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FASTAptamer: A Bioinformatic Toolkit for High-throughput Sequence Analysis of Combinatorial Selections
High-throughput sequence (HTS) analysis of combinatorial selection populations accelerates lead discovery and optimization and offers dynamic insight into selection processes. An underlying principle is that selection enriches high-fitness sequences as a fraction of the population, whereas low-fitne...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4354339/ https://www.ncbi.nlm.nih.gov/pubmed/25734917 http://dx.doi.org/10.1038/mtna.2015.4 |
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author | Alam, Khalid K Chang, Jonathan L Burke, Donald H |
author_facet | Alam, Khalid K Chang, Jonathan L Burke, Donald H |
author_sort | Alam, Khalid K |
collection | PubMed |
description | High-throughput sequence (HTS) analysis of combinatorial selection populations accelerates lead discovery and optimization and offers dynamic insight into selection processes. An underlying principle is that selection enriches high-fitness sequences as a fraction of the population, whereas low-fitness sequences are depleted. HTS analysis readily provides the requisite numerical information by tracking the evolutionary trajectory of individual sequences in response to selection pressures. Unlike genomic data, for which a number of software solutions exist, user-friendly tools are not readily available for the combinatorial selections field, leading many users to create custom software. FASTAptamer was designed to address the sequence-level analysis needs of the field. The open source FASTAptamer toolkit counts, normalizes and ranks read counts in a FASTQ file, compares populations for sequence distribution, generates clusters of sequence families, calculates fold-enrichment of sequences throughout the course of a selection and searches for degenerate sequence motifs. While originally designed for aptamer selections, FASTAptamer can be applied to any selection strategy that can utilize next-generation DNA sequencing, such as ribozyme or deoxyribozyme selections, in vivo mutagenesis and various surface display technologies (peptide, antibody fragment, mRNA, etc.). FASTAptamer software, sample data and a user's guide are available for download at http://burkelab.missouri.edu/fastaptamer.html. |
format | Online Article Text |
id | pubmed-4354339 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-43543392015-03-17 FASTAptamer: A Bioinformatic Toolkit for High-throughput Sequence Analysis of Combinatorial Selections Alam, Khalid K Chang, Jonathan L Burke, Donald H Mol Ther Nucleic Acids Original Article High-throughput sequence (HTS) analysis of combinatorial selection populations accelerates lead discovery and optimization and offers dynamic insight into selection processes. An underlying principle is that selection enriches high-fitness sequences as a fraction of the population, whereas low-fitness sequences are depleted. HTS analysis readily provides the requisite numerical information by tracking the evolutionary trajectory of individual sequences in response to selection pressures. Unlike genomic data, for which a number of software solutions exist, user-friendly tools are not readily available for the combinatorial selections field, leading many users to create custom software. FASTAptamer was designed to address the sequence-level analysis needs of the field. The open source FASTAptamer toolkit counts, normalizes and ranks read counts in a FASTQ file, compares populations for sequence distribution, generates clusters of sequence families, calculates fold-enrichment of sequences throughout the course of a selection and searches for degenerate sequence motifs. While originally designed for aptamer selections, FASTAptamer can be applied to any selection strategy that can utilize next-generation DNA sequencing, such as ribozyme or deoxyribozyme selections, in vivo mutagenesis and various surface display technologies (peptide, antibody fragment, mRNA, etc.). FASTAptamer software, sample data and a user's guide are available for download at http://burkelab.missouri.edu/fastaptamer.html. Nature Publishing Group 2015-03 2015-03-03 /pmc/articles/PMC4354339/ /pubmed/25734917 http://dx.doi.org/10.1038/mtna.2015.4 Text en Copyright © 2015 American Society of Gene & Cell Therapy http://creativecommons.org/licenses/by-nc-sa/4.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/ |
spellingShingle | Original Article Alam, Khalid K Chang, Jonathan L Burke, Donald H FASTAptamer: A Bioinformatic Toolkit for High-throughput Sequence Analysis of Combinatorial Selections |
title | FASTAptamer: A Bioinformatic Toolkit for High-throughput Sequence Analysis of Combinatorial Selections |
title_full | FASTAptamer: A Bioinformatic Toolkit for High-throughput Sequence Analysis of Combinatorial Selections |
title_fullStr | FASTAptamer: A Bioinformatic Toolkit for High-throughput Sequence Analysis of Combinatorial Selections |
title_full_unstemmed | FASTAptamer: A Bioinformatic Toolkit for High-throughput Sequence Analysis of Combinatorial Selections |
title_short | FASTAptamer: A Bioinformatic Toolkit for High-throughput Sequence Analysis of Combinatorial Selections |
title_sort | fastaptamer: a bioinformatic toolkit for high-throughput sequence analysis of combinatorial selections |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4354339/ https://www.ncbi.nlm.nih.gov/pubmed/25734917 http://dx.doi.org/10.1038/mtna.2015.4 |
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