Eleven grand challenges in single-cell data science

David Lähnemann; Johannes Köster; Ewa Szczurek; Davis J. McCarthy; Stephanie C. Hicks; Mark D. Robinson; Catalina A. Vallejos; Kieran R. Campbell; Niko Beerenwinkel; Ahmed Mahfouz; Luca Pinello; Pavel Skums; Alexandros Stamatakis; Camille Stephan Otto Attolini; Samuel Aparicio; Jasmijn Baaijens; Marleen Balvert; Buys de Barbanson; Antonio Cappuccio; Giacomo Corleone; Bas E. Dutilh; Maria Florescu; Victor Guryev; Rens Holmer; Katharina Jahn; Thamar Jessurun Lobo; Emma M. Keizer; Indu Khatri; Szymon M. Kielbasa; Jan O. Korbel; Alexey M. Kozlov; Tzu Hao Kuo; Boudewijn P.F. Lelieveldt; Ion I. Mandoiu; John C. Marioni; Tobias Marschall; Felix Mölder; Amir Niknejad; Lukasz Raczkowski; Marcel Reinders; Jeroen de Ridder; Antoine Emmanuel Saliba; Antonios Somarakis; Oliver Stegle; Fabian J. Theis; Huan Yang; Alex Zelikovsky; Alice C. McHardy; Benjamin J. Raphael; Sohrab P. Shah; Alexander Schönhuth

doi:10.1186/s13059-020-1926-6

Eleven grand challenges in single-cell data science

David Lähnemann, Johannes Köster, Ewa Szczurek, Davis J. McCarthy, Stephanie C. Hicks, Mark D. Robinson, Catalina A. Vallejos, Kieran R. Campbell, Niko Beerenwinkel, Ahmed Mahfouz, Luca Pinello, Pavel Skums, Alexandros Stamatakis, Camille Stephan Otto Attolini, Samuel Aparicio, Jasmijn Baaijens, Marleen Balvert, Buys de Barbanson, Antonio Cappuccio, Giacomo CorleoneBas E. Dutilh, Maria Florescu, Victor Guryev, Rens Holmer, Katharina Jahn, Thamar Jessurun Lobo, Emma M. Keizer, Indu Khatri, Szymon M. Kielbasa, Jan O. Korbel, Alexey M. Kozlov, Tzu Hao Kuo, Boudewijn P.F. Lelieveldt, Ion I. Mandoiu, John C. Marioni, Tobias Marschall, Felix Mölder, Amir Niknejad, Lukasz Raczkowski, Marcel Reinders, Jeroen de Ridder, Antoine Emmanuel Saliba, Antonios Somarakis, Oliver Stegle, Fabian J. Theis, Huan Yang, Alex Zelikovsky, Alice C. McHardy, Benjamin J. Raphael, Sohrab P. Shah, Alexander Schönhuth

Research output: Contribution to journal › Review article › peer-review

342 Scopus citations

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 language	English (US)
Article number	31
Journal	Genome biology
Volume	21
Issue number	1
DOIs	https://doi.org/10.1186/s13059-020-1926-6
State	Published - Feb 7 2020

All Science Journal Classification (ASJC) codes

Ecology, Evolution, Behavior and Systematics
Genetics
Cell Biology

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10.1186/s13059-020-1926-6

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Lähnemann, D., Köster, J., Szczurek, E., McCarthy, D. J., Hicks, S. C., Robinson, M. D., Vallejos, C. A., Campbell, K. R., Beerenwinkel, N., Mahfouz, A., Pinello, L., Skums, P., Stamatakis, A., Attolini, C. S. O., Aparicio, S., Baaijens, J., Balvert, M., Barbanson, B. D., Cappuccio, A., ... Schönhuth, A. (2020). Eleven grand challenges in single-cell data science. Genome biology, 21(1), [31]. https://doi.org/10.1186/s13059-020-1926-6

