/HiCBricks

HiCBricks offers user-friendly and efficient solutions for handling large high-resolution Hi-C datasets. The package provides a R/Bioconductor framework with the bricks to build more complex data analysis pipelines and algorithms.

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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

  • 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, 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.