- recipe bioconductor-cetf
Coexpression for Transcription Factors using Regulatory Impact Factors and Partial Correlation and Information Theory analysis
- Homepage:
- License:
GPL-3
- Recipe:
This package provides the necessary functions for performing the Partial Correlation coefficient with Information Theory (PCIT) (Reverter and Chan 2008) and Regulatory Impact Factors (RIF) (Reverter et al. 2010) algorithm. The PCIT algorithm identifies meaningful correlations to define edges in a weighted network and can be applied to any correlation-based network including but not limited to gene co-expression networks, while the RIF algorithm identify critical Transcription Factors (TF) from gene expression data. These two algorithms when combined provide a very relevant layer of information for gene expression studies (Microarray, RNA-seq and single-cell RNA-seq data).
- package bioconductor-cetf¶
- versions:
1.14.0-0,1.12.0-0,1.9.0-0,1.6.0-2,1.6.0-1,1.6.0-0,1.4.0-0,1.2.4-0,1.2.2-0,1.14.0-0,1.12.0-0,1.9.0-0,1.6.0-2,1.6.0-1,1.6.0-0,1.4.0-0,1.2.4-0,1.2.2-0,1.0.1-0- depends bioconductor-clusterprofiler:
>=4.10.0,<4.11.0- depends bioconductor-clusterprofiler:
>=4.10.0,<4.11.0a0- depends bioconductor-complexheatmap:
>=2.18.0,<2.19.0- depends bioconductor-complexheatmap:
>=2.18.0,<2.19.0a0- depends bioconductor-deseq2:
>=1.42.0,<1.43.0- depends bioconductor-deseq2:
>=1.42.0,<1.43.0a0- depends bioconductor-rcy3:
>=2.22.0,<2.23.0- depends bioconductor-rcy3:
>=2.22.1,<2.23.0a0- depends bioconductor-s4vectors:
>=0.40.0,<0.41.0- depends bioconductor-s4vectors:
>=0.40.2,<0.41.0a0- depends bioconductor-summarizedexperiment:
>=1.32.0,<1.33.0- depends bioconductor-summarizedexperiment:
>=1.32.0,<1.33.0a0- depends libblas:
>=3.9.0,<4.0a0- depends libgcc-ng:
>=12- depends liblapack:
>=3.9.0,<4.0a0- depends libstdcxx-ng:
>=12- depends r-base:
>=4.3,<4.4.0a0- depends r-circlize:
- depends r-dplyr:
- depends r-genomictools.filehandler:
- depends r-ggally:
- depends r-ggnetwork:
- depends r-ggplot2:
- depends r-ggpubr:
- depends r-ggrepel:
- depends r-igraph:
- depends r-matrix:
- depends r-network:
- depends r-rcpp:
- depends r-rcpparmadillo:
- requirements:
- additional platforms:
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-cetf and update with:: mamba update bioconductor-cetf
To create a new environment, run:
mamba create --name myenvname bioconductor-cetf
with
myenvnamebeing 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-cetf:<tag> (see `bioconductor-cetf/tags`_ for valid values for ``<tag>``)
Download stats¶
Link to this page¶
Render an 
badge with the following MarkDown:
[](http://bioconda.github.io/recipes/bioconductor-cetf/README.html)
