/asi_sig_hackathon

My notebooks to test some tools

Primary LanguageJupyter NotebookMIT LicenseMIT

Hackathon ASI 2022

Overview

This repository contains scripts and generated data to assist in the 2022 ASI Systems Immunology Hackathon. The challanges in the Hackathon are

  1. Minimal cluster identification/marker extraction: Identifying the ideal/minimal (i.e. 12-15) protein marker combinations to identify the maximal number of cell clusters based on RNA ± CITE-seq reference data set.
    • 1a Novel pipeline that allows extraction
    • 1b Utility: Lead to better panel choice for subsequent experiments
    • 1c Reference of rank order gene-protein correlation values (e.g. CD8 terrible with RNA, great with protein)
    • 1d Create minimal marker reference from dataset that can evolve for people to split into all immune subsets. Ala Simon Haas but better? Different?
    • 1e Novel biomarker identification from clinical cohorts
  2. Cell-cell, protein-protein interaction (visualisation? More refined? Interpretation?)
    • 2a Don’t reinvent the great databases out there? Rather leverage these so immunologists can better use them
    • 3b Interfacing with the proteogenomics data
  3. Can we use RNA+protein references to inform genes likely to be expressed in FACS subsets? Vice versa?
    • 3a Hopefully have a normalised reference FACS whole blood data set. Perhaps healthy vs COVID

Paper and datasets

The datasets for this Hackathon are taken from two papers: Liu_et_al_Cell_2021_COVID and Triana_et_al_Nat_Immunol_2021_Leukemia. Instructions for downloading the data can be found in Angli's page here.

Code and generated data

The notebooks in this repo describe a probably optional background correction step, followed by integration with MOFA/WNN to examine the new embeddings and factors.