Single-Cell RNA Sequencing Data in Forensic Science

Music City Center 

While DNA remains the cornerstone of forensic science, RNA offers significant potential for additional applications. Single-cell RNA sequencing provides exceptional resolution to address complicated mixed samples, but it suffers from sparsity due to both biological zeros and technical dropouts. We begin by discussing the role of RNA in forensic science, then investigate imputation methods to recover missing gene expression values and enhance the reliability of RNA evidence. Focusing on different categories of imputation, we discuss the advantages and limitations of each. Simulation studies demonstrate the potential of these techniques to improve data quality, ultimately paving the way for more robust RNA-based forensic analyses.

Missing data

Matrix completion

Data imputation

Clustering

Dimension reduction

Single-cell RNA sequencing 

IMS