Evidence map›Paper›PMID 41987571›Full record

ArticleBioinformatics (Oxford, England)2026

QCatch: a framework for quality control assessment and analysis of single-cell sequencing data.

Yuan Gao, Dongze He, Rob Patro

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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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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

5 · Who and what money

Authors and funding

3 authors.

Yuan GaoCenter for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, United States.ORCID 0009-0001-7517-588X
Dongze HeSan Diego Institute of Technology, Altos Labs, San Diego, CA 92108, United States.ORCID 0000-0001-8259-7434
Rob PatroCenter for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, United States.ORCID 0000-0001-8463-1675

Funding

A Modular Framework for Accurate, Interpretable, and Reproducible Analysis of Long Read RNA-Seq DataR01HG009937 · NHGRI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Michael Isaiah Love, Robert Patro · 2018 to 2026
$2.8M
Chan Zuckerberg Initiative DAFNHGRI NIH HHS R01 HG009937NIH HHS DAF2022-252586NIH HHS DAF2024-342821NIH HHS R01HG009937
6 · The paper itself

Abstract

motivationSingle-cell sequencing data analysis requires robust quality control (QC) to mitigate technical artifacts and ensure reliable downstream results. While tools like alevin-fry and simpleaf (and augmented execution context for the alevin-fry), offer flexibility and computational efficiency to process single-cell data, this ecosystem will further benefit from a standardized QC reporting tailored for its outputs.

resultsWe introduce QCatch, a Python-based command-line tool that generates comprehensive and interactive HTML QC reports designed specifically for single-cell quantification results. Taking the output directory of alevin-fry or simpleaf as the input, QCatch is able to perform essential processing steps, like cell calling, and generate detailed QC reports that contain informative visualizations and statistics, including unique molecular identifier (UMI) count distributions, sequencing saturation estimates, and splicing status information, for QC assurance. Built for seamless integration into downstream analysis workflows, QCatch exports the processed results in a richly-annotated H5AD format file, a widely used data format common among many downstream single-cell data analysis tools. AVAILABILITY AND IMPLEMENTATION: The source code and documentation of QCatch are available on GitHub at https://github.com/COMBINE-lab/QCatch. QCatch can be installed via both Bioconda and PyPI.

Indexed as

Computational BiologyHigh-Throughput Nucleotide SequencingSingle-Cell AnalysisSoftwareQuality Control

Identifiers

PMID41987571
PMCPMC13171171

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.