{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T04:10:42Z","timestamp":1779336642174,"version":"3.51.4"},"reference-count":14,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T00:00:00Z","timestamp":1776297600000},"content-version":"vor","delay-in-days":1,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"NIH","doi-asserted-by":"publisher","award":["R01HG009937"],"award-info":[{"award-number":["R01HG009937"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"NIH","doi-asserted-by":"publisher","award":["DAF2024-342821"],"award-info":[{"award-number":["DAF2024-342821"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"NIH","doi-asserted-by":"publisher","award":["DAF2022-252586"],"award-info":[{"award-number":["DAF2022-252586"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Chan Zuckerberg Initiative DAF"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,5,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Single-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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We 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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btag184","type":"journal-article","created":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T11:44:28Z","timestamp":1776253468000},"source":"Crossref","is-referenced-by-count":0,"title":["QCatch: a framework for quality control assessment and analysis of single-cell sequencing data"],"prefix":"10.1093","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-7517-588X","authenticated-orcid":false,"given":"Yuan","family":"Gao","sequence":"first","affiliation":[{"name":"Center for Bioinformatics and Computational Biology, University of Maryland , College Park, MD 20742,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8259-7434","authenticated-orcid":false,"given":"Dongze","family":"He","sequence":"additional","affiliation":[{"name":"San Diego Institute of Technology, Altos Labs , San Diego, CA 92108,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8463-1675","authenticated-orcid":false,"given":"Rob","family":"Patro","sequence":"additional","affiliation":[{"name":"Center for Bioinformatics and Computational Biology, University of Maryland , College Park, MD 20742,","place":["United States"]},{"name":"Department of Computer Science, University of Maryland , College Park, MD 20742,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2026,4,15]]},"reference":[{"key":"2026052023573561400_btag184-B1","doi-asserted-by":"publisher","first-page":"475","DOI":"10.1038\/s41592-018-0046-7","article-title":"Bioconda: sustainable and comprehensive software distribution for the life sciences","volume":"15","author":"Gr\u00fcning","year":"2018","journal-title":"Nat 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