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Alfred: interactive multi-sample BAM alignment statistics, feature counting and feature annotation for long- and short-read sequencing

SUMMARY: Harmonizing quality control (QC) of large-scale second and third-generation sequencing datasets is key for enabling downstream computational and biological analyses. We present Alfred, an efficient and versatile command-line application that computes multi-sample QC metrics in a read-group...

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Detalles Bibliográficos
Autores principales: Rausch, Tobias, Hsi-Yang Fritz, Markus, Korbel, Jan O, Benes, Vladimir
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6612896/
https://www.ncbi.nlm.nih.gov/pubmed/30520945
http://dx.doi.org/10.1093/bioinformatics/bty1007
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author Rausch, Tobias
Hsi-Yang Fritz, Markus
Korbel, Jan O
Benes, Vladimir
author_facet Rausch, Tobias
Hsi-Yang Fritz, Markus
Korbel, Jan O
Benes, Vladimir
author_sort Rausch, Tobias
collection PubMed
description SUMMARY: Harmonizing quality control (QC) of large-scale second and third-generation sequencing datasets is key for enabling downstream computational and biological analyses. We present Alfred, an efficient and versatile command-line application that computes multi-sample QC metrics in a read-group aware manner, across a wide variety of sequencing assays and technologies. In addition to standard QC metrics such as GC bias, base composition, insert size and sequencing coverage distributions it supports haplotype-aware and allele-specific feature counting and feature annotation. The versatility of Alfred allows for easy pipeline integration in high-throughput settings, including DNA sequencing facilities and large-scale research initiatives, enabling continuous monitoring of sequence data quality and characteristics across samples. Alfred supports haplo-tagging of BAM/CRAM files to conduct haplotype-resolved analyses in conjunction with a variety of next-generation sequencing based assays. Alfred’s companion web application enables interactive exploration of results and comparison to public datasets. AVAILABILITY AND IMPLEMENTATION: Alfred is open-source and freely available at https://tobiasrausch.com/alfred/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-66128962019-07-12 Alfred: interactive multi-sample BAM alignment statistics, feature counting and feature annotation for long- and short-read sequencing Rausch, Tobias Hsi-Yang Fritz, Markus Korbel, Jan O Benes, Vladimir Bioinformatics Applications Notes SUMMARY: Harmonizing quality control (QC) of large-scale second and third-generation sequencing datasets is key for enabling downstream computational and biological analyses. We present Alfred, an efficient and versatile command-line application that computes multi-sample QC metrics in a read-group aware manner, across a wide variety of sequencing assays and technologies. In addition to standard QC metrics such as GC bias, base composition, insert size and sequencing coverage distributions it supports haplotype-aware and allele-specific feature counting and feature annotation. The versatility of Alfred allows for easy pipeline integration in high-throughput settings, including DNA sequencing facilities and large-scale research initiatives, enabling continuous monitoring of sequence data quality and characteristics across samples. Alfred supports haplo-tagging of BAM/CRAM files to conduct haplotype-resolved analyses in conjunction with a variety of next-generation sequencing based assays. Alfred’s companion web application enables interactive exploration of results and comparison to public datasets. AVAILABILITY AND IMPLEMENTATION: Alfred is open-source and freely available at https://tobiasrausch.com/alfred/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2019-07 2018-12-06 /pmc/articles/PMC6612896/ /pubmed/30520945 http://dx.doi.org/10.1093/bioinformatics/bty1007 Text en © The Author(s) 2018. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Notes
Rausch, Tobias
Hsi-Yang Fritz, Markus
Korbel, Jan O
Benes, Vladimir
Alfred: interactive multi-sample BAM alignment statistics, feature counting and feature annotation for long- and short-read sequencing
title Alfred: interactive multi-sample BAM alignment statistics, feature counting and feature annotation for long- and short-read sequencing
title_full Alfred: interactive multi-sample BAM alignment statistics, feature counting and feature annotation for long- and short-read sequencing
title_fullStr Alfred: interactive multi-sample BAM alignment statistics, feature counting and feature annotation for long- and short-read sequencing
title_full_unstemmed Alfred: interactive multi-sample BAM alignment statistics, feature counting and feature annotation for long- and short-read sequencing
title_short Alfred: interactive multi-sample BAM alignment statistics, feature counting and feature annotation for long- and short-read sequencing
title_sort alfred: interactive multi-sample bam alignment statistics, feature counting and feature annotation for long- and short-read sequencing
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6612896/
https://www.ncbi.nlm.nih.gov/pubmed/30520945
http://dx.doi.org/10.1093/bioinformatics/bty1007
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