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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
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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. |
format | Online Article Text |
id | pubmed-6612896 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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