60.4894124261347	58.6568163419903
heart	53.8243034527498	56.6790673297223	54.8092746396868
kidney	61.1072785098049	57.0834937059545	60.842399693562
liver	57.8649097448853	56.7367922831728	55.9920747669369
stomach	50.9118915501055	66.5062054133092	56.8956504612511
testicle	56.3069264084972	57.2919411958488	56.5648731795198
cont.diffExp=-2.42297693389342,-5.04547686206959,-5.32273375742536,-2.85476387697241,4.02378480385032,1.12811746171251,-15.5943138632037,-0.985014787351595
cont.diffExpScore=1.33141022759425

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,-1,0
cont.diffExp1.3Score=0.5
cont.diffExp1.2=0,0,0,0,0,0,-1,0
cont.diffExp1.2Score=0.5

tran.correlation=0.118463917679661
cont.tran.correlation=-0.605447973456931

tran.covariance=0.00062998487334871
cont.tran.covariance=-0.00189189065521855

tran.mean=55.7515670592662
cont.tran.mean=57.7692373343387

weightedLogRatios:
wLogRatio
Lung	-1.24986431644804
cerebhem	-1.62771649094417
cortex	-2.24943338617547
heart	-0.984926386158023
kidney	-0.664831987766247
liver	-0.711486349457847
stomach	-1.14271479705729
testicle	-0.358989320014596

cont.weightedLogRatios:
wLogRatio
Lung	-0.165671622600820
cerebhem	-0.35651607818467
cortex	-0.373633124671139
heart	-0.207317109015966
kidney	0.277816019564276
liver	0.079703323046457
stomach	-1.08581440439677
testicle	-0.0700544992036289

varWeightedLogRatios=0.36030110671409
cont.varWeightedLogRatios=0.164658710463153

