recipe bioconductor-scshapes

A Statistical Framework for Modeling and Identifying Differential Distributions in Single-cell RNA-sequencing Data

Homepage:

https://bioconductor.org/packages/3.18/bioc/html/scShapes.html

License:

GPL-3

Recipe:

/bioconductor-scshapes/meta.yaml

We present a novel statistical framework for identifying differential distributions in single-cell RNA-sequencing (scRNA-seq) data between treatment conditions by modeling gene expression read counts using generalized linear models (GLMs). We model each gene independently under each treatment condition using error distributions Poisson (P), Negative Binomial (NB), Zero-inflated Poisson (ZIP) and Zero-inflated Negative Binomial (ZINB) with log link function and model based normalization for differences in sequencing depth. Since all four distributions considered in our framework belong to the same family of distributions, we first perform a Kolmogorov-Smirnov (KS) test to select genes belonging to the family of ZINB distributions. Genes passing the KS test will be then modeled using GLMs. Model selection is done by calculating the Bayesian Information Criterion (BIC) and likelihood ratio test (LRT) statistic.

package bioconductor-scshapes

(downloads) docker_bioconductor-scshapes

versions:

1.8.0-01.6.0-01.4.0-01.0.0-0

depends bioconductor-biocparallel:

>=1.36.0,<1.37.0

depends r-base:

>=4.3,<4.4.0a0

depends r-dgof:

depends r-emdbook:

depends r-magrittr:

depends r-mass:

depends r-matrix:

depends r-pscl:

depends r-vgam:

requirements:

Installation

You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install bioconductor-scshapes

and update with::

   mamba update bioconductor-scshapes

To create a new environment, run:

mamba create --name myenvname bioconductor-scshapes

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull quay.io/biocontainers/bioconductor-scshapes:<tag>

(see `bioconductor-scshapes/tags`_ for valid values for ``<tag>``)

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