https://github.com/murrellgroup/codonmolecularevolution.jl
https://github.com/murrellgroup/codonmolecularevolution.jl
Last synced: 10 months ago
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- Host: GitHub
- URL: https://github.com/murrellgroup/codonmolecularevolution.jl
- Owner: MurrellGroup
- License: mit
- Created: 2023-08-15T12:00:07.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2025-06-17T20:00:35.000Z (12 months ago)
- Last Synced: 2025-07-17T23:43:35.305Z (11 months ago)
- Language: Julia
- Size: 3.08 MB
- Stars: 3
- Watchers: 2
- Forks: 3
- Open Issues: 13
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# CodonMolecularEvolution.jl
[](https://MurrellGroup.github.io/CodonMolecularEvolution.jl/dev/)
[](https://codecov.io/gh/MurrellGroup/CodonMolecularEvolution.jl)
[](https://github.com/MurrellGroup/CodonMolecularEvolution.jl/actions/workflows/CI.yml?query=branch%3Amain)
Descendant of [MolecularEvolution.jl](https://github.com/MurrellGroup/MolecularEvolution.jl), specializing in codon models. The current dN/dS catalogue consists of
- FUBAR
- difFUBAR
To run our models in the cloud, see [ColabMolecularEvolution](https://github.com/MurrellGroup/ColabMolecularEvolution).
## Installation
In a julia REPL, type
`]add CodonMolecularEvolution`
## Documentation
https://MurrellGroup.github.io/CodonMolecularEvolution.jl
## Extensions
To trigger our plotting extension, one must `using Plots, Phylo`.
## Examples
This section demonstrates how to use our dN/dS models with real biological data, showcasing both the input requirements and the type of evolutionary insights you can obtain.
```julia
using MolecularEvolution, FASTX, CodonMolecularEvolution
```
**Note**: To enable plotting, one would add `using Plots, Phylo`.
### FUBAR
We perform FUBAR analysis on [this FASTA file](https://raw.githubusercontent.com/MurrellGroup/CodonMolecularEvolution.jl/main/test/data/Ace2_with_bat/Ace2_with_bat.fasta), and a phylogeny from [this Newick tree file](https://raw.githubusercontent.com/MurrellGroup/CodonMolecularEvolution.jl/main/test/data/Ace2_with_bat/Ace2_with_bat.tre).
```julia
# Read data
outdir = "fubar"
seqnames, seqs = read_fasta("Ace2_with_bat.fasta")
treestring = readlines("Ace2_with_bat.tre")[1]
# Perform analysis
fgrid = alphabetagrid(seqnames, seqs, treestring);
method = DirichletFUBAR() # Standard FUBAR
fubar_df, params = FUBAR_analysis(method, fgrid, analysis_name=outdir*"/Ace2_with_bat");
```
The above call will write results to `outdir*"/Ace2_with_bat"`, but here we only display what's written to sdout
```
Step 1: Initialization.
Step 2: Optimizing global codon model parameters.
Optimized single α,β LL=-66072.56532041529 with α=1.940881909909932 and β=0.7757100788818039.
Step 3: Calculating conditional likelihoods.
Step 4: Model fitting.
Step 5: Tabulating results.
19 sites with positive selection above threshold.
487 sites with purifying selection above threshold.
```
Now we show some of the above-threshold sites
```julia
above_threshold_sites = fubar_df[(fubar_df.positive_posterior .> 0.95) .| (fubar_df.purifying_posterior .> 0.95), :]
above_threshold_sites[1:10, :]
```
```
10×5 DataFrame
Row │ site positive_posterior purifying_posterior beta_posterior_mean alpha_posterior_mean
│ Int64 Float64 Float64 Float64 Float64
─────┼─────────────────────────────────────────────────────────────────────────────────────
1 │ 1 0.00564089 0.985948 0.0126755 1.42783
2 │ 4 5.12413e-5 0.998737 0.218888 1.12801
3 │ 6 0.0092943 0.981231 0.0227715 1.47458
4 │ 9 0.0118501 0.964818 0.0658507 0.392239
5 │ 11 2.29686e-8 0.999994 0.277966 2.10407
6 │ 15 1.43323e-6 0.999887 0.20953 1.42799
7 │ 17 0.000436892 0.995299 0.199044 0.917965
8 │ 19 8.04229e-9 0.999999 0.152897 2.47035
9 │ 25 0.000141827 0.996911 0.275294 1.36792
10 │ 27 0.995895 3.74494e-5 2.94698 1.05116
```
### difFUBAR (awaiting the correct link)
We perform difFUBAR analysis on [this FASTA file](https://raw.githubusercontent.com/MurrellGroup/CodonMolecularEvolution.jl/main/test/data/Ace2_no_background/Ace2_tiny_test.fasta), and a tagged phylogeny from [this NEXUS tree file](https://raw.githubusercontent.com/MurrellGroup/CodonMolecularEvolution.jl/main/test/data/Ace2_no_background/Ace2_no_background.nex).
```julia
# Read data
analysis_name = "difFUBAR/Ace2_tiny"
seqnames,seqs = read_fasta("data/Ace2_tiny_test.fasta");
treestring, tags, tag_colors = import_colored_figtree_nexus_as_tagged_tree("data/Ace2_no_background.nex")
# Perform analysis
df,results = difFUBAR(seqnames, seqs, treestring, tags, analysis_name);
```
`difFUBAR` will write its results to the export directory `analysis_name`,
but here we show a short-hand representation of the results, which are written to stdout.
```
Step 1: Initialization. If exports = true, tree showing the assignment of branches to groups/colors will be exported to: output/Ace2_tagged_input_tree.svg.
Step 2: Optimizing global codon model parameters.
0.0% 29.0% 58.0% 87.0%
Step 4: Running Gibbs sampler to infer site categories.
Step 5: Tabulating and plotting. Detected sites:
Site 3 - P(ω1 > ω2):0.0075; P(ω2 > ω1):0.9805; P(ω1 > 1):0.1205; P(ω2 > 1):0.9675
Site 13 - P(ω1 > ω2):0.0175; P(ω2 > ω1):0.9605; P(ω1 > 1):0.13; P(ω2 > 1):0.9305
```