/DeepFLR

GitHub Desktop tutorial repository

Primary LanguagePythonBSD 3-Clause "New" or "Revised" LicenseBSD-3-Clause

DeepFLR

DeepFLR is a deep learning-based framework that accurately predicts phosphopeptides spectra and effectively controls false localization rates in phosphoproteomics.

Requirements

Model construction was performed using python (3.8.3, Anaconda distribution version 5.3.1, https://www.anaconda.com/) with the following packages: FastNLP (0.6.0), pytorch (1.8.1), transformers (4.12.5), bidict (0.22.0) and pyteomics (4.5.5).

Data analysis for FLR estimation was performed using python (3.8.3) with the following packages: pandas (1.0.5) and numpy (1.18.5).

Users can install packages using the command provided in the User Guide, or use the “pip install -r requirements.txt” command to install all the required packages.

Tutorial

Tutorials are avaliable in User guide.docx.

Model

Users can either use the model parameters used in DeepFLR or finetune the model or retrain a model following the User guide.docx. The Model parameters "best__2deepchargeModelms2_bert_mediancos_2021-09-20-01-17-50-729399" (329 MB) can be downloaded from Model and put it in phosT folder.

Publications

Waiting for publication...(paper)

License

DeepFLR is distributed under a BSD license. See the LICENSE file for details.

Contacts

Please report any problems directly to the github issue tracker. Also, you can send feedback to liang_qiao@fudan.edu.cn.