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ReDeeM: Repository for Deep Learning Models for Mass Spectrometry

ReDeeM is a Rust crate designed for implementing deep learning models specifically tailored for mass spectrometry data. The primary goal of this project is to facilitate the prediction of peptide properties and to develop classifier scoring models (TDA).

Usage

The ReDeeM crates are designed to be used as a library in other projects, i.e. in Sage. To use the ReDeeM crates, add the following to your Cargo.toml file:

[dependencies]
redeem-properties = { git = "https://github.com/singjc/redeem.git", branch = "master" }
redeem-classifiers = { git = "https://github.com/singjc/redeem.git", branch = "master" }

Note: The ReDeeM crates are still under development and are not yet available on crates.io.

Current Crates

The ReDeeM project consists of two primary crates:

1. redeem-properties:

   • This crate focuses on deep learning models for peptide property prediction. It implements models for predicting retention time (RT), ion mobility (IM), and MS2 fragment intensities using the Candle library.

   • The models can be trained, fine-tuned on new data and can be saved in the safetensor format for later use.

   • Current Models

   Model	Name	Architecture	Implemented
   AlphaPept RT Model	rt_cnn_lstm	CNN-LSTM	✔️
   AlphaPept MS2 Model	ms2_bert	Bert	✔️
   AlphaPept CCS Model	ccs_cnn_lstm	CNN-LSTM	✔️
   RT Model	rt_tf_lstm	CNN-Transformer	✔️
   CCS Model	ccs_tf_lstm	CNN-Transformer	✔️

2. redeem-classifiers:

   • This crate is aimed at developing semi-supervised scoring classifier models. The goal is to create models for separating target peptides from decoys.

   • Current Models

   Model	Name	Architecture	Implemented
   XGBoost Classifier	redeem_classifiers::XGBoostClassifier	XGBoost	✔️
   GBDT Classifier	redeem_classifiers::GBDTClassifier	GBDT	✔️
   SVM Classifier	redeem_classifiers::SVMClassifier	SVM	✔️

Note

To use the XGBoost classifier, or the SVM classifier, you need to compile with the --features xgboost or --features linfa flag respectively.

Important

The XGBoost crate is a wrapper around the original XGBoost library, which requires clang/c++ to be installed on the system. On Ubuntu, you can do the following:

```bash
sudo apt update
sudo apt install build-essential
sudo apt install clang
sudo apt install libstdc++-12-dev
```