Evidence map›Paper›PMID 40802540›Full record

ArticleBioinformatics (Oxford, England)2025

NanoFilter: enhancing phasing performance by utilizing highly consistent INDELs and SNVs in nanopore sequencing.

Shanming Chen, Fan Nie, Jianxin Wang

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2025. 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

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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

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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

3 authors.

Shanming ChenSchool of Computer Science and Engineering, Central South University, Changsha 410083, China.
Fan NieSchool of Computer Science and Engineering, Central South University, Changsha 410083, China.
Jianxin WangSchool of Computer Science and Engineering, Central South University, Changsha 410083, China.ORCID 0000-0003-1516-0480

Funding

National Natural Science Foundation of China 62332020National Natural Science Foundation of China 62350004
6 · The paper itself

Abstract

motivationNanopore sequencing data offer longer reads compared to other technologies, which is beneficial for phasing and genome assembly. INDELs provide valuable haplotype information and have significant potential to improve phasing performance. However, accurately identifying INDELs with variant callers is challenging, and incorporating INDELs into phasing remains a complex task. To address these issues, we developed NanoFilter, a novel filtering strategy designed to filter out INDELs that contain wrong phasing information based on their consistency.

resultsOur assessment using Nanopore R10 simplex data shows that filtering out low-consistency INDELs increases their precision from 88.3% to 98.8%, nearly matching the precision of SNVs. In the phasing results of Margin, incorporating these filtered INDELs leads to a 12.77% increase in N50 length and fewer switch errors. Furthermore, we found that SNVs filtered by NanoFilter will enhance assembly performance. When NanoFilter is integrated into the HapDup assembly pipeline, NanoFilter reduces the Hamming error rate and increases N50 length by 7.8%. AVAILABILITY AND IMPLEMENTATION: NanoFilter is available at https://github.com/Chenshanming-repo/NanoFilter (DOI: 10.5281/zenodo.16777826) and HapDup-NanoFilter is available at https://github.com/Chenshanming-repo/HapDup-NanoFilter (DOI: 10.5281/zenodo.16777890).

Indexed as

INDEL MutationNanopore SequencingPolymorphism, Single NucleotideSequence Analysis, DNASoftwareAlgorithmsHumansNanopores

Identifiers

PMID40802540
PMCPMC12448842

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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.