Please note: This PhD seminar will take place online.
Johra Muhammad Moosa, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Bin Ma
The sequence database searching method is widely used in proteomics for peptide identification. To control the false discovery rate (FDR) of the search results, the target−decoy method generates and searches a decoy database together with the target database. A known problem is that the target protein sequence database may contain numerous repeated peptides. The structures of these repeats are not preserved by most existing decoy generation algorithms. Previous studies suggest that such a discrepancy between the target and decoy databases may lead to an inaccurate FDR estimation.
Based on the de Bruijn graph model, we propose a new repeat-preserving algorithm to generate decoy databases. We prove that this algorithm preserves the structures of the repeats in the target database to a great extent. The de Bruijn method has been compared with a few other commonly used methods and demonstrated superior FDR estimation accuracy and an improved number of peptide identification.