# HiContacts
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HiContacts provides tools to import `(m)cool` matrices in R and work with them there.
It creates a new `contacts` class of objects, built on pre-existing Bioconductor objects, namely `InteractionSet`, `GenomicInterations` and `ContactMatrix` (`Lun, Perry & Ing-Simmons, F1000Research 2016`), and provides **analytical** and **visualization** tools to investigate contact maps.
## Installation
`HiContacts` will soon be available in Bioconductor.
To install the current release use:
```r
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("HiContacts")
```
For now, `HiContacts` can be installed from Github as follows:
```r
install.packages("devtools")
devtools::install_github("js2264/HiContacts")
library(HiContacts)
```
## Citation
If you are using `HiContacts` in your research, please cite:
> Serizay J (2022). _HiContacts: HiContacts: R interface to cool files_.
> R package version 0.99.0
> <https://github.com/js2264/HiContacts>.
## How to use `HiContacts`
`HiContacts` includes a introduction vignette where its usage is
illustrated. To access the vignette, please use:
```r
vignette('HiContacts')
```
## Overview
### Import a .(m)cool file as `contacts`
```r
mcool_file <- HiContactsData::HiContactsData('yeast_wt', format = 'mcool')
range <- 'I:20000-80000' # range of interest
lsCoolResolutions(mcool_file, verbose = TRUE)
contacts <- contacts(mcool_file, focus = range, res = 1000)
contacts
```
### Plotting matrices
```r
plotMatrix(contacts, use.scores = 'raw')
plotMatrix(contacts, use.scores = 'balanced', limits = c(-4, -1))
```
### Distance law, a.k.a. P(s)
```r
contacts <- contacts(
mcool_file,
pairs = HiContactsData::HiContactsData('yeast_wt', format = 'pairs')
)
ps <- distanceLaw(contacts)
plotPs(ps, aes(x = binned_distance, y = norm_p))
```
### Virtual 4C
```r
contacts <- contacts(mcool_file, res = 1000)
v4C <- virtual4C(contacts, viewpoint = GRanges('V:150000-170000'))
gg4C(v4C, aes(x = center, y = score, col = chr)) +
facet_wrap(~chr, scales = 'free_x')
```
### Cis-trans ratios
```r
contacts <- contacts(mcool_file, res = 1000)
cisTransRatio(contacts)
```
