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aLFQ: an R-package for estimating absolute protein quantities from label-free LC-MS/MS proteomics data
Motivation: The determination of absolute quantities of proteins in biological samples is necessary for multiple types of scientific inquiry. While relative quantification has been commonly used in proteomics, few proteomic datasets measuring absolute protein quantities have been reported to date. V...
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/PMC4147881/ https://www.ncbi.nlm.nih.gov/pubmed/24753486 http://dx.doi.org/10.1093/bioinformatics/btu200 |
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author | Rosenberger, George Ludwig, Christina Röst, Hannes L. Aebersold, Ruedi Malmström, Lars |
author_facet | Rosenberger, George Ludwig, Christina Röst, Hannes L. Aebersold, Ruedi Malmström, Lars |
author_sort | Rosenberger, George |
collection | PubMed |
description | Motivation: The determination of absolute quantities of proteins in biological samples is necessary for multiple types of scientific inquiry. While relative quantification has been commonly used in proteomics, few proteomic datasets measuring absolute protein quantities have been reported to date. Various technologies have been applied using different types of input data, e.g. ion intensities or spectral counts, as well as different absolute normalization strategies. To date, a user-friendly and transparent software supporting large-scale absolute protein quantification has been lacking. Results: We present a bioinformatics tool, termed aLFQ, which supports the commonly used absolute label-free protein abundance estimation methods (TopN, iBAQ, APEX, NSAF and SCAMPI) for LC-MS/MS proteomics data, together with validation algorithms enabling automated data analysis and error estimation. Availability and implementation: aLFQ is written in R and freely available under the GPLv3 from CRAN (http://www.cran.r-project.org). Instructions and example data are provided in the R-package. The raw data can be obtained from the PeptideAtlas raw data repository (PASS00321). Contact: lars.malmstroem@imsb.biol.ethz.ch Supplementary information: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-4147881 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-41478812014-09-02 aLFQ: an R-package for estimating absolute protein quantities from label-free LC-MS/MS proteomics data Rosenberger, George Ludwig, Christina Röst, Hannes L. Aebersold, Ruedi Malmström, Lars Bioinformatics Applications Notes Motivation: The determination of absolute quantities of proteins in biological samples is necessary for multiple types of scientific inquiry. While relative quantification has been commonly used in proteomics, few proteomic datasets measuring absolute protein quantities have been reported to date. Various technologies have been applied using different types of input data, e.g. ion intensities or spectral counts, as well as different absolute normalization strategies. To date, a user-friendly and transparent software supporting large-scale absolute protein quantification has been lacking. Results: We present a bioinformatics tool, termed aLFQ, which supports the commonly used absolute label-free protein abundance estimation methods (TopN, iBAQ, APEX, NSAF and SCAMPI) for LC-MS/MS proteomics data, together with validation algorithms enabling automated data analysis and error estimation. Availability and implementation: aLFQ is written in R and freely available under the GPLv3 from CRAN (http://www.cran.r-project.org). Instructions and example data are provided in the R-package. The raw data can be obtained from the PeptideAtlas raw data repository (PASS00321). Contact: lars.malmstroem@imsb.biol.ethz.ch Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2014-09-01 2014-04-20 /pmc/articles/PMC4147881/ /pubmed/24753486 http://dx.doi.org/10.1093/bioinformatics/btu200 Text en © The Author 2014. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes Rosenberger, George Ludwig, Christina Röst, Hannes L. Aebersold, Ruedi Malmström, Lars aLFQ: an R-package for estimating absolute protein quantities from label-free LC-MS/MS proteomics data |
title | aLFQ: an R-package for estimating absolute protein quantities from label-free LC-MS/MS proteomics data |
title_full | aLFQ: an R-package for estimating absolute protein quantities from label-free LC-MS/MS proteomics data |
title_fullStr | aLFQ: an R-package for estimating absolute protein quantities from label-free LC-MS/MS proteomics data |
title_full_unstemmed | aLFQ: an R-package for estimating absolute protein quantities from label-free LC-MS/MS proteomics data |
title_short | aLFQ: an R-package for estimating absolute protein quantities from label-free LC-MS/MS proteomics data |
title_sort | alfq: an r-package for estimating absolute protein quantities from label-free lc-ms/ms proteomics data |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4147881/ https://www.ncbi.nlm.nih.gov/pubmed/24753486 http://dx.doi.org/10.1093/bioinformatics/btu200 |
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