Herald:The Biostar Herald for Monday, March 11, 2024
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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 Mensur Dlakic, Istvan Albert, Rob, and was edited by Istvan Albert,


Analysis of multi-condition single-cell data with latent embedding multivariate regression | bioRxiv (www.biorxiv.org)

A continuous low-dimensional latent embedding of differential expression.

submitted by: Mensur Dlakic


mulea - an R package for enrichment analysis using multiple ontologies and empirical FDR correction | bioRxiv (www.biorxiv.org)

We introduce mulea, an R package offering comprehensive overrepresentation and functional enrichment analysis. mulea employs an innovative empirical false discovery rate (eFDR) correction method, specifically designed for interconnected biological data, to accurately identify significant terms within diverse ontologies. mulea expands beyond traditional tools by incorporating a wide range of ontologies, encompassing Gene Ontology, pathways, regulatory elements, genomic locations, and protein domains.

submitted by: Istvan Albert


submitted by: Istvan Albert


submitted by: Istvan Albert


Oarfish: Enhanced probabilistic modeling leads to improved accuracy in long read transcriptome quantification | bioRxiv (www.biorxiv.org)

We introduce a new method and software tool for long read transcript quantification called oarfish. Our model incorporates a novel and innovative coverage score, which affects the conditional probability of fragment assignment in the underlying probabilistic model. We demonstrate that by accounting for this coverage information, oarfish is able to produce more accurate quantification estimates than existing long read quantification methods, particularly when one considers the primary isoforms present in a particular cell line or tissue type.

submitted by: Rob


[2402.16185] Exploring gene content with pangenome gene graphs (arxiv.org)

submitted by: Istvan Albert


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