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AutoFACT: An Automatic Functional Annotation and Classification Tool
BACKGROUND: Assignment of function to new molecular sequence data is an essential step in genomics projects. The usual process involves similarity searches of a given sequence against one or more databases, an arduous process for large datasets. RESULTS: We present AutoFACT, a fully automated and cu...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2005
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1182349/ https://www.ncbi.nlm.nih.gov/pubmed/15960857 http://dx.doi.org/10.1186/1471-2105-6-151 |
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author | Koski, Liisa B Gray, Michael W Lang, B Franz Burger, Gertraud |
author_facet | Koski, Liisa B Gray, Michael W Lang, B Franz Burger, Gertraud |
author_sort | Koski, Liisa B |
collection | PubMed |
description | BACKGROUND: Assignment of function to new molecular sequence data is an essential step in genomics projects. The usual process involves similarity searches of a given sequence against one or more databases, an arduous process for large datasets. RESULTS: We present AutoFACT, a fully automated and customizable annotation tool that assigns biologically informative functions to a sequence. Key features of this tool are that it (1) analyzes nucleotide and protein sequence data; (2) determines the most informative functional description by combining multiple BLAST reports from several user-selected databases; (3) assigns putative metabolic pathways, functional classes, enzyme classes, GeneOntology terms and locus names; and (4) generates output in HTML, text and GFF formats for the user's convenience. We have compared AutoFACT to four well-established annotation pipelines. The error rate of functional annotation is estimated to be only between 1–2%. Comparison of AutoFACT to the traditional top-BLAST-hit annotation method shows that our procedure increases the number of functionally informative annotations by approximately 50%. CONCLUSION: AutoFACT will serve as a useful annotation tool for smaller sequencing groups lacking dedicated bioinformatics staff. It is implemented in PERL and runs on LINUX/UNIX platforms. AutoFACT is available at . |
format | Text |
id | pubmed-1182349 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2005 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-11823492005-08-04 AutoFACT: An Automatic Functional Annotation and Classification Tool Koski, Liisa B Gray, Michael W Lang, B Franz Burger, Gertraud BMC Bioinformatics Software BACKGROUND: Assignment of function to new molecular sequence data is an essential step in genomics projects. The usual process involves similarity searches of a given sequence against one or more databases, an arduous process for large datasets. RESULTS: We present AutoFACT, a fully automated and customizable annotation tool that assigns biologically informative functions to a sequence. Key features of this tool are that it (1) analyzes nucleotide and protein sequence data; (2) determines the most informative functional description by combining multiple BLAST reports from several user-selected databases; (3) assigns putative metabolic pathways, functional classes, enzyme classes, GeneOntology terms and locus names; and (4) generates output in HTML, text and GFF formats for the user's convenience. We have compared AutoFACT to four well-established annotation pipelines. The error rate of functional annotation is estimated to be only between 1–2%. Comparison of AutoFACT to the traditional top-BLAST-hit annotation method shows that our procedure increases the number of functionally informative annotations by approximately 50%. CONCLUSION: AutoFACT will serve as a useful annotation tool for smaller sequencing groups lacking dedicated bioinformatics staff. It is implemented in PERL and runs on LINUX/UNIX platforms. AutoFACT is available at . BioMed Central 2005-06-16 /pmc/articles/PMC1182349/ /pubmed/15960857 http://dx.doi.org/10.1186/1471-2105-6-151 Text en Copyright © 2005 Koski et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Software Koski, Liisa B Gray, Michael W Lang, B Franz Burger, Gertraud AutoFACT: An Automatic Functional Annotation and Classification Tool |
title | AutoFACT: An Automatic Functional Annotation and Classification Tool |
title_full | AutoFACT: An Automatic Functional Annotation and Classification Tool |
title_fullStr | AutoFACT: An Automatic Functional Annotation and Classification Tool |
title_full_unstemmed | AutoFACT: An Automatic Functional Annotation and Classification Tool |
title_short | AutoFACT: An Automatic Functional Annotation and Classification Tool |
title_sort | autofact: an automatic functional annotation and classification tool |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1182349/ https://www.ncbi.nlm.nih.gov/pubmed/15960857 http://dx.doi.org/10.1186/1471-2105-6-151 |
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