recipe bioconductor-tcc

This package provides a series of functions for performing differential expression analysis from RNA-seq count data using robust normalization strategy (called DEGES). The basic idea of DEGES is that potential differentially expressed genes or transcripts (DEGs) among compared samples should be removed before data normalization to obtain a well-ranked gene list where true DEGs are top-ranked and non-DEGs are bottom ranked. This can be done by performing a multi-step normalization strategy (called DEGES for DEG elimination strategy). A major characteristic of TCC is to provide the robust normalization methods for several kinds of count data (two-group with or without replicates, multi-group/multi-factor, and so on) by virtue of the use of combinations of functions in depended packages.

Homepage

https://bioconductor.org/packages/3.9/bioc/html/TCC.html

License

GPL-2

Recipe

/bioconductor-tcc/meta.yaml

Links

biotools: tcc

package bioconductor-tcc

(downloads) docker_bioconductor-tcc

Versions

1.22.0-0, 1.20.1-0, 1.18.0-0

Depends bioconductor-bayseq

>=2.16.0,<2.17.0

Depends bioconductor-deseq

>=1.34.0,<1.35.0

Depends bioconductor-deseq2

>=1.22.0,<1.23.0

Depends bioconductor-edger

>=3.24.0,<3.25.0

Depends bioconductor-roc

>=1.58.0,<1.59.0

Depends r-base

>=3.5.1,<3.5.2.0a0

Requirements

Installation

With an activated Bioconda channel (see 2. Set up channels), install with:

conda install bioconductor-tcc

and update with:

conda update bioconductor-tcc

or use the docker container:

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

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

Link to this page

Render an install-with-bioconda 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-tcc/README.html)