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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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