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detect and visualize contact domain boundaries (CDBs) or differential CDBs from Hi-C (R version)

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ChenFengling/RHiCDB

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RHiCDB – user guide

Overview

  RHiCDB is an open-source R package based on HiCDB methods that detects the contact domain boundaries (CDBs) from Hi-C contact matrix. RHiCDB function takes raw or normalized contact matrix and outputs consistency annotated CDBs or differential CDBs. visHiCDB function takes raw or normalized contact matrix and HiCDB results and outputs visualization of CDBs on single Hi-C map or differential CDBs on two Hi-C maps. HiCDB are also implemented as MATLAB version.
  Here is the general features of HiCDB.

  Here is the general steps of how we detect CDBs.

Requirements and install

Install RHiCDB with devtools

#install.packages("devtools")
devtools::install_github("ChenFengling/RHiCDB")

OR Download RHiCDB_1.0.tar.gz and install in R.

install.packages("RHiCDB_1.0.tar.gz")

RHiCDB depends on pracma,limma,Matrix,gridExtra,rasterVis and lattice.

Quick start

Download the test data set with URL https://github.com/ChenFengling/HiCDB/raw/master/testdata.tar.gz .
Unzip the testdata.tar.gz, you will find the dense format Hi-C data of hESC (Doxin et al.) in directory named 'h1_rep1/'.

tar -zxvf testdata.tar.gz
Run RHiCDB to get the CDBs.
library('RHiCDB')
hicfile='h1_rep1/'
resolution=40000
chrsizes='hg19'
outdir='h1_rep1/'
RHiCDB(hicfile,resolution,chrsizes,ref='hg19',outdir=outdir)

This will take the intra-chromosome matrix ('chr1.matrix',...,'chr23.matrix') in 'h1_rep1/' as input and set the resolution as 40000,chrsizes as 'hg19', the CTCF motif ref as 'hg19' and output the contact domain boundaries.

Run visHiCDB to display the region chr17:67100000-71100000.
hicfile='h1_rep1/chr17.matrix'
resolution=40000
outdir='h1_rep1'
CDBfile='h1_rep1/CDB.txt'
chr=17
startloc=67100000
endloc=71100000
visHiCDB(hicfile,CDBfile,resolution,chr,startloc,endloc,outdir)

You will get this output in 17_67100000_71100000_HiCmap.pdf. The dot is CDB detected(dark blue:consistently detected CDBs; light blue:other CDBs)

Get .bed file

As "chrX" is named as "chr23" and as "23" in the output CDB.txt file. You could use the following shell code to change CDB.txt into .bed file.

awk -v OFS="\t" '{ print "chr"$1,$2,$3,$4,$5}' CDB.txt >CDB.bed
sed -i  's/chr23/chrX/g' CDB.bed

1. Run RHiCDB

Input

hicfile: The directory of all intra-chromosome matrix of a sample. The intra-chromosome matrix must be named as "chr+number.matrix" according to the chromosome order like 'chr1.matrix','chr2.matrix',...,'chr23.matrix'. As HiCDB matches "chr*.matrix" to recognize the Hi-C matrix, avoid to use the "chr*.matrix" as the name of other files. The intra-chromosome matrix could be in a dense (a NxN matrix) or sparse (a Kx3 table,Rao et al.) format. hicfile should be set as 'SAMPLE_DIR' when option is "singlemap", list('SAMPLE_DIR1','SAMPLE_DIR2') or list(c(’SAMPLE1_rep1’,’SAMPLE1_rep2’),c(’SAMPLE2_rep1’,’SAMPLE2_rep2’)) when option is ‘comparemap’. This is required.
Dense format contains the contact frequencies of the Hi-C NxN matrix.
Sparse format (Rao et al.) has three fields: i, j, and M_i,j. (i and j are written as the left edge of the bin at a given resolution; for example, at 10 kb resolution, the entry corresponding to the first row and tenth column of the matrix would correspond to M_i,j, where i=0, j=90000). As the Hi-C matrix is symmetric, only the upper triangle of the matrix is saved in sparse format. An example is as following:

