HOMER
Software for motif discovery and next-gen sequencing analysis
New Hi-C analysis routines in HOMER
Many of HOMER's Hi-C analysis tools have been upgraded and changed. Most of the tools below still work, but some of the default behavior has changed. In general we recommend you follow the new Hi-C workflows here.
Analyzing Hi-C genome-wide interaction data
HOMER contains several programs and analysis routines to
facilitate the analysis of Hi-C data. Hi-C couples chromosome
conformation capture (3C) with deep sequencing to
reveal regions of genomic DNA that are in close spatial
proximity in the nucleus. Hi-C has emerged as a
powerful technique to understand how the genome is packaged
in cells to control gene expression. Unlike ChIP-PET,
5C, or 4C, Hi-C is unbiased. While HOMER can be
jury-rigged to gleam information from other 3C-sequencing
based methods, it has been specifically tailored Hi-C
analysis.Several tools for analyzing Hi-C data with HOMER have been upgraded. However, the tools described below are still available within the HOMER software. If you want to learn more about the newer tools, a description of the newer version of HOMER's Hi-C analysis routines can be found here.
Specialized Hi-C programs in HOMER
HOMER has several specialized programs for Hi-C analysis. Each is covered in the tutorials below:
makeTagDirectory - special paired-end
operations for making HOMER-style tag directories and
filtering options for Hi-C
analyzeHiC - primary analysis program - generates interaction matrices, normalization, identification of significant interactions, clustering of domains, generates Circos plots (most of the following programs use this one internally)
runHiCpca.pl - automated PCA analysis on Hi-C data to identify "compartments"
getHiCcorrDiff.pl - calculates the difference in correlation profiles between two Hi-C experiments
findHiCCompartments.pl - find continuous or differential regions from PCA/corrDiff results that describe what compartment regions of DNA belong to (name changed - was called getDomains.pl)
findHiCInteractionsByChr.pl - helps automate the finding of high-resolution intra-chromosomal interactions
annotateInteractions.pl - program for re-analysis of significant interactions, such as relating them to ChIP-Seq peaks
SIMA.pl - Novel tool to boost sensitivity by pooling features together when performing interaction calculations
analyzeHiC - primary analysis program - generates interaction matrices, normalization, identification of significant interactions, clustering of domains, generates Circos plots (most of the following programs use this one internally)
runHiCpca.pl - automated PCA analysis on Hi-C data to identify "compartments"
getHiCcorrDiff.pl - calculates the difference in correlation profiles between two Hi-C experiments
findHiCCompartments.pl - find continuous or differential regions from PCA/corrDiff results that describe what compartment regions of DNA belong to (name changed - was called getDomains.pl)
findHiCInteractionsByChr.pl - helps automate the finding of high-resolution intra-chromosomal interactions
annotateInteractions.pl - program for re-analysis of significant interactions, such as relating them to ChIP-Seq peaks
SIMA.pl - Novel tool to boost sensitivity by pooling features together when performing interaction calculations
3rd Party Software
The following 3rd Party [Free] Software is used by HOMER for visualizing Hi-C results. They are required for specific functions (i.e. if you don't care about PCA, don't worry about installing R). Most are straightforward to install:
Java Tree View
- view interaction matrices (or any software to generate
and view heatmaps, needed to view standard analyzeHiC
output)
Circos - software to generating circle interaction diagrams. Tips on installing Circos (Needed when running analyzeHiC with "-circos" option)
R - statistical computing environment, used for PCA analysis (no special packages needed, used by runHiCpca.pl program)
Cytoscape - view processed network files created by annotateInteractions.pl and SIMA.pl
Make sure R and circos are available in your executable path as Homer will attempt to call these programs directly. Java Tree View is strictly for visualizing output files, as is Cytoscape.
Circos - software to generating circle interaction diagrams. Tips on installing Circos (Needed when running analyzeHiC with "-circos" option)
R - statistical computing environment, used for PCA analysis (no special packages needed, used by runHiCpca.pl program)
Cytoscape - view processed network files created by annotateInteractions.pl and SIMA.pl
Make sure R and circos are available in your executable path as Homer will attempt to call these programs directly. Java Tree View is strictly for visualizing output files, as is Cytoscape.
Analyzing Hi-C data with Homer
Below is a description of the general workflow of Hi-C analysis with HOMER, and each section contains detailed information about various analysis steps.
1. Creating Tag Directories,
quality control, and read filtering for Hi-C data (makeTagDirectory)
2. Creating Background Models for Hi-C Data (analyzeHiC)
3. Making Interaction matrices and normalizing interaction counts (analyzeHiC)
4. Sub-nuclear compartment analysis/PCA/Clustering (runHiCpca.pl, getHiCcorrDiff.pl, findHiCCompartments.pl)
5. Identifying significant interactions (analyzeHiC, findHiCInteractionsByChr.pl)
6. Analysis and annotation of interactions with respect to other data types (annotateInteractions.pl)
7. Visualizing Interactions and Other Sequencing data with Circos (analyzeHiC)
8. Structured Interaction Matrix Analysis (SIMA.pl)
Important Tips for analyzing Hi-C data with HOMER
2. Creating Background Models for Hi-C Data (analyzeHiC)
3. Making Interaction matrices and normalizing interaction counts (analyzeHiC)
4. Sub-nuclear compartment analysis/PCA/Clustering (runHiCpca.pl, getHiCcorrDiff.pl, findHiCCompartments.pl)
5. Identifying significant interactions (analyzeHiC, findHiCInteractionsByChr.pl)
6. Analysis and annotation of interactions with respect to other data types (annotateInteractions.pl)
7. Visualizing Interactions and Other Sequencing data with Circos (analyzeHiC)
8. Structured Interaction Matrix Analysis (SIMA.pl)
Important Tips for analyzing Hi-C data with HOMER
Can't figure something out? Questions, comments, concerns, or other feedback:
cbenner@ucsd.edu