The Biostar Herald publishes user submitted links of bioinformatics relevance. It aims to provide a summary of interesting and relevant information you may have missed. You too can submit links here.
This edition of the Herald was brought to you by contribution from Istvan Albert, and was edited by Istvan Albert,
The Snakemake Wrappers repository — Snakemake Wrappers tags/v2.13.0 documentation (snakemake-wrappers.readthedocs.io)
The Snakemake Wrapper Repository is a collection of reusable wrappers that allow to quickly use popular tools from Snakemake rules and workflows.
submitted by: Istvan Albert
We are excited to release several new GIAB products in advance of #ASHG23, including v1.0 TR and X&Y benchmarks, corrected GRCh38 reference, stratifications for T2T-CHM13, RNA-seq, GIAB tumor/normal data, and a v1.0 T2T-HG002 assembly with #T2T. Details at https://t.co/LduvNJXKCA
— Genome in a Bottle (@GenomeInABottle) November 1, 2023
We are excited to release several new GIAB products in advance of #ASHG23, including v1.0 TR and X&Y benchmarks, corrected GRCh38 reference, stratifications for T2T-CHM13, RNA-seq, GIAB tumor/normal data, and a v1.0 T2T-HG002 assembly with #T2T. Details at https://t.co/LduvNJXKCA
— Genome in a Bottle (@GenomeInABottle) November 1, 2023submitted by: Istvan Albert
An international consensus on effective, inclusive, and career-spanning short-format training in the life sciences and beyond | PLOS ONE (journals.plos.org)
The 14 recommendations were derived through a Delphi method, where consensus was achieved in real time as the group completed a series of meetings and tasks designed to elicit specific recommendations.
submitted by: Istvan Albert
https://academic.oup.com/bioinformatics/article/39/10/btad621/7319363
Here, we present PanKmer, a toolkit designed for reference-free analysis of pangenome datasets consisting of dozens to thousands of individual genomes. PanKmer decomposes a set of input genomes into a table of observed k-mers and their presence–absence values in each genome. These are stored in an efficient k-mer index data format that encodes SNPs, INDELs, and SVs. It also includes functions for downstream analysis of the k-mer index, such as calculating sequence similarity statistics between individuals at whole-genome or local scales.
submitted by: Istvan Albert
ONT accuracy vs depth update | Ryan Wick’s bioinformatics blog (rrwick.github.io)
You can see in the plot that accuracy improved up to ~100× depth, after which additional reads brought no benefit. In fact, some of the genomes got a bit worse with higher depth, which was surprising.8 This suggests that if you have very-high-depth read sets, subsampling them (e.g. with Filtlong) before Flye assembly might benefit not just computational time but also sequence accuracy.
submitted by: Istvan Albert
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