TY - JOUR
T1 - Benchmarked approaches for reconstruction of in vitro cell lineages and in silico models of C. elegans and M. musculus developmental trees
AU - Gong, Wuming
AU - Granados, Alejandro A
AU - Hu, Jingyuan
AU - Jones, Matthew G
AU - Raz, Ofir
AU - Salvador-Martínez, Irepan
AU - Zhang, Hanrui
AU - Chow, Ke-Huan K
AU - Kwak, Il-Youp
AU - Retkute, Renata
AU - Prusokas, Alidivinas
AU - Prusokas, Augustinas
AU - Khodaverdian, Alex
AU - Zhang, Richard
AU - Rao, Suhas
AU - Wang, Robert
AU - Rennert, Phil
AU - Saipradeep, Vangala G
AU - Sivadasan, Naveen
AU - Rao, Aditya
AU - Joseph, Thomas
AU - Srinivasan, Rajgopal
AU - Peng, Jiajie
AU - Han, Lu
AU - Shang, Xuequn
AU - Garry, Daniel J
AU - Yu, Thomas
AU - Chung, Verena
AU - Mason, Michael
AU - Liu, Zhandong
AU - Guan, Yuanfang
AU - Shendure, Jay
AU - Telford, Maximilian J
AU - Shapiro, Ehud
AU - Elowitz, Michael B
AU - Meyer, Pablo
N1 - Publisher Copyright: © 2021 The Authors
PY - 2021/8/18
Y1 - 2021/8/18
N2 - The recent advent of CRISPR and other molecular tools enabled the reconstruction of cell lineages based on induced DNA mutations and promises to solve the ones of more complex organisms. To date, no lineage reconstruction algorithms have been rigorously examined for their performance and robustness across dataset types and number of cells. To benchmark such methods, we decided to organize a DREAM challenge using in vitro experimental intMEMOIR recordings and in silico data for a C. elegans lineage tree of about 1,000 cells and a Mus musculus tree of 10,000 cells. Some of the 22 approaches submitted had excellent performance, but structural features of the trees prevented optimal reconstructions. Using smaller sub-trees as training sets proved to be a good approach for tuning algorithms to reconstruct larger trees. The simulation and reconstruction methods here generated delineate a potential way forward for solving larger cell lineage trees such as in mouse.
AB - The recent advent of CRISPR and other molecular tools enabled the reconstruction of cell lineages based on induced DNA mutations and promises to solve the ones of more complex organisms. To date, no lineage reconstruction algorithms have been rigorously examined for their performance and robustness across dataset types and number of cells. To benchmark such methods, we decided to organize a DREAM challenge using in vitro experimental intMEMOIR recordings and in silico data for a C. elegans lineage tree of about 1,000 cells and a Mus musculus tree of 10,000 cells. Some of the 22 approaches submitted had excellent performance, but structural features of the trees prevented optimal reconstructions. Using smaller sub-trees as training sets proved to be a good approach for tuning algorithms to reconstruct larger trees. The simulation and reconstruction methods here generated delineate a potential way forward for solving larger cell lineage trees such as in mouse.
UR - http://www.scopus.com/inward/record.url?scp=85112267236&partnerID=8YFLogxK
U2 - https://doi.org/10.1016/j.cels.2021.05.008
DO - https://doi.org/10.1016/j.cels.2021.05.008
M3 - مقالة
C2 - 34146472
SN - 2405-4712
VL - 12
SP - 810-826.e4
JO - Cell Systems
JF - Cell Systems
IS - 8
ER -