- recipe bioconductor-sscu
Strength of Selected Codon Usage
- Homepage:
- License:
GPL (>= 2)
- Recipe:
- Links:
biotools: sscu, doi: 10.1038/nmeth.3252
The package calculates the indexes for selective stength in codon usage in bacteria species. (1) The package can calculate the strength of selected codon usage bias (sscu, also named as s_index) based on Paul Sharp's method. The method take into account of background mutation rate, and focus only on four pairs of codons with universal translational advantages in all bacterial species. Thus the sscu index is comparable among different species. (2) The package can detect the strength of translational accuracy selection by Akashi's test. The test tabulating all codons into four categories with the feature as conserved/variable amino acids and optimal/non-optimal codons. (3) Optimal codon lists (selected codons) can be calculated by either op_highly function (by using the highly expressed genes compared with all genes to identify optimal codons), or op_corre_CodonW/op_corre_NCprime function (by correlative method developed by Hershberg & Petrov). Users will have a list of optimal codons for further analysis, such as input to the Akashi's test. (4) The detailed codon usage information, such as RSCU value, number of optimal codons in the highly/all gene set, as well as the genomic gc3 value, can be calculate by the optimal_codon_statistics and genomic_gc3 function. (5) Furthermore, we added one test function low_frequency_op in the package. The function try to find the low frequency optimal codons, among all the optimal codons identified by the op_highly function.
- package bioconductor-sscu¶
- Versions:
2.40.0-0,2.36.0-0,2.32.0-0,2.30.0-0,2.28.0-0,2.24.0-0,2.22.0-0,2.20.0-1,2.20.0-0,2.40.0-0,2.36.0-0,2.32.0-0,2.30.0-0,2.28.0-0,2.24.0-0,2.22.0-0,2.20.0-1,2.20.0-0,2.18.0-0,2.16.0-0,2.14.0-1,2.12.0-0,2.10.0-0,2.8.0-0,2.6.0-0- Depends:
on bioconductor-biocgenerics
>=0.56.0,<0.57.0on bioconductor-biostrings
>=2.78.0,<2.79.0on r-base
>=4.5,<4.6.0a0on r-seqinr
>=3.1-3
- 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-sscu
to add into an existing workspace instead, run:
pixi add bioconductor-sscu
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-sscu
Alternatively, to install into a new environment, run:
conda create -n envname bioconductor-sscu
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-sscu:<tag>
(see bioconductor-sscu/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:
[](http://bioconda.github.io/recipes/bioconductor-sscu/README.html)
