Name
Title | ||
|---|---|---|
SW-Tandem: a highly efficient tool for large-scale peptide identification with parallel spectrum dot product on Sunway TaihuLight. |
Abstract | ||
|---|---|---|
aSummary: Tandem mass spectrometry based database searching is a widely acknowledged and adopted method that identifies peptide sequence in shotgun proteomics. However, database searching is extremely computationally expensive, which can take days even weeks to process a large spectra dataset. To address this critical issue, this paper presents SW-Tandem, a new tool for large-scale peptide sequencing. SW-Tandem parallelizes the spectrum dot product scoring algorithm and leverages the advantages of Sunway TaihuLight, the No. 1 supercomputer in the world in 2017. Sunway TaihuLight is powered by the brand new many-core SW26010 processors and provides a peak computation performance greater than 100PFlops. To fully utilize the Sunway TaihuLights capacity, SW-Tandem employs three mechanisms to accelerate large-scale peptide identification, memory-access optimizations, double buffering and vectorization. The results of experiments conducted on multiple datasets demonstrate the performance of SW-Tandem against three state-of-the-art tools for peptide identification, including X!! Tandem, MR-Tandem and MSFragger. In addition, it shows high scalability in the experiments on extremely large datasets sized up to 12 GB. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1093/bioinformatics/btz147 | BIOINFORMATICS |
Field | DocType | Volume |
Data mining,Tandem,Computer science,Peptide,Computational science,Dot product,Sunway TaihuLight | Journal | 35 |
Issue | ISSN | Citations |
19 | 1367-4803 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |