Multimodal joint deconvolution and integrative signature selection in proteomics

Abstract

Deconvolution is an efficient approach for detecting cell-type-specific (cs) transcriptomic signals without cellular segmentation. However, this type of methods have not been extended to the proteomics research. Here we present a novel algorithm and tool to dissect bulk proteome by leveraging the information shared between transcriptome-proteome. Our tool first identifies potential cell marker proteins by integrating RNA and protein bulk expression profiles and then jointly quantifies the cell abundance in mixture proteomes without using a reference signature matrix, enabling the downstream analyses such as cs-protein Quantitative Trait Loci (cspQTL) mapping. This new method and the cspQTL analysis are implemented in the R package MIC-SQTL that also provides integrative visualization of bulk multimodal samples, available at https://bioconductor.org/packages/MICSQTL.