Bayesian proteoform modeling improves protein quantification of global proteomic measurements

ABSTRACT: Data used for the implementation of a Bayesian Proteoform Quantification model (BP-Quant) that uses statistically derived peptide signatures to identify peptides that are outside the dominant pattern, or the existence of multiple over-expressed patterns to improve relative protein abundance estimates. BP-Quant is available on GitHub as both MatLab and R packages: https://github.com/PNNL-Comp-Mass-Spec/BP-Quant Plasma samples collected from standard inbred mice were digested with trypsin then analyzed with an LTQ-Orbitrap Velos mass spectrometer. Data was searched with SEQUEST using PNNL's DMS processing pipeline.

INSTRUMENT(S): LTQ Orbitrap Velos

ORGANISM(S): Mus Musculus (ncbitaxon:10090)

SUBMITTER: Richard Smith   Katrina Waters  

PROVIDER: MSV000087701 | MassIVE | Thu Jun 24 18:24:00 BST 2021

REPOSITORIES: MassIVE