Evidence map›Paper›PMID 38069903›Full record

ArticleMolecular biology and evolution2024

A Fast, Reproducible, High-throughput Variant Calling Workflow for Population Genomics.

Cade D Mirchandani, Allison J Shultz, Gregg W C Thomas, Sara J Smith, Mara Baylis, Brian Arnold, Russ Corbett-Detig, Erik Enbody, Timothy B Sackton

Abstract read
In one paragraph

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 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing 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

45 citing papers in PubMed.

  1. Article
  2. Variant calling in nonmodel organisms with snpArcher.Molecular biology and evolution · 2026
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  8. Ancient DNA from shells reveals delayed genomic erosion and rapid immune adaptation in the critically endangered black abalone.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  9. Article
  10. Diversity and divergence of two sympatric, sibling octopus species.bioRxiv : the preprint server for biology · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Cade D MirchandaniDepartment of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA.ORCID 0009-0002-1970-430X
Allison J ShultzOrnithology Department, Natural History Museum of Los Angeles County, Los Angeles, CA 90007, USA.ORCID 0000-0002-2089-4086
Gregg W C ThomasInformatics Group, Harvard University, Cambridge, MA, USA.
Sara J SmithInformatics Group, Harvard University, Cambridge, MA, USA.
Mara BaylisDepartment of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA.
Brian ArnoldDepartment of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA.
Russ Corbett-DetigDepartment of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA.
Erik EnbodyDepartment of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA.ORCID 0000-0003-1349-628X
Timothy B SacktonInformatics Group, Harvard University, Cambridge, MA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The increasing availability of genomic resequencing data sets and high-quality reference genomes across the tree of life present exciting opportunities for comparative population genomic studies. However, substantial challenges prevent the simple reuse of data across different studies and species, arising from variability in variant calling pipelines, data quality, and the need for computationally intensive reanalysis. Here, we present snpArcher, a flexible and highly efficient workflow designed for the analysis of genomic resequencing data in nonmodel organisms. snpArcher provides a standardized variant calling pipeline and includes modules for variant quality control, data visualization, variant filtering, and other downstream analyses. Implemented in Snakemake, snpArcher is user-friendly, reproducible, and designed to be compatible with high-performance computing clusters and cloud environments. To demonstrate the flexibility of this pipeline, we applied snpArcher to 26 public resequencing data sets from nonmammalian vertebrates. These variant data sets are hosted publicly to enable future comparative population genomic analyses. With its extensibility and the availability of public data sets, snpArcher will contribute to a broader understanding of genetic variation across species by facilitating the rapid use and reuse of large genomic data sets.

Indexed as

MetagenomicsSoftwareAnimalsGenomicsHigh-Throughput Nucleotide SequencingSequence Analysis, DNAWorkflowcomparative population genomicsconservation genomicsevolutionary genomicsgenomic workflow

Identifiers

PMID38069903
PMCPMC10764099

What OpenQuestion holds

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LicenceCC BY
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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.