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Informing biologically relevant signal from spatial transcriptomic data

Emir Radkevich, Darwin D’souzaiD, Raphaël MattiuziD, Raphaël MerandiD, Rachel CheniD, Jarod Morgenroth-Rebin, Krista Angeliadis, Daniella Nelson, Anis Kara, Travis DawsoniD, Igor De Souza, Kai NieiD, Pauline HamoniD, Samarth HegdeiD, Jesse BoumelhaiD, Rachel BrodyiD, Sinem OzbeyiD, Clotilde Hennequin, Di FengiD, Jie Dai, Edgar Gonzalez‐KozlovaiD, Zhi Hong CheniD, Seunghee Kim‐SchulzeiD, Sacha GnjaticiD, Miriam MéradiD, Vladimir RoudkoiD

PDFDOI

Abstract

Visium is a spatial sequencing technology that utilizes messenger RNA (mRNA) to spatially map gene expression within tissues. Despite its potential, research utilizing deconvolution tools and exploring microenvironment dynamics remains challenging. We address this gap by benchmarking deconvolution tools across diverse biological contexts, identifying optimal methodologies. Subsequently, we introduce a novel pipeline integrating advanced deconvolution techniques and novel tools for reproducible tissue microenvironment analysis. Through this approach, we uncover intricate immune aggregate biology, highlighting the power of our methodology in unraveling complex biological phenomena.

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