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Expanded functionality, increased accuracy, and enhanced speed in the de novo genotyping-by-sequencing pipeline GBS-SNP-CROP.
Bioinformatics 2018 October 16
Summary: GBS-SNP-CROP is a bioinformatics pipeline originally developed to support the cost-effective genome-wide characterization of plant genetic resources through paired-end genotyping-by-sequencing (GBS), particularly in the absence of a reference genome. Since its 2016 release, the pipeline's functionality has greatly expanded, its computational efficiency has improved, and its applicability to a broad set of genomic studies for both plants and animals has been demonstrated. This note details the suite of improvements to date, as realized in GBS-SNP-CROP v.4.0, with specific attention paid to a new integrated metric that facilitates reliable variant identification despite the complications of homologs. Using the new de novo GBS read simulator GBS-Pacecar, also introduced in this note, results show an improvement in overall pipeline accuracy from 66% (v.1.0) to 84% (v.4.0), with a time saving of approximately 70%. Both GBS-SNP-CROP versions significantly outperform TASSEL-UNEAK; and v.4.0 resolves the issue of non-overlapping variant calls observed between UNEAK and v.1.0.
Availability and implementation: GBS-SNP-CROP source code and User Manual are available at https://github.com/halelab/GBS-SNP-CROP.
Supplementary information: Supplementary data are available at Bioinformatics online.
Availability and implementation: GBS-SNP-CROP source code and User Manual are available at https://github.com/halelab/GBS-SNP-CROP.
Supplementary information: Supplementary data are available at Bioinformatics online.
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