Package Recipe 'bioconductor-tradeseq'

recipe bioconductor-tradeseq

trajectory-based differential expression analysis for sequencing data

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/tradeSeq.html
License:: MIT + file LICENSE
Recipe:: /bioconductor-tradeseq/meta.yaml

tradeSeq provides a flexible method for fitting regression models that can be used to find genes that are differentially expressed along one or multiple lineages in a trajectory. Based on the fitted models, it uses a variety of tests suited to answer different questions of interest, e.g. the discovery of genes for which expression is associated with pseudotime, or which are differentially expressed (in a specific region) along the trajectory. It fits a negative binomial generalized additive model (GAM) for each gene, and performs inference on the parameters of the GAM.

package bioconductor-tradeseq¶

Versions:

1.24.0-0, 1.20.0-0, 1.16.0-0, 1.14.0-0, 1.12.0-0, 1.8.0-0, 1.6.0-0, 1.4.0-1, 1.4.0-0,

1.24.0-0, 1.20.0-0, 1.16.0-0, 1.14.0-0, 1.12.0-0, 1.8.0-0, 1.6.0-0, 1.4.0-1, 1.4.0-0, 1.2.0-0, 1.0.0-0

Depends:

on bioconductor-biobase >=2.70.0,<2.71.0
on bioconductor-biocparallel >=1.44.0,<1.45.0
on bioconductor-edger >=4.8.0,<4.9.0
on bioconductor-s4vectors >=0.48.0,<0.49.0
on bioconductor-singlecellexperiment >=1.32.0,<1.33.0
on bioconductor-slingshot >=2.18.0,<2.19.0
on bioconductor-summarizedexperiment >=1.40.0,<1.41.0
on bioconductor-trajectoryutils >=1.18.0,<1.19.0
on r-base >=4.5,<4.6.0a0
on r-ggplot2
on r-igraph
on r-magrittr
on r-mass
on r-matrix
on r-matrixstats
on r-mgcv
on r-pbapply
on r-princurve
on r-rcolorbrewer
on r-tibble
on r-viridis

Additional platforms:

Installation¶

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi¶

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install bioconductor-tradeseq

to add into an existing workspace instead, run:

pixi add bioconductor-tradeseq

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda¶

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install bioconductor-tradeseq

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-tradeseq

with envname being the name of the desired environment.

Container¶

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

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

(see bioconductor-tradeseq/tags for valid values for <tag>).

Integrated deployment¶

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

Download stats¶

Link to this page¶

Render an badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-tradeseq/README.html)