Accurately Assigning Peptides to Spectra When Only a Subset of Peptides Are Relevant

ABSTRACT: The standard proteomics database search strategy involves searching spectra against a peptide database and estimating the false discovery rate (FDR) of the resulting set of peptide-spectrum matches. One assumption of this protocol is that all the peptides in the database are reDR control strategies are needed. Recently, two methods were proposed to address this problem: subset-search and all-sub. We show that both methods fail to control the FDR. For subset-search, this failure is due to the presence of “neighbor” peptides, which are defined as irrelevant peptides with a similar precursor mass and fragmentation spectrum as a relevant peptide. Not considering neighbors compromises the FDR estimate because a spectrum generated by an irrelevant peptide can incorrectly match well to a relevant peptide. Therefore, we have developed a new method, “filter then subset-neighbor search” (FSNS), that accounts for neighbor peptides. We show evidence that FSNS properly controls the FDR when neighbors are present and that FSNS outperforms group-FDR, the only other method able to control the FDR relative to a subset of relevant peptides

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human) Ricinus Communis Saccharomyces Cerevisiae (baker's Yeast)

SUBMITTER: Andy Lin  

LAB HEAD: Willian Stafford Noble

PROVIDER: PXD022778 | Pride | 2021-06-17

REPOSITORIES: Pride