DECOMICS, a shiny application for unsupervised cell type deconvolution and biological interpretation of bulk omic data

Slim Karkar (1) , Ashwini Sharma (2) , Carl Herrmann (2) , Yuna Blum (3) , Magali Richard (4)

1 IGBC, UMR 5095, University of Bordeaux - IGBC
2 Bioquant
3 IGDR - Institut de Génétique et Développement de Rennes
4 TIMC-MAGe - Modèles et Algorithmes pour la Génomique

Unsupervised deconvolution algorithms are often used to estimate cell composition from bulk tissue samples. However, applying cell type deconvolution and interpreting the results remains a challenge, even more without prior training in bioinformatics. We propose here a tool for estimating and identifying cell type composition from bulk transcriptomes or methylomes. DECOMICS is a shiny-web application dedicated to unsupervised deconvolution approaches of bulk omic data. It provides (i) a variety of existing algorithms to perform deconvolution on the gene expression or methylation-level matrix, (ii) an enrichment analysis module to aid biological interpretation of the deconvolved components, based on enrichment analysis, and (iii) some visualisation tools. Input data can be downloaded in csv format and pre-processed in the web application (normalisation, transformation and feature selection). The results of the deconvolution, enrichment and visualisation processes can be downloaded.

Keywords: R shiny deconvolution unsupervised approaches transcriptomic data methylome tissue heterogeneity; R shiny; deconvolution; unsupervised approaches; transcriptomic data; methylome; tissue heterogeneity

Domains: Life Sciences [q-bio]

Slim Karkar, Ashwini Sharma, Carl Herrmann, Yuna Blum, Magali Richard. DECOMICS, a shiny application for unsupervised cell type deconvolution and biological interpretation of bulk omic data. 2024. ⟨hal-04660629⟩