Related Experiment Video
Updated: Jun 16, 2025
Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
Published on: July 29, 2022
cypress: an R/Bioconductor package for cell-type-specific differential expression analysis power assessment
Shilin Yu1, Guanqun Meng2, Wen Tang2
1Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH 44106, United States.
Summary:
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.
Availability And Implementation:
cypress is an open-source R/Bioconductor package at https://bioconductor.org/packages/cypress/.
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