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 GenoMax, Istvan Albert, Dunois, and was edited by lakhujanivijay, GenoMax, Istvan Albert,
Effective variant filtering and expected candidate variant yield in studies of rare human disease | npj Genomic Medicine (www.nature.com)
In an effort to establish recommendations for rare disease research, we explore effective guidelines for variant (SNP and INDEL) filtering and report the expected number of candidates for de novo dominant, recessive, and autosomal dominant modes of inheritance.
submitted by: Istvan Albert
As far as I know there hasn't been any assessment of the rate of analytical errors in scientific spreadsheets except for the case of gene name errors. We are considering this as a follow up study.
— Mark Ziemann (@mdziemann) August 3, 2021
As far as I know there hasn't been any assessment of the rate of analytical errors in scientific spreadsheets except for the case of gene name errors. We are considering this as a follow up study.
— Mark Ziemann (@mdziemann) August 3, 2021The Twitter thread that goes with the article:
- "Gene name errors: Lessons not learned"
We wonder, will the situation ever improve? Short, cynical answer ... no.
submitted by: Istvan Albert
Gene name errors: Lessons not learned (journals.plos.org)
Overall, gene name errors continued to accumulate unabated in the period after 2016. An improved scanning software we developed identified gene name errors in 30.9% (3,436/11,117) of articles with supplementary Excel gene lists; a figure significantly higher than previously estimated.
submitted by: Istvan Albert
An analysis and visualization platform for 'omics data – Meren Lab (merenlab.org)
Anvi’o is an open-source, community-driven analysis and visualization platform for microbial ‘omics. It brings together many aspects of today’s cutting-edge strategies including genomics, metagenomics, metatranscriptomics, pangenomics, metapangenomics, phylogenomics, and microbial population genetics in an integrated and easy-to-use fashion through extensive interactive visualization capabilities.
submitted by: Istvan Albert
Accurate prediction of protein structures and interactions using a three-track neural network | Science (science.sciencemag.org)
Accurate prediction of protein structures and interactions using a three-track neural network (Baker group's contender for the protein structure prediction crown.)
submitted by: Dunois
ACE: Explaining cluster from an adversarial perspective | bioRxiv (www.biorxiv.org)
Abstract: A common workflow in single-cell RNA-seq analysis is to project the data to a latent space, cluster the cells in that space, and identify sets of marker genes that explain the differences among the discovered clusters. A primary drawback to this three-step procedure is that each step is carried out independently, thereby neglecting the effects of the nonlinear embedding and inter-gene dependencies on the selection of marker genes. Here we propose an integrated deep learning framework, Adversarial Clustering Explanation (ACE), that bundles all three steps into a single work-flow. The method thus moves away from the notion of “marker genes” to instead identify a panel of explanatory genes. This panel may include genes that are not only enriched but also depleted relative to other cell types, as well as genes that exhibit differences between closely related cell types.
submitted by: GenoMax
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