%0 Journal Article
%T Panpipes: a pipeline for multiomic single-cell and spatial transcriptomic data analysis.
%A Curion F
%A Rich-Griffin C
%A Agarwal D
%A Ouologuem S
%A Rue-Albrecht K
%A May L
%A Garcia GEL
%A Heumos L
%A Thomas T
%A Lason W
%A Sims D
%A Theis FJ
%A Dendrou CA
%J Genome Biol
%V 25
%N 1
%D 2024 Jul 8
%M 38978088
暂无%R 10.1186/s13059-024-03322-7
%X Single-cell multiomic analysis of the epigenome, transcriptome, and proteome allows for comprehensive characterization of the molecular circuitry that underpins cell identity and state. However, the holistic interpretation of such datasets presents a challenge given a paucity of approaches for systematic, joint evaluation of different modalities. Here, we present Panpipes, a set of computational workflows designed to automate multimodal single-cell and spatial transcriptomic analyses by incorporating widely-used Python-based tools to perform quality control, preprocessing, integration, clustering, and reference mapping at scale. Panpipes allows reliable and customizable analysis and evaluation of individual and integrated modalities, thereby empowering decision-making before downstream investigations.