Fig. 1: Schematic overview of iDEA. | Nature Communications

Fig. 1: Schematic overview of iDEA.

From: Integrative differential expression and gene set enrichment analysis using summary statistics for scRNA-seq studies

Fig. 1: Schematic overview of iDEA.The alternative text for this image may have been generated using AI.

iDEA is designed to jointly model all genes together for integrative differential expression (DE) analysis and gene set enrichment (GSE) analysis. iDEA requires input association summary statistics from existing scRNA-seq DE methods in terms of the DE effect size estimate \(\hat \beta _j\) and its standard error \({\mathrm{se}}\left( {\hat \beta _j} \right)\) for every gene (\(j = 1,2, \cdots ,p\)) (top left panels). iDEA also requires a pre-defined set of gene sets that we have compiled and pruned for use with the software (top right panels). With these two inputs, iDEA performs joint DE and GSE analysis through a Bayesian hierarchical model. For each gene set, iDEA outputs a p-value for testing whether the gene set is enriched with DE genes (bottom right panel) for GSE analysis. In addition, iDEA outputs the posterior inclusion probability of each gene being DE (bottom left panel) for DE analysis. By modeling all genes together and integrating DE and GSE analyses in a joint framework, iDEA can increase the power of both analyses.

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