### Install Hogwash Package

Source: https://github.com/katiesaund/hogwash/wiki/C)-Running-hogwash

Install the hogwash package from GitHub using devtools. This is a one-time installation.

```r
install.packages("devtools")
devtools::install_github("katiesaund/hogwash")
```

--------------------------------

### Install R Package from GitHub

Source: https://github.com/katiesaund/hogwash/blob/master/README.md

Use this command to install the hogwash package directly from its GitHub repository. Requires devtools.

```r
devtools::install_github("katiesaund/hogwash")
```

--------------------------------

### Install R Package from CRAN

Source: https://github.com/katiesaund/hogwash/blob/master/README.md

Use this command to install the hogwash package from CRAN. Ensure devtools is installed first.

```r
install.packages("devtools")
```

--------------------------------

### Run Continuous Test Example

Source: https://github.com/katiesaund/hogwash/wiki/C)-Running-hogwash

Execute the continuous test using example phenotype, genotype, and tree data. This demonstrates a basic usage of the hogwash() function.

```r
library(hogwash)
phenotype <- hogwash::growth
genotype <- hogwash::snp_genotype
tree <- hogwash::tree

hogwash(pheno = phenotype, 
        geno = genotype,  
        tree = tree)
```

--------------------------------

### Run Hogwash with Default Values

Source: https://github.com/katiesaund/hogwash/wiki/C)-Running-hogwash

Example of calling the hogwash() function with its default parameters. Ensure 'pheno', 'geno', and 'tree' are provided.

```r
library(hogwash)
hogwash(pheno, 
        geno,  
        tree,      
        tree_type = "phylogram",
        file_name = "hogwash",
        dir = ".",
        perm = 10000,
        fdr = 0.15,
        bootstrap = 0.70,
        group_genotype_key = NULL, 
        grouping_method = "post-ar",
        test = "both")
```

--------------------------------

### Load R Package

Source: https://github.com/katiesaund/hogwash/blob/master/README.md

Load the hogwash package into your R session after installation to use its functions.

```r
library(hogwash)
```

--------------------------------

### Run Synchronous Test and PhyC

Source: https://github.com/katiesaund/hogwash/wiki/C)-Running-hogwash

Execute both the synchronous test and the PhyC analysis using example data. This is useful for a comprehensive evolutionary analysis.

```r
library(hogwash)
phenotype <- hogwash::antibiotic_resistance
genotype <- hogwash::snp_genotype
tree <- hogwash::tree

hogwash(pheno = phenotype, 
        geno = genotype,  
        tree = tree, 
        test = "both")
```

--------------------------------

### Phylogenetic Signal Output

Source: https://github.com/katiesaund/hogwash/wiki/C)-Running-hogwash

Example output from the report_phylogenetic_signal() function, indicating how well the phenotype is modeled by Brownian Motion.

```text
[1] "The phenotype is modeled well by Brownian Motion; Pagel's lambda = 0.99993"
```

--------------------------------

### Run PhyC with SNP Grouping

Source: https://github.com/katiesaund/hogwash/wiki/C)-Running-hogwash

Execute the PhyC analysis with SNPs grouped into genes. This specifically targets PhyC for gene-level evolutionary insights.

```r
library(hogwash)
phenotype <- hogwash::antibiotic_resistance
genotype <- hogwash::snp_genotype
tree <- hogwash::tree
key <- hogwash::snp_gene_key

hogwash(pheno = phenotype, 
        geno = genotype,  
        tree = tree,      
        group_genotype_key = key, 
        test = "phyc", 
        grouping_method = "post-ar")
```

--------------------------------

### Run Continuous Test with SNP Grouping

Source: https://github.com/katiesaund/hogwash/wiki/C)-Running-hogwash

Perform the continuous test while grouping SNPs into genes using a provided key. This allows for gene-level analysis.

```r
library(hogwash)
phenotype <- hogwash::growth
genotype <- hogwash::snp_genotype
tree <- hogwash::tree
key <- hogwash::snp_gene_key

hogwash(pheno = phenotype, 
        geno = genotype,  
        tree = tree,      
        group_genotype_key = key, 
        grouping_method = "post-ar")
```

--------------------------------

### Adjust P-values using Bonferroni

Source: https://github.com/katiesaund/hogwash/wiki/F)-Exploring-your-hogwash-results

Accesses raw, unadjusted P-values from hogwash and applies the Bonferroni correction method. This allows for custom P-value adjustment.

```r
p.adjust(exp(-hogwash_phyc$raw_pvals$neg_log_unadjusted_pvals), method = "bonferroni")
```

--------------------------------

### Plot P-value vs. Epsilon

Source: https://github.com/katiesaund/hogwash/wiki/F)-Exploring-your-hogwash-results

Generates a scatter plot of corrected P-values against epsilon values. Requires the tidyverse package and a loaded 'phyc_output_file_name.rda' file.

```r
library(tidyverse)
load("phyc_output_file_name.rda")
df <- as_tibble(cbind(hogwash_phyc$hit_pvals$fdr_corrected_pvals, 
                      hogwash_phyc$convergence$epsilon))
colnames(df) <- c("P-value", "Epsilon")
df %>%
  ggplot(aes(x = Epsilon, y = `P-value`)) +
  geom_jitter()
```

--------------------------------

### Run Synchronous Test with SNP Grouping

Source: https://github.com/katiesaund/hogwash/wiki/C)-Running-hogwash

Perform the synchronous test with SNPs grouped into genes. This focuses the analysis on gene-level evolutionary patterns.

```r
library(hogwash)
phenotype <- hogwash::antibiotic_resistance
genotype <- hogwash::snp_genotype
tree <- hogwash::tree
key <- hogwash::snp_gene_key

hogwash(pheno = phenotype, 
        geno = genotype,  
        tree = tree,      
        group_genotype_key = key, 
        test = "synchronous", 
        grouping_method = "post-ar")
```

--------------------------------

### Report Phylogenetic Signal

Source: https://github.com/katiesaund/hogwash/wiki/C)-Running-hogwash

Use report_phylogenetic_signal() to assess the phylogenetic signal of a phenotype before running hogwash. This helps understand if the phenotype aligns with Brownian motion or white noise models.

```r
library(hogwash)
phenotype <- hogwash::growth
tree <- hogwash::tree
hogwash::report_phylogenetic_signal(phenotype, tree)
```

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