Eleven grand challenges in single-cell data science
all co-authors
(2020) Genome Biology, volume 21, issue 1, pp. 1 - 35
(Article)
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
... read more
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.
show less
Download/Full Text
Keywords: Animals, Data Science/methods, Genomics/methods, Humans, RNA-Seq/methods, Single-Cell Analysis/methods, Genetics, Ecology, Evolution, Behavior and Systematics, Cell Biology, Review, Research Support, Non-U.S. Gov't, Research Support, U.S. Gov't, Non-P.H.S., Journal Article, Research Support, N.I.H., Extramural
ISSN: 1465-6906
Publisher: BioMed Central
Note: Funding Information: AC was supported by an IAS Fellowship for external researchers at the University of Amsterdam. ACM was supported by the Helmholtz Incubator (Sparse2Big ZT-I-0007). AMK and ASt were supported by the Klaus Tschira Foundation. AZ was supported by the National Science Foundation (NSF: DBI-1564899, CCF-1619110) and the National Institutes of Health (NIH: 1R01EB025022-01). BdB was supported by the Oncode Institute (220-H72009 – KWF/2016-1/10158). BED was supported by the Netherlands Organisation for Scientific Research (NWO: Vidi grant 864.14.004). BJR was supported by the NSF (CCF-1053753), the NIH (R01HG007069), and the Chan Zuckerberg Initiative (CZI) Donor-Advised Fund (DAF) (2018-182608), an advised fund of the Silicon Valley Community Foundation. CAV was supported by the University of Edinburgh (Chancellor’s Fellowship) and by The Alan Turing Institute (EPSRC grant EP/N510129/1). DJM was supported by the National Health and Medical Research Council of Australia (GNT1112681 and GNT1162829). DL was supported by the Katharina Hardt Stiftung and the Deutsche Krebshilfe (national Network Genomic Medicine Lung Cancer, nNGM). FJT was supported by the German Research Foundation (DFG: Collaborative Research Centre 1243, Subproject A17), the Helmholtz Incubator (Sparse2big ZT-I-0007), the BMBF (01IS18036A, 01IS18053A, and 01ZX1711A), and the CZI DAF (182835). GC was supported by Marie Sklodowska-Curie grant (agreement no. 642691, Epipredict). IIM was supported by the NSF (award 1564936). JCM was supported by core funding from the European Molecular Biology Laboratory (EMBL) and core support from Cancer Research UK (CRUK: C9545/A29580). JdR was supported by the NWO (Vidi grant 639.072.715). JK was supported by the NWO (Veni grant 016.173.076). JOK was supported by core funding from the EMBL. KJ was supported by SystemsX.ch (RTD Grant 2013/150). KRC was funded by postdoctoral fellowships from the Canadian Institutes of Health Research (CIHR), the Canadian Statistical Sciences Institute (CANSSI), and the UBC Data Science Institute. LP was supported by the NIH – National Human Genome Research Institute (NHGRI) Career Development Award (R00HG008399), the Genomic Innovator Award (R35HG010717), and the CZI DAF (2018-182734). MB was supported by the NWO (Vidi grant 639.072.309 and Vidi grant 864.14.004). MDR was supported by the Swiss National Science Foundation (310030 175841, CRSII5 177208) and the CZI DAF (2018-182828) and acknowledges support from the University Research Priority Program Evolution in Action at the University of Zurich. NB was supported by the ERC (Synergy Grant 609883). OS was supported by core funding from the EMBL. PS was supported by the NIH (1R01EB025022). SA was supported by BC Cancer Foundation, CIHR, Canadian Cancer Society (CCS) Research Institute (CCSRI), Terry Fox Research Institute (TFRI), and CRUK. SCH was supported by the NIH – NHGRI (R00HG009007) and by the CZI DAF (182891, 193161, 356-01). SPS was supported by a Susan G. Komen scholar award, the Nicholls Biondi Endowed Chair in Computational Oncology, Cycle for Survival Benefitting Memorial Sloan Kettering Cancer Center, the TFRI, and the CCS. THK was supported by the Award of a Research Fellowships for the Promotion of Scientific Cooperation at the Helmholtz-Centre for Infection Research. Publisher Copyright: © 2020 The Author(s). Copyright: Copyright 2020 Elsevier B.V., All rights reserved.
(Peer reviewed)
