CIBERSORTx Signature Matrix and GEP Files for Bulk RNA Transcriptomic Deconvolution to Predict Tumour Microenvironment Component Abundance

Research output: Other contribution


Gregory et al (2023) used single cell RNA-seq data from three sporadic vestibular schwannoma (VS) from Xu et al (2022) to create VS-specific CIBERSORTx signature matrix and gene expression profile (GEP) files to use for the deconvolution workflow of bulk transcriptomic VS. Deconvolution using these files can be used to estimate the abundance of Schwann cells, macrophages, endothelial cells, T-cells, neutrophils, fibroblasts, vascular endothelium, and mast cells within the VS tumour microenvironment. Compatible with CIBERSORTx.
Original languageUndefined
TypeInternally Reviewed
Publication statusPublished - 15 Feb 2023

Cite this