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Eleven grand challenges in single-cell data science.

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.

SUBMITTER: Lahnemann D 

PROVIDER: S-EPMC7007675 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Eleven grand challenges in single-cell data science.

Lähnemann David D   Köster Johannes J   Szczurek Ewa E   McCarthy Davis J DJ   Hicks Stephanie C SC   Robinson Mark D MD   Vallejos Catalina A CA   Campbell Kieran R KR   Beerenwinkel Niko N   Mahfouz Ahmed A   Pinello Luca L   Skums Pavel P   Stamatakis Alexandros A   Attolini Camille Stephan-Otto CS   Aparicio Samuel S   Baaijens Jasmijn J   Balvert Marleen M   Barbanson Buys de B   Cappuccio Antonio A   Corleone Giacomo G   Dutilh Bas E BE   Florescu Maria M   Guryev Victor V   Holmer Rens R   Jahn Katharina K   Lobo Thamar Jessurun TJ   Keizer Emma M EM   Khatri Indu I   Kielbasa Szymon M SM   Korbel Jan O JO   Kozlov Alexey M AM   Kuo Tzu-Hao TH   Lelieveldt Boudewijn P F BPF   Mandoiu Ion I II   Marioni John C JC   Marschall Tobias T   Mölder Felix F   Niknejad Amir A   Rączkowska Alicja A   Reinders Marcel M   Ridder Jeroen de J   Saliba Antoine-Emmanuel AE   Somarakis Antonios A   Stegle Oliver O   Theis Fabian J FJ   Yang Huan H   Zelikovsky Alex A   McHardy Alice C AC   Raphael Benjamin J BJ   Shah Sohrab P SP   Schönhuth Alexander A  

Genome biology 20200207 1

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 questio  ...[more]

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