RRC ID 80770
Author Govek KW, Nicodemus P, Lin Y, Crawford J, Saturnino AB, Cui H, Zoga K, Hart MP, Camara PG.
Title CAJAL enables analysis and integration of single-cell morphological data using metric geometry.
Journal Nat Commun
Abstract High-resolution imaging has revolutionized the study of single cells in their spatial context. However, summarizing the great diversity of complex cell shapes found in tissues and inferring associations with other single-cell data remains a challenge. Here, we present CAJAL, a general computational framework for the analysis and integration of single-cell morphological data. By building upon metric geometry, CAJAL infers cell morphology latent spaces where distances between points indicate the amount of physical deformation required to change the morphology of one cell into that of another. We show that cell morphology spaces facilitate the integration of single-cell morphological data across technologies and the inference of relations with other data, such as single-cell transcriptomic data. We demonstrate the utility of CAJAL with several morphological datasets of neurons and glia and identify genes associated with neuronal plasticity in C. elegans. Our approach provides an effective strategy for integrating cell morphology data into single-cell omics analyses.
Volume 14(1)
Pages 3672
Published 2023-6-21
DOI 10.1038/s41467-023-39424-2
PII 10.1038/s41467-023-39424-2
PMID 37339989
PMC PMC10282047
MeSH Animals Caenorhabditis elegans* / genetics Gene Expression Profiling Neurons* Transcriptome
C.elegans tm463