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Meta-aligner: long-read alignment based on genome statistics

BACKGROUND: Current development of sequencing technologies is towards generating longer and noisier reads. Evidently, accurate alignment of these reads play an important role in any downstream analysis. Similarly, reducing the overall cost of sequencing is related to the time consumption of the alig...

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Autores principales: Nashta-ali, Damoon, Aliyari, Ali, Ahmadian Moghadam, Ahmad, Edrisi, Mohammad Amin, Motahari, Seyed Abolfazl, Hossein Khalaj, Babak
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5324271/
https://www.ncbi.nlm.nih.gov/pubmed/28231760
http://dx.doi.org/10.1186/s12859-017-1518-y
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author Nashta-ali, Damoon
Aliyari, Ali
Ahmadian Moghadam, Ahmad
Edrisi, Mohammad Amin
Motahari, Seyed Abolfazl
Hossein Khalaj, Babak
author_facet Nashta-ali, Damoon
Aliyari, Ali
Ahmadian Moghadam, Ahmad
Edrisi, Mohammad Amin
Motahari, Seyed Abolfazl
Hossein Khalaj, Babak
author_sort Nashta-ali, Damoon
collection PubMed
description BACKGROUND: Current development of sequencing technologies is towards generating longer and noisier reads. Evidently, accurate alignment of these reads play an important role in any downstream analysis. Similarly, reducing the overall cost of sequencing is related to the time consumption of the aligner. The tradeoff between accuracy and speed is the main challenge in designing long read aligners. RESULTS: We propose Meta-aligner which aligns long and very long reads to the reference genome very efficiently and accurately. Meta-aligner incorporates available short/long aligners as subcomponents and uses statistics from the reference genome to increase the performance. Meta-aligner estimates statistics from reads and the reference genome automatically. Meta-aligner is implemented in C++ and runs in popular POSIX-like operating systems such as Linux. CONCLUSIONS: Meta-aligner achieves high recall rates and precisions especially for long reads and high error rates. Also, it improves performance of alignment in the case of PacBio long-reads in comparison with traditional schemes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-017-1518-y) contains supplementary material, which is available to authorized users.
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spelling pubmed-53242712017-03-01 Meta-aligner: long-read alignment based on genome statistics Nashta-ali, Damoon Aliyari, Ali Ahmadian Moghadam, Ahmad Edrisi, Mohammad Amin Motahari, Seyed Abolfazl Hossein Khalaj, Babak BMC Bioinformatics Research Article BACKGROUND: Current development of sequencing technologies is towards generating longer and noisier reads. Evidently, accurate alignment of these reads play an important role in any downstream analysis. Similarly, reducing the overall cost of sequencing is related to the time consumption of the aligner. The tradeoff between accuracy and speed is the main challenge in designing long read aligners. RESULTS: We propose Meta-aligner which aligns long and very long reads to the reference genome very efficiently and accurately. Meta-aligner incorporates available short/long aligners as subcomponents and uses statistics from the reference genome to increase the performance. Meta-aligner estimates statistics from reads and the reference genome automatically. Meta-aligner is implemented in C++ and runs in popular POSIX-like operating systems such as Linux. CONCLUSIONS: Meta-aligner achieves high recall rates and precisions especially for long reads and high error rates. Also, it improves performance of alignment in the case of PacBio long-reads in comparison with traditional schemes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-017-1518-y) contains supplementary material, which is available to authorized users. BioMed Central 2017-02-23 /pmc/articles/PMC5324271/ /pubmed/28231760 http://dx.doi.org/10.1186/s12859-017-1518-y Text en © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Nashta-ali, Damoon
Aliyari, Ali
Ahmadian Moghadam, Ahmad
Edrisi, Mohammad Amin
Motahari, Seyed Abolfazl
Hossein Khalaj, Babak
Meta-aligner: long-read alignment based on genome statistics
title Meta-aligner: long-read alignment based on genome statistics
title_full Meta-aligner: long-read alignment based on genome statistics
title_fullStr Meta-aligner: long-read alignment based on genome statistics
title_full_unstemmed Meta-aligner: long-read alignment based on genome statistics
title_short Meta-aligner: long-read alignment based on genome statistics
title_sort meta-aligner: long-read alignment based on genome statistics
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5324271/
https://www.ncbi.nlm.nih.gov/pubmed/28231760
http://dx.doi.org/10.1186/s12859-017-1518-y
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