Decomprolute is a benchmarking platform designed for multiomics-based tumor deconvolution

Journal Article · 25 February 2024 · Cell Reports. Methods

DOI: https://doi.org/10.1016/j.crmeth.2024.100708 · OSTI ID:2406489

Feng, Song  ^[1]; Calinawan, Anna ^[2]; Pugliese, Pietro ^[3]; Wang, Pei ^[2]; Ceccarelli, Michele ^[4]; Petralia, Francesca ^[2]; Gosline, Sara J.C.  ^[1]

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1. Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
2. Icahn School of Medicine at Mount Sinai, New York, NY (United States)
3. University of Sannio, Benevento (Italy)
4. Univ. of Naples Federico II (Italy)

Tumor deconvolution is a reliable way to disentangle the diverse cell types that comprise solid tumors. To date, however, both the algorithms developed to deconvolve tumor samples, and the gold standard datasets used to assess the algorithms are geared toward the analysis of gene expression (e.g., RNA-seq) rather than protein levels in tumor cells. While gene expression is less expensive to measure, protein levels provide a more accurate view of immune markers. To facilitate the development as well as improve the reproducibility and reusability of multi-omic deconvolution algorithms, we introduce Decomprolute, a Common Workflow Language framework that leverages containerization to compare tumor deconvolution algorithms across multiomic data sets. Decomprolute incorporates the large-scale multiomic data sets produced by the Clinical Proteomic Tumor Analysis Consortium (CPTAC), which include matched mRNA expression and proteomic data from thousands of tumors across multiple cancer types to build a fully open-source, containerized proteogenomic tumor deconvolution benchmarking platform. The platform consists of modular architecture and it comes with well-defined input and output formats at each module. As a result, it is robust and extendable easily with additional algorithms or analyses. The platform is available for access and use at http://pnnl-compbio.github.io/decomprolute.

• Research Organization: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
• Sponsoring Organization: USDOE
• Grant/Contract Number: AC05-76RL01830
• OSTI ID: 2406489
• Report Number(s): PNNL-SA--180136
• Journal Information: Cell Reports. Methods, Journal Name: Cell Reports. Methods Journal Issue: 2 Vol. 4; ISSN 2667-2375
• Publisher: ElsevierCopyright Statement
• Country of Publication: United States
• Language: English