Accelerating SARS-CoV-2 low frequency variant calling on ultra deep sequencing datasets

Bryce Kille; Yunxi Liu; Nicolae Sapoval; Michael Nute; Lawrence Rauchwerger; Nancy Amato; Todd J. Treangen

doi:10.1109/IPDPSW52791.2021.00038

Accelerating SARS-CoV-2 low frequency variant calling on ultra deep sequencing datasets

Bryce Kille, Yunxi Liu, Nicolae Sapoval, Michael Nute, Lawrence Rauchwerger, Nancy Amato, Todd J. Treangen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

With recent advances in sequencing technology it has become affordable and practical to sequence genomes to very high depth-of-coverage, allowing researchers to discover low-frequency variants in the genome. However, due to the errors in sequencing it is an active area of research to develop algorithms that can separate noise from the true variants. LoFreq is a state of the art algorithm for low-frequency variant detection but has a relatively long runtime compared to other tools. In addition to this, the interface for running in parallel could be simplified, allowing for multithreading as well as distributing jobs to a cluster. In this work we describe some specific contributions to LoFreq that remedy these issues.

Original language	English (US)
Title of host publication	2021 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2021 - In conjunction with IEEE IPDPS 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	204-208
Number of pages	5
ISBN (Electronic)	9781665435772
DOIs	https://doi.org/10.1109/IPDPSW52791.2021.00038
State	Published - Jun 2021
Externally published	Yes
Event	2021 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2021 - Virtual, Portland, United States Duration: May 17 2021 → …

Publication series

Name	2021 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2021 - In conjunction with IEEE IPDPS 2021

Conference

Conference	2021 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2021
Country/Territory	United States
City	Virtual, Portland
Period	5/17/21 → …

ASJC Scopus subject areas

Computer Networks and Communications
Hardware and Architecture
Information Systems

Online availability

10.1109/IPDPSW52791.2021.00038

Library availability

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Cite this

Kille, B., Liu, Y., Sapoval, N., Nute, M., Rauchwerger, L., Amato, N., & Treangen, T. J. (2021). Accelerating SARS-CoV-2 low frequency variant calling on ultra deep sequencing datasets. In 2021 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2021 - In conjunction with IEEE IPDPS 2021 (pp. 204-208). Article 9460605 (2021 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2021 - In conjunction with IEEE IPDPS 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IPDPSW52791.2021.00038

Accelerating SARS-CoV-2 low frequency variant calling on ultra deep sequencing datasets. / Kille, Bryce; Liu, Yunxi; Sapoval, Nicolae et al.
2021 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2021 - In conjunction with IEEE IPDPS 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 204-208 9460605 (2021 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2021 - In conjunction with IEEE IPDPS 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kille, B, Liu, Y, Sapoval, N, Nute, M, Rauchwerger, L , Amato, N & Treangen, TJ 2021, Accelerating SARS-CoV-2 low frequency variant calling on ultra deep sequencing datasets. in 2021 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2021 - In conjunction with IEEE IPDPS 2021., 9460605, 2021 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2021 - In conjunction with IEEE IPDPS 2021, Institute of Electrical and Electronics Engineers Inc., pp. 204-208, 2021 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2021, Virtual, Portland, United States, 5/17/21. https://doi.org/10.1109/IPDPSW52791.2021.00038

Kille B, Liu Y, Sapoval N, Nute M, Rauchwerger L , Amato N et al. Accelerating SARS-CoV-2 low frequency variant calling on ultra deep sequencing datasets. In 2021 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2021 - In conjunction with IEEE IPDPS 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 204-208. 9460605. (2021 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2021 - In conjunction with IEEE IPDPS 2021). doi: 10.1109/IPDPSW52791.2021.00038

Kille, Bryce ; Liu, Yunxi ; Sapoval, Nicolae et al. / Accelerating SARS-CoV-2 low frequency variant calling on ultra deep sequencing datasets. 2021 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2021 - In conjunction with IEEE IPDPS 2021. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 204-208 (2021 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2021 - In conjunction with IEEE IPDPS 2021).

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abstract = "With recent advances in sequencing technology it has become affordable and practical to sequence genomes to very high depth-of-coverage, allowing researchers to discover low-frequency variants in the genome. However, due to the errors in sequencing it is an active area of research to develop algorithms that can separate noise from the true variants. LoFreq is a state of the art algorithm for low-frequency variant detection but has a relatively long runtime compared to other tools. In addition to this, the interface for running in parallel could be simplified, allowing for multithreading as well as distributing jobs to a cluster. In this work we describe some specific contributions to LoFreq that remedy these issues.",

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Accelerating SARS-CoV-2 low frequency variant calling on ultra deep sequencing datasets

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