ArticleMolecular biology and evolution2024
scalepopgen: Bioinformatic Workflow Resources Implemented in Nextflow for Comprehensive Population Genomic Analyses.
Article in Molecular biology and evolution, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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Who cites it
2 citing papers in PubMed.
- Unravelling the genetic structure and genetic relationships of indigenous Greek sheep breeds using SNP markers.Genetics, selection, evolution : GSE · 2026Article
- ShiNyP: Unlocking SNP-Based Population Genetics-AI-Assisted Platform for Rapid and Interactive Visual Exploration.Molecular biology and evolution · 2025Article
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Authors and funding
3 authors.
Funding
Abstract
Population genomic analyses such as inference of population structure and identifying signatures of selection usually involve the application of a plethora of tools. The installation of tools and their dependencies, data transformation, or series of data preprocessing in a particular order sometimes makes the analyses challenging. While the usage of container-based technologies has significantly resolved the problems associated with the installation of tools and their dependencies, population genomic analyses requiring multistep pipelines or complex data transformation can greatly be facilitated by the application of workflow management systems such as Nextflow and Snakemake. Here, we present scalepopgen, a collection of fully automated workflows that can carry out widely used population genomic analyses on the biallelic single nucleotide polymorphism data stored in either variant calling format files or the plink-generated binary files. scalepopgen is developed in Nextflow and can be run locally or on high-performance computing systems using either Conda, Singularity, or Docker. The automated workflow includes procedures such as (i) filtering of individuals and genotypes; (ii) principal component analysis, admixture with identifying optimal K-values; (iii) running TreeMix analysis with or without bootstrapping and migration edges, followed by identification of an optimal number of migration edges; (iv) implementing single-population and pair-wise population comparison-based procedures to identify genomic signatures of selection. The pipeline uses various open-source tools; additionally, several Python and R scripts are also provided to collect and visualize the results. The tool is freely available at https://github.com/Popgen48/scalepopgen.
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Registered trials
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.