The peak caller for ChIP-Seq data

PeakRanger is a multi-purporse software suite for analyzing next-generation sequencing (NGS) data. The suite contains the following tools:

1. nr noise rate estimator. Estimates signal to noise ratio which is an indicator for ChIP enrichment
2. lc library complexity calculator. Calculates the ratio of unique reads over total reads. Only accepts bam files.
3. wig coverage file generator. Generates variable step format wiggle file
4. wigpe coverage file generator. Generates bedGraph format wiggle file and supports spliced alignments and thus only supports bam files
5. ranger ChIP-Seq peak caller. It is able to identify enriched genomic regions while at the same time discover summits within these regions.
6. ccat ChIP-Seq peak caller. Tuned for the discovery of broad peaks
7. bcp ChIP-Seq peak caller. Tuned for the discovery of broad peaks.

ranger, ccat and bcp support HTML-based annotation reports.

wigpe can also generate coverage files for bam files containing spliced reads, such as those from RNA-Seq experiments.

If you use PeakRanger in your research, please cite:

Feng X, Grossman R, Stein L: PeakRanger:A cloud-enabled peak caller for ChIP-seq data.BMC Bioinformatics 2011, 12(1):139.(http://www.biomedcentral.com/1471-2105/12/139/)

If you use the ccat tool, please also cite:

Xu, H., L. Handoko, et al. (2010).A signal-noise model for significance analysis of ChIP-seq with negative control.Bioinformatics 26(9): 1199-1204.(http://bioinformatics.oxfordjournals.org/content/26/9/1199)

If you use the bcp tool, please also cite:

Xing H, Mo Y, Liao W, Zhang MQ (2012) Genome-Wide Localization of Protein-DNA Binding and Histone Modification by a Bayesian Change-Point Method with ChIP-seq Data. PLoS Comput Biol 8(7): e1002613. doi:10.1371/journal.pcbi.1002613.(http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002613)

1. The ranger and ccat tool depends on the R programming environment to generate HTML reports. But they can run without it, even with --report and --gene_annot_file set.
2. When the number of peaks called by ranger or ccat is huge, it takes a while for user's browser to parse the generated HTML file.
3. The lc tool needs about 1.7G ram per 10 million aligned reads.

##ranger Calling narrow peaks It turns out that ranger servers better as a narrow-peak caller. It behaves in a conservative but sensitive way compared to similar algorithms.

The algorithm ranger uses a staged algorithm to discover enriched regions and the summits within them. In the first step, PeakRanger implements a FDR based adapative thresholding algorithm, which was originally proposed by PeakSeq. PeakRanger uses this thresholder to find regions with enriched reads that exceed expects. After that, PeakRanger searches for summits in these regions. The summit-search algorithm first looks for the location with largest number of reads. It then searchs for sub-summits with the sensitivity, the delta -r, specified by the user. Smaller -r will generate more summits.The coverage profiles are smoothed and padded before calling summits. The smoothing grade varies with -b. Higher smoothing bandwidth results less false summits at the cost of degraded summit accuracy .To measure the significance of the enriched regions, PeakRanger uses binormial distribution to model the relative enrichment of sample over control. A p value is generated as a result. Users can thus select highly significant peaks by using a smaller -p.

Reads extending ranger extends reads before calling peaks. The default reads extension length is 200. However, users can change this by -l if the datasets come with a different fragment size. The extension length will change the reads coverages generated from the raw reads as it will change the heights of peaks.

##wigpe and wig To help visualizing the results, wigpe and wig generates reads coverage files in the wig format. These files can then be loaded into browsers to evaluate the authenticity of called peaks. Since smaller wiggle files take less time and memory to load, --split can be set to generate one small wig file per chromosome.

##ccat Calling broad peaks Calling broad peaks remain unsolved for the ChIP-Seq community. It seems the CCAT algorithm is one of those that is designed for this problem, especially for calling histone modification marks.

The algorithm For details of the algorithm, please refer to the original manuscript of CCAT:

Xu, H., L. Handoko, et al. (2010).A signal-noise model for significance analysis of ChIP-seq with negative control.Bioinformatics 26(9): 1199-1204.(http://bioinformatics.oxfordjournals.org/content/26/9/1199)

##bcp Calling broad peaks bcp also serves as a broad peak caller. In many situations we perfer bcp over ccat while there are certain scenarios ccat outperforms. A drawback of the current implementation is that it does not support summit calling which is supported by ranger and ccat.

The algorithm For details of the algorithm, please refer to the original manuscript of bcp:

Xing H, Mo Y, Liao W, Zhang MQ (2012) Genome-Wide Localization of Protein-DNA Binding and Histone Modification by a Bayesian Change-Point Method with ChIP-seq Data. PLoS Comput Biol 8(7): e1002613. doi:10.1371/journal.pcbi.1002613.(http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002613)

##nr nr is a module of the original CCAT algorithm that estimates the similarity of data and control. It indicates roughly how data departs from control

##lc lc measures the percentage of unique reads. The result measures how diversified the reads are in