Determination of the Stage Composition of <i>Plasmodium</i> Infections from Bulk Gene Expression Data
Kieran Tebben, Aliou Dia, David Serre
Abstract
Differences in cell type proportions among samples can introduce artifacts in gene expression analyses and mask genuine differences in gene regulation. Gene expression deconvolution allows estimation of the proportion of each cell type present in one sample directly from bulk RNA sequencing data, but this approach requires a reference data set with the signature profile of each cell type. Here, we evaluate the suitability of a rodent malaria parasite gene expression data set for estimating the proportions of each parasite developmental stage present in bulk RNA sequencing data generated from blood-stage infections with the human parasites Plasmodium falciparum and Plasmodium vivax. These analyses provide a species-agnostic approach for reliably estimating stage proportions in infected human blood and correcting subsequent gene expression analyses for these variations.