In:
Bioinformatics, Oxford University Press (OUP), Vol. 30, No. 22 ( 2014-11-15), p. 3287-3288
Kurzfassung:
Summary: Non-targeted metabolomics technologies often yield data in which abundance for any given metabolite is observed and quantified for some samples and reported as missing for other samples. Apparent missingness can be due to true absence of the metabolite in the sample or presence at a level below detectability. Mixture-model analysis can formally account for metabolite ‘missingness’ due to absence or undetectability, but software for this type of analysis in the high-throughput setting is limited. The R package metabomxtr has been developed to facilitate mixture-model analysis of non-targeted metabolomics data in which only a portion of samples have quantifiable abundance for certain metabolites. Availability and implementation: metabomxtr is available through Bioconductor. It is released under the GPL-2 license. Contact: dscholtens@northwestern.edu Supplementary information: Supplementary data are available at Bioinformatics online.
Materialart:
Online-Ressource
ISSN:
1367-4811
,
1367-4803
DOI:
10.1093/bioinformatics/btu509
Sprache:
Englisch
Verlag:
Oxford University Press (OUP)
Publikationsdatum:
2014
ZDB Id:
1468345-3
SSG:
12
