chr14.7725_chr14_15866844_15871372_-_2.R 

fitVsDatCorrelation=0.856193988585693
cont.fitVsDatCorrelation=0.290300372948051

fstatistic=5612.44733793821,51,669
cont.fstatistic=1626.72111846803,51,669

residuals=-0.547501131020215,-0.123611272679822,0.000553920034131119,0.105544927311684,1.03274423225249
cont.residuals=-0.86439734600512,-0.272911702475298,-0.0233644446638442,0.208161200482647,1.88167396848161

predictedValues:
Include	Exclude	Both
chr14.7725_chr14_15866844_15871372_-_2.R.tl.Lung	80.729049640053	59.8232164501668	71.6899341584503
chr14.7725_chr14_15866844_15871372_-_2.R.tl.cerebhem	66.5095282980284	59.2749237289551	100.794869529237
chr14.7725_chr14_15866844_15871372_-_2.R.tl.cortex	113.612764371692	92.5239495843306	154.871391632087
chr14.7725_chr14_15866844_15871372_-_2.R.tl.heart	78.5845982386292	72.8185367573957	77.7594654166468
chr14.7725_chr14_15866844_15871372_-_2.R.tl.kidney	78.4050228676487	53.4532078265778	63.6722329410444
chr14.7725_chr14_15866844_15871372_-_2.R.tl.liver	76.5086818258906	52.2423794945724	61.4467933914026
chr14.7725_chr14_15866844_15871372_-_2.R.tl.stomach	100.612615453958	55.6086345785825	73.3573805970762
chr14.7725_chr14_15866844_15871372_-_2.R.tl.testicle	73.1529285757558	57.6154284381351	69.4573236119681


diffExp=20.9058331898862,7.2346045690733,21.0888147873611,5.76606148123355,24.9518150410709,24.2663023313182,45.0039808753754,15.5375001376207
diffExpScore=0.993966996299279
diffExp1.5=0,0,0,0,0,0,1,0
diffExp1.5Score=0.5
diffExp1.4=0,0,0,0,1,1,1,0
diffExp1.4Score=0.75
diffExp1.3=1,0,0,0,1,1,1,0
diffExp1.3Score=0.8
diffExp1.2=1,0,1,0,1,1,1,1
diffExp1.2Score=0.857142857142857

cont.predictedValues:
Include	Exclude	Both
Lung	79.1878276802024	77.0893832601671	80.6866803611974
cerebhem	75.085397666604	79.112034824887	81.5206323376903
cortex	68.2560301475351	81.4985532652341	71.38313089564
heart	79.5082324564179	77.4051304872621	74.7929921928154
kidney	69.7551256041453	83.8607597962098	78.9650712081943
liver	78.0036504185297	86.7925998321272	78.5620896830482
stomach	68.8847516724143	79.7186098156697	84.632642166533
testicle	78.0538330532356	79.6934589664286	73.5211166724749
cont.diffExp=2.09844442003528,-4.02663715828308,-13.2425231176990,2.10310196915577,-14.1056341920644,-8.78894941359746,-10.8338581432553,-1.63962591319297
cont.diffExpScore=1.14975201203728

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

tran.correlation=0.653813370280034
cont.tran.correlation=-0.276581497574285

tran.covariance=0.0197708405193406
cont.tran.covariance=-0.00076279500134271

tran.mean=73.2172166331482
cont.tran.mean=77.6190861841919

weightedLogRatios:
wLogRatio
Lung	1.27112123857457
cerebhem	0.476730769698616
cortex	0.950697240667228
heart	0.329669184367298
kidney	1.59758224597280
liver	1.58198889286031
stomach	2.55841869203629
testicle	0.996393781711999

cont.weightedLogRatios:
wLogRatio
Lung	0.117053502861775
cerebhem	-0.226964766966203
cortex	-0.76458841270158
heart	0.116946584865581
kidney	-0.798745532658192
liver	-0.470851685769408
stomach	-0.628892161304521
testicle	-0.0908009846730068

varWeightedLogRatios=0.505034752563227
cont.varWeightedLogRatios=0.140541250874014

