Florent Petitprez

This study uses spatial transcriptomics to identify stromal cell gradients in DCIS associated with recurrence as invasive breast cancer, highlighting TREM2+ macrophages and their interactions with epithelial cells.

The paper identifies six distinct tumor microenvironment niches in glioblastoma that correlate with patient survival and immunotherapy response.

The paper evaluates deconvolution methods for inferring immune infiltration from bulk gene expression using a DREAM Challenge, finding that some community-contributed methods, especially deep learning-based ones, perform well.

DECONbench benchmarks deconvolution methods for quantifying tumor cell-type heterogeneity by providing datasets, tools, and performance evaluation.

The paper investigates the genetic basis of spontaneous masculinization in XX female rainbow trout using GWAS and WGS, identifying candidate genes associated with maleness.

The paper introduces mMCP-counter, a method to quantify immune and stromal cell populations in murine samples using gene expression, showing it outperforms existing methods and predicts treatment response.

The paper evaluates computational methods for estimating immune-cell composition from bulk RNA-seq data using simulated and real datasets, finding high accuracy for well-defined cell-type signatures.

MS.liverK is an R package that implements tools for computing molecular subtypes and functional signatures in liver cancer using transcriptome data.

The paper develops a sequence-based method to predict gene expression accurately, showing that nucleotide composition and regulatory region contributions are key factors.