Decipher is a single-cell analysis package to integrate and compare perturbed samples to healthy samples, to identify the origin of the cell-states perturbations.
Project description
Decipher
Decipher is a single-cell analysis toolkit to jointly analyze samples from distinct conditions (e.g. normal vs perturbed samples).
Install
Decipher is available on PyPI under the name scdecipher
.
Step 1 (optional but recommended)
Create a conda environment with a recent Python version: conda create -n "decipher-env" python=3.11
Step 2
Install Decipher: pip install scdecipher
Quickstart tutorials
The data used in the tutorial can be downloaded from here.
Directories
.
├── decipher: Source code
└── examples: Examples and tutorials
How to cite Decipher
Please cite our preprint: https://www.biorxiv.org/content/10.1101/2023.11.11.566719v1
Deep generative model Deciphers derailed trajectories in Acute Myeloid Leukemia
BibTex
@article {Nazaret2023.11.11.566719,
title = {Deep generative model deciphers derailed trajectories in acute myeloid leukemia},
author = {Achille Nazaret and Joy Linyue Fan and Vincent-Philippe Lavallee and Andrew E. Cornish and Vaidotas Kiseliovas and Ignas Masilionis and Jaeyoung Chun and Robert L. Bowman and Shira E. Eisman and James Wang and Lingting Shi and Ross L. Levine and Linas Mazutis and David Blei and Dana Pe'er and Elham Azizi},
journal = {bioRxiv}
year = {2023},
publisher = {Cold Spring Harbor Laboratory},
}
Chicago
Nazaret Achille, Fan Joy Linyue, Lavallee Vincent-Philippe, Cornish Andrew E., Kiseliovas Vaidotas et al. "Deep generative model deciphers derailed trajectories in acute myeloid leukemia." bioRxiv (2023).
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