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.60447691528069	0.103173881500272	44.6283191862717	9.91642787586352e-203	***
df.mm.trans1	-0.222234482768183	0.0865139297014182	-2.56877110466686	0.0104217060340030	*  
df.mm.trans2	-0.519301394797094	0.079500814982617	-6.53202605420637	1.28499800504189e-10	***
df.mm.exp2	-0.543697843900998	0.103173881500272	-5.26972365481439	1.84521144085811e-07	***
df.mm.exp3	0.0075263943570671	0.103173881500272	0.0729486401754429	0.941868791897077	   
df.mm.exp4	0.088384039928558	0.103173881500272	0.856651302086812	0.391944364994204	   
df.mm.exp5	-0.0231958727019572	0.103173881500272	-0.224823107986842	0.822185540081185	   
df.mm.exp6	-0.0350153491007946	0.103173881500272	-0.339381911309622	0.734428552847381	   
df.mm.exp7	0.124131065761274	0.103173881500272	1.20312489901766	0.229353581618329	   
df.mm.exp8	-0.104511919056299	0.103173881500272	-1.01296876240935	0.311441293627367	   
df.mm.trans1:exp2	0.349944582717425	0.0893512023862805	3.91650669908788	9.90614348620098e-05	***
df.mm.trans2:exp2	0.534490368554024	0.0729549512501793	7.32630697978447	6.83226973456096e-13	***
df.mm.trans1:exp3	0.334170986786144	0.0893512023862805	3.73997190705354	0.000199812226254536	***
df.mm.trans2:exp3	0.428547310508432	0.0729549512501794	5.87413606841905	6.69986152468483e-09	***
df.mm.trans1:exp4	-0.115306792115330	0.0893512023862805	-1.29048954055301	0.197326566054606	   
df.mm.trans2:exp4	0.108192688085321	0.0729549512501793	1.48300679023557	0.138543523770849	   
df.mm.trans1:exp5	-0.00601461606301736	0.0893512023862805	-0.0673143270866702	0.946351583585513	   
df.mm.trans2:exp5	-0.0893912967288579	0.0729549512501794	-1.22529444810832	0.220895501212062	   
df.mm.trans1:exp6	-0.0186789098443612	0.0893512023862805	-0.209050458701262	0.83447248511837	   
df.mm.trans2:exp6	-0.100484438250339	0.0729549512501793	-1.37734912474624	0.168864963165786	   
df.mm.trans1:exp7	0.0960481049104756	0.0893512023862806	1.07495033469436	0.282784496235527	   
df.mm.trans2:exp7	-0.197186398951827	0.0729549512501793	-2.70285149359677	0.00704922287674099	** 
df.mm.trans1:exp8	0.00596559967449888	0.0893512023862805	0.0667657459013094	0.946788140908149	   
df.mm.trans2:exp8	0.0669084851546596	0.0729549512501793	0.91712055190353	0.359409966169141	   
df.mm.trans1:probe2	-0.120486215235981	0.0631808411145106	-1.90700555913158	0.0569479191459872	.  
df.mm.trans1:probe3	0.159827792979647	0.0631808411145106	2.52968764201748	0.0116448697573298	*  
df.mm.trans1:probe4	0.0897850527574167	0.0631808411145106	1.42108036508548	0.155759336545478	   
df.mm.trans1:probe5	-0.0546201571261044	0.0631808411145106	-0.864505064551284	0.387620363648661	   
df.mm.trans1:probe6	-0.123961973503051	0.0631808411145106	-1.96201841122024	0.0501745253667164	.  
df.mm.trans1:probe7	-0.318443836891739	0.0631808411145106	-5.04019622522251	5.9928030533599e-07	***
df.mm.trans1:probe8	0.125246158550636	0.0631808411145106	1.98234395651106	0.0478494638365512	*  
df.mm.trans1:probe9	0.134341955836583	0.0631808411145106	2.12630844203385	0.0338430780509926	*  
df.mm.trans1:probe10	-0.0874294604547285	0.0631808411145106	-1.38379703265218	0.16688211609602	   
df.mm.trans1:probe11	0.117007257266764	0.0631808411145106	1.85194206349196	0.0644745144023204	.  
