Juicer is a platform for analyzing kilobase resolution Hi-C data. In this distribution, we include the pipeline for generating Hi-C maps from fastq raw data files and command line tools for feature annotation on the Hi-C maps.
Juicer is currently in its beta release, Juicer version 1.5.
For general questions, please use
the Google Group.
If you have further difficulties using Juicer, please do not
hesitate to contact us ([email protected])
If you use Juicer in your research, please cite: Neva C. Durand, Muhammad S. Shamim, Ido Machol, Suhas S. P. Rao, Miriam H. Huntley, Eric S. Lander, and Erez Lieberman Aiden. "Juicer provides a one-click system for analyzing loop-resolution Hi-C experiments." Cell Systems 3(1), 2016.
Run the Juicer pipeline on your cluster of choice with "juicer.sh [options]"
Usage: juicer.sh [-g genomeID] [-d topDir] [-q queue] [-l long queue] [-s site]
[-a about] [-R end] [-S stage] [-p chrom.sizes path]
[-y restriction site file] [-z reference genome file]
[-C chunk size] [-D Juicer scripts directory]
[-Q queue time limit] [-L long queue time limit] [-r] [-h] [-x]
* [genomeID] must be defined in the script, e.g. "hg19" or "mm10" (default
"hg19"); alternatively, it can be defined using the -z command
* [topDir] is the top level directory (default
"/Users/nchernia/Downloads/neva-muck/UGER")
[topDir]/fastq must contain the fastq files
[topDir]/splits will be created to contain the temporary split files
[topDir]/aligned will be created for the final alignment
* [queue] is the queue for running alignments (default "short")
* [long queue] is the queue for running longer jobs such as the hic file
creation (default "long")
* [site] must be defined in the script, e.g. "HindIII" or "MboI"
(default "MboI")
* [about]: enter description of experiment, enclosed in single quotes
* -r: use the short read version of the aligner, bwa aln
(default: long read, bwa mem)
* [end]: use the short read aligner on read end, must be one of 1 or 2
* [stage]: must be one of "merge", "dedup", "final", "postproc", or "early".
-Use "merge" when alignment has finished but the merged_sort file has not
yet been created.
-Use "dedup" when the files have been merged into merged_sort but
merged_nodups has not yet been created.
-Use "final" when the reads have been deduped into merged_nodups but the
final stats and hic files have not yet been created.
-Use "postproc" when the hic files have been created and only
postprocessing feature annotation remains to be completed.
-Use "early" for an early exit, before the final creation of the stats and
hic files
* [chrom.sizes path]: enter path for chrom.sizes file
* [restriction site file]: enter path for restriction site file (locations of
restriction sites in genome; can be generated with the script
(misc/generate_site_positions.py) )
* [reference genome file]: enter path for reference sequence file, BWA index
files must be in same directory
* [chunk size]: number of lines in split files, must be multiple of 4
(default 90000000, which equals 22.5 million reads)
* [Juicer scripts directory]: set the Juicer directory,
which should have scripts/ references/ and restriction_sites/ underneath it
(default /broad/aidenlab)
* [queue time limit]: time limit for queue, i.e. -W 12:00 is 12 hours
(default 1200)
* [long queue time limit]: time limit for long queue, i.e. -W 168:00 is one week
(default 3600)
* -x: exclude fragment-delimited maps from hic file creation
* -h: print this help and exit
See below and the cluster-specific READMEs for more details.
In this repository, we include the scripts for running Juicer on LSF, Univa Grid Engine, and SLURM
/AWS - scripts for running pipeline and postprocessing on AWS (LSF)
/UGER - scripts for running pipeline and postprocessing on UGER (Univa)
/SLURM - scripts for running pipeline and postprocessing on SLURM
/misc - miscellaneous helpful scripts
Juicer is a pipeline optimized for parallel computation on a cluster. Juicer consists of two parts: the pipeline that creates Hi-C files from raw data, and the post-processing command line tools.
