Linking Expression of Cell-Surface Receptors with Transcription Factors by Computational Analysis of Paired Single-Cell Proteomes and Transcriptomes

Complex signaling and transcriptional programs control the development and physiology of specialized cell types. Genetic perturbations in these programs cause human cancers to arise from a diverse set of specialized cell types and developmental states. Understanding these complex systems and their p...

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Bibliographic Details
Published in:Methods in molecular biology (Clifton, N.J.) Vol. 2660; p. 149
Main Authors: Sagan, April, Ma, Xiaojun, Ramjattun, Koushul, Osmanbeyoglu, Hatice Ulku
Format: Journal Article
Language:English
Published: United States 2023
Subjects:
Humans
Leukocytes, Mononuclear
Proteome
Proteomics
Single-Cell Analysis
Transcription Factors - genetics
Transcriptome
Droplet-based scRNA-seq
scVerse and Scanpy ecosystems
Affinity regression (AR)
scADT-seq
Jupyter notebook
pySPaRTAN package
DoRothEA database
Single-cell Proteomic and RNA-based Transcription factor Activity Network (SPaRTAN)
Python package
Cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq)
Antibody-derived tags (ADTs)
ISSN:1940-6029, 1940-6029
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Summary:Complex signaling and transcriptional programs control the development and physiology of specialized cell types. Genetic perturbations in these programs cause human cancers to arise from a diverse set of specialized cell types and developmental states. Understanding these complex systems and their potential to drive cancer is critical for the development of immunotherapies and druggable targets. Pioneering single-cell multi-omics technologies that analyze transcriptional states have been coupled with the expression of cell-surface receptors. This chapter describes SPaRTAN (Single-cell Proteomic and RNA-based Transcription factor Activity Network), a computational framework, to link transcription factors with cell-surface protein expression. SPaRTAN uses CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing) data and cis-regulatory sites to model the effect of interactions between transcription factors and cell-surface receptors on gene expression. We demonstrate the pipeline for SPaRTAN using CITE-seq data from peripheral blood mononuclear cells.
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ISSN:1940-6029
1940-6029
DOI:10.1007/978-1-0716-3163-8_11