BioinformaticsBioinformaticsPeer-reviewed journal article
CiteFuse enables multi-modal analysis of CITE-seq data
Hani Jieun KimiD, Yingxin LiniD, Thomas A. GeddesiD, Jean Yee Hwa YangiD, Pengyi YangiD
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Abstract
Multi-modal profiling of single cells represents one of the latest technological advancements in molecular biology. Among various single-cell multi-modal strategies, cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) allows simultaneous quantification of two distinct species: RNA and surface marker proteins (ADT). Here, we introduce CiteFuse, a streamlined package consisting of a suite of tools for pre-processing, modality integration, clustering, differential RNA and ADT expression analysis, ADT evaluation, ligand-receptor interaction analysis, and interactive web-based visualization of CITE-seq data. We show the capacity of CiteFuse to integrate the two data modalities and its relative advantage against data generated from single modality profiling. Furthermore, we illustrate the pre-processing steps in CiteFuse and in particular a novel doublet detection method based on a combined index of cell hashing and transcriptome data. Collectively, we demonstrate the utility and effectiveness of CiteFuse for the integrative analysis of transcriptome and epitope profiles from CITE-seq data.
- assay: CITE-seq
- research focus: cell type annotation
- research focus: clustering
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
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