###Cluster requirements:
Juicer requires the use of a cluster, with ideally >= 4 cores (min 1 core) and >= 64 GB RAM (min 16 GB RAM)
Juicer currently works with the following resource management software:
- OpenLava (http://www.openlava.org/)
- LSF (http://www-03.ibm.com/systems/services/platformcomputing/lsf.html)
- SLURM (http://slurm.schedmd.com/download.html)
- GridEngine (Univa, etc. any flavor)
###Command line tool requirements
The minimum software requirement to run Juicer is a working Java installation (version >= 1.7) on Windows, Linux, and Mac OSX. We recommend using the latest Java version available, but please do not use the Java Beta Version. Minimum system requirements for running Java can be found at http://java.com/en/download/help/sysreq.xml
To download and install the latest Java Runtime Environment (JRE), please go to http://www.java.com/download
###GNU CoreUtils
The latest version of GNU coreutils can be downloaded from https://www.gnu.org/software/coreutils/manual/
###Burrows-Wheeler Aligner (BWA)
The latest version of BWA should be installed from http://bio-bwa.sourceforge.net/
###CUDA (for HiCCUPS peak calling)
You must have an NVIDIA GPU to install CUDA Instructions for installing the latest version of CUDA can be found on the NVIDIA Developer site: https://developer.nvidia.com/cuda-downloads
The native libraries included with Juicer are compiled for CUDA 7 or CUDA 7.5 (AWS/scripts/juicebox_tools.7.0.jar) or (UGER/scripts/juicebox_tools.7.5.jar) Other versions of CUDA can be used, but you will need to download the respective native libraries from http://www.jcuda.org/downloads/downloads.html
For best performance, use a dedicated GPU. You may also be able to obtain access to GPU clusters through Amazon Web Services or a local research institution.
###Building new jars
See the Juicebox documentation at https://github.com/theaidenlab/Juicebox for details on building new jars of the juicebox_tools.
We have extensive documentation below for how to use Juicer.
- Running Juicer with no arguments will run it with genomeID hg19 and site MboI
- Providing a genome ID: if not defined in the script, you can either directly modify the script or provide the script with the files needed. You would provide the script with the files needed via "-z reference_sequence_path" (needs to have the BWA index files in same directory), "-p chrom_sizes_path" (these are the chromosomes you want included in .hic file), and "-s site_file" (this is the listing of all the restriction site locations, one line per chromosome). Note that ligation junction won't be defined in this case. The script (misc/generate_site_positions.py) can help you generate the file
- Providing a restriction enzyme: if not defined in the script, you can either directly modify the script or provide the files needed via the "-s site_file" flag, as above. Alternatively, if you don't want to do any fragment-level analysis (as with a DNAse experiment), you should assign the site "none", as in
juicer.sh -s none - Directory structure: Juicer expects the fastq files to be stored in a directory underneath the top-level directory. E.g. HIC001/fastq. By default, the top-level directory is the directory where you are when you launch Juicer; you can change this via the -d flag. Fastqs can be zipped. [topDir]/splits will be created to contain the temporary split files and should be deleted once your run is completed. [topDir]/aligned will be created for the final files, including the hic files, the statistics, the valid pairs (merged_nodups), the collisions, and the feature annotations.
- Queues are complicated and it's likely that you'll have to modify the script for your system, though we did our best to avoid this. By default there's a short queue and a long queue. We also allow you to pass in wait times for those queues; this is currently ignored by the UGER and SLURM versions. The short queue should be able to complete alignment of one split file. The long queue is for jobs that we expect to take a while, like writing out the merged_sort file
- Chunk size is intimitely associated with your queues; a smaller chunk size means more alignment jobs that complete in a faster time. If you have a hard limit on the number of jobs, you don't want too small of a chunk size. If your short queue has a very limited runtime ceiling, you don't want too big of a chunk size. Run time for alignment will also depend on the particulars of your cluster. We launch ~5 jobs per chunk. Chunk size must be a multiple of 4.
