ArticleMethods in molecular biology (Clifton, N.J.)2027
Pathway and Kinase Analysis in Proteomics and Phosphoproteomics with rROMA.
Article in Methods in molecular biology (Clifton, N.J.), 2027. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Advances in data acquisition tools, particularly mass spectrometry-based techniques, have made high-throughput methods like proteomics and phosphoproteomics increasingly accessible. However, the volume and complexity of the data require specialized computational tools for analysis and interpretation to extract meaningful insights. Here, we describe the use of rROMA software to analyze pathway and kinase activity in proteomic and phosphoproteomic datasets. rROMA is an open-source package available on Github at: www.github.com/sysbio-curie/rROMA . As a case study, we applied rROMA to breast cancer samples from the Clinical Proteomic Tumor Analysis Consortium (CPTAC), which provides precise relative quantification of proteins and phosphorylation sites of a large cohort of breast cancer samples through Tandem mass tag (TMT)-based mass spectrometry. These analyses illustrate how to identify active pathways and kinase-driven mechanisms potentially involved in disease subtypes, along with their associated proteins and phosphosites.
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