Star Protocols: Protocol to benchmark gene expression signature scoring techniques for single-cell RNA sequencing data in cancer (Zheng Lab)
- • Protocol for benchmarking signature scoring techniques in scRNAseq data analysis
- • Comparing single-cell and bulk-based approaches in sensitivity and specificity
- • Using down sampling to simulate the impact of dropouts on signature scoring techniques
Summary
Scoring gene signatures are common for bulk and single-cell RNA sequencing (scRNAseq) data. Here, using cancer as a data model, we describe steps to benchmark signature scoring techniques for scRNAseq data in the context of uneven gene dropouts. These steps include identifying and comparing deregulated signatures, generating gold standard signatures for specificity and sensitivity tests, and simulating the impact of dropouts using downsampling. The protocol provides a framework for benchmarking scRNAseq algorithms in such a context.
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Since 2004, UT Health San Antonio, Greehey Children’s Cancer Research Institute’s (Greehey CCRI) mission has been to advance scientific knowledge relevant to childhood cancer, contribute to understanding its causes, and accelerate the translation of knowledge into novel therapies. Greehey CCRI strives to have a national and global impact on childhood cancer by discovering, developing, and disseminating new scientific knowledge. Our mission consists of three key areas — research, clinical, and education.
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Since 2004, UT Health San Antonio, Greehey Children’s Cancer Research Institute’s (Greehey CCRI) mission has been to advance scientific knowledge relevant to childhood cancer, contribute to understanding its causes, and accelerate the translation of knowledge into novel therapies. Greehey CCRI strives to have a national and global impact on childhood cancer by discovering, developing, and disseminating new scientific knowledge. Our mission consists of three key areas — research, clinical, and education.
Stay connected with the Greehey CCRI on Facebook, Twitter, LinkedIn, and Instagram.