50000 50000 1.0
60000 60000 1.0
540000 560000 1.0
560000 560000 59.0
560000 570000 1.0
560000 600000 1.0
560000 700000 1.0
690000 710000 1.0
700000 710000 1.0
710000 710000 66.0

resolution: resolution of Hi-C matrix. This is required.
chrsizes: Ordered chromosome sizes of the genome. Optional setting is ‘hg19’, ‘hg38’, ‘mm9’, ‘mm10’ or any other chromosome size files which can be generated following the instructions in annotation/README.md. This is required.
ref: ref should be set when you want to get a cutoff using a CTCF motif or the option is 'comparemap'. Optional ref is ‘hg19’, ‘hg38’, ‘mm9’, ‘mm10’ or any other custom motif locus files which can be generated from instructions in annotation/README.md. Only ‘hg19’ and ‘hg38’ can be annotated with conservation. To decide the cutoff in other organisms, users could use the motif of other insulators as a reference instead of CTCF. According to our experience, it is reliable to check the CDBs on Hi-C map under several cutoff to decide the cutoff in other organisms. As HiCDB implements visualizations for the Hi-C maps with annotated CDBs and works well under a broad parameter range, it won’t be too hard. The current cutoff in 40kb and 10kb human sample are approximately the half and third quitile of the total local maximum peaks respectively.

Examples

1. Output all the local maximum peaks and let customers to decide the cutoff.

RHiCDB('sample1/',10000,chrsizes='custom_chrsizes.txt');
RHiCDB('sample1/',10000,chrsizes='custom_chrsizes.txt',outdir='sample1/outputs/');

2. Use GSEA-like methods to decide the cutoff .

RHiCDB('sample1/',10000,chrsizes='hg19',ref='hg19');
RHiCDB('sample1/',10000,chrsizes='custom_chrsizes.txt',ref='custom_motiflocs.txt')

3. To detect differential CDBs

RHiCDB(list('sample1','sample2'),10000,'hg19',ref='hg19');
RHiCDB(list(c("sample1_rep1","sample1_rep2"),c("sample2_rep1","sample2_rep2")),10000,'hg19',ref='hg19');

Output(s)

1.CDB.txt:

chr start end LRI avgRI conserve_or_not consistent_or_differential
19 53100000 53140000 0.394707211 0.647392804 0 1
16 5060000 5100000 0.342727704 0.663101081 1 1
19 19620000 19660000 0.329837698 0.609237673 1 0

2. localmax.txt: all the local maximum peaks detected before cutoff decision. User can decide custom CDB cutoff upon this file.
3. EScurve.png: CTCF motif enrichment on ranked local maximum peaks.
These output files can be found in custom output directory or default directory namely the directory of the first sample.
4. aRI.txt: average RI score for each genomic bin.
5. LRI.txt: LRI score for each genomic bin.

2. Run visHiCDB

Input

hicfile: Hi-C matrix of the intersested chromosome.
CDBfile: CDBfile sould be a cell array storing the CDB location. The CDB files should be formatted as the output files of function HiCDB.
resolution: resolution of Hi-C map.
chr,startloc,endloc: observation locus on Hi-C map.

Examples

1.Show CDB on single Hi-C map

visHiCDB('sample1/chr18.matrix','CDB1.txt',40000,18,25000000,31150000)

2. Show differential CDBs on Hi-C maps

visHiCDB(list('sample1/chr18.matrix','sample2/chr18.matrix'),list('CDB1.txt','CDB2.txt'),40000,18,25000000,31150000)

Output(s)

HiCmap.pdf: a pdf containing figure showing CDBs on single Hi-C map or different kinds of CDBs between two Hi-C maps.
These output files can be found in custom output directory or default directory namely the directory of the first sample.

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