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Sage: proteomics searching so fast it seems like magic

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For more information please read the online documentation!

Introduction

Sage is, at it's core, a proteomics database search engine - a tool that transforms raw mass spectra from proteomics experiments into peptide identifications via database searching & spectral matching.

However, Sage includes a variety of advanced features that make it a one-stop shop: retention time prediction, quantification (both isobaric & LFQ), peptide-spectrum match rescoring, and FDR control. You can directly use results from Sage without needing to use other tools for these tasks.

Additionally, Sage was designed with cloud computing in mind - massively parallel processing and the ability to directly stream compressed mass spectrometry data to/from AWS S3 enables unprecedented search speeds with minimal cost.

Sage also runs just as well reading local files from your Mac/PC/Linux device!

Why use Sage instead of other tools?

Sage is simple to configure, powerful and flexible. It also happens to be well-tested, mind-boggingly fast, open-source (MIT-licensed) and free.

Citation

If you use Sage in a scientific publication, please cite the following paper:

Sage: An Open-Source Tool for Fast Proteomics Searching and Quantification at Scale

Features

Interoperability

Sage is well-integrated into the open-source proteomics ecosystem. The following projects support analyzing results from Sage (typically in addition to other tools), or redistribute Sage binaries for use in their pipelines.

  • SearchGUI: a graphical user interface for running searches
  • PeptideShaker: visualize peptide-spectrum matches
  • MS2Rescore: AI-assisted rescoring of results
  • Picked group FDR: scalable protein group FDR for large-scale experiments
  • sagepy: Python bindings to the sage-core library
  • quantms: nextflow pipeline for running searches with Sage
  • OpenMS: Sage is included as a "TOPP" tool in OpenMS
  • sager: R package for analyzing results from Sage searches
  • If your project supports Sage and it's not listed, please open a pull request! If you need help integrating or interfacing with Sage in some way, please reach out.

Check out the (now outdated) blog post introducing the first version of Sage for more information and full benchmarks!