Laehnemann D, Koester J, Szczurek E, Mccarthy DJ, Hicks SC, Robinson MD, Vallejos CA, Campbell KR, Beerenwinkel N, Mahfouz A, Pinello L, Skums P, Stamatakis A, Attolini CSO, Aparicio S, Baaijens J, Balvert M, De Barbanson B, Cappuccio A, Corleone G, Dutilh BE, Florescu M, Guryev V, Holmer R, Jahn K, Lobo TJ, Keizer EM, Khatri I, Kielbasa SM, Korbel JO, Kozlov AM, Kuo TH, Lelieveldt BPF, Mandoiu II, Marioni JC, Marschall T, Moelder F, Niknejad A, Raczkowski L, Reinders M, De Ridder J, Saliba AE, Somarakis A, Stegle O, Theis FJ, Yang H, Zelikovsky A, Mchardy AC, Raphael BJ, Shah SP, Schonhuth A (2020)
Publication Type: Journal article, Review article
Publication year: 2020
Book Volume: 21
Article Number: 31
Journal Issue: 1
DOI: 10.1186/s13059-020-1926-6
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.
APA:
Laehnemann, D., Koester, J., Szczurek, E., Mccarthy, D.J., Hicks, S.C., Robinson, M.D.,... Schonhuth, A. (2020). Eleven grand challenges in single-cell data science. Genome Biology, 21(1). https://doi.org/10.1186/s13059-020-1926-6
MLA:
Laehnemann, David, et al. "Eleven grand challenges in single-cell data science." Genome Biology 21.1 (2020).
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