- Relaunch via the same script. Type
juicer.sh [options] -S stagewhere "stage" is one of merge, dedup, final, postproc, or early. "merge" is for when alignment has finished but merged_sort hasn't been created; "dedup" is for when merged_sort is there but not merged_nodups (this will relaunch all dedup jobs); "final" is for when merged_nodups is there and you want the stats and hic files; "postproc" is for when you have the hic files and just want feature annotations; and "early" is for early exit, before hic file creation. If your jobs failed at the alignment stage, runrelaunch_prep.shand then run juicer.sh. - Miscelleaneous options include -a 'experiment description', which will add the experiment description to the statistics file and the meta data in the hic file; -r, which allows you to use bwa aln instead of bwa mem, useful for shorter reads; -R [end], in case you have one read end that's short and one that's long and you want to align the short end with bwa aln and the long end with bwa mem; and -D [Juicer scripts directory], to set an alternative Juicer directory; must have scripts/, references/, and restriction_sites/ underneath it
To launch the command line tools, use the shell script “juicebox.sh” on Unix/MacOS or type
java -jar juicebox_tools.jar (command...) [flags...] <parameters...>`
There are two flavors of juicebox_tools: 7.0 uses CUDA7.0 and 7.5 uses CUDA 7.5
For HiCCUPS loop calling without the shell or bat script, you will need to
call:
java -Xms512m -Xmx2048m -Djava.library.path=path/to/natives/ -jar Juicebox_CLT.jar hiccups [flags...] <parameters...>
where path/to/natives is the path to the native libraries used for Jcuda
By default, these are located in the lib/jcuda folder.
In the command line tools, there are 4 functions:
apa for conducting aggregate peak analysis
hiccups for annotating loops
motifs for finding CTCF motifs
arrowhead for annotating contact domains
The juicebox.sh (Unix/MacOS) script can be used in place of the unwieldy
java -Djava.library.path=path/to/natives/ -jar juicebox_tools.jar
arrowhead [-c chromosome(s)] [-m matrix size] [-r resolution] [-k normalization (NONE/VC/VC_SQRT/KR)] <HiC file(s)> <output_file> [feature_list] [control_list]
The required arguments are:
<HiC file(s)>: Address of HiC file(s) which should end with ".hic". This is the file you will
load into Juicebox. URLs or local addresses may be used.
<output_file>: Final list of all contact domains found by Arrowhead. Can be visualized directly in Juicebox
as a 2D annotation.
-- NOTE -- If you want to find scores for a feature and control list, both must be provided:
[feature_list]: Feature list of loops/domains for which block scores are to be calculated
[control_list]: Control list of loops/domains for which block scores are to be calculated
The optional arguments are:
-c <String(s)> Chromosome(s) on which Arrowhead will be run. The number/letter for the chromosome can be used with or
without appending the "chr" string. Multiple chromosomes can be specified using commas (e.g. 1,chr2,X,chrY)
-m <int> Size of the sliding window along the diagonal in which contact domains will be found. Must be an even
number as (m/2) is used as the increment for the sliding window. (Default 2000)
-r <int> resolution for which Arrowhead will be run. Generally, 5kB (5000) or 10kB (10000)
resolution is used depending on the depth of sequencing in the HiC file(s).
-k <NONE/VC/VC_SQRT/KR> Normalizations (case sensitive) that can be selected. Generally, KR (Knight-Ruiz)
balancing should be used when available.
Default settings of optional arguments:
Medium resolution maps:
-c (all chromosomes)
-m 2000
-r 10000
-k KR
High resolution maps:
-c (all chromosomes)
-m 2000
-r 5000
-k KR
NOTE: Arrowhead will choose appropriate defaults for HiC files if no specifications are given
arrowhead https://hicfiles.s3.amazonaws.com/hiseq/ch12-lx-b-lymphoblasts/in-situ/combined_30.hic contact_domains_list
This command will run Arrowhead on a mouse cell line HiC map (medium resolution) at resolution 10 kB and save all contact domains to the contact_domains_list file. These are the settings used to generate the official contact domain list on the ch12-lx-b-lymphoblast cell line.
arrowhead https://hicfiles.s3.amazonaws.com/hiseq/gm12878/in-situ/combined_30.hic contact_domains_list
This command will run Arrowhead at resolution 5kB on the GM12878 HiC map (high resolution) and save all contact domains to the contact_domains_list file. These are the settings used to generate the official GM12878 contact domain list.
hiccups [-m matrixSize] [-c chromosome(s)] [-r resolution(s)] [-k normalization (NONE/VC/VC_SQRT/KR)] [-f fdr] [-p peak width] [-i window] [-t thresholds] [-d centroid distances] <HiC file(s)> <outputLoopsList>
The required arguments are:
<HiC file(s)>: Address of HiC file(s) which should end with ".hic". This is the file you will
load into Juicebox. URLs or local addresses may be used.
<outputLoopsList>: Final list of all loops found by HiCCUPS. Can be visualized directly in Juicebox as a 2D annotation.
By default, various values critical to the HICCUPS algorithm are saved as attributes for each loop found. These can be
disabled using the suppress flag below.
The optional arguments are:
-m <int> Maximum size of the submatrix within the chromosome passed on to GPU (Must be an even number greater than 40
to prevent issues from running the CUDA kernel). The upper limit will depend on your GPU. Dedicated GPUs
should be able to use values such as 500, 1000, or 2048 without trouble. Integrated GPUs are unlikely to run
sizes larger than 90 or 100. Matrix size will not effect the result, merely the time it takes for hiccups.
Larger values (with a dedicated GPU) will run fastest.
-c <String(s)> Chromosome(s) on which HiCCUPS will be run. The number/letter for the chromosome can be used with or
without appending the "chr" string. Multiple chromosomes can be specified using commas (e.g. 1,chr2,X,chrY)
-r <int(s)> Resolution(s) for which HiCCUPS will be run. Multiple resolutions can be specified using commas
(e.g. 25000,10000,5000). Due to the nature of DNA looping, it is unlikely that loops will be found at
lower resolutions (i.e. 50kB or 100kB)
IMPORTANT: if multiple resolutions are used, the flags below can be configured so that different parameters are
used for the different resolutions.
-k <NONE/VC/VC_SQRT/KR> Normalizations (case sensitive) that can be selected. Generally, KR (Knight-Ruiz)
balancing should be used when available.
-f <int(s)> FDR values actually corresponding to max_q_val (i.e. for 1% FDR use 0.01, for 10%FDR use 0.1). Different
FDR values can be used for each resolution using commas. (e.g "-r 5000,10000 -f 0.1,0.15" would run HiCCUPS at
10% FDR for resolution 5000 and 15% FDR for resolution 10000)
-p <int(s)> Peak width used for finding enriched pixels in HiCCUPS. Different peak widths can be used for each
resolution using commas. (e.g "-r 5000,10000 -p 4,2" would run at peak width 4 for resolution 5000 and
peak width 2 for resolution 10000)
-i <int(s)> Window width used for finding enriched pixels in HiCCUPS. Different window widths can be used for each
resolution using commas. (e.g "-r 5000,10000 -p 10,6" would run at window width 10 for resolution 5000 and
window width 6 for resolution 10000)
-t <floats> Thresholds for merging loop lists of different resolutions. Four values must be given, separated by
commas (e.g. 0.02,1.5,1.75,2). These thresholds (in order) represent:
- threshold allowed for sum of FDR values of the horizontal, vertical, donut, and bottom left filters
(an accepted loop must stay below this threshold)
- threshold ratio that both the horizontal and vertical filters must exceed
- threshold ratio that both the donut and bottom left filters must exceed
- threshold ratio that at least one of the donut and bottom left filters must exceed
-d <ints> Distances used for merging nearby pixels to a centroid. Different distances can be used for each
resolution using commas. (e.g "-r 5000,10000 -d 20000,21000” would merge pixels within 20kB of each
other at 5kB resolution and within 21kB at 10kB resolution.
Defaults:
Medium resolution maps:
-m 512
-c (all chromosomes)
-r 10000
-k KR
-f .1
-p 2
-i 5
-t 0.02,1.5,1.75,2
-d 20000,20000,50000
High resolution maps:
-m 512
-c (all chromosomes)
-r 5000,10000
-k KR
-f .1,.1
-p 4,2
-i 7,5
-t 0.02,1.5,1.75,2
-d 20000,20000,50000
hiccups HIC006.hic all_hiccups_loops
This command will run HiCCUPS on HIC006 and save all found loops to the all_hiccups_loops files
hiccups -m 500 -r 5000,10000 -f 0.1,0.1 -p 4,2 -i 7,5 -d 20000,20000,0 -c 22 HIC006.hic all_hiccups_loops
This command will run HiCCUPS on chromosome 22 of HIC006 at 5kB and 10kB resolution using the following values:
5kB: fdr 10%, peak width 4, window width 7, and centroid distance 20kB
10kB: fdr 10%, peak width 2, window width 5, and centroid distance 20kB
The resulting loop list will be merged and saved as all_hiccups_loops
Note that these are values used for generating the GM12878 loop list
The "apa" command takes three required arguments and a number of optional arguments.
apa [-n minval] [-x maxval] [-w window] [-r resolution(s)] [-c chromosome(s)] [-k NONE/VC/VC_SQRT/KR] <HiC file(s)> <PeaksFile> <SaveFolder>
The required arguments are:
<HiC file(s)>: Address of HiC file(s) which should end with ".hic". This is the file you will
load into Juicebox. URLs or local addresses may be used. To sum multiple HiC Files together,
use the '+' symbol between the addresses (no whitespace between addresses)
<PeaksFile>: List of peaks in standard 2D feature format (chr1 x1 x2 chr2 y1 y2 color ...)
<SaveFolder>: Working directory where outputs will be saved
The optional arguments are:
-n <int> minimum distance away from the diagonal. Used to filter peaks too close to the diagonal.
Units are in terms of the provided resolution. (e.g. -n 30 @ resolution 5kB will filter loops
within 30(5000/sqrt(2)) units of the diagonal)
-x <int> maximum distance away from the diagonal. Used to filter peaks too far from the diagonal.
Units are in terms of the provided resolution. (e.g. -n 30 @ resolution 5kB will filter loops
further than 30(5000/sqrt(2)) units of the diagonal)
-w <int> width of region to be aggregated around the specified loops (units of resolution)
-r <int(s)> resolution for APA; multiple resolutions can be specified using commas (e.g. 5000,10000)
-c <String(s)> Chromosome(s) on which APA will be run. The number/letter for the chromosome can be
used with or without appending the "chr" string. Multiple chromosomes can be specified using
commas (e.g. 1,chr2,X,chrY)
-k <NONE/VC/VC_SQRT/KR> Normalizations (case sensitive) that can be selected. Generally, KR (Knight-Ruiz)
balancing should be used when available.
Default settings of optional arguments:
-n 30
-x (infinity)
-w 10
-r 25000,10000
-c (all chromosomes)
-k KR
apa HIC006.hic all_loops.txt results1
This command will run APA on HIC006 using loops from the all_loops files and save them under the results1 folder.
apa https://hicfiles.s3.amazonaws.com/hiseq/gm12878/in-situ/combined.hic all_loops.txt results1
This command will run APA on the GM12878 mega map using loops from the all_loops files and save them under the results1 folder.
apa -r 10000,5000 -c 17,18 HIC006.hic+HIC007.hic all_loops.txt results
This command will run APA at 50 kB resolution on chromosomes 17 and 18 for the summed HiC maps (HIC006 and HIC007) using loops from the all_loops files and save them under the results folder
motifs <genomeID> <bed_file_dir> <looplist> [custom_global_motif_list]
The required arguments are:
<genomeID>: hg19 supported by default. For other genome assemblies, provide a
custom_global_motif_list in FIMO format.
<bed_file_dir> File path to a directory (e.g. ) which contains two folders: "unique" and
"inferred". These folders should contain a combination of RAD21, SMC3, and CTCF BED files.
By intersecting these 1D tracks, the strongest peaks will be identified. Unique motifs
generally use a more stringent combination of BED files than inferred motifs.
<looplist>: List of peaks in standard 2D feature format (chr1 x1 x2 chr2 y1 y2 color ...)
-- NOTE -- If you want to use a custom list of potential motifs:
[custom_global_motif_list]: Motif list output using FIMO format can be used as an alternative to the internal motif list
Assuming the following file structure is present:
/path/to/local/bed/files/unique/CTCF.bed
/path/to/local/bed/files/unique/RAD21.bed
/path/to/local/bed/files/unique/SMC3.bed
/path/to/local/bed/files/inferred/CTCF.bed
motifs hg19 /path/to/local/bed/files /gm12878_hiccups_loops.txt
This command will find motifs from the internal hg19 motif list for the loops in gm12878_hiccups_loops.txt and save them to gm12878_hiccups_loops_with_motifs.txt. The CTCF, RAD21, and SMC3 BED files will be used together (i.e. intersected) to find unique motifs. Just the CTCF track will be used to infer best motifs.
motifs hg19 /path/to/local/bed/files gm12878_hiccups_loops.txt hg_19_custom_motif_list.txt
This command will find motifs from hg_19_custom_motif_list.txt for the loops in gm12878_hiccups_loops.txt and save them to gm12878_hiccups_loops_with_motifs.txt. The CTCF, RAD21, and SMC3 BED files will be used together (i.e. intersected) to find unique motifs. Just the CTCF track will be used to infer best motifs.
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