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.11524661777075	0.0682024529984965	60.3386892530312	0	***
df.mm.trans1	-0.304335064216235	0.0566344268018581	-5.37367607305332	9.95980240128763e-08	***
df.mm.trans2	0.00159058371636402	0.0517244183470467	0.0307511184696548	0.975475217159001	   
df.mm.exp2	0.141828481367689	0.0661660982680059	2.1435219104686	0.0323534117425219	*  
df.mm.exp3	0.0479410730194531	0.0661660982680059	0.724556446191941	0.468922874056136	   
df.mm.exp4	-0.095012684799165	0.0661660982680059	-1.43597230736375	0.151376833825068	   
df.mm.exp5	-0.141009826403758	0.0661660982680059	-2.13114918507960	0.0333622050871882	*  
df.mm.exp6	-0.0872092398257725	0.0661660982680059	-1.31803509816358	0.187845735617658	   
df.mm.exp7	-0.0146568552042550	0.0661660982680059	-0.221516087360741	0.82474362930418	   
df.mm.exp8	-0.0562674272957881	0.0661660982680059	-0.850396634661407	0.395343241391611	   
df.mm.trans1:exp2	-0.045966070063997	0.0562303710344766	-0.817459839199954	0.413893956760153	   
df.mm.trans2:exp2	0.0350479730109630	0.0441107321786706	0.794545256446914	0.427099073233524	   
df.mm.trans1:exp3	-0.0685778822130475	0.0562303710344766	-1.21958793711321	0.222958228952258	   
df.mm.trans2:exp3	0.167816037854003	0.0441107321786706	3.80442648683009	0.000152277125874631	***
df.mm.trans1:exp4	0.0877248905805881	0.0562303710344766	1.56009802117082	0.119107632537319	   
df.mm.trans2:exp4	0.0239555478734574	0.0441107321786706	0.543077538963203	0.58721829441919	   
df.mm.trans1:exp5	0.127270082864805	0.0562303710344766	2.26336907481495	0.0238634937821707	*  
df.mm.trans2:exp5	-0.0153103244171407	0.0441107321786706	-0.347088421818215	0.728610504883128	   
df.mm.trans1:exp6	0.106588561714059	0.0562303710344766	1.89556924048582	0.0583548300887018	.  
df.mm.trans2:exp6	-0.0258351383233175	0.0441107321786706	-0.585688267849924	0.558239940351348	   
df.mm.trans1:exp7	0.0364443090885981	0.0562303710344766	0.64812499754364	0.517078524968298	   
df.mm.trans2:exp7	0.00909240843773585	0.0441107321786706	0.206126899025549	0.836740973926784	   
df.mm.trans1:exp8	0.126270645243257	0.0562303710344766	2.24559509247835	0.0249852897063842	*  
df.mm.trans2:exp8	-0.0954146298462662	0.0441107321786706	-2.16307064366534	0.0308129089637122	*  
df.mm.trans1:probe2	0.0166854316291150	0.0427100327792517	0.390667731756477	0.696140399935903	   
df.mm.trans1:probe3	0.0778034576639788	0.0427100327792517	1.82166700892291	0.068855630098377	.  
df.mm.trans1:probe4	-0.0196319672312277	0.0427100327792517	-0.459657039663168	0.64587953668813	   
df.mm.trans1:probe5	0.00970874977680999	0.0427100327792517	0.227317778635058	0.820231119716321	   
df.mm.trans1:probe6	-0.0153142789681825	0.0427100327792517	-0.358563971311728	0.720010026625102	   
df.mm.trans1:probe7	0.198339925254423	0.0427100327792517	4.64387199793431	3.95818300303663e-06	***
df.mm.trans1:probe8	0.124492069877113	0.0427100327792517	2.91482028404320	0.00365205308773019	** 
df.mm.trans1:probe9	0.16842818720323	0.0427100327792517	3.94352746282723	8.68811426067055e-05	***
df.mm.trans1:probe10	0.216637405426311	0.0427100327792517	5.07228375463932	4.82416946685747e-07	***
df.mm.trans1:probe11	0.210564741729922	0.0427100327792517	4.93010021364848	9.87663686213827e-07	***
df.mm.trans1:probe12	0.128555051863495	0.0427100327792517	3.00994973541549	0.00268984816588337	** 
df.mm.trans2:probe2	0.166219609582206	0.0427100327792517	3.8918164835255	0.000107252266366416	***
df.mm.trans2:probe3	0.189056115552979	0.0427100327792517	4.42650363979166	1.08197067359355e-05	***
df.mm.trans2:probe4	0.412219941219772	0.0427100327792517	9.65159505613927	5.46220193530967e-21	***
df.mm.trans2:probe5	0.177515147816098	0.0427100327792517	4.15628685497835	3.56097425544072e-05	***
df.mm.trans2:probe6	0.128046554159866	0.0427100327792517	2.99804392147577	0.00279603323679749	** 
