Skip to content

Predicting single-cell glycosylation features from scRNA-seq

License

Notifications You must be signed in to change notification settings

BojarLab/scGlycomics_b16_branching

Repository files navigation

Deep Learning Explains the Biology of Branched Glycans from Single-Cell Sequencing Data

This repository contains the code and the trained model from our recent preprint "Deep Learning Explains the Biology of Branched Glycans from Single-Cell Sequencing Data" (Qin et al., 2022), made by https://github.com/rruiqin. In this work, we demonstrate a method to gain insight into the multimodal role of glycans by analyzing paired single-cell transcriptomics data and lectin-sequencing via a dedicated deep learning model.

The processed RNA and PHA-L reads can be found here.

About

Predicting single-cell glycosylation features from scRNA-seq

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published