Travis CI: [](https://travis-ci.com/koustav-pal/HiCBricks) [<img src="https://www.bioconductor.org/images/logo/jpg/bioconductor_logo_rgb.jpg" width="300" align="right"/>](https://bioconductor.org/) <br/><br/><br/><br/> <a href="https://bioconductor.org/checkResults/devel/bioc-LATEST/HiCBricks/"><img src="https://bioconductor.org/shields/build/devel/bioc/HiCBricks.svg" align="right"/></a> <a href="https://bioconductor.org/packages/devel/bioc/html/HiCBricks.html#since"><img src="https://bioconductor.org/shields/years-in-bioc/HiCBricks.svg" align="right"/></a> <a href="https://bioconductor.org/packages/devel/bioc/html/HiCBricks.html#archives"><img src="https://bioconductor.org/shields/availability/3.9/HiCBricks.svg" align="right"/></a> <br/><br/>  # HiCBricks HiCBricks is a **R/Bioconductor** package for handling high-resolution Hi-C datasets through HDF (Hierarchical Data Format) files. Read more about HDF [here](https://en.wikipedia.org/wiki/Hierarchical_Data_Format) - HiCBricks greatly simplifies user handling of Hi-C contact matrices. - Forces users to adhere to a set of Hi-C analysis good-practices. - HiCBricks simplifies how users interaction with HDF files containing Hi-C contact matrices. ## Features - Import Hi-C data in multiple data formats. Currently, NxN dimensional matrices, _mcool_ files and sparse matrices are supported, with more to come. - Fetch different subset of the Hi-C data by their features with easy to use functions. Feature examples: by distance, matrix squares, rows or columns. - Keep user-defined annotations associated to the HDF files. - Use HiCBricks accessors to build more complex analysis such as TAD calling and visualizations. ## Installation To install the most stable development version from Bioconductor, run this from a R console. **Note:** `R version >= 3.5` is required. This command will first installs `BiocManager` from CRAN. `BiocManager` is a convenient utility to install `Bioconductor` packages. Then, we install `HiCBricks` through `BiocManager`. ``` if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("HiCBricks", version = "3.11") ``` To install the stable release version from Bioconductor, run this from a R console. ``` if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("HiCBricks", version = "3.11") ``` To install the most cutting-edge stable version of HiCBricks, do this from a R console to download it directly from GitHub. ``` if (!requireNamespace("devtools", quietly = TRUE)) install.packages("devtools") devtools::install_git("https://github.com/koustav-pal/HiCBricks") ``` ## Getting Started To start working with **HiCBricks**, please checkout the vignette (tutorial) [here](http://bioconductor.org/packages/devel/bioc/vignettes/HiCBricks/inst/doc/IntroductionToHiCBricks.html), at the main Bioconductor website. It contains an in-depth walkthrough of almost all functions in **HiCBricks** and will guide users through the process of - Loading data from text 2D files. - Loading data from mcool files. - Loading data from sparse matrices. - Making TAD calls and spohisticated heatmaps with example functions built using HiCBricks accessor functions. ## Development Notes - **HiCBricks** API is now stable. While we may move to sparse or feather representations later, this API will not change. - With Bioconductor release 3.10, a formal S4 class has been implemented for a better user experience. - With Bioconductor release 3.11, sparse matrix support has been implemented. ## Future Roadmap There are many new developments which are planned for future releases of HiCBricks. Broadly speaking, - I will try to implement `read and export functions` for as many new Hi-C data formats as possible. On top priority is HiCExplorer and .hic. ## Contributing If you would like to help out, let me know via email at koustav.pal@ifom.eu.