MICSQTL (Multi-omic deconvolution, Integration and Cell-type-specific Quantitative Trait Loci) is a tool that estimates cell type proportions in bulk proteomes by leveraging shared information in matched transcriptomes. Based on the deconvoluted cell fractions, MICSQTL further integrates and visualizes multi-source profiles at bulk or cell type levels, as well as performs Quantitative Trait Loci (QTL) mapping at cellular resolution. This is a novel pipeline for multi-omic integrative data analysis that fulfills the need for comprehensive analysis of diverse data sources. This pipeline enables valuable insights into cellular composition, facilitates cell-type-specific protein QTL mapping, and streamlines multi-modal data integration and dimension reduction.
MICSQTL 1.0.0
Our pipeline, MICSQTL, integrates RNA and protein expressions to detect potential cell marker proteins and estimate cell abundance in mixed proteomes without a reference signature matrix. MICSQTL enables cell-type-specific quantitative trait loci (QTL) mapping for proteins or transcripts using bulk expression data and estimated cellular composition per molecule type, eliminating the necessity for single-cell sequencing. We use matched transcriptome-proteome from human brain frontal cortex tissue samples to demonstrate the input and output of our tool.