### Install G4SNVHunter from GitHub

Source: https://github.com/rongxinzh/g4snvhunter/blob/main/README.md

Install the G4SNVHunter package directly from GitHub using the devtools package. Ensure devtools is installed first.

```r
# install.packages("devtools")
devtools::install_github("rongxinzh/G4SNVHunter")
```

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

### Install G4SNVHunter from GitHub with Dependencies

Source: https://github.com/rongxinzh/g4snvhunter/blob/main/README.md

Install the G4SNVHunter package from GitHub, including all necessary dependencies for running vignette examples. Ensure devtools is installed first.

```r
# install.packages("devtools")
devtools::install_github("rongxinzh/G4SNVHunter", dependencies = TRUE)
```

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

### Install G4SNVHunter from Bioconductor

Source: https://github.com/rongxinzh/g4snvhunter/blob/main/README.md

Install the G4SNVHunter package from Bioconductor's development version. This requires BiocManager to be installed and the devel version to be initialized.

```r
if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install(version = 'devel')

BiocManager::install("G4SNVHunter")
```

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

### Install G4SNVHunter from Bioconductor with Dependencies

Source: https://github.com/rongxinzh/g4snvhunter/blob/main/README.md

Install the G4SNVHunter package from Bioconductor's development version, including dependencies. Ensure BiocManager is installed and the devel version is initialized.

```r
BiocManager::install("G4SNVHunter", dependencies = TRUE)
```

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

### Load Human Genome Sequence Data

Source: https://github.com/rongxinzh/g4snvhunter/blob/main/README.md

Load the human genome sequence for chromosome 16 (hg19 version) using the BSgenome.Hsapiens.UCSC.hg19 package. Install the package if it's not already present. The sequence is then converted to a DNAStringSet and chromosome names are assigned.

```r
if (!requireNamespace("BSgenome.Hsapiens.UCSC.hg19", quietly = TRUE)) {
    BiocManager::install("BSgenome.Hsapiens.UCSC.hg19")
}
library(BSgenome.Hsapiens.UCSC.hg19)

# Load sequence for chromosome 16 (hg19)
hg19 <- BSgenome.Hsapiens.UCSC.hg19

chr16_seq <- DNAStringSet(hg19$chr16)

# Chromosome names are needed for analysis
names(chr16_seq) <- "chr16"
```

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

### Load G4SNVHunter Package

Source: https://github.com/rongxinzh/g4snvhunter/blob/main/README.md

Load the G4SNVHunter package into the R session to make its functions available for use.

```r
library(G4SNVHunter)
```

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

### Load Variant Data

Source: https://github.com/rongxinzh/g4snvhunter/blob/main/README.md

Load variant data from a VCF file using the loadVariant function. The file path is obtained using system.file. Chromosome levels of the loaded variants are then updated to match the expected format.

```r
vcf_file <- system.file("extdata", 
                        "example_variants_chr16.vcf", 
                        package = "G4SNVHunter")
variants <- loadVariant(vcf_file, file_type = "vcf")
seqlevels(variants) <- paste0("chr", seqlevels(variants))
```

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

### Evaluate Variant Impact on G4 Formation

Source: https://github.com/rongxinzh/g4snvhunter/blob/main/README.md

Evaluate the impact of variants on G4 structure formation using the G4VarImpact function. This requires the detected G4 regions and the variant data, specifying the reference and alternative allele columns.

```r
result <- G4VarImpact(G4 = chr16_G4, 
                      variants = variants, 
                      ref_col = "REF",
                      alt_col = "ALT")
```

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

### Detect G4-Prone Regions

Source: https://github.com/rongxinzh/g4snvhunter/blob/main/README.md

Detect G-quadruplex (G4)-prone regions in the provided DNA sequence using the G4HunterDetect function.

```r
chr16_G4 <- G4HunterDetect(chr16_seq)
```

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

### Filter Variant Impact Results

Source: https://github.com/rongxinzh/g4snvhunter/blob/main/README.md

Filter the results of variant impact evaluation based on raw score and mutation score thresholds. The filtered results are then printed.

```r
filtered_var_eff <- filterVarImpact(result, 
                                    raw_score_threshold = 1.5,
                                    mut_score_threshold = 1.2)

print(filtered_var_eff)
```

=== COMPLETE CONTENT === This response contains all available snippets from this library. No additional content exists. Do not make further requests.