Evidence map›Paper›PMID 39941033›Full record

ArticleInternational journal of molecular sciences2025

Evaluating the Performance of Peak Calling Algorithms Available for Intracellular G-Quadruplex Sequencing.

Yuqi Wang, Ke Xiao, Tiantong Tao, Rongxin Zhang, Huiling Shu, Xiao Sun

Abstract read
In one paragraph

Article in International journal of molecular sciences, 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

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

6 authors.

Yuqi WangState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, China.ORCID 0000-0003-1200-3885
Ke XiaoState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, China.ORCID 0000-0002-0169-4185
Tiantong TaoState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, China.
Rongxin ZhangState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, China.
Huiling ShuState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, China.
Xiao SunState Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 211189, China.ORCID 0000-0003-1048-7775

Funding

Fundamental Research Funds for the Central Universities of China No. 2242023K5005Leading Technology Program of Jiangsu Province BK20222008National Natural Science Foundation of China No. 62472084 and 62002060
6 · The paper itself

Abstract

DNA G-quadruplexes (G4) are non-canonical DNA structures that play key roles in various biological processes. Antibody-dependent sequencing is an important tool for identifying intracellularly formed DNA G4s, and peak calling is a crucial step in processing the sequencing data. As the applicability of existing peak calling algorithms to intracellular G4 data has not been previously assessed, we systematically compared and evaluated these algorithms to determine those best suited for G4 detection. We selected seven representative candidates from 43 published peak calling algorithms for detailed evaluation. The performance of each candidate on six published intracellular G4 sequencing datasets (GSE107690, GSE145090, GSE133379, GSE178668ChIP-seq, GSE178668CUT&Tag, GSE221437) were assessed by precision and recall against customized benchmarks integrating results from multiple algorithms, as well as consistency with known G4 information (pG4 predicted by pqsfinder, oG4 from GSE63874, and multi-cell-line conserved G4s) and epigenetic signals. We identified MACS2, PeakRanger, and GoPeaks as the most effective algorithms for analyzing intracellular G4 sequencing data, and attributed their superior performance partially to the distribution model of sequencing reads/fragments used in the hypothesis testing step of the peak calling procedures. These findings provide guidance and rationale for selecting peak callers appropriate for intracellular G4 data.

Indexed as

AlgorithmsDNAG-QuadruplexesSequence Analysis, DNAHigh-Throughput Nucleotide SequencingHumansDNAG-quadruplex (G4)peak calling algorithmsperformance comparison

Identifiers

PMID39941033
PMCPMC11818603

What OpenQuestion holds

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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.