df.mm.trans1:probe12	0.291278595724765	0.0631808411145106	4.61023611883932	4.81866843581222e-06	***
df.mm.trans2:probe2	0.0310439457993393	0.0631808411145106	0.49135062547006	0.623339633452822	   
df.mm.trans2:probe3	-0.0132346487231004	0.0631808411145106	-0.209472499726834	0.834143171586666	   
df.mm.trans2:probe4	-0.00502060832792573	0.0631808411145106	-0.0794640944843746	0.936687252970032	   
df.mm.trans2:probe5	0.0459285072353403	0.0631808411145106	0.72693725542682	0.467518679849139	   
df.mm.trans2:probe6	0.0532122054909136	0.0631808411145106	0.84222059333573	0.399965466581868	   
df.mm.trans3:probe2	0.607813599219248	0.0631808411145106	9.6202201252375	1.31626613025761e-20	***
df.mm.trans3:probe3	-0.00876804874666718	0.0631808411145106	-0.138777018349214	0.889668117929772	   
df.mm.trans3:probe4	-0.0256041444936146	0.0631808411145106	-0.405251719381340	0.685422049098469	   
df.mm.trans3:probe5	0.580195980658483	0.0631808411145106	9.1830999781551	5.1662147284499e-19	***
df.mm.trans3:probe6	0.946237332465854	0.0631808411145106	14.9766498162136	6.07660352063121e-44	***
df.mm.trans3:probe7	0.0183696870303440	0.0631808411145106	0.290747744194325	0.77133436305506	   
df.mm.trans3:probe8	0.535063617604564	0.0631808411145106	8.46876376075464	1.57031924402276e-16	***
df.mm.trans3:probe9	0.434442657818063	0.0631808411145106	6.87617717894366	1.4125479207114e-11	***
df.mm.trans3:probe10	0.131050689315281	0.0631808411145106	2.07421564834442	0.0384411970909911	*  
df.mm.trans3:probe11	0.880676267123766	0.0631808411145106	13.9389766199473	5.89490031361399e-39	***
df.mm.trans3:probe12	0.81343410274866	0.0631808411145106	12.8746956893843	4.79280274756188e-34	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.37021750132919	0.191096295427453	22.869190067519	5.7249898198016e-86	***
df.mm.trans1	-0.0333760684862862	0.160239115059063	-0.208289146342228	0.83506660153483	   
df.mm.trans2	-0.00465920345056931	0.147249584931061	-0.0316415387707249	0.974767354103747	   
df.mm.exp2	-0.0375796901403601	0.191096295427453	-0.196653158850098	0.844158692496935	   
df.mm.exp3	0.0295748173321973	0.191096295427453	0.154763949065800	0.877054091972914	   
df.mm.exp4	0.083974783727414	0.191096295427453	0.43943700499047	0.660486824326761	   
df.mm.exp5	-0.0210715686469165	0.191096295427453	-0.110266756348063	0.91223089034669	   
df.mm.exp6	0.130173069029174	0.191096295427453	0.681190960494533	0.495986382786998	   
df.mm.exp7	-0.153596789937983	0.191096295427453	-0.803766444526882	0.421817369157463	   
df.mm.exp8	0.111798945187464	0.191096295427453	0.585039835217043	0.558718195682036	   
df.mm.trans1:exp2	-0.0156168046246034	0.165494246409270	-0.094364637825431	0.924847760520745	   
df.mm.trans2:exp2	0.063479130123332	0.135125486356380	0.469779105593094	0.638665929121615	   
df.mm.trans1:exp3	-0.178131629462246	0.165494246409270	-1.07636146468635	0.282153626796003	   
df.mm.trans2:exp3	0.0260448812283422	0.135125486356380	0.192745883331376	0.847216484016503	   
df.mm.trans1:exp4	-0.0799368106196306	0.165494246409270	-0.483018668950855	0.629240506427533	   
df.mm.trans2:exp4	-0.079887290145266	0.135125486356380	-0.591208159906795	0.554580651063892	   
df.mm.trans1:exp5	-0.105760124089622	0.165494246409270	-0.639056199138644	0.523005108592566	   
