Package: sscu 2.35.0
Yu Sun
sscu: Strength of Selected Codon Usage
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.
Authors:
sscu_2.35.0.tar.gz
sscu_2.35.0.zip(r-4.5)sscu_2.35.0.zip(r-4.4)sscu_2.35.0.zip(r-4.3)
sscu_2.35.0.tgz(r-4.4-any)sscu_2.35.0.tgz(r-4.3-any)
sscu_2.35.0.tar.gz(r-4.5-noble)sscu_2.35.0.tar.gz(r-4.4-noble)
sscu_2.35.0.tgz(r-4.4-emscripten)sscu_2.35.0.tgz(r-4.3-emscripten)
sscu.pdf |sscu.html✨
sscu/json (API)
NEWS
| # Install 'sscu' in R: |
| install.packages('sscu', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
On BioConductor:sscu-2.35.0(bioc 3.20)sscu-2.34.0(bioc 3.19)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 months agofrom:5ebec20aa5
Exports:akashi_testgenomic_gc3low_frequency_opop_corre_CodonWop_corre_NCprimeop_highlyop_highly_statss_index
Dependencies:ade4askpassBiocGenericsBiostringscrayoncurlGenomeInfoDbGenomeInfoDbDatahttrIRangesjsonlitelatticeMASSmimenlmeopensslpixmapR6RcppRcppArmadilloS4VectorssegmentedseqinrspsysUCSC.utilsXVectorzlibbioc
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Strength of Selected Codon Usage | sscu-package |
| akashi test for codon usage | akashi_test |
| genomic gc3 for an multifasta genomic file | genomic_gc3 |
| the function identify low frequency optimal codons | low_frequency_op |
| Identify optimal codons by using the correlative method from Hershberg & Petrov, the input file is from CodonW | op_corre_CodonW |
| Identify optimal codons by using the correlative method from Hershberg & Petrov, the input file is from NCprime | op_corre_NCprime |
| Identify optimal codons by using the highly expressed genes method | optimal_codons op_highly selected_codons |
| statistics for the optimal codons | optimal_codons_table optimal_codon_statistics op_highly_stats |
| S index (Strength of Selected Codon Usage) | s_index |
