Veneer
The lack of standardization in how cell surface proteomics have been analyzed and reported presents challenges to comparing methodologies, datasets, and inspiring confidence in claims of subcellular localization. Veneer provides a solution to this problem.
Veneer is an automated, standardized solution for curation, classification, annotation and reporting of data generated by N-glycocapture workflows.
Veneer features:
Reliance on gene ontology terms and database annotations are avoided by using experimental evidence and applying stringent criteria to accurately classify proteins identified in a cell surface glycoproteomics experiment as cell surface N-glycoproteins.
Veneer output provides easy access to N-glycosite information that is valuable for determining the orientation of uncharacterized transmembrane proteins, which is essential for informing downstream antibody development.
Veneer processes qualitative and quantitative N-glycocapture datasets (experiments that include deglycosylation with PNGase F).
Inputs/outputs are agnostic of vendor or platform used for data acquisition or database searching.
