---
title: "Overview of concordexR"
author: "Lambda Moses, Kayla Jackson"
date: "`r format(Sys.Date(), '%b %d, %Y')`"
output:
    BiocStyle::html_document:
        toc: true
        number_sections: true
        toc_depth: 3
        toc_float:
            collapsed: true
vignette: >
  %\VignetteIndexEntry{overview}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
    collapse = TRUE,
    comment = "#>", fig.align = "center"
)
```

The goal of concordexR is to identify spatial homogeneous regions (SHRs) as defined in the recent manuscrpt["Identification of spatial homogenous regions in tissues with concordex"](https://doi.org/10.1101/2023.06.28.546949). Briefly, SHRs are are domains that are homogeneous with respect to cell type composition. concordex relies on the the k-nearest-neighbor (kNN) graph to representing similarities between cells and uses common clustering algorithms to identify SHRs.

## Installation

This package is under active development will be available in the Bioconductor version 3.20 release. 

Until then, please install the package from Github or from the Bioconductor devel branch. 

```{r, eval=FALSE}
if (!requireNamespace("BiocManager", quietly=TRUE))
    install.packages("BiocManager")

#BiocManager::install("concordexR", version="devel")
devtools::install_github("pachterlab/concordexR")
```

## Example of main functionality

This is a basic example which shows you how to solve a common problem:

```{r example}
library(concordexR)
library(SFEData)

sfe <- McKellarMuscleData("small")
```

```{r}
res <- calculateConcordex(sfe, labels=colData(sfe)[["in_tissue"]])
```


## SessionInfo
```{r}
sessionInfo()
```
