Evidence map›Paper›PMID 32972461›Full record

ArticleGenome biology2020

GraphAligner: rapid and versatile sequence-to-graph alignment.

Mikko Rautiainen, Tobias Marschall

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in Genome biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 136 papers.

0numbers the graph read from it
0cells of the map it votes in
136citing papers in PubMed
13.0field-weighted citation impact, top 1% 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

136 citing papers in PubMed, 270 citations in OpenAlex.

  1. Article
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  12. GBZ-base and GAF-base: Indexed pangenome file formats.bioRxiv : the preprint server for biology · 2026
    Article
  13. Article
  14. Article
  15. Review
  16. Approaches to Studying Viral Pangenome Variation Graphs.Genomics, proteomics & bioinformatics · 2026
    Review
  17. Lossless pangenome indexing using tag arrays.Algorithms for molecular biology : AMB · 2026
    Article
  18. Article
  19. Article
  20. Article

76 more citing papers are in PubMed but not listed here.

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

2 authors at 2 institutions in 1 country.

Mikko RautiainenCenter for Bioinformatics, Saarland University, Saarland Informatics Campus E2.1, Saarbrücken, 66123, Germany. m_rautiainen@hotmail.com.ORCID 0000-0003-2971-267X
Tobias MarschallHeinrich Heine University Düsseldorf, Medical Faculty, Institute for Medical Biometry and Bioinformatics, Moorenstraße 5, Düsseldorf, 40225, Germany. tobias.marschall@hhu.de.ORCID 0000-0002-9376-1030
Heinrich Heine University Düsseldorf · DEMax Planck Institute for Informatics · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genome graphs can represent genetic variation and sequence uncertainty. Aligning sequences to genome graphs is key to many applications, including error correction, genome assembly, and genotyping of variants in a pangenome graph. Yet, so far, this step is often prohibitively slow. We present GraphAligner, a tool for aligning long reads to genome graphs. Compared to the state-of-the-art tools, GraphAligner is 13x faster and uses 3x less memory. When employing GraphAligner for error correction, we find it to be more than twice as accurate and over 12x faster than extant tools.Availability: Package manager: https://anaconda.org/bioconda/graphaligner and source code: https://github.com/maickrau/GraphAligner.

Indexed as

SoftwareAlgorithmsAnimalsGenomicsHumansSequence AlignmentError correctionGenome graphsLong readsPangenomeSequence alignment

Identifiers

PMID32972461
PMCPMC7513500
OpenAlexW3088400220

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.