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IsoformResolver: A Peptide-Centric Algorithm for Protein Inference
[Image: see text] When analyzing proteins in complex samples using tandem mass spectrometry of peptides generated by proteolysis, the inference of proteins can be ambiguous, even with well-validated peptides. Unresolved questions include whether to show all possible proteins vs a minimal list, what...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2011
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3167374/ https://www.ncbi.nlm.nih.gov/pubmed/21599010 http://dx.doi.org/10.1021/pr200039p |
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author | Meyer-Arendt, Karen Old, William M. Houel, Stephane Renganathan, Kutralanathan Eichelberger, Brian Resing, Katheryn A. Ahn, Natalie G. |
author_facet | Meyer-Arendt, Karen Old, William M. Houel, Stephane Renganathan, Kutralanathan Eichelberger, Brian Resing, Katheryn A. Ahn, Natalie G. |
author_sort | Meyer-Arendt, Karen |
collection | PubMed |
description | [Image: see text] When analyzing proteins in complex samples using tandem mass spectrometry of peptides generated by proteolysis, the inference of proteins can be ambiguous, even with well-validated peptides. Unresolved questions include whether to show all possible proteins vs a minimal list, what to do when proteins are inferred ambiguously, and how to quantify peptides that bridge multiple proteins, each with distinguishing evidence. Here we describe IsoformResolver, a peptide-centric protein inference algorithm that clusters proteins in two ways, one based on peptides experimentally identified from MS/MS spectra, and the other based on peptides derived from an in silico digest of the protein database. MS/MS-derived protein groups report minimal list proteins in the context of all possible proteins, without redundantly listing peptides. In silico-derived protein groups pull together functionally related proteins, providing stable identifiers. The peptide-centric grouping strategy used by IsoformResolver allows proteins to be displayed together when they share peptides in common, providing a comprehensive yet concise way to organize protein profiles. It also summarizes information on spectral counts and is especially useful for comparing results from multiple LC–MS/MS experiments. Finally, we examine the relatedness of proteins within IsoformResolver groups and compare its performance to other protein inference software. |
format | Online Article Text |
id | pubmed-3167374 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-31673742011-09-06 IsoformResolver: A Peptide-Centric Algorithm for Protein Inference Meyer-Arendt, Karen Old, William M. Houel, Stephane Renganathan, Kutralanathan Eichelberger, Brian Resing, Katheryn A. Ahn, Natalie G. J Proteome Res [Image: see text] When analyzing proteins in complex samples using tandem mass spectrometry of peptides generated by proteolysis, the inference of proteins can be ambiguous, even with well-validated peptides. Unresolved questions include whether to show all possible proteins vs a minimal list, what to do when proteins are inferred ambiguously, and how to quantify peptides that bridge multiple proteins, each with distinguishing evidence. Here we describe IsoformResolver, a peptide-centric protein inference algorithm that clusters proteins in two ways, one based on peptides experimentally identified from MS/MS spectra, and the other based on peptides derived from an in silico digest of the protein database. MS/MS-derived protein groups report minimal list proteins in the context of all possible proteins, without redundantly listing peptides. In silico-derived protein groups pull together functionally related proteins, providing stable identifiers. The peptide-centric grouping strategy used by IsoformResolver allows proteins to be displayed together when they share peptides in common, providing a comprehensive yet concise way to organize protein profiles. It also summarizes information on spectral counts and is especially useful for comparing results from multiple LC–MS/MS experiments. Finally, we examine the relatedness of proteins within IsoformResolver groups and compare its performance to other protein inference software. American Chemical Society 2011-05-21 2011-07-01 /pmc/articles/PMC3167374/ /pubmed/21599010 http://dx.doi.org/10.1021/pr200039p Text en Copyright © 2011 American Chemical Society http://pubs.acs.org This is an open-access article distributed under the ACS AuthorChoice Terms & Conditions. Any use of this article, must conform to the terms of that license which are available at http://pubs.acs.org. |
spellingShingle | Meyer-Arendt, Karen Old, William M. Houel, Stephane Renganathan, Kutralanathan Eichelberger, Brian Resing, Katheryn A. Ahn, Natalie G. IsoformResolver: A Peptide-Centric Algorithm for Protein Inference |
title | IsoformResolver: A Peptide-Centric Algorithm for Protein Inference |
title_full | IsoformResolver: A Peptide-Centric Algorithm for Protein Inference |
title_fullStr | IsoformResolver: A Peptide-Centric Algorithm for Protein Inference |
title_full_unstemmed | IsoformResolver: A Peptide-Centric Algorithm for Protein Inference |
title_short | IsoformResolver: A Peptide-Centric Algorithm for Protein Inference |
title_sort | isoformresolver: a peptide-centric algorithm for protein inference |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3167374/ https://www.ncbi.nlm.nih.gov/pubmed/21599010 http://dx.doi.org/10.1021/pr200039p |
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