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MatriSpace is a web application developed by the Naba and Izzi labs that uses Matrisome lists to identify matrisome genes/proteins in spatial transcriptomic (ST) datasets. MatriSpace provides spatially resolved maps of matrisome gene expression in relation to cell populations at multiple levels, from single-gene analysis to tissue niches and functional ECM units. Users can process their own datasets or query a collection of curated open-access ST datasets.
Using MatriSpace? Please cite:
Oshinjo A, Chen D, Petrov PB, Izzi, V, and Naba A. MatriSpace: Identification and visualization of spatially resolved ECM gene expression patterns in health and disease. bioRxiv, 2026. Preprint access
MatriCom is a web application developed by the Naba and Izzi labs to mine scRNA-Seq datasets and infer communications between ECM components and between different cell populations and the ECM. To impute interactions from expression data, MatriCom relies on a unique database, MatriComDB, that includes over 25,000 curated interactions involving matrisome components, with data on 80% of the ~1,000 genes that compose the mammalian matrisome. MatriCom offers the option to query open-access datasets sourced from large sequencing efforts (Tabula Sapiens, The Human Protein Atlas, HuBMAP) or to process user-generated datasets.
Using MatriCom? Please cite:
Lamba R, Paguntalan AM, Petrov PB, Naba A*, Izzi V*. MatriCom: a scRNA-Seq data mining tool to infer ECM-ECM and cell-ECM communication systems. Journal of Cell Science, 2025, 138 (13): jcs263927. Journal Access
Read the feature in the Highlight section of the Journal of Cell Science.
Matrisome AnalyzeR is a web application developed by the Naba and Izzi labs that uses Matrisome lists to identify matrisome genes/proteins in -omic datasets and annotates and tabulates these molecules according to matrisome divisions and categories.
🔗 Test file gallery | R package
Using Matrisome AnalyzeR? Please cite:
Petrov PB, Considine JM, Izzi, V, and Naba A. Matrisome AnalyzeR: A suite of tools to annotate and quantify ECM molecules in big datasets across organisms. Journal of Cell Science, 2023, 136 (17): jcs261255. Journal Access
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