Signature-scoring methods developed for bulk samples are not adequate for cancer single-cell RNA sequencing data
- The University of Texas Health Science Center at San Antonio, United States
- University of Texas Health Science Center at San Antonio, United States
Abstract
Quantifying the activity of gene expression signatures is common in analyses of single-cell RNA sequencing data. Methods originally developed for bulk samples are often used for this purpose without accounting for contextual differences between bulk and single-cell data. More broadly, these methods have not been benchmarked. Here we benchmark five such methods, including single sample gene set enrichment analysis (ssGSEA), Gene Set Variation Analysis (GSVA), AUCell, Single Cell Signature Explorer (SCSE), and a new method we developed, Jointly Assessing Signature Mean and Inferring Enrichment (JASMINE). Using cancer as an example, we show cancer cells consistently express more genes than normal cells. This imbalance leads to bias in performance by bulk-sample-based ssGSEA in gold standard tests and down sampling experiments. In contrast, single-cell-based methods are less susceptible. Our results suggest caution should be exercised when using bulk-sample-based methods in single-cell data analyses, and cellular contexts should be taken into consideration when designing benchmarking strategies.
Data availability
The current manuscript is a computational study, so no data have been generated for this manuscript. Single cell data sets used in this study including their downloading sources were listed in Supplementary Table 1. Gene sets were downloaded from MSigDB v.7.2. JASMINE source code is available on Github (https://github.com/NNoureen/JASMINE). Source Data contain the numerical data used to generate the figures.
Article and author information
Author details
Funding
Cancer Prevention and Research Institute of Texas (RR170055)
- Siyuan Zheng
Cancer Prevention and Research Institute of Texas (RP170345)
- Nighat Noureen
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2022, Noureen et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Signature-scoring methods developed for bulk samples are not adequate for cancer single-cell RNA sequencing data
eLife 11:e71994.
https://doi.org/10.7554/eLife.71994
