recipe bioconductor-rifi

'rifi' analyses data from rifampicin time series created by microarray or RNAseq

Homepage:

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

License:

GPL-3 + file LICENSE

Recipe:

/bioconductor-rifi/meta.yaml

'rifi' analyses data from rifampicin time series created by microarray or RNAseq. 'rifi' is a transcriptome data analysis tool for the holistic identification of transcription and decay associated processes. The decay constants and the delay of the onset of decay is fitted for each probe/bin. Subsequently, probes/bins of equal properties are combined into segments by dynamic programming, independent of a existing genome annotation. This allows to detect transcript segments of different stability or transcriptional events within one annotated gene. In addition to the classic decay constant/half-life analysis, 'rifi' detects processing sites, transcription pausing sites, internal transcription start sites in operons, sites of partial transcription termination in operons, identifies areas of likely transcriptional interference by the collision mechanism and gives an estimate of the transcription velocity. All data are integrated to give an estimate of continous transcriptional units, i.e. operons. Comprehensive output tables and visualizations of the full genome result and the individual fits for all probes/bins are produced.

package bioconductor-rifi

versions:

1.6.0-0,  1.4.1-0,  1.2.0-0

depends bioconductor-rtracklayer:

>=1.62.0,<1.63.0

depends bioconductor-s4vectors:

>=0.40.0,<0.41.0

depends bioconductor-summarizedexperiment:

>=1.32.0,<1.33.0

depends r-base:

>=4.3,<4.4.0a0

depends r-car:

depends r-cowplot:

depends r-domc:

depends r-dplyr:

depends r-egg:

depends r-foreach:

depends r-ggplot2:

depends r-nls2:

depends r-nnet:

depends r-reshape2:

depends r-rlang:

depends r-scales:

depends r-stringr:

depends r-tibble:

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-rifi

and update with::

   mamba update bioconductor-rifi

To create a new environment, run:

mamba create --name myenvname bioconductor-rifi

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-rifi:<tag>

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

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