TY - JOUR
T1 - Eleven grand challenges in single-cell data science
AU - Lähnemann, David
AU - Köster, Johannes
AU - Robinson, Mark D.
AU - Vallejos, Catalina A.
AU - Campbell, Kieran R.
AU - Beerenwinkel, Niko
AU - Pinello, Luca
AU - Lelieveldt, Boudewijn P.F.
AU - Reinders, Marcel
AU - More Authors, null
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
U2 - 10.1186/s13059-020-1926-6
DO - 10.1186/s13059-020-1926-6
M3 - Review article
C2 - 32033589
AN - SCOPUS:85079082934
SN - 1474-760X
VL - 21
JO - Genome biology
JF - Genome biology
IS - 1
M1 - 31
ER -