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BMC Bioinformatics
. 2021 Jul 17;22(1):373.
doi: 10.1186/s12859-021-04294-2.
HAVoC, a bioinformatic pipeline for reference-based consensus assembly and lineage assignment for SARS-CoV-2 sequences
Phuoc Thien Truong Nguyen 1 , Ilya Plyusnin 2 3 , Tarja Sironen 4 3 , Olli Vapalahti 4 3 5 , Ravi Kant # 4 3 , Teemu Smura # 4 5
Affiliations
- PMID: 34273961
- DOI: 10.1186/s12859-021-04294-2
Abstract
Background: SARS-CoV-2 related research has increased in importance worldwide since December 2019. Several new variants of SARS-CoV-2 have emerged globally, of which the most notable and concerning currently are the UK variant B.1.1.7, the South African variant B1.351 and the Brazilian variant P.1. Detecting and monitoring novel variants is essential in SARS-CoV-2 surveillance. While there are several tools for assembling virus genomes and performing lineage analyses to investigate SARS-CoV-2, each is limited to performing singular or a few functions separately.
Results: Due to the lack of publicly available pipelines, which could perform fast reference-based assemblies on raw SARS-CoV-2 sequences in addition to identifying lineages to detect variants of concern, we have developed an open source bioinformatic pipeline called HAVoC (Helsinki university Analyzer for Variants of Concern). HAVoC can reference assemble raw sequence reads and assign the corresponding lineages to SARS-CoV-2 sequences.
Conclusions: HAVoC is a pipeline utilizing several bioinformatic tools to perform multiple necessary analyses for investigating genetic variance among SARS-CoV-2 samples. The pipeline is particularly useful for those who need a more accessible and fast tool to detect and monitor the spread of SARS-CoV-2 variants of concern during local outbreaks. HAVoC is currently being used in Finland for monitoring the spread of SARS-CoV-2 variants. HAVoC user manual and source code are available at https://www.helsinki.fi/en/projects/havoc and https://bitbucket.org/auto_cov_pipeline/havoc , respectively.
Keywords: Coronavirus; Lineage identification; Reference assembly; SARS-CoV2; Sequence analysis; Variant detection.