Sampling to capture single-cell heterogeneity

Advances in single-cell technologies have highlighted the prevalence and biological significance of cellular heterogeneity. A critical question is how to design experiments that faithfully capture the true range of heterogeneity from samples of cellular populations. Here, we develop a data-driven ap...

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Detalles Bibliográficos
Autores principales: Rajaram, Satwik, Heinrich, Louise E., Gordan, John D., Avva, Jayant, Bonness, Kathy M., Witkiewicz, Agnieszka K., Malter, James S., Atreya, Chloe E., Warren, Robert S., Wu, Lani F., Altschuler, Steven J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5658002/
https://www.ncbi.nlm.nih.gov/pubmed/28869755
http://dx.doi.org/10.1038/nmeth.4427
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author Rajaram, Satwik
Heinrich, Louise E.
Gordan, John D.
Avva, Jayant
Bonness, Kathy M.
Witkiewicz, Agnieszka K.
Malter, James S.
Atreya, Chloe E.
Warren, Robert S.
Wu, Lani F.
Altschuler, Steven J.
author_facet Rajaram, Satwik
Heinrich, Louise E.
Gordan, John D.
Avva, Jayant
Bonness, Kathy M.
Witkiewicz, Agnieszka K.
Malter, James S.
Atreya, Chloe E.
Warren, Robert S.
Wu, Lani F.
Altschuler, Steven J.
author_sort Rajaram, Satwik
collection PubMed
description Advances in single-cell technologies have highlighted the prevalence and biological significance of cellular heterogeneity. A critical question is how to design experiments that faithfully capture the true range of heterogeneity from samples of cellular populations. Here, we develop a data-driven approach, illustrated in the context of image data, that estimates sampling depth required for prospective investigations of single-cell heterogeneity from an existing collection of samples.
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spelling pubmed-56580022018-03-04 Sampling to capture single-cell heterogeneity Rajaram, Satwik Heinrich, Louise E. Gordan, John D. Avva, Jayant Bonness, Kathy M. Witkiewicz, Agnieszka K. Malter, James S. Atreya, Chloe E. Warren, Robert S. Wu, Lani F. Altschuler, Steven J. Nat Methods Article Advances in single-cell technologies have highlighted the prevalence and biological significance of cellular heterogeneity. A critical question is how to design experiments that faithfully capture the true range of heterogeneity from samples of cellular populations. Here, we develop a data-driven approach, illustrated in the context of image data, that estimates sampling depth required for prospective investigations of single-cell heterogeneity from an existing collection of samples. 2017-09-04 2017-10 /pmc/articles/PMC5658002/ /pubmed/28869755 http://dx.doi.org/10.1038/nmeth.4427 Text en Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
Rajaram, Satwik
Heinrich, Louise E.
Gordan, John D.
Avva, Jayant
Bonness, Kathy M.
Witkiewicz, Agnieszka K.
Malter, James S.
Atreya, Chloe E.
Warren, Robert S.
Wu, Lani F.
Altschuler, Steven J.
Sampling to capture single-cell heterogeneity
title Sampling to capture single-cell heterogeneity
title_full Sampling to capture single-cell heterogeneity
title_fullStr Sampling to capture single-cell heterogeneity
title_full_unstemmed Sampling to capture single-cell heterogeneity
title_short Sampling to capture single-cell heterogeneity
title_sort sampling to capture single-cell heterogeneity
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5658002/
https://www.ncbi.nlm.nih.gov/pubmed/28869755
http://dx.doi.org/10.1038/nmeth.4427
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