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SeqPanther: Sequence manipulation and mutation statistics toolset

Authors: James Emmanuel San; Stephanie van Wyk; Houriiyah Tegally; Simeon Eche; Eduan Wilkinson; Aquillah M. Kanzi; Tulio de Oliveira; +1 Authors

SeqPanther: Sequence manipulation and mutation statistics toolset

Abstract

Abstract Pathogen genomes harbor critical information necessary to support genomic investigations that inform public health interventions such as treatment, control, and eradication. To extract this information, their sequences are analysed to identify structural variations such as single nucleotide polymorphisms (SNPs) and insertions and deletions (indels) that may be associated with phenotypes of interest. Typically, this involves generating a consensus sequence from raw reads, aligning it to a reference and identifying positions where variations occur. Several pipelines exist to map raw reads and assemble whole genomes for downstream analysis. However, there is no easy to use, freely available bioinformatics quality control (QC) tool to explore mappings for both positional codons and nucleotide distributions in mapped short reads of microbial genomes. To address this problem, we have developed a fast and accurate tool to summarise read counts associated with codons, nucleotides, and indels in mapped next-generation sequencing (NGS) short reads. The tool, developed in Python, also provides a visualization of the genome sequencing depth and coverage. Furthermore, the tool can be run in single or batch mode, where several genomes need to be analysed. Our tool produces a text-based report that enables quick review or can be imported into any analytical tool for upstream analysis. Additionally, the tool also provides functionality to modify the consensus sequences by adding, masking, or restoring to wild type mutations specified by the user. Availability SeqPanther is available at https://github.com/codemeleon/seqPanther , along with the necessary documentation for installation and usage.

Keywords

SARS-CoV-2, BAM

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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