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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; Pinello, Luca; Skums, Pavel; Stamatakis, Alexandros; Attolini, Camille S.; Aparicio, Samuel, 1963-; Baaijens, Jasmijn; Balvert, Marleen; Barbanson, Buys d.; Cappuccio, Antonio; Corleone, Giacomo; Dutilh, Bas E.; Florescu, Maria; Guryev, Victor; Holmer, Rens; Jahn, Katharina; Lobo, Thamar J.; Keizer, Emma M.; Khatri, Indu; Kielbasa, Szymon M.; Korbel, Jan O.; Kozlov, Alexey M.; Kuo, Tzu-Hao; Lelieveldt, Boudewijn P.; Mandoiu, Ion I.; Marioni, John C.; Marschall, Tobias; Mölder, Felix; Niknejad, Amir; Raczkowski, Lukasz; Reinders, Marcel; Ridder, Jeroen d.; Saliba, Antoine-Emmanuel; Somarakis, Antonios; Stegle, Oliver; Theis, Fabian J.; Yang, Huan; Zelikovsky, Alex; McHardy, Alice C.; Raphael, Benjamin J.; Shah, Sohrab P.; Schönhuth, Alexander

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.

Item Metadata

Title
Eleven grand challenges in single-cell data science
Creator
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; Pinello, Luca; Skums, Pavel; Stamatakis, Alexandros; Attolini, Camille S.; Aparicio, Samuel, 1963-; Baaijens, Jasmijn; Balvert, Marleen; Barbanson, Buys d.; Cappuccio, Antonio; Corleone, Giacomo; Dutilh, Bas E.; Florescu, Maria; Guryev, Victor; Holmer, Rens; Jahn, Katharina; Lobo, Thamar J.; Keizer, Emma M.; Khatri, Indu; Kielbasa, Szymon M.; Korbel, Jan O.; Kozlov, Alexey M.; Kuo, Tzu-Hao; Lelieveldt, Boudewijn P.; Mandoiu, Ion I.; Marioni, John C.; Marschall, Tobias; Mölder, Felix; Niknejad, Amir; Raczkowski, Lukasz; Reinders, Marcel; Ridder, Jeroen d.; Saliba, Antoine-Emmanuel; Somarakis, Antonios; Stegle, Oliver; Theis, Fabian J.; Yang, Huan; Zelikovsky, Alex; McHardy, Alice C.; Raphael, Benjamin J.; Shah, Sohrab P.; Schönhuth, Alexander
Contributor
University of British Columbia. Data Science Institute
Publisher
BioMed Central
Date Issued
2020-02-07
Description
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.
Genre
Article
Type
Text
Language
eng
Date Available
2020-02-10
Provider
Vancouver : University of British Columbia Library
Rights
Attribution 4.0 International (CC BY 4.0)
DOI
10.14288/1.0388594
URI
http://hdl.handle.net/2429/73506
Affiliation
Medicine, Faculty of; Science, Faculty of; Other UBC; Non UBC; Pathology and Laboratory Medicine, Department of; Statistics, Department of
Citation
Genome Biology. 2020 Feb 07;21(1):31
Publisher DOI
10.1186/s13059-020-1926-6
Peer Review Status
Reviewed
Scholarly Level
Faculty
Copyright Holder
The Author(s)
Rights URI
http://creativecommons.org/licenses/by/4.0/
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Attribution 4.0 International (CC BY 4.0)