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Cell-level metadata are indispensable for documenting single-cell sequencing datasets
Single-cell RNA sequencing (scRNA-seq) provides an unprecedented view of cellular diversity of biological systems. However, across the thousands of publications and datasets generated using this technology, we estimate that only a minority (<25%) of studies provide cell-level metadata information...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8121533/ https://www.ncbi.nlm.nih.gov/pubmed/33945522 http://dx.doi.org/10.1371/journal.pbio.3001077 |
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author | Puntambekar, Sidhant Hesselberth, Jay R. Riemondy, Kent A. Fu, Rui |
author_facet | Puntambekar, Sidhant Hesselberth, Jay R. Riemondy, Kent A. Fu, Rui |
author_sort | Puntambekar, Sidhant |
collection | PubMed |
description | Single-cell RNA sequencing (scRNA-seq) provides an unprecedented view of cellular diversity of biological systems. However, across the thousands of publications and datasets generated using this technology, we estimate that only a minority (<25%) of studies provide cell-level metadata information containing identified cell types and related findings of the published dataset. Metadata omission hinders reproduction, exploration, validation, and knowledge transfer and is a common problem across journals, data repositories, and publication dates. We encourage investigators, reviewers, journals, and data repositories to improve their standards and ensure proper documentation of these valuable datasets. |
format | Online Article Text |
id | pubmed-8121533 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-81215332021-05-25 Cell-level metadata are indispensable for documenting single-cell sequencing datasets Puntambekar, Sidhant Hesselberth, Jay R. Riemondy, Kent A. Fu, Rui PLoS Biol Essay Single-cell RNA sequencing (scRNA-seq) provides an unprecedented view of cellular diversity of biological systems. However, across the thousands of publications and datasets generated using this technology, we estimate that only a minority (<25%) of studies provide cell-level metadata information containing identified cell types and related findings of the published dataset. Metadata omission hinders reproduction, exploration, validation, and knowledge transfer and is a common problem across journals, data repositories, and publication dates. We encourage investigators, reviewers, journals, and data repositories to improve their standards and ensure proper documentation of these valuable datasets. Public Library of Science 2021-05-04 /pmc/articles/PMC8121533/ /pubmed/33945522 http://dx.doi.org/10.1371/journal.pbio.3001077 Text en © 2021 Puntambekar et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Essay Puntambekar, Sidhant Hesselberth, Jay R. Riemondy, Kent A. Fu, Rui Cell-level metadata are indispensable for documenting single-cell sequencing datasets |
title | Cell-level metadata are indispensable for documenting single-cell sequencing datasets |
title_full | Cell-level metadata are indispensable for documenting single-cell sequencing datasets |
title_fullStr | Cell-level metadata are indispensable for documenting single-cell sequencing datasets |
title_full_unstemmed | Cell-level metadata are indispensable for documenting single-cell sequencing datasets |
title_short | Cell-level metadata are indispensable for documenting single-cell sequencing datasets |
title_sort | cell-level metadata are indispensable for documenting single-cell sequencing datasets |
topic | Essay |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8121533/ https://www.ncbi.nlm.nih.gov/pubmed/33945522 http://dx.doi.org/10.1371/journal.pbio.3001077 |
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