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

Chenxin Li, Mingxuan Gao, Wenxian Yang, Chuan‐Qi Zhong, Rongshan Yu

2020Bioinformatics13 citationsDOI

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.

Topics & Concepts

Computer scienceWorkflowPipeline (software)DiamondSoftwareData processingIdentification (biology)DatabaseOperating systemChemistryBotanyOrganic chemistryBiologyAdvanced Proteomics Techniques and ApplicationsMass Spectrometry Techniques and ApplicationsMetabolomics and Mass Spectrometry Studies
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