Evidence map›Paper›PMID 37846049›Full record

ArticleBioinformatics (Oxford, England)2023

PanKmer: k-mer-based and reference-free pangenome analysis.

Anthony J Aylward, Semar Petrus, Allen Mamerto, Nolan T Hartwick, Todd P Michael

Open access · goldAbstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
4.3field-weighted citation impact, top 5% of its field
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

24 citing papers in PubMed, 28 citations in OpenAlex.

  1. Article
  2. Review
  3. Approaches to Studying Viral Pangenome Variation Graphs.Genomics, proteomics & bioinformatics · 2026
    Review
  4. Persistent trade-offs balance competition and colonization across centuries.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Mem-based pangenome indexing for k-mer queries.Algorithms for molecular biology : AMB · 2025
    Article
  14. Can a plant biologist fix a thermostat?The New phytologist · 2025
    Review
  15. Article
  16. Review
  17. Article
  18. Jan and mini-Jan, a model system for potato functional genomics.bioRxiv : the preprint server for biology · 2024
    Article
  19. Early Detection of BothInternational journal of molecular sciences · 2024
    Article
  20. Article
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

5 authors at 1 institution in 1 country.

Anthony J AylwardThe Plant Molecular and Cellular Biology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, United States.ORCID 0000-0003-3524-856X
Semar PetrusThe Plant Molecular and Cellular Biology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, United States.
Allen MamertoThe Plant Molecular and Cellular Biology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, United States.ORCID 0009-0000-6061-4977
Nolan T HartwickThe Plant Molecular and Cellular Biology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, United States.ORCID 0000-0001-7916-7791
Todd P MichaelThe Plant Molecular and Cellular Biology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, United States.ORCID 0000-0001-6272-2875
Salk Institute for Biological Studies · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

summaryPangenomes are replacing single reference genomes as the definitive representation of DNA sequence within a species or clade. Pangenome analysis predominantly leverages graph-based methods that require computationally intensive multiple genome alignments, do not scale to highly complex eukaryotic genomes, limit their scope to identifying structural variants (SVs), or incur bias by relying on a reference genome. Here, we present PanKmer, a toolkit designed for reference-free analysis of pangenome datasets consisting of dozens to thousands of individual genomes. PanKmer decomposes a set of input genomes into a table of observed k-mers and their presence-absence values in each genome. These are stored in an efficient k-mer index data format that encodes SNPs, INDELs, and SVs. It also includes functions for downstream analysis of the k-mer index, such as calculating sequence similarity statistics between individuals at whole-genome or local scales. For example, k-mers can be "anchored" in any individual genome to quantify sequence variability or conservation at a specific locus. This facilitates workflows with various biological applications, e.g. identifying cases of hybridization between plant species. PanKmer provides researchers with a valuable and convenient means to explore the full scope of genetic variation in a population, without reference bias. AVAILABILITY AND IMPLEMENTATION: PanKmer is implemented as a Python package with components written in Rust, released under a BSD license. The source code is available from the Python Package Index (PyPI) at https://pypi.org/project/pankmer/ as well as Gitlab at https://gitlab.com/salk-tm/pankmer. Full documentation is available at https://salk-tm.gitlab.io/pankmer/.

Indexed as

GenomeSoftwareDocumentationEukaryotaHumansSequence Analysis, DNA

Identifiers

PMID37846049
PMCPMC10603592
OpenAlexW4387691790

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.