cypress: an R/Bioconductor package for cell-type-specific differential expression analysis power assessment

TL;DR

The paper introduces cypress, a new R package for simulating and analyzing cell-type-specific gene expression in bulk RNA-seq data.

Contribution

The novel contribution is the first tool for experimental design and power analysis in cell-type-specific differential expression studies.

Findings

Cypress models cell-type-specific profiles and variations to simulate bulk RNA-seq data.

It helps researchers optimize experimental design and assess statistical power for csDE gene detection.

The tool supports simulation and evaluation using multiple statistical metrics.

Abstract

Recent methodology advances in computational signal deconvolution have enabled bulk transcriptome data analysis at a finer cell-type level. Through deconvolution, identifying cell-type-specific differentially expressed (csDE) genes is drawing increasing attention in clinical applications. However, researchers still face a number of difficulties in adopting csDE genes detection methods in practice, especially in their experimental design. Here we present cypress, the first experimental design and statistical power analysis tool in csDE genes identification. This tool can reliably model purified cell-type-specific (CTS) profiles, cell-type compositions, biological and technical variations, offering a high-fidelity simulator for bulk RNA-seq convolution and deconvolution. cypress conducts simulation and evaluates the impact of multiple influencing factors, by various statistical metrics, to help researchers optimize experimental design and conduct power analysis.

cypress is an open-source R/Bioconductor package at https://bioconductor.org/packages/cypress/.

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