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bioRxiv · 10.1101/864165

DrivAER: Identification of driving transcriptional programs in single-cell RNA sequencing data

Simon, L. M.·Yan, F.·Zhao, Z.
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Abstract

Single cell RNA sequencing (scRNA-seq) unfolds complex transcriptomic data sets into detailed cellular maps. Despite recent success, there is a pressing need for specialized methods tailored towards the functional interpretation of these cellular maps. Here, we present DrivAER, a machine learning approach that scores annotated gene sets based on their relevance to user-specified outcomes such as pseudotemporal ordering or disease status. We demonstrate that DrivAER extracts the key driving pathways and transcription factors that regulate complex biological processes from scRNA-seq data.

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Simon, L. M., Yan, F., Zhao, Z.. 2019-12-05. DrivAER: Identification of driving transcriptional programs in single-cell RNA sequencing data. https://doi.org/10.1101/864165

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