DIA-NN (Data-Independent Acquisition by Neural Networks) is a universal software suite for DIA proteomics data analysis. Processes raw mass spectrometry files (.mzML, .raw, .d, .wiff) using neural net
Use with AI
Install the MCP server or CLI to instantly fetch DIA-NN (diann-nextflow) documentation:
Install command
claude mcp add biocontext7 -- npx @biocontext7/mcpOr share this page: biocontext7.com/tools/diann-nextflow
FlashLFQ — ultrafast label-free quantification for mass spectrometry proteomics. Quantifies peptide and protein abundances from MS/MS identifications using peak detection on raw/mzML spectra. Supports
2 shared topics • 2 shared operations
MSstats — Bioconductor R package for statistical analysis of quantitative mass spectrometry-based proteomics experiments. Supports label-free DDA, TMT, iTRAQ, SRM/MRM, and DIA workflows. Provides prep
2 shared topics • 2 shared operations
AlphaPept — Python-based, open-source proteomics pipeline for DDA mass spectrometry data analysis. Provides feature detection, peptide identification via database search, deep learning-based scoring,
2 shared topics • 1 shared operation
Comet — open-source tandem mass spectrometry (MS/MS) sequence database search engine for peptide identification. Searches MS/MS spectra against FASTA protein databases producing pepXML, mzIdentML, SQT
2 shared topics • 1 shared operation
MaxQuant — quantitative proteomics platform for analyzing large-scale mass spectrometry data. Integrates the Andromeda search engine for peptide identification, supports label-free quantification (LFQ
2 shared topics • 1 shared operation