Diamond: a multi-modal DIA mass spectrometry data processing pipeline

Chenxin Li; Mingxuan Gao; Wenxian Yang; Chuanqi Zhong; Rongshan Yu

doi:10.1093/bioinformatics/btaa1093

Diamond: a multi-modal DIA mass spectrometry data processing pipeline

Bioinformatics. 2021 Apr 19;37(2):265-267. doi: 10.1093/bioinformatics/btaa1093.

Authors

Chenxin Li¹, Mingxuan Gao¹, Wenxian Yang², Chuanqi Zhong³, Rongshan Yu^{1

2}

Affiliations

¹ Department of Computer Science, School of Informatics, Xiamen University, 361005 Xiamen, China.
² Aginome Scientific, 361005 Xiamen, China.
³ Department of Biology, School of Life Science, Xiamen University, 361005 Xiamen, China.

PMID: 33416868
DOI: 10.1093/bioinformatics/btaa1093

Abstract

Summary: Currently, various software tools are used to support two mainstream workflows for data-independent acquisition (DIA) mass spectrometry (MS) data processing, namely, spectrum-centric scoring (SCS) and peptide-centric scoring (PCS). However, a fully automatic, easily reproducible and freely accessible pipeline that simultaneously integrates SCS and PCS strategies and supports both library-free and library-based modes is absent. We developed Diamond, a Nextflow-based, containerized, multi-modal DIA-MS data processing pipeline for peptide identification and quantification. Diamond integrated two mainstream workflows for DIA data analysis, namely, SCS and PCS, for use cases both with and without assay libraries. This multi-modal pipeline serves as a versatile, easy-to-use and easily extendable toolbox for large-scale DIA data processing.

Availability: Diamond is hosted on GitHub (https://github.com/xmuyulab/Diamond) and is released under the highly permissive MIT license to encourage further customization and modification. The Docker image for Diamond is freely accessible at https://hub.docker.com/r/zeroli/diamond.