Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View

arXiv:2403.15500v1 Announce Type: cross
Abstract: Gene regulatory network inference (GRNI) is a challenging problem, particularly owing to the presence of zeros in single-cell RNA sequencing data: some are biological zeros representing no gene expression, while some others are technical zeros arising from the sequencing procedure (aka dropouts), which may bias GRNI by distorting the joint distribution of the measured gene expressions. Existing approaches typically handle dropout error via imputation, which may introduce spurious relations as the true joint distribution is …

abstract arxiv causal cs.lg data gene inference network q-bio.mn q-bio.qm regulatory rna sequencing technical type view