@article{3b9017b168fa4ad69d34a1f439f323a4,

title = "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.",

author = "David L{\"a}hnemann and Johannes K{\"o}ster and Ewa Szczurek and McCarthy, {Davis J.} and Hicks, {Stephanie C.} and Robinson, {Mark D.} and Vallejos, {Catalina A.} and Campbell, {Kieran R.} and Niko Beerenwinkel and Ahmed Mahfouz and Luca Pinello and Pavel Skums and Alexandros Stamatakis and Attolini, {Camille Stephan Otto} and Samuel Aparicio and Jasmijn Baaijens and Marleen Balvert and Barbanson, {Buys de} and Antonio Cappuccio and Giacomo Corleone and Dutilh, {Bas E.} and Maria Florescu and Victor Guryev and Rens Holmer and Katharina Jahn and Lobo, {Thamar Jessurun} and Keizer, {Emma M.} and Indu Khatri and Kielbasa, {Szymon M.} and Korbel, {Jan O.} and Kozlov, {Alexey M.} and Kuo, {Tzu Hao} and Lelieveldt, {Boudewijn P.F.} and Mandoiu, {Ion I.} and Marioni, {John C.} and Tobias Marschall and Felix M{\"o}lder and Amir Niknejad and Lukasz Raczkowski and Marcel Reinders and Ridder, {Jeroen de} and Saliba, {Antoine Emmanuel} and Antonios Somarakis and Oliver Stegle and Theis, {Fabian J.} and Huan Yang and Alex Zelikovsky and McHardy, {Alice C.} and Raphael, {Benjamin J.} and Shah, {Sohrab P.} and Alexander Sch{\"o}nhuth",

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{\textquoteright}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: {\textcopyright} 2020 The Author(s).",

year = "2020",

month = feb,

day = "7",

doi = "10.1186/s13059-020-1926-6",

language = "English (US)",

volume = "21",

journal = "Genome Biology",

issn = "1474-7596",

publisher = "BioMed Central",

number = "1",

}

Lähnemann, D, Köster, 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, Barbanson, BD, 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, Mölder, F, Niknejad, A, Raczkowski, L, Reinders, M, Ridder, JD, Saliba, AE, Somarakis, A, Stegle, O, Theis, FJ, Yang, H, Zelikovsky, A, McHardy, AC, Raphael, BJ, Shah, SP & Schönhuth, A 2020, 'Eleven grand challenges in single-cell data science', Genome biology, vol. 21, no. 1, 31. https://doi.org/10.1186/s13059-020-1926-6

TY - JOUR

T1 - Eleven grand challenges in single-cell data science

AU - Lähnemann, David

AU - Köster, Johannes

AU - Szczurek, Ewa

AU - McCarthy, Davis J.

AU - Hicks, Stephanie C.

AU - Robinson, Mark D.

AU - Vallejos, Catalina A.

AU - Campbell, Kieran R.

AU - Beerenwinkel, Niko

AU - Mahfouz, Ahmed

AU - Pinello, Luca

AU - Skums, Pavel

AU - Stamatakis, Alexandros

AU - Attolini, Camille Stephan Otto

AU - Aparicio, Samuel

AU - Baaijens, Jasmijn

AU - Balvert, Marleen

AU - Barbanson, Buys de

AU - Cappuccio, Antonio

AU - Corleone, Giacomo

AU - Dutilh, Bas E.

AU - Florescu, Maria

AU - Guryev, Victor

AU - Holmer, Rens

AU - Jahn, Katharina

AU - Lobo, Thamar Jessurun

AU - Keizer, Emma M.

AU - Khatri, Indu

AU - Kielbasa, Szymon M.

AU - Korbel, Jan O.

AU - Kozlov, Alexey M.

AU - Kuo, Tzu Hao

AU - Lelieveldt, Boudewijn P.F.

AU - Mandoiu, Ion I.

AU - Marioni, John C.

AU - Marschall, Tobias

AU - Mölder, Felix

AU - Niknejad, Amir

AU - Raczkowski, Lukasz

AU - Reinders, Marcel

AU - Ridder, Jeroen de

AU - Saliba, Antoine Emmanuel

AU - Somarakis, Antonios

AU - Stegle, Oliver

AU - Theis, Fabian J.

AU - Yang, Huan

AU - Zelikovsky, Alex

AU - McHardy, Alice C.

AU - Raphael, Benjamin J.

AU - Shah, Sohrab P.

AU - Schönhuth, Alexander

N1 - 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).

PY - 2020/2/7

Y1 - 2020/2/7

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85079082934&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85079082934&partnerID=8YFLogxK

U2 - 10.1186/s13059-020-1926-6

DO - 10.1186/s13059-020-1926-6

M3 - Review article

C2 - 32033589

AN - SCOPUS:85079082934

SN - 1474-7596

VL - 21

JO - Genome Biology

JF - Genome Biology

IS - 1

M1 - 31

ER -

Eleven grand challenges in single-cell data science

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