Evidence map›Paper›PMID 41924242›Full record

ArticleBio-protocol2026

A Bioinformatics Workflow to Identify eccDNA Using ECCFP From Long-Read Nanopore Sequencing Data.

Wang Li, Biyuan Miao, Shaogui Wan

Abstract read
In one paragraph

Article in Bio-protocol, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Wang LiInstitute of Genomics and Precision Medicine, School of Medical Technology, Gannan Medical University, Ganzhou, China.
Biyuan MiaoInstitute of Genomics and Precision Medicine, School of Medical Technology, Gannan Medical University, Ganzhou, China.
Shaogui WanInstitute of Genomics and Precision Medicine, School of Medical Technology, Gannan Medical University, Ganzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Extrachromosomal circular DNA (eccDNA) is a type of circular DNA that exists independently of chromosomes and has garnered significant attention in various fields, particularly in the context of smaller eccDNAs, which have considerable roles in gene regulation through various mechanisms. Current methods such as Circle-Seq and 3SEP can enrich small eccDNAs during sample preparation, but most bioinformatics pipelines remain challenging, exhibiting low accuracy and efficiency. This protocol describes the detailed workflow of a newly developed bioinformatics analysis pipeline, named EccDNA Caller based on Consecutive Full Pass (ECCFP), to accurately identify eccDNA from long-read Nanopore sequencing data. Compared to other pipelines, ECCFP significantly improves detection sensitivity, accuracy, and runtime efficiency. The process includes raw data quality control, trimming of adapters and barcodes, alignment to a reference genome, and identification of eccDNA, with detailed results encompassing accurate positioning of eccDNA, consensus sequences, and variants of individual eccDNA. Key features • This protocol provides a beginner-friendly, step-by-step workflow that enables researchers without bioinformatics experience to successfully execute the entire eccDNA identification process. • It offers an efficient computational pipeline for eccDNA detection from Nanopore sequencing data, integrating quality control, trimming, alignment, and eccDNA identification. • ECCFP exhibits sensitivity, accuracy, high efficiency, and low false-positive rates compared to existing long-read-based tools.

Indexed as

BioinformaticsECCFPExtrachromosomal circular DNANanopore sequencingRolling circle amplification (RCA)

Identifiers

PMID41924242
PMCPMC13037781

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Registered trials

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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.