Evidence map›Paper›PMID 40894551›Full record

ArticlebioRxiv : the preprint server for biology2025

WeavePop: A bioinformatics workflow to explore and analyze genomic variants of eukaryotic populations.

Claudia Zirión-Martínez, Paul M Magwene

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Claudia Zirión-MartínezDepartment of Biology, Duke University, PO Box 90338, Durham, NC 27708.
Paul M MagweneDepartment of Biology, Duke University, PO Box 90338, Durham, NC 27708.ORCID 0000-0002-7659-2589

Funding

The Genetic Basis of Virulence in Cryptococcus NeoformansR01AI133654 · NIAID · DUKE UNIVERSITY · PI JOSEPH HEITMAN, Paul Mitaari Magwene · 2017 to 2026
$4.7M
NIAID NIH HHS R01 AI133654
6 · The paper itself

Abstract

Analyzing genomic variants in large datasets composed of short-read sequencing data is a process that requires multiple steps and computational tools, which makes it a complicated task that is difficult to reproduce across projects and laboratories. To address this need, we developed a reproducible and scalable Snakemake workflow called WeavePop, which aligns samples to selected references, obtains reference-based assemblies, annotations, and sequences, and identifies small variants and copy-number variants in eukaryotic haploid organisms. All the results are integrated into a database that can be easily shared and explored through a graphical web interface provided alongside the workflow, making the discovery of variants in a population of study very simple. WeavePop is available from GitHub (https://github.com/magwenelab/WeavePop) for Linux operating systems. Here we exemplify the use of WeavePop in a large collection of isolates of the pathogenic fungus

Indexed as

Copy-number variantsdatabaseeukaryoticpopulation genomicsshinysmall variantssnakemakeworkflow

Identifiers

PMID40894551
PMCPMC12393431

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.