841835
doi
10.5281/zenodo.841835
oai:zenodo.org:841835
Louise E. Heinrich
UCSF
John D. Gordan
UCSF
Jayant Avva
UTSW
Kathy M. Bonness
UTSW
Agnieszka K. Witkiewicz
University of Arizona, Tuscon
James S. Malter
UTSW
Chloe E. Atreya
UCSF
Robert S. Warren
UCSF
Lani F. Wu
UCSF
Steven J. Altschuler
UCSF
Sampling strategies to capture single-cell heterogeneity
Satwik Rajaram
UCSF
doi:10.1038/nmeth.4427
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Sampling
Cellular Heterogeneity
Microscopy
<p><strong>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 the sampling depth required for prospective investigations of single-cell heterogeneity from an existing collection of samples. </strong></p>
<p>This dataset contains the tissue image data needed to reproduce Fig.1. </p>
This is supplementary data associated with the paper "Sampling strategies to capture single-cell heterogeneity" to appear in Nature Methods on Sep 4th 2017.
Zenodo
2017-09-04
info:eu-repo/semantics/article
841834
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md5:fdd788ff1b17851555227e3a1353c0b3
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70281
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https://zenodo.org/records/841835/files/Papadeno_L34_MS1_Tumor3_DAPI.tif
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https://zenodo.org/records/841835/files/Papadeno_L34_MS1_Tumor3_Alexa Fluor 568.tif
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md5:ba64f648d7c7830411579cd6806fdd60
https://zenodo.org/records/841835/files/Papadeno_L34_MS1_Tumor3_2Channel.afi
public
10.1038/nmeth.4427
Is cited by
doi
10.5281/zenodo.841834
isVersionOf
doi
Nature Methods
2017-09-04