Skip to content

Update README.md #19

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
iamakhilverma wants to merge 1 commit into
base: main
Choose a base branch
from
Open

Update README.md #19

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
7 changes: 4 additions & 3 deletions README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,14 +1,15 @@
# The single-cell **Co**lorectal **C**ancer **A**tlas

> Marteau V., Nemati N., Handler K., ... & Arnold IC, Salcher S., Trajanoski Z. (2025). Single-cell integration and multi-modal profiling reveals phenotypes and spatial organization of neutrophils in colorectal cancer. bioRxiv. [doi:10.1101/2024.08.26.609563](https://www.biorxiv.org/content/10.1101/2024.08.26.609563)
> Marteau V., Nemati N., Handler K., ... & Arnold IC, Salcher S., Trajanoski Z. (2026). Single-cell integration and multi-modal profiling reveals phenotypes and spatial organization of neutrophils in colorectal cancer. Cancer Cell, 44, 146-165.e14. [doi:10.1016/j.ccell.2025.12.003](https://www.cell.com/cancer-cell/fulltext/S1535-6108(25)00537-9)

The single cell colorectal cancer atlas is a resource integrating more than 4.27 million cells from 650 patients across 49 studies (77 datasets) representing 7 billion expression values. These samples encompass the full spectrum of disease progression, from normal colon to polyps, primary tumors, and metastases, covering both early and advanced stages of CRC.

The atlas is publicly available for interactive exploration through a *cell-x-gene* instance. We also provide
`h5ad` objects which allows custom analyses of the atlas. For more information, check out the

* [project website](https://crc.icbi.at) and
* our [preprint](https://www.biorxiv.org/content/10.1101/2024.08.26.609563).
* [project website](https://crc.icbi.at),
* [publication](https://www.cell.com/cancer-cell/fulltext/S1535-6108(25)00537-9), and
* [preprint](https://www.biorxiv.org/content/10.1101/2024.08.26.609563).

This repository contains the source-code to reproduce the single-cell data analysis for the paper.
The analyses are wrapped into [nextflow](https://github.com/nextflow-io/nextflow/) pipelines, all dependencies are
Expand Down