Description
Functional Shannon Entropy for Virome Mutational Analysis.
Description
Estimates Shannon entropy, per gene and per genomic position, associated with non-synonymous mutation frequencies in viral populations, such as wastewater samples. The package uses codon translations for functional insights. Each amino acid can be treated as an individual state, resulting in a 20-state entropy computation, or grouped into one of six physicochemical classes, adding further functional context. Provides normalized values (0-1 scale) to facilitate the direct comparison of different genomic positions or total functional entropy across multiple metagenomes. Designed to analyze mutational data using tabular 'Single Nucleotide Variant' (SNV) frequency tables generated by variant callers (e.g., 'iVar' or 'LoFreq'), operating independently of consensus sequence estimation and multiple sequence alignment.
README.md
Metaentropy
The goal of Metaentropy is to …
Installation
You can install the development version of Metaentropy like so:
# FILL THIS IN! HOW CAN PEOPLE INSTALL YOUR DEV PACKAGE?
Example
This is a basic example which shows you how to solve a common problem:
library(Metaentropy)
## basic example code
What is special about using README.Rmd instead of just README.md? You can include R chunks like so:
summary(cars)
#> speed dist
#> Min. : 4.0 Min. : 2.00
#> 1st Qu.:12.0 1st Qu.: 26.00
#> Median :15.0 Median : 36.00
#> Mean :15.4 Mean : 42.98
#> 3rd Qu.:19.0 3rd Qu.: 56.00
#> Max. :25.0 Max. :120.00
You’ll still need to render README.Rmd regularly, to keep README.md up-to-date. devtools::build_readme() is handy for this.
You can also embed plots, for example:
In that case, don’t forget to commit and push the resulting figure files, so they display on GitHub and CRAN.