Benchmarking & evaluating single-cell gene-enhancer regulatory networks

Deuner Cos, Gerard

Benchmarking & evaluating single-cell gene-enhancer regulatory networks

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Citation

Deuner Cos, G. Benchmarking & evaluating single-cell gene-enhancer regulatory networks. 2023. handle: http://hdl.handle.net/10230/59916

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Abstract

The project consists of benchmarking GRaNIE, a enhancer inclusive gene regulatory network inference method from bulk RNA-seq and ATA-seq data, at the single-cell level. We propose a way of carrying out the benchmark through a validation-based approach that assesses the network's ability to predict real regulatory interactions from cell-type-specific pcHi-C, eQTL and ChIP-Seq data. Additionally, we perform a biological comprehensive analysis of the output eGRNs and evaluate their predictive power utilizing GRaNPA, a machine learning framework, that assesses how well a GRN can predicit cell-type-specific differential gene expression data.