Evidence map›Paper›PMID 41659213›Full record

ArticlePNAS nexus2026

Fast barcode calling based on

Riko Corwin Uphoff, Steffen Schüler, Ivo Grosse, Matthias Müller-Hannemann

Abstract read
In one paragraph

Article in PNAS nexus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Riko Corwin UphoffInstitute of Computer Science, Martin Luther University Halle-Wittenberg, Von-Seckendorff-Platz 1, D 06099 Halle, Germany.ORCID https://orcid.org/0009-0007-3886-089X
Steffen SchülerInstitute of Computer Science, Martin Luther University Halle-Wittenberg, Von-Seckendorff-Platz 1, D 06099 Halle, Germany.ORCID https://orcid.org/0000-0003-3445-8645
Ivo GrosseInstitute of Computer Science, Martin Luther University Halle-Wittenberg, Von-Seckendorff-Platz 1, D 06099 Halle, Germany.ORCID https://orcid.org/0000-0001-5318-4825
Matthias Müller-HannemannInstitute of Computer Science, Martin Luther University Halle-Wittenberg, Von-Seckendorff-Platz 1, D 06099 Halle, Germany.ORCID https://orcid.org/0000-0001-6976-0006

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

DNA barcodes, which are short DNA strings, are regularly used as tags in pooled sequencing experiments to enable the identification of reads originating from the same sample. A crucial task in the subsequent analysis of pooled sequences is barcode calling, where one must identify the corresponding barcode for each read. This task is computationally challenging when the probability of synthesis and sequencing errors is high, like in photolithographic microarray synthesis. Identifying the most similar barcode for each read is a theoretically attractive solution for barcode calling. However, an all-to-all exact similarity calculation is practically infeasible for applications with millions of barcodes and billions of reads. Hence, several computational approaches for barcode calling have been proposed, but the challenge of developing an efficient and precise computational approach remains. Here, we propose a simple, yet highly effective new barcode calling approach that uses a filtering technique based on precomputed

Indexed as

algorithm engineeringDNA barcode callingk-mer filteringSequence Levenshtein distancespatial transcriptomics

Identifiers

PMID41659213
PMCPMC12880182

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.