Evidence map›Paper›PMID 41129325›Full record

ArticleGigaScience2025

GFFx: A Rust-based suite of utilities for ultra-fast genomic feature extraction.

Baohua Chen, Dongya Wu, Guojie Zhang

Abstract read
In one paragraph

Article in GigaScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
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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.

Baohua ChenSchool of Basic Medical Sciences, Zhejiang University School of Medicine, Hangzhou 310058, China.ORCID 0000-0002-3065-0739
Dongya WuSchool of Basic Medical Sciences, Zhejiang University School of Medicine, Hangzhou 310058, China.ORCID 0000-0003-1967-2264
Guojie ZhangSchool of Basic Medical Sciences, Zhejiang University School of Medicine, Hangzhou 310058, China.ORCID 0000-0001-6860-1521

Funding

National Key Research and Development of China 2025YFC3410300Young Scientists Fund of the National Natural Science Foundation of China 32300490
6 · The paper itself

Abstract

backgroundGenome annotations have become increasingly complex with the discovery of diverse regulatory elements and transcript variants, posing growing challenges for efficient data querying and storage. Existing tools often show performance bottlenecks when processing large-scale annotation files, especially for region-based searches and hierarchical feature extraction. Leveraging Rust's advantages in execution speed, memory safety, and multithreading offers a promising path toward scalable solutions for genome annotation access.

findingsWe present GFFx, a Rust-based toolkit for high-performance access to GFF annotation files. It employs a compact, model-aware indexing system and memory-mapped I/O to enable fast random access with minimal overhead. Benchmarks across multiple genomes show 10-80 times faster ID-based extraction, 20-60 times faster region retrieval, and 7-14 times faster coverage profiling than existing tools, while maintaining low memory use and small index size.

conclusionsGFFx offers a lightweight and scalable infrastructure for efficient genome annotation access and quantitative analysis. By combining Rust's performance and safety with an extensible design, it provides a robust foundation for large-scale and multi-omics workflows.

Indexed as

Computational BiologyGenomicsMolecular Sequence AnnotationSoftwarefeature extractiongenome annotationGFF fileRust programming

Identifiers

PMID41129325
PMCPMC12548526

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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.