df.mm.trans3:probe2	-0.0479897694508407	0.0427100327792517	-1.12361818355133	0.261491160327820	   
df.mm.trans3:probe3	0.125006943605614	0.0427100327792517	2.92687538433222	0.00351481158746323	** 
df.mm.trans3:probe4	0.384233437439308	0.0427100327792517	8.99632738343312	1.48648273587486e-18	***
df.mm.trans3:probe5	-0.0276212906121519	0.0427100327792517	-0.646716680244979	0.51798929948227	   
df.mm.trans3:probe6	0.602827947248659	0.0427100327792517	14.1144341978007	8.26760893658567e-41	***
df.mm.trans3:probe7	0.0206361435037654	0.0427100327792517	0.483168524136332	0.629100070761454	   
df.mm.trans3:probe8	0.319750311709843	0.0427100327792517	7.48653866323363	1.76347070991563e-13	***
df.mm.trans3:probe9	0.259895985621244	0.0427100327792517	6.08512728062105	1.75672263338286e-09	***
df.mm.trans3:probe10	0.955446777062402	0.0427100327792517	22.3705465645663	1.38790472017755e-87	***
df.mm.trans3:probe11	-0.0434690455734800	0.0427100327792517	-1.01777129973539	0.309075234279033	   
df.mm.trans3:probe12	0.504104116404328	0.0427100327792517	11.8029437956606	6.90829652942249e-30	***
df.mm.trans3:probe13	0.254288895494497	0.0427100327792517	5.95384454066796	3.82423624734762e-09	***
df.mm.trans3:probe14	0.364846708576644	0.0427100327792517	8.54241228196586	5.99686949598215e-17	***
df.mm.trans3:probe15	-0.0504180817385576	0.0427100327792517	-1.18047396496147	0.238140829574328	   
df.mm.trans3:probe16	0.363781119506473	0.0427100327792517	8.51746289652103	7.31515193392244e-17	***
df.mm.trans3:probe17	0.144304930562779	0.0427100327792517	3.37871270922747	0.000761275112384662	***
df.mm.trans3:probe18	0.0187980833274356	0.0427100327792517	0.440132730044814	0.65995247807403	   
df.mm.trans3:probe19	0.292429774879625	0.0427100327792517	6.84686374255573	1.44299929693151e-11	***
df.mm.trans3:probe20	0.529496589136902	0.0427100327792517	12.3974755972121	1.42902676140496e-32	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.09696152558853	0.131047567421043	31.2631634925767	1.40443773261991e-143	***
df.mm.trans1	-0.0575161134367905	0.108820189573419	-0.528542668986854	0.597260226576136	   
df.mm.trans2	0.0113395572288669	0.0993858564119131	0.114096287321499	0.909188314322866	   
df.mm.exp2	-0.173407174494465	0.127134814695814	-1.36396293107725	0.172939025308488	   
df.mm.exp3	-0.0967228218360304	0.127134814695814	-0.760789419227547	0.44699310465291	   
df.mm.exp4	-0.118575868041416	0.127134814695814	-0.932678183588998	0.351250067020637	   
df.mm.exp5	-0.0889874327959524	0.127134814695814	-0.699945432011411	0.484152226616076	   
df.mm.exp6	-0.0665226180139613	0.127134814695814	-0.52324470030593	0.600939872164568	   
df.mm.exp7	-0.0516736216363964	0.127134814695814	-0.406447453123142	0.684515809652794	   
df.mm.exp8	-0.0942571564841606	0.127134814695814	-0.741395318895791	0.458657842806443	   
df.mm.trans1:exp2	0.105688318702640	0.108043816831827	0.978198677182487	0.328253410901089	   
df.mm.trans2:exp2	0.153276674052602	0.0847565431305429	1.80843470475812	0.0708909111556233	.  
df.mm.trans1:exp3	0.0357108814298387	0.108043816831827	0.330522212903897	0.741086576110883	   
df.mm.trans2:exp3	0.0873295983832406	0.0847565431305429	1.03035819014863	0.303133950970551	   
df.mm.trans1:exp4	0.0329299061317957	0.108043816831827	0.304782884364888	0.760605864295901	   
df.mm.trans2:exp4	0.0441192557588541	0.0847565431305428	0.520541000485369	0.60282164158675	   
df.mm.trans1:exp5	0.130247352310599	0.108043816831827	1.20550491578183	0.228342741092358	   
df.mm.trans2:exp5	0.0216408587594390	0.0847565431305428	0.255329653146750	0.798530050166991	   
df.mm.trans1:exp6	0.0532627054447962	0.108043816831827	0.492973193715483	0.622158405434278	   
df.mm.trans2:exp6	-0.0069160597639905	0.0847565431305428	-0.0815991250768488	0.934984639128747	   
