Eleven grand challenges in single-cell data science

David Lähnemann, Johannes Köster, Mark D. Robinson, Catalina A. Vallejos, Kieran R. Campbell, Niko Beerenwinkel, Luca Pinello, Boudewijn P.F. Lelieveldt, Marcel Reinders, More Authors

Research output: Contribution to journalReview articleScientificpeer-review

10 Citations (Scopus)
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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.

Original languageEnglish
Article number31
Number of pages1
JournalGenome biology
Volume21
Issue number1
DOIs
Publication statusPublished - 7 Feb 2020

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    Lähnemann, D., Köster, J., Robinson, M. D., Vallejos, C. A., Campbell, K. R., Beerenwinkel, N., Pinello, L., Lelieveldt, B. P. F., Reinders, M., & More Authors (2020). Eleven grand challenges in single-cell data science. Genome biology, 21(1), [31]. https://doi.org/10.1186/s13059-020-1926-6