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Lotfollahi, M. ; Hao, Y.* ; Theis, F.J. ; Satija, R.*

The future of rapid and automated single-cell data analysis using reference mapping.

Cell 187, 2343-2358 (2024)
Verlagsversion DOI PMC
Open Access Gold (Paid Option)
As the number of single-cell datasets continues to grow rapidly, workflows that map new data to well-curated reference atlases offer enormous promise for the biological community. In this perspective, we discuss key computational challenges and opportunities for single-cell reference-mapping algorithms. We discuss how mapping algorithms will enable the integration of diverse datasets across disease states, molecular modalities, genetic perturbations, and diverse species and will eventually replace manual and laborious unsupervised clustering pipelines.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Review
Korrespondenzautor
Schlagwörter Cross-species Comparisons ; Machine Learning ; Multimodal Analysis ; Reference Mapping ; Single-cell Analysis; Chromatin Accessibility; Atlas; Prediction; Rna
ISSN (print) / ISBN 0092-8674
e-ISSN 1097-4172
Zeitschrift Cell
Quellenangaben Band: 187, Heft: 10, Seiten: 2343-2358 Artikelnummer: , Supplement: ,
Verlag Cell Press
Verlagsort Cambridge, Mass.
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Computational Biology (ICB)
Förderungen National Institutes of Health
BMBF
European Union
Helmholtz Association's Initiative and Networking Fund through Helmholtz AI
Chan Zuckerberg Initiative
Joachim Herz Stiftung via Addon Fellowships for Interdisciplinary Life Science