From 04378433adceb93a8d1f6d3810647aefda63852c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?J=C3=A9r=C3=A9mie=20Kalfon?= Date: Wed, 13 Nov 2024 16:10:22 +0100 Subject: [PATCH] Update README.md --- README.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index f8baea8..769325b 100644 --- a/README.md +++ b/README.md @@ -10,6 +10,8 @@ [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) [![DOI](https://img.shields.io/badge/DOI-10.1101%2F2024.07.29.605556-blue)](https://doi.org/10.1101/2024.07.29.605556) + + GRnnData works similarly to anndata. The goal was to use the .varm/.varp of anndata to store the GRN data associated with a dataset and have a formal way to work with GRNs. GRnnData is a subclass of anndata.AnnData, it enforces only that a .varp exists for the anndata @@ -17,7 +19,6 @@ GRnnData is a subclass of anndata.AnnData, it enforces only that a .varp exists GRnnData also contains multiple helper functions to work with GRNs in scRNAseq like compute_connectivities, get_centrality, compute_cluster, enrichment, metrics, etc. but also accessing the grn with .grn, .targets, .regulators,... The package has been designed together with the [scPRINT paper](https://doi.org/10.1101/2024.07.29.605556) and [model](https://github.com/cantinilab/scPRINT), and the GRN benchmarking tool [BenGRN](https://github.com/jkobject/BenGRN) - ## Install it from PyPI ```bash