df.mm.trans2:exp5	0.105263800460052	0.135125486356380	0.779007745307417	0.436250614206155	   
df.mm.trans1:exp6	-0.145240039299305	0.165494246409270	-0.877613829184877	0.380468376469472	   
df.mm.trans2:exp6	-0.0116172765694554	0.135125486356380	-0.0859739852392906	0.931512821056528	   
df.mm.trans1:exp7	0.0142090363670786	0.165494246409270	0.0858581894861736	0.931604837432784	   
df.mm.trans2:exp7	0.187134276610315	0.135125486356380	1.38489252957630	0.166546981347307	   
df.mm.trans1:exp8	-0.126222785306844	0.165494246409270	-0.762701955176697	0.445910000420796	   
df.mm.trans2:exp8	-0.078577003625888	0.135125486356380	-0.581511347301641	0.56109174839283	   
df.mm.trans1:probe2	0.372792703284203	0.117022103883352	3.18566057960983	0.00151136038775525	** 
df.mm.trans1:probe3	0.063821068188408	0.117022103883352	0.545376181682948	0.585676597412923	   
df.mm.trans1:probe4	-0.0611576215919914	0.117022103883352	-0.522615980763372	0.601414537580064	   
df.mm.trans1:probe5	0.0901273928232035	0.117022103883352	0.770174093887787	0.441468502559483	   
df.mm.trans1:probe6	0.105497637372609	0.117022103883352	0.901518891488816	0.367636930352787	   
df.mm.trans1:probe7	-0.040015301810417	0.117022103883352	-0.341946525335968	0.732498523993984	   
df.mm.trans1:probe8	0.00560376430861663	0.117022103883352	0.0478863746476688	0.96182109000392	   
df.mm.trans1:probe9	0.178792581334949	0.117022103883352	1.52785307563064	0.127021661828906	   
df.mm.trans1:probe10	0.0658099882999129	0.117022103883352	0.562372287935553	0.574050777391588	   
df.mm.trans1:probe11	-0.0487791106923834	0.117022103883352	-0.416836726341943	0.676931549923931	   
df.mm.trans1:probe12	0.107054816705774	0.117022103883352	0.914825602627057	0.360612797824429	   
df.mm.trans2:probe2	0.0203858629652538	0.117022103883352	0.174205233787066	0.861756874322217	   
df.mm.trans2:probe3	-0.154672460011834	0.117022103883352	-1.32173713237980	0.186707486135106	   
df.mm.trans2:probe4	-0.0559895218840277	0.117022103883352	-0.478452531838242	0.63248446953691	   
df.mm.trans2:probe5	-0.187249522181981	0.117022103883352	-1.60012096833117	0.110043852944013	   
df.mm.trans2:probe6	0.0068565425716781	0.117022103883352	0.058591858667254	0.953294691945563	   
df.mm.trans3:probe2	-0.0319401086745751	0.117022103883352	-0.272940817287074	0.784982939238853	   
df.mm.trans3:probe3	-0.140297544472500	0.117022103883352	-1.19889781346222	0.230992167184374	   
df.mm.trans3:probe4	0.171856850447859	0.117022103883352	1.46858452159744	0.142415541942154	   
df.mm.trans3:probe5	0.0589898233500438	0.117022103883352	0.504091290384292	0.614363192733734	   
df.mm.trans3:probe6	0.00250189572116806	0.117022103883352	0.0213796850179855	0.982949153766409	   
df.mm.trans3:probe7	0.0806993211281474	0.117022103883352	0.689607505335816	0.490680170913972	   
df.mm.trans3:probe8	0.118737550953708	0.117022103883352	1.01465917133113	0.310635136954903	   
df.mm.trans3:probe9	0.142637912528520	0.117022103883352	1.21889718091807	0.22331283438973	   
df.mm.trans3:probe10	0.266486478069366	0.117022103883352	2.27723198631773	0.0230871888860433	*  
df.mm.trans3:probe11	0.0791716049607456	0.117022103883352	0.676552568561438	0.498923720954652	   
df.mm.trans3:probe12	-0.0481484123144838	0.117022103883352	-0.411447160123511	0.680876455036345