baredSC: Bayesian Approach to Retreive Expression Distribution of Single Cell
Project description
baredSC
baredSC (Bayesian Approach to Retreive Expression Distribution of Single Cell) is a tool that uses a Monte-Carlo Markov Chain to estimate a confidence interval on the probability density function (PDF) of expression of one or two genes from single-cell RNA-seq data. It uses the raw counts and the total number of UMI for each cell. The PDF is approximated by a number of 1d or 2d gaussians provided by the user. The likelihood is estimated using the asumption that the raw counts follow a Poisson distribution of parameter equal to the proportion of mRNA for the gene in the cell multiplied by the total number of UMI identified in this cell.
Documentation
Visit our documentation to see the possible options and follow the tutorials.
Citation
If you are using baredSC, please cite our biorxiv paper.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file baredSC-1.1.3.tar.gz
.
File metadata
- Download URL: baredSC-1.1.3.tar.gz
- Upload date:
- Size: 4.7 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.0.0 CPython/3.9.18
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | f173e6037119a0879d73e3c79f3d601c26e2bcc370552e6a161045f6106d5781 |
|
MD5 | caafbaf6e25dd4625ef89a6d9cc45dc6 |
|
BLAKE2b-256 | 80ee9369a44a59dbb5615dfb16c8bcd9552fe47ea13be70347ba2656ca3d18a0 |
File details
Details for the file baredSC-1.1.3-py3-none-any.whl
.
File metadata
- Download URL: baredSC-1.1.3-py3-none-any.whl
- Upload date:
- Size: 49.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.0.0 CPython/3.9.18
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3b030b644c50fb1c5a8adeb4a22336f778cb6a13075ae191bebe5049e999e325 |
|
MD5 | 32fa34dbeac5d1d1016372ee485a4cea |
|
BLAKE2b-256 | b7566698eb9dde73b0f2dc936123419bb5251f64862a7c15fe68d6e9a09dbc52 |