Evidence map›Paper›PMID 38898394›Full record

ArticleBMC bioinformatics2024

PxBLAT: an efficient python binding library for BLAT.

Yangyang Li, Rendong Yang

Abstract read
In one paragraph

Article in BMC bioinformatics, 2024. 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

5 · Who and what money

Authors and funding

2 authors.

Yangyang LiDepartment of Urology, Northwestern University Feinberg School of Medicine, 303 E Superior St, Chicago, IL, 60611, USA.
Rendong YangDepartment of Urology, Northwestern University Feinberg School of Medicine, 303 E Superior St, Chicago, IL, 60611, USA. rendong.yang@northwestern.edu.

Funding

Computational approaches to delineate non-canonical splicing eventsR35GM142441 · NIGMS · UNIVERSITY OF MINNESOTA · PI YANG, RENDONG · 2021 to 2025
$2.0M
NIGMS NIH HHS R35 GM142441US National Institute of General Medical Sciences R35GM142441
6 · The paper itself

Abstract

backgroundWith the surge in genomic data driven by advancements in sequencing technologies, the demand for efficient bioinformatics tools for sequence analysis has become paramount. BLAST-like alignment tool (BLAT), a sequence alignment tool, faces limitations in performance efficiency and integration with modern programming environments, particularly Python. This study introduces PxBLAT, a Python-based framework designed to enhance the capabilities of BLAT, focusing on usability, computational efficiency, and seamless integration within the Python ecosystem.

resultsPxBLAT demonstrates significant improvements over BLAT in execution speed and data handling, as evidenced by comprehensive benchmarks conducted across various sample groups ranging from 50 to 600 samples. These experiments highlight a notable speedup, reducing execution time compared to BLAT. The framework also introduces user-friendly features such as improved server management, data conversion utilities, and shell completion, enhancing the overall user experience. Additionally, the provision of extensive documentation and comprehensive testing supports community engagement and facilitates the adoption of PxBLAT.

conclusionsPxBLAT stands out as a robust alternative to BLAT, offering performance and user interaction enhancements. Its development underscores the potential for modern programming languages to improve bioinformatics tools, aligning with the needs of contemporary genomic research. By providing a more efficient, user-friendly tool, PxBLAT has the potential to impact genomic data analysis workflows, supporting faster and more accurate sequence analysis in a Python environment.

Indexed as

Computational BiologySequence AlignmentSoftwareGenomicsProgramming LanguagesBLATSequence analysisSoftware libraries

Identifiers

PMID38898394
PMCPMC11549839

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.