df.mm.trans1:exp7	-0.0896009204694185	0.108043816831827	-0.829301695337966	0.407165717163931	   
df.mm.trans2:exp7	0.137107307476361	0.0847565431305429	1.61766044734962	0.106105494106147	   
df.mm.trans1:exp8	0.0537036467416778	0.108043816831827	0.497054327738802	0.619278824982512	   
df.mm.trans2:exp8	0.0305555560533227	0.0847565431305429	0.360509701372091	0.718555255700278	   
df.mm.trans1:probe2	0.0828658420295285	0.0820651700066758	1.00975653889205	0.312898286849665	   
df.mm.trans1:probe3	0.112842766085285	0.0820651700066758	1.37503847339992	0.169480561435579	   
df.mm.trans1:probe4	0.129599483755231	0.0820651700066758	1.57922640926338	0.114654867514903	   
df.mm.trans1:probe5	0.175378948125121	0.0820651700066758	2.13706921110203	0.0328762087612067	*  
df.mm.trans1:probe6	0.0599182522548081	0.0820651700066758	0.73013011792864	0.465511118939824	   
df.mm.trans1:probe7	0.131437392964562	0.0820651700066758	1.60162213706339	0.109609431737443	   
df.mm.trans1:probe8	0.0791623620132694	0.0820651700066758	0.964628014623375	0.335004551469919	   
df.mm.trans1:probe9	0.0836123439118362	0.0820651700066758	1.01885299092215	0.308561644837941	   
df.mm.trans1:probe10	0.0335904386042401	0.0820651700066758	0.409314190191863	0.68241185872515	   
df.mm.trans1:probe11	0.0800037287089074	0.0820651700066758	0.97488043590721	0.329895950135526	   
df.mm.trans1:probe12	0.0532093043671764	0.0820651700066758	0.64837865275668	0.516914571650543	   
df.mm.trans2:probe2	0.0159274684113604	0.0820651700066758	0.194083170851468	0.846156968412459	   
df.mm.trans2:probe3	-0.0687731061201409	0.0820651700066758	-0.838030386271623	0.402248391856124	   
df.mm.trans2:probe4	0.104353793918906	0.0820651700066758	1.27159663363174	0.203863069616351	   
df.mm.trans2:probe5	-0.0117839081559843	0.0820651700066758	-0.143592076334281	0.885856512299066	   
df.mm.trans2:probe6	0.0528484695020179	0.0820651700066758	0.643981722059661	0.519760398891228	   
df.mm.trans3:probe2	-0.00529100661818365	0.0820651700066758	-0.0644732304551766	0.948608527614846	   
df.mm.trans3:probe3	-0.00112323947032725	0.0820651700066758	-0.0136871643626142	0.98908276437105	   
df.mm.trans3:probe4	0.0150730624970563	0.0820651700066758	0.183671860983534	0.854314535807324	   
df.mm.trans3:probe5	0.0982349043378427	0.0820651700066758	1.19703528707552	0.231625365126318	   
df.mm.trans3:probe6	0.0518397656516302	0.0820651700066758	0.631690224335284	0.527758565412301	   
df.mm.trans3:probe7	-0.0466217233774175	0.0820651700066758	-0.568106096333255	0.570112438131217	   
df.mm.trans3:probe8	-0.00277772582418979	0.0820651700066758	-0.0338478044213377	0.973006433909575	   
df.mm.trans3:probe9	0.0143034374815466	0.0820651700066758	0.17429364345901	0.861676051437149	   
df.mm.trans3:probe10	-0.00896617085919008	0.0820651700066758	-0.109256714614260	0.913024574375234	   
df.mm.trans3:probe11	0.0338689561614773	0.0820651700066758	0.412708048478084	0.679924237660274	   
df.mm.trans3:probe12	-0.0304263708597029	0.0820651700066758	-0.370758640446706	0.710909362457524	   
df.mm.trans3:probe13	-0.0850072877359825	0.0820651700066758	-1.03585099170656	0.300565225401105	   
df.mm.trans3:probe14	-0.102862301933804	0.0820651700066758	-1.25342215126633	0.210395555622566	   
df.mm.trans3:probe15	0.0611666723572021	0.0820651700066758	0.745342663059449	0.456269916859494	   
df.mm.trans3:probe16	0.00198411236326350	0.0820651700066758	0.0241772771944797	0.980716857599728	   
df.mm.trans3:probe17	-0.114982541725758	0.0820651700066758	-1.40111257572980	0.161544113007693	   
df.mm.trans3:probe18	-0.00372273306796769	0.0820651700066758	-0.0453631311269429	0.963828485167987	   
df.mm.trans3:probe19	0.0437564885172751	0.0820651700066758	0.533191956023677	0.594039597021236	   
df.mm.trans3:probe20	-0.0264230648241761	0.0820651700066758	-0.321976604959530	0.747549306559484