Evidence map›Paper›PMID 38641647›Full record

ArticleGenome biology2024

Measuring, visualizing, and diagnosing reference bias with biastools.

Mao-Jan Lin, Sheila Iyer, Nae-Chyun Chen, Ben Langmead

Abstract read
In one paragraph

Article in Genome biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
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  4. Movi 2: fast and space-efficient queries on pangenomes.Bioinformatics (Oxford, England) · 2026
    Article
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  6. Article
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  10. Review
  11. The complete genome of the KOLF2.1J reference iPSC line.bioRxiv : the preprint server for biology · 2026
    Article
  12. Polymorphic 3D genome architecture mediated by transposable elements.bioRxiv : the preprint server for biology · 2026
    Article
  13. Article
  14. Article
  15. Movi 2: Fast and Space-Efficient Queries on Pangenomes.bioRxiv : the preprint server for biology · 2025
    Article
  16. Article
  17. Article
  18. Article
  19. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Mao-Jan LinDepartment of Computer Science, Johns Hopkins University, Baltimore, USA. mlin77@jhu.edu.
Sheila IyerDepartment of Computer Science, Johns Hopkins University, Baltimore, USA.
Nae-Chyun ChenDepartment of Computer Science, Johns Hopkins University, Baltimore, USA.
Ben LangmeadDepartment of Computer Science, Johns Hopkins University, Baltimore, USA. langmea@cs.jhu.edu.ORCID 0000-0003-2437-1976

Funding

Personal and panel references for improved alignmentR01HG011392 · NHGRI · JOHNS HOPKINS UNIVERSITY · PI LANGMEAD, BENJAMIN THOMAS · 2020 to 2025
$4.2M
NHGRI NIH HHS R01 HG011392NHGRI NIH HHS R01HG011392
6 · The paper itself

Abstract

Many bioinformatics methods seek to reduce reference bias, but no methods exist to comprehensively measure it. Biastools analyzes and categorizes instances of reference bias. It works in various scenarios: when the donor's variants are known and reads are simulated; when donor variants are known and reads are real; and when variants are unknown and reads are real. Using biastools, we observe that more inclusive graph genomes result in fewer biased sites. We find that end-to-end alignment reduces bias at indels relative to local aligners. Finally, we use biastools to characterize how T2T references improve large-scale bias.

Indexed as

GenomeGenomicsBiasComputational BiologyHigh-Throughput Nucleotide SequencingINDEL MutationSequence Analysis, DNASoftwarePangenomicsReference biasSequence alignment

Identifiers

PMID38641647
PMCPMC11027314

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.