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Metabomxtr: an R package for mixture-model analysis of non-targeted metabolomics data
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 b...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4221120/ https://www.ncbi.nlm.nih.gov/pubmed/25075114 http://dx.doi.org/10.1093/bioinformatics/btu509 |
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author | Nodzenski, Michael Muehlbauer, Michael J. Bain, James R. Reisetter, Anna C. Lowe, William L. Scholtens, Denise M. |
author_facet | Nodzenski, Michael Muehlbauer, Michael J. Bain, James R. Reisetter, Anna C. Lowe, William L. Scholtens, Denise M. |
author_sort | Nodzenski, Michael |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-4221120 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-42211202014-11-10 Metabomxtr: an R package for mixture-model analysis of non-targeted metabolomics data Nodzenski, Michael Muehlbauer, Michael J. Bain, James R. Reisetter, Anna C. Lowe, William L. Scholtens, Denise M. Bioinformatics Applications Notes 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. Oxford University Press 2014-11-15 2014-07-29 /pmc/articles/PMC4221120/ /pubmed/25075114 http://dx.doi.org/10.1093/bioinformatics/btu509 Text en © The Author 2014. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Applications Notes Nodzenski, Michael Muehlbauer, Michael J. Bain, James R. Reisetter, Anna C. Lowe, William L. Scholtens, Denise M. Metabomxtr: an R package for mixture-model analysis of non-targeted metabolomics data |
title | Metabomxtr: an R package for mixture-model analysis of non-targeted metabolomics data |
title_full | Metabomxtr: an R package for mixture-model analysis of non-targeted metabolomics data |
title_fullStr | Metabomxtr: an R package for mixture-model analysis of non-targeted metabolomics data |
title_full_unstemmed | Metabomxtr: an R package for mixture-model analysis of non-targeted metabolomics data |
title_short | Metabomxtr: an R package for mixture-model analysis of non-targeted metabolomics data |
title_sort | metabomxtr: an r package for mixture-model analysis of non-targeted metabolomics data |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4221120/ https://www.ncbi.nlm.nih.gov/pubmed/25075114 http://dx.doi.org/10.1093/bioinformatics/btu509 |
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