Skip to content

cmap/lincs-workshop-2020

main
Switch branches/tags

Name already in use

A tag already exists with the provided branch name. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Are you sure you want to create this branch?
Code

Latest commit

 

Git stats

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
 
 
 
 
 
 
 
 

Connectivity Map/LINCS Workshop

The Connectivity Map (CMap) project at the Broad Institute is focused on generating a public resource of high-dimensional perturbational signatures of cell state that can be leveraged to accelerate functional hypothesis generation. This project is part of a larger NIH-funded effort called the Library of Integrated Network-Based Cellular Signatures (LINCS).

This repository contains notebooks from used in the Connectivity Map/LINCS 2020 workshop, hosted virtually on December 17 & 18, 2020. The notebooks will be reviewed during the workshop, but they are also posted here for reference. This repository will serve as a public resource of code demonstrating how to interact with and access CMap data stored in Google BigQuery, as well as other common formats such as GCTx.

Content

The content in this repository is organized into a few sections, listed below.

Data Access

notebooks/data_access

CMap has generated a dataset of over 3M gene expression profiles. These data are stored in Google BigQuery in ortder to faciliate access to arbitrary subsets of the dataset. The notebooks in this section illustrate how to query and access these data using an API, and the CMap BQ Toolkit, written in python.

Analyzing Gene Expression Data

notebooks/gene_expression

In addition to BigQuery, CMap data are provided in the GCTx file format. GCTx files are annotated data matrices that support access to arbitrary subsets of the data matrix. The notebooks in this section illustrate how to parse GCTx files and perform common analyses on CMap data and metadata using the packages cmapR and cmapPy.

Analyzing Cell Fitness Data

notebooks/cell_fitness

Similar to gene expression, there are ongoing efforts at the Broad Institute and other LINCS centers to generate perturbational signatures of cell fitness. The notebooks in this section contain exploratory analyses of perturbational cell viability data generated using the PRISM assay.

References

About

CMap Notebooks for LINCS 2020 Workshop

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published