title: "sitePath: phylogeny-based sequence clustering using site polymorphism"
output: github_document

```{r setup, include=FALSE}
  fig.path = "inst/"

The below demonstrates the result of phylogeny-based sequence clustering for a H3N2 virus dataset (included in the package)

```{r example}

data(h3n2_align) # load the H3N2 sequences
data(h3n2_tree) # load the corresponding phylogenetic tree

options(list("cl.cores" = 10)) # Use 10 cores for multiprocessing

paths <- lineagePath(h3n2_tree, alignment = h3n2_align, Nmin = 0.05)
minEntropy <- sitesMinEntropy(paths)

p1 <- plotSingleSite(paths, site = 208) # The site polymorphism of site 208 on the tree
p2 <- plotSingleSite(minEntropy, site = 208) # The result of clustering using site 208
gridExtra::grid.arrange(p1, p2, ncol = 2)

```{r extractTips}
grp1 <- extractTips(paths, 208) # Grouping result using site polymorphism only
grp2 <- extractTips(minEntropy, 208) # Phylogeny-based clustering result

# Installation

[R programming language](https://cran.r-project.org/) >= 4.1.0 is required to use `sitePath`.

The stable release is available on [Bioconductor](https://bioconductor.org/packages/sitePath/).
if (!requireNamespace("BiocManager", quietly = TRUE))


The installation from [GitHub](https://github.com/wuaipinglab/sitePath/) is in experimental stage but gives the newest feature:
if (!requireNamespace("remotes", quietly = TRUE))


# QuickStart

The following is a quick tutorial on how to use `sitePath` to find fixation and parallel sites including how to import data, run analysis and visualization of the results.

## 1. Data preparation
You need a _tree_ and a _MSA_ (multiple sequence alignment) file and the sequence names have to be matched!
```{r data_prep}
library(sitePath) # Load the sitePath package

# The path to your tree and MSA files
tree_file <- system.file("extdata", "ZIKV.newick", package = "sitePath")
alignment_file <- system.file("extdata", "ZIKV.fasta", package = "sitePath")

tree <- read.tree(tree_file) # Read the tree file into R
align <- read.alignment(alignment_file, format = "fasta") # Read the MSA file into R


## 2. Run analysis
`Nmin` and `minSNP` are the respective parameters for finding fixation and parallel sites (18 and 1 are used as an example for this dataset). The default values will be used if you don't specify them.

```{r run_analysis}
options(list("cl.cores" = 1)) # Set this bigger than 1 to use multiprocessing

paraFix <- paraFixSites(tree, alignment = align, Nmin = 18, minSNP = 1) # Run analysis to find fixation and parallel sites

## 3. Fixation sites
Use `allSitesName` and set `type` as "fixation" to retrieve fixation sites name
``` {r fixSites_name}
allSitesName(paraFix, type = "fixation")

Use `plotFixationSites` to view fixation sites
```{r plot_fixSites}
plotFixationSites(paraFix) # View all fixation sites on the tree
plotFixationSites(paraFix, site = 139) # View a single site


## 4. Parallel sites
Use `allSitesName` and set `type` as "parallel" to retrieve parallel sites name
``` {r paraSites_name}
allSitesName(paraFix, type = "parallel")

Use `plotParallelSites` to view parallel sites
plotParallelSites(paraFix) # View all parallel sites on the tree
plotParallelSites(paraFix, site = 105) # View a single site

# Read more

The above uses wrapper functions but the analysis can be dissembled into step functions (so you can view the result of each step and modify parameters). Click [here](https://wuaipinglab.github.io/sitePath/articles/sitePath.html) for a detailed breakdown of the functionality.

# Getting help

Post on Bioconductor [support site](https://support.bioconductor.org/) if having trouble using `sitePath`. Or open an [issue](https://github.com/wuaipinglab/sitePath/issues/new?assignees=&labels=&template=bug_report.md&title=) if a bug is found.