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      VCPA: genomic variant calling pipeline and data management tool for Alzheimer’s Disease Sequencing Project

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          Abstract

          Summary

          We report VCPA, our SNP/Indel Variant Calling Pipeline and data management tool used for the analysis of whole genome and exome sequencing (WGS/WES) for the Alzheimer’s Disease Sequencing Project. VCPA consists of two independent but linkable components: pipeline and tracking database. The pipeline, implemented using the Workflow Description Language and fully optimized for the Amazon elastic compute cloud environment, includes steps from aligning raw sequence reads to variant calling using GATK. The tracking database allows users to view job running status in real time and visualize >100 quality metrics per genome. VCPA is functionally equivalent to the CCDG/TOPMed pipeline. Users can use the pipeline and the dockerized database to process large WGS/WES datasets on Amazon cloud with minimal configuration.

          Availability and implementation

          VCPA is released under the MIT license and is available for academic and nonprofit use for free. The pipeline source code and step-by-step instructions are available from the National Institute on Aging Genetics of Alzheimer’s Disease Data Storage Site ( http://www.niagads.org/VCPA).

          Supplementary information

          Supplementary data are available at Bioinformatics online.

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          SAMBLASTER: fast duplicate marking and structural variant read extraction

          Gregory Faust, Ira Hall (2014)
          Motivation: Illumina DNA sequencing is now the predominant source of raw genomic data, and data volumes are growing rapidly. Bioinformatic analysis pipelines are having trouble keeping pace. A common bottleneck in such pipelines is the requirement to read, write, sort and compress large BAM files multiple times. Results: We present SAMBLASTER, a tool that reduces the number of times such costly operations are performed. SAMBLASTER is designed to mark duplicates in read-sorted SAM files as a piped post-pass on DNA aligner output before it is compressed to BAM. In addition, it can simultaneously output into separate files the discordant read-pairs and/or split-read mappings used for structural variant calling. As an alignment post-pass, its own runtime overhead is negligible, while dramatically reducing overall pipeline complexity and runtime. As a stand-alone duplicate marking tool, it performs significantly better than PICARD or SAMBAMBA in terms of both speed and memory usage, while achieving nearly identical results. Availability and implementation: SAMBLASTER is open-source C++ code and freely available for download from https://github.com/GregoryFaust/samblaster. Contact: imh4y@virginia.edu
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            Aligning Sequence Reads, Clone Sequences and Assembly Contigs with BWA-MEM

            H. Li, Li, H Li (2013)
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              xAtlas: Scalable small variant calling across heterogeneous next-generation sequencing experiments

              Farek, J. Farek (2018)
              Article 0 comments Cited 2 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Prabhakaran Gangadharan: On behalf of : Alzheimer’s Disease Sequencing Project (ADSP)
                John Hancock: Role: Associate Editor
                Journal
                Journal ID (nlm-ta): Bioinformatics
                Journal ID (iso-abbrev): Bioinformatics
                Journal ID (publisher-id): bioinformatics
                Title: Bioinformatics
                Publisher: Oxford University Press
                ISSN (Print): 1367-4803
                ISSN (Electronic): 1367-4811
                Publication date (Print): 15 May 2019
                Publication date (Electronic): 23 October 2018
                Publication date PMC-release: 23 October 2018
                Volume: 35
                Issue: 10
                Pages: 1768-1770
                Affiliations
                [1 ]Department of Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Penn Neurodegeneration Genomics Center, Philadelphia, PA, USA
                [2 ]Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
                Author notes
                To whom correspondence should be addressed. Email: yyee@ 123456pennmedicine.upenn.edu or lswang@ 123456pennmedicine.upenn.edu
                Article
                Publisher ID: bty894
                DOI: 10.1093/bioinformatics/bty894
                PMC ID: 6513159
                PubMed ID: 30351394
                SO-VID: 1076fed5-8a40-403a-b5e5-14eb244293b0
                Copyright © © The Author(s) 2018. Published by Oxford University Press.
                License:

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                Date received : 10 June 2018
                Date revision received : 27 September 2018
                Date accepted : 22 October 2018
                Page count
                Pages: 3
                Funding
                Funded by: National Institute on Aging 10.13039/100000049
                Award ID: U54-AG052427
                Award ID: U01-AG032984
                Award ID: U24-AG041689
                Categories
                Subject: Applications Notes
                Subject: Sequence Analysis

                ScienceOpen disciplines: Bioinformatics & Computational biology
                Data availability:
                ScienceOpen disciplines: Bioinformatics & Computational biology

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