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Eleven grand challenges in single-cell data science.
Lähnemann, David Köster, Johannes Szczurek, Ewa McCarthy, Davis J Hicks, Stephanie C Robinson, Mark D Vallejos, Catalina A Campbell, Kieran R Beerenwinkel, Niko Mahfouz, Ahmed
Lähnemann, David
Köster, Johannes
Szczurek, Ewa
McCarthy, Davis J
Hicks, Stephanie C
Robinson, Mark D
Vallejos, Catalina A
Campbell, Kieran R
Beerenwinkel, Niko
Mahfouz, Ahmed
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2020-02-07
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Abstract
The recent boom in microfluidics and combinatorial indexing strategies, combined with low sequencing costs, has empowered single-cell sequencing technology. Thousands-or even millions-of cells analyzed in a single experiment amount to a data revolution in single-cell biology and pose unique data science problems. Here, we outline eleven challenges that will be central to bringing this emerging field of single-cell data science forward. For each challenge, we highlight motivating research questions, review prior work, and formulate open problems. This compendium is for established researchers, newcomers, and students alike, highlighting interesting and rewarding problems for the coming years.
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Genome Biol. 2020 Feb 7;21(1):31. doi: 10.1186/s13059-020-1926-6.
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Article
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en
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1474-760X
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Attribution-NonCommercial-ShareAlike 4.0 International