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baredSC: Bayesian Approach to Retreive Expression Distribution of Single Cell

Project description

baredSC

PyPI Version DOI

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.

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Visit our documentation to see the possible options and follow the tutorials.

Citation

If you are using baredSC, please cite our biorxiv paper.

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