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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...

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Detalles Bibliográficos
Autores principales: Puntambekar, Sidhant, Hesselberth, Jay R., Riemondy, Kent A., Fu, Rui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
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.
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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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