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, Rob, and was edited by Istvan Albert,
eVITTA at UBC - easy Visualization and Inference Toolbox for Transcriptome Analysis (tau.cmmt.ubc.ca)
easy Visualization and Inference Toolbox for Transcriptome Analysis
submitted by: Istvan Albert
#Bioinformatics people, which programs do you use for GO-terms enrichment analysis? All seems well until you stick to one program only. I was running DAVID, PANTHER, GOrilla, and TopGO. Got different results. Read this study, but it did not clarify things: https://t.co/XvSVTPKU7K
— Irina Chelysheva, PhD (@chelysheva_i) July 4, 2021
#Bioinformatics people, which programs do you use for GO-terms enrichment analysis? All seems well until you stick to one program only. I was running DAVID, PANTHER, GOrilla, and TopGO. Got different results. Read this study, but it did not clarify things: https://t.co/XvSVTPKU7K
— Irina Chelysheva, PhD (@chelysheva_i) July 4, 2021submitted by: Istvan Albert
Popularity and performance of bioinformatics software: the case of gene set analysis | BMC Bioinformatics | Full Text (bmcbioinformatics.biomedcentral.com)
Gene Set Analysis (GSA) is arguably the method of choice for the functional interpretation of omics results. The following paper explores the popularity and the performance of all the GSA methodologies and software published during the 20 years since its inception. "Popularity" is estimated according to each paper's citation counts, while "performance" is based on a comprehensive evaluation of the validation strategies used by papers in the field, as well as the consolidated results from the existing benchmark studies.
submitted by: Istvan Albert
scverse (scverse.org)
scverse is a consortium of foundational tools (mostly in Python) for omics data in life sciences. It has been founded to ensure the long-term maintenance of these core tools.
submitted by: Istvan Albert
https://github.com/pachterlab/gget
gget is a free and open-source command-line tool and Python package that enables efficient querying of genomic databases. gget consists of a collection of separate but interoperable modules, each designed to facilitate one type of database querying in a single line of code.
submitted by: Istvan Albert
As a group working on #scRNA-seq and #snRNA-seq analysis, we’ve noticed that certain popular and publicly-available datasets, e.g. the PBMC datasets from 10x Genomics, are used repeatedly for tutorials, method development, etc. and often reprocessed. 1/🧵
— Rob Patro (@nomad421) May 6, 2022
As a group working on #scRNA-seq and #snRNA-seq analysis, we’ve noticed that certain popular and publicly-available datasets, e.g. the PBMC datasets from 10x Genomics, are used repeatedly for tutorials, method development, etc. and often reprocessed. 1/🧵
— Rob Patro (@nomad421) May 6, 2022The thread describes:
A Nextflow workflow (quantaf) for processing single-cell and single-nucleus data with
alevin-fry.An R package (roe) for allowing easy programmatic fetching of already processed data.
A python package (pyroe) for allowing easy programmatic fetching of already processed data and also a CLI for preprocessed data fetching.
A website with descriptions of these tools and daw links to these data.
submitted by: Rob
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