IOBR is an R package to perform comprehensive analysis of tumor microenvironment and signatures for immuno-oncology.

Deciphering tumor ecosystems at super-resolution from spatial transcriptomics with TESLA

Spatial profiling toolbox for spatial characterization of tumor immune microenvironment in multiplex images

A collection of tumour microenvironment single-cell RNA sequencing datasets for use in R and other pipelines.

Predictive models and analysis of cancer prognosis and drug response using primary tumor microbial abundances derived from WGS and RNA-seq sequencing data for 32 TCGA cancers (Poore et al. Nature 2020), including equivalent models using TCGA RNA-seq gene expression and combined microbial abundance and gene expression for comparison.

Analysis of treatment naive and neo-adjuvant chemotherapy treated high-grade serous ovarian cancer samples

A classifier for tumor microenvironment subtype based on ensemble machine learning models

Distinct mesenchymal cell states mediate prostate cancer progression

Tracking Multiphase blood flow into a tumor

Spatial EcoTyper is a machine learning framework for systematic identification of spatially distinct multicellular communities from single-cell spatial transcriptomics data.

Code and experiments for "Non-convex SVM for cancer diagnosis based on morphologic features of tumor microenvironment"