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,
For anyone interested in drawing phylogenetic trees, here’s a new free and powerful tree-drawing software application called TreeViewer. Available on Windows/macOS/Linux, it lets you transform phylogenetic trees, add layers, map data to branches, align text, and much more! 👇…
— Bento Lab 🧬 (@theBentoLab) May 7, 2024
For anyone interested in drawing phylogenetic trees, here’s a new free and powerful tree-drawing software application called TreeViewer. Available on Windows/macOS/Linux, it lets you transform phylogenetic trees, add layers, map data to branches, align text, and much more! 👇…
— Bento Lab 🧬 (@theBentoLab) May 7, 2024submitted by: Istvan Albert
TreeViewer: Flexible, modular software to visualise and manipulate phylogenetic trees (onlinelibrary.wiley.com)
We present TreeViewer, a new software to draw phylogenetic trees. TreeViewer is flexible, modular, and user-friendly. Plots are produced as the result of a user-defined pipeline, which can be finely customised and easily applied to different trees.
submitted by: Istvan Albert
Introduction - Bactopia (bactopia.github.io)
Bactopia is a flexible pipeline for complete analysis of bacterial genomes. The goal of Bactopia is process your data with a broad set of tools, so that you can get to the fun part of analyses quicker!
submitted by: Istvan Albert
EconPapers: Mass Reproducibility and Replicability: A New Hope (econpapers.repec.org)
This study pushes our understanding of research reliability by reproducing and replicating claims from 110 papers in leading economic and political science journals. The analysis involves computational reproducibility checks and robustness assessments. It reveals several patterns. First, we uncover a high rate of fully computationally reproducible results (over 85%). Second, excluding minor issues like missing packages or broken pathways, we uncover coding errors for about 25% of studies, with some studies containing multiple errors. Third, we test the robustness of the results to 5,511 re-analyses. We find a robustness reproducibility of about 70%.
submitted by: Istvan Albert
Highly Effective Batch Effect Correction Method for RNA-seq Count Data | bioRxiv (www.biorxiv.org)
Building on the foundations of ComBat-seq, ComBat-ref employs a negative binomial model to adjust count data but innovates by using a pooled dispersion parameter for entire batches and preserving count data for the reference batch. Our method demonstrated superior performance in both simulated environments and real datasets, such as the growth factor receptor network (GFRN) data and NASA GeneLab transcriptomic datasets, significantly improving sensitivity and specificity over existing methods.
submitted by: Istvan Albert
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