Dataset Information

PanSVR: Pan-Genome Augmented Short Read Realignment for Sensitive Detection of Structural Variations.

ABSTRACT: The comprehensive discovery of structure variations (SVs) is fundamental to many genomics studies and high-throughput sequencing has become a common approach to this task. However, due the limited length, it is still non-trivial to state-of-the-art tools to accurately align short reads and produce high-quality SV callsets. Pan-genome provides a novel and promising framework to short read-based SV calling since it enables to comprehensively integrate known variants to reduce the incompleteness and bias of single reference to breakthrough the bottlenecks of short read alignments and provide new evidences to the detection of SVs. However, it is still an open problem to develop effective computational approaches to fully take the advantage of pan-genomes. Herein, we propose Pan-genome augmented Structure Variation calling tool with read Re-alignment (PanSVR), a novel pan-genome-based SV calling approach. PanSVR uses several tailored methods to implement precise re-alignment for SV-spanning reads against well-organized pan-genome reference with plenty of known SVs. PanSVR enables to greatly improve the quality of short read alignments and produce clear and homogenous SV signatures which facilitate SV calling. Benchmark results on real sequencing data suggest that PanSVR is able to largely improve the sensitivity of SV calling than that of state-of-the-art SV callers, especially for the SVs from repeat-rich regions and/or novel insertions which are difficult to existing tools.

SUBMITTER: Li G

PROVIDER: S-EPMC8417358 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundStructural variations play an important role in bacterial genomes. They can mediate genome adaptation quickly in response to the external environment and thus can also play a role in antibiotic resistance. The detection of structural variations in bacteria is challenging, and the recognition of even small rearrangements can be important. Even though most detection tools are aimed at and benchmarked on eukaryotic genomes, they can also be used on prokaryotic genomes. The key features of detection are the ability to detect small rearrangements and support haploid genomes. Because of the limiting performance of a single detection tool, combining the detection abilities of multiple tools can lead to more robust results. There are already available workflows for structural variation detection for long-reads technologies and for the detection of single-nucleotide variation and indels, both aimed at bacteria. Yet we are unaware of structural variations detection workflows for the short-reads sequencing platform. Motivated by this gap we created our workflow. Further, we were interested in increasing the detection performance and providing more robust results.ResultsWe developed an open-source bioinformatics pipeline, ProcaryaSV, for the detection of structural variations in bacterial isolates from paired-end short sequencing reads. Multiple tools, starting with quality control and trimming of sequencing data, alignment to the reference genome, and multiple structural variation detection tools, are integrated. All the partial results are then processed and merged with an in-house merging algorithm. Compared with a single detection approach, ProcaryaSV has improved detection performance and is a reproducible easy-to-use tool.ConclusionsThe ProcaryaSV pipeline provides an integrative approach to structural variation detection from paired-end next-generation sequencing of bacterial samples. It can be easily installed and used on Linux machines. It is publicly available on GitHub at https://github.com/robinjugas/ProcaryaSV .

Dataset Information

PanSVR: Pan-Genome Augmented Short Read Realignment for Sensitive Detection of Structural Variations.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets