PuSH - Publikationsserver des Helmholtz Zentrums München

Michielsen, L.* ; Lotfollahi, M. ; Strobl, D.C. ; Sikkema, L. ; Reinders, M.J.T.* ; Theis, F.J. ; Mahfouz, A.*

Single-cell reference mapping to construct and extend cell-type hierarchies.

NAR Gen. Bioinfo. 5:lqad070 (2023)
Verlagsversion DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
Single-cell genomics is now producing an ever-increasing amount of datasets that, when integrated, could provide large-scale reference atlases of tissue in health and disease. Such large-scale atlases increase the scale and generalizability of analyses and enable combining knowledge generated by individual studies. Specifically, individual studies often differ regarding cell annotation terminology and depth, with different groups specializing in different cell type compartments, often using distinct terminology. Understanding how these distinct sets of annotations are related and complement each other would mark a major step towards a consensus-based cell-type annotation reflecting the latest knowledge in the field. Whereas recent computational techniques, referred to as 'reference mapping' methods, facilitate the usage and expansion of existing reference atlases by mapping new datasets (i.e. queries) onto an atlas; a systematic approach towards harmonizing dataset-specific cell-type terminology and annotation depth is still lacking. Here, we present 'treeArches', a framework to automatically build and extend reference atlases while enriching them with an updatable hierarchy of cell-type annotations across different datasets. We demonstrate various use cases for treeArches, from automatically resolving relations between reference and query cell types to identifying unseen cell types absent in the reference, such as disease-associated cell states. We envision treeArches enabling data-driven construction of consensus atlas-level cell-type hierarchies and facilitating efficient usage of reference atlases.
Altmetric
Weitere Metriken?
[➜Einloggen]
Zusatzinfos bearbeiten [➜Einloggen]
Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter Enrichr
ISSN (print) / ISBN 2631-9268
e-ISSN 2631-9268
Zeitschrift NAR: Genomics and Bioinformatics
Quellenangaben Band: 5, Heft: 3, Seiten: , Artikelnummer: lqad070 Supplement: ,
Verlag Oxford University Press
Verlagsort Great Clarendon St, Oxford Ox2 6dp, England
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Computational Biology (ICB)