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GMAP: identifying TADs and subTADs from Hi-C data

GMAP is an algorithm to call topologically associating domains (TAD) and subdomains (subTAD) from normalized Hi-C data. It's implemented through a R package rGMAP.

Install from Github

library(devtools)
install_github("wbaopaul/rGMAP")

Install from source codes

  • Download source codes here and In R type:
install.packages('path to rGMAP_1.4.tar.gz', type = 'source', rep = NULL)

Note

  • The latest rGMAP was built under R-3.5.1

Input

  • For a single chromosome, a HiC contact matrix hic_obj supports three types of format:

    1. a 3-column Hi-C contact matrix, corresponding to the i_th, j_th bin of a chromosom and the contact number;
    2. a n by n matrix, with (i,j) th element corresponding to contact number between the i_th and j_th bin of a chromosome;
    3. a tab or space delimited text file of the above two types of data

  • For multiple chromosomes, a genomic coordinate index file index_obj for HiC bin was required, and hic_obj and index_obj are compatible with HiC-Pro stype HiC matrix and index files. Both hic_obj and index_obj supports R data frame/data table and tab/space delimited files

    • An example of index_obj (chromosome start end id) in 10kb resolution:
    chr1	0	10000	1
chr1	10000	20000	2
chr1	20000	30000	3
......
    • An example of corresponding 3-column hic_obj file (bin_i bin_j count):
    10	11	1.15
10	15	1.89
15	20	2.20
......

Output

  • data frames providing the genomic coordinates of the identified hierarchical domains
  • the final parameters for calling TADs

Vignette

  • Detailed vignette for the latest version 1.4.

A quick example

  • A quick instruction and example:
library(rGAMP)
help(rGAMP)

## use an example data from Rao et al. (2014 Cell)
hic_rao_IMR90_chr15   # normalized Hi-C data for IMR90, chr15 with resolution 10kb
res = rGMAP(hic_rao_IMR90_chr15, resl = 10 * 1000)
names(res)


## quickly visualize some hierarchical domains
pp = plotdom(hic_rao_IMR90_chr15, NULL, res$hierTads, NULL, 5950, 6950, 30, 10000)
pp$p2



## for more information of usage of plotdom
help(plotdom)

Run in Docker

A dockerized commad line version was posted Here

Reference

The detailed information of GMAP algorithm is described in the following paper:

Yu, W., He, B., & Tan, K. (2017). Identifying topologically associating domains and subdomains by Gaussian Mixture model And Proportion test. Nature Communications, 8, 535.