chr2.13471_chr2_94174974_94175826_+_1.R 

fitVsDatCorrelation=0.900923733473956
cont.fitVsDatCorrelation=0.310737197489360

fstatistic=9315.41438112266,39,393
cont.fstatistic=1933.96479859201,39,393

residuals=-0.368667720248292,-0.083189988206699,0.00318556771871406,0.0793783123997539,0.720997378499138
cont.residuals=-0.506322691391384,-0.206147341191577,-0.0824235830311685,0.158009711952094,1.15463625080786

predictedValues:
Include	Exclude	Both
chr2.13471_chr2_94174974_94175826_+_1.R.tl.Lung	51.9356992877553	48.9750235505962	78.256081718465
chr2.13471_chr2_94174974_94175826_+_1.R.tl.cerebhem	53.9244683173154	43.0595481542246	71.8718283700562
chr2.13471_chr2_94174974_94175826_+_1.R.tl.cortex	50.8916771561378	55.0724345598828	102.285093104111
chr2.13471_chr2_94174974_94175826_+_1.R.tl.heart	51.510286385022	53.4815182707586	85.540039763067
chr2.13471_chr2_94174974_94175826_+_1.R.tl.kidney	46.4910145301027	44.6787874000199	66.1437220279976
chr2.13471_chr2_94174974_94175826_+_1.R.tl.liver	49.7953411055976	48.5396550318809	64.5627043434889
chr2.13471_chr2_94174974_94175826_+_1.R.tl.stomach	49.7386675903867	48.5354203951425	88.88629972243
chr2.13471_chr2_94174974_94175826_+_1.R.tl.testicle	52.2107809194322	46.9560519070282	80.2217515371513


diffExp=2.96067573715911,10.8649201630908,-4.18075740374501,-1.97123188573661,1.81222713008278,1.25568607371667,1.20324719524417,5.25472901240398
diffExpScore=1.62111492346627
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=0,1,0,0,0,0,0,0
diffExp1.2Score=0.5

cont.predictedValues:
Include	Exclude	Both
Lung	50.273309699618	62.6206567773841	58.3200439093628
cerebhem	56.5835819433302	61.8862004790697	55.1374250022079
cortex	56.594503971826	54.57560860262	65.1673897615206
heart	54.0638388071008	59.0784660850022	53.248688361247
kidney	63.1014739546108	55.5958877210673	59.3834152138662
liver	50.6875622840287	54.0455140047117	59.6032088752775
stomach	53.1318529470674	59.8093712352254	59.0226262131015
testicle	56.7183278873428	59.0673155650187	60.387807237181
cont.diffExp=-12.3473470777662,-5.30261853573943,2.01889536920601,-5.01462727790136,7.50558623354345,-3.35795172068296,-6.677518288158,-2.34898767767591
cont.diffExpScore=1.68046207357382

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

tran.correlation=0.0299367867766919
cont.tran.correlation=-0.282266563616227

tran.covariance=0.000151186979777166
cont.tran.covariance=-0.00109463565469100

tran.mean=49.7372734100802
cont.tran.mean=56.739591997814

weightedLogRatios:
wLogRatio
Lung	0.230126796486478
cerebhem	0.871895231811233
cortex	-0.313365974674942
heart	-0.148737273934787
kidney	0.151859361810027
liver	0.0994834648277129
stomach	0.095372574956871
testicle	0.413938665458081

cont.weightedLogRatios:
wLogRatio
Lung	-0.884475863642851
cerebhem	-0.365525181647492
cortex	0.145944040111550
heart	-0.357865385812739
kidney	0.516851025638671
liver	-0.253873991450555
stomach	-0.477327702344128
testicle	-0.164690721575140

varWeightedLogRatios=0.128811354776858
cont.varWeightedLogRatios=0.175454544169633

coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	3.24460480960734	0.0729807538741719	44.4583624773383	2.08960325496538e-155	***
df.mm.trans1	0.704618700102339	0.0595885360117892	11.8247358848174	8.24695600130436e-28	***
df.mm.trans2	0.652776469129448	0.0595885360117892	10.9547324505556	1.49777450087517e-24	***
df.mm.exp2	-0.00604633799961077	0.0809648769893366	-0.0746785300545457	0.940508487422331	   
df.mm.exp3	-0.170745535490376	0.0809648769893366	-2.10888402279501	0.0355867572834910	*  
df.mm.exp4	-0.0091972008731009	0.0809648769893366	-0.113594946538512	0.909616899495345	   
df.mm.exp5	-0.0344023867000837	0.0809648769893366	-0.42490506969602	0.67113841799286	   
df.mm.exp6	0.141335311103839	0.0809648769893366	1.74563732274247	0.0816554702733762	.  
df.mm.exp7	-0.17961182035833	0.0809648769893366	-2.21839181429233	0.02709900045077	*  
df.mm.exp8	-0.0616238891508067	0.0809648769893366	-0.761118789310614	0.447042562849355	   
df.mm.trans1:exp2	0.0436242692951818	0.0661075452370272	0.6598984902369	0.509705514780188	   
df.mm.trans2:exp2	-0.122680108218806	0.0661075452370273	-1.8557655979955	0.064235391206417	.  
df.mm.trans1:exp3	0.150438530783755	0.0661075452370273	2.27566354558108	0.0234037292004307	*  
df.mm.trans2:exp3	0.288084401547188	0.0661075452370273	4.35781423306926	1.67911065302367e-05	***
df.mm.trans1:exp4	0.000972322968365843	0.0661075452370273	0.0147081995690446	0.988272441477136	   
df.mm.trans2:exp4	0.0972228975092102	0.0661075452370273	1.47067777453571	0.142178458089809	   
df.mm.trans1:exp5	-0.0763449565522566	0.0661075452370272	-1.15485995249897	0.248849489282781	   
df.mm.trans2:exp5	-0.0574092238268049	0.0661075452370273	-0.868421654759155	0.385693543089587	   
df.mm.trans1:exp6	-0.183420284807353	0.0661075452370272	-2.77457412992274	0.00579118639859632	** 
df.mm.trans2:exp6	-0.150264662414258	0.0661075452370272	-2.27303346199722	0.0235632778228432	*  
df.mm.trans1:exp7	0.136388069626182	0.0661075452370273	2.06312409781918	0.0397571678756115	*  
df.mm.trans2:exp7	0.170595224475143	0.0661075452370272	2.58057115664297	0.0102255705126133	*  
df.mm.trans1:exp8	0.0669064924769929	0.0661075452370273	1.01208556810121	0.31211983947843	   
df.mm.trans2:exp8	0.0195255429059629	0.0661075452370272	0.29536027749865	0.767874655662595	   
df.mm.trans1:probe2	-0.0918082139674889	0.0404824384946683	-2.26785286117536	0.0238803213879633	*  
df.mm.trans1:probe3	0.0621471306057785	0.0404824384946683	1.53516272528799	0.125548504909862	   
df.mm.trans1:probe4	0.00617832653113453	0.0404824384946683	0.152617449957918	0.878778286740778	   
df.mm.trans1:probe5	0.00996300736131538	0.0404824384946683	0.246106897997944	0.805727968570622	   
df.mm.trans1:probe6	0.0229144480900392	0.0404824384946683	0.566034284052754	0.571693531437049	   
df.mm.trans2:probe2	0.0044718871570168	0.0404824384946683	0.110464866329773	0.912097100294649	   
df.mm.trans2:probe3	0.0827771002828403	0.0404824384946683	2.04476566533269	0.0415436775051506	*  
df.mm.trans2:probe4	-0.0301703614708391	0.0404824384946683	-0.74527035901784	0.456553769386032	   
df.mm.trans2:probe5	-0.0318780911598372	0.0404824384946683	-0.787454816093543	0.431490316418867	   
df.mm.trans2:probe6	-0.098050543247776	0.0404824384946683	-2.42205131147645	0.0158847652609426	*  
df.mm.trans3:probe2	-0.0374316500442333	0.0404824384946683	-0.924639212362744	0.355720997783392	   
df.mm.trans3:probe3	-0.073478635896227	0.0404824384946683	-1.81507435393015	0.0702746116130933	.  
df.mm.trans3:probe4	-0.4724419902354	0.0404824384946683	-11.6702947698574	3.18856957717267e-27	***
df.mm.trans3:probe5	-0.272525618001104	0.0404824384946683	-6.73194669429306	5.94951222409309e-11	***
df.mm.trans3:probe6	-0.596202690606915	0.0404824384946683	-14.7274401636017	2.09973312078062e-39	***

cont.coeff:
Name	Estimate	Std-Error	t-value	Pr(>|t|)	Signif
df.mm.(Intercept)	4.03383303484385	0.159842187841287	25.2363477334856	3.12090895985717e-84	***
df.mm.trans1	-0.127621243486902	0.130510599860418	-0.97786113636282	0.328744555803393	   
df.mm.trans2	0.0873753774488482	0.130510599860418	0.669488743000925	0.503576885497587	   
df.mm.exp2	0.162563711032249	0.177328985921264	0.91673513040011	0.359843656036769	   
df.mm.exp3	-0.130083932750959	0.177328985921264	-0.733573995673316	0.463645789330967	   
df.mm.exp4	0.105435192304745	0.177328985921264	0.594573931368218	0.552470450016231	   
df.mm.exp5	0.0902147051999636	0.177328985921264	0.508742012656745	0.611218548601551	   
df.mm.exp6	-0.160825986189988	0.177328985921264	-0.906935689923792	0.364996545821785	   
df.mm.exp7	-0.00260556919518852	0.177328985921264	-0.0146934195876213	0.98828422542064	   
df.mm.exp8	0.0273642418007678	0.177328985921264	0.154313417282597	0.877441832203636	   
df.mm.trans1:exp2	-0.0443191535765254	0.144788510704093	-0.306095790066529	0.759693799598359	   
df.mm.trans2:exp2	-0.174361692825465	0.144788510704093	-1.20425088964283	0.229217392950255	   
df.mm.trans1:exp3	0.248521496272149	0.144788510704093	1.71644486888919	0.0868686331735613	.  
df.mm.trans2:exp3	-0.00742421734486908	0.144788510704093	-0.0512762877991203	0.959131414455299	   
df.mm.trans1:exp4	-0.0327439578591689	0.144788510704093	-0.22615024976732	0.821202133303181	   
df.mm.trans2:exp4	-0.163663902477224	0.144788510704093	-1.13036525951777	0.259011726393221	   
df.mm.trans1:exp5	0.137055109099621	0.144788510704093	0.946588292352307	0.344430256327652	   
df.mm.trans2:exp5	-0.209200672673913	0.144788510704093	-1.44487067141302	0.149291050533768	   
df.mm.trans1:exp6	0.169032232847771	0.144788510704093	1.16744230620084	0.243739611267597	   
df.mm.trans2:exp6	0.0135573255492661	0.144788510704093	0.0936353684649293	0.925446530293267	   
df.mm.trans1:exp7	0.0579078707692199	0.144788510704093	0.399947968852082	0.689412130860339	   
df.mm.trans2:exp7	-0.0433272766506077	0.144788510704093	-0.299245267735065	0.764911097967858	   
df.mm.trans1:exp8	0.0932588458622573	0.144788510704093	0.644103909963217	0.519883783801386	   
df.mm.trans2:exp8	-0.0857817106383602	0.144788510704093	-0.592462138198755	0.553881887836056	   
df.mm.trans1:probe2	-0.0237792382190209	0.088664492960632	-0.268193472099131	0.788691113106909	   
df.mm.trans1:probe3	0.0974600806356777	0.088664492960632	1.09920078919248	0.272353398967999	   
df.mm.trans1:probe4	0.0581587367896202	0.088664492960632	0.655941683616725	0.512245475743786	   
df.mm.trans1:probe5	-0.00444882760317396	0.088664492960632	-0.0501759774924703	0.960007645794106	   
df.mm.trans1:probe6	0.00775952013601132	0.088664492960632	0.0875155304779855	0.930306315481616	   
df.mm.trans2:probe2	-0.0663332954498996	0.088664492960632	-0.748138214463734	0.45482425279445	   
df.mm.trans2:probe3	0.115553126463484	0.088664492960632	1.30326269970089	0.193248096210464	   
df.mm.trans2:probe4	0.0284507237851637	0.088664492960632	0.320880691189382	0.748471369708441	   
df.mm.trans2:probe5	0.0216523712266980	0.088664492960632	0.244205662308495	0.807198981820519	   
df.mm.trans2:probe6	0.0913185761885403	0.088664492960632	1.02993400333420	0.303674421447375	   
df.mm.trans3:probe2	0.220971781685055	0.088664492960632	2.49222404940802	0.0131057107502827	*  
df.mm.trans3:probe3	-0.0622113838055996	0.088664492960632	-0.701649349455166	0.48331315897469	   
df.mm.trans3:probe4	0.162235540990146	0.088664492960632	1.82976900417374	0.0680418566662266	.  
df.mm.trans3:probe5	0.0264335346930250	0.088664492960632	0.298129880523444	0.765761588946461	   
df.mm.trans3:probe6	0.086722557227443	0.088664492960632	0.97809793223482	0.328627586140258