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• W2022200628 abstract "Next-generation sequencing (NGS) is now a commonplace tool for molecular characterisation of virtually any species of interest. Despite the ever-increasing use of NGS in laboratories worldwide, analysis of whole genome re-sequencing (WGS) datasets from start to finish remains nontrivial due to the fragmented nature of NGS software and the lack of experienced bioinformaticists in many research teams. We describe SPANDx (S ynergised P ipeline for A nalysis of N GS D ata in Linux), a new tool for high-throughput comparative analysis of haploid WGS datasets comprising one through thousands of genomes. SPANDx consolidates several well-validated, open-source packages into a single tool, mitigating the need to learn and manipulate individual NGS programs. SPANDx incorporates BWA for alignment of raw NGS reads against a reference genome or pan-genome, followed by data filtering, variant calling and annotation using Picard, GATK, SAMtools and SnpEff. BEDTools has also been included for genetic locus presence/absence (P/A) determination to easily visualise the core and accessory genomes. Additional SPANDx features include construction of error-corrected single-nucleotide polymorphism (SNP) and insertion-deletion matrices, and P/A matrices, to enable user-friendly visualisation of genetic variants. The SNP matrices generated using VCFtools and GATK are directly importable into PAUP*, PHYLIP or RAxML for downstream phylogenetic analysis. SPANDx has been developed to handle NGS data from Illumina, Ion Personal Genome Machine (PGM) and 454 platforms, and we demonstrate that it has comparable performance across Illumina MiSeq/HiSeq2000 and Ion PGM data. SPANDx is an all-in-one tool for comprehensive haploid WGS analysis. SPANDx is open source and is freely available at: http://sourceforge.net/projects/spandx/ ." @default.
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• W2022200628 date "2014-09-08" @default.
• W2022200628 modified "2023-10-09" @default.
• W2022200628 title "SPANDx: a genomics pipeline for comparative analysis of large haploid whole genome re-sequencing datasets" @default.
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• W2022200628 doi "https://doi.org/10.1186/1756-0500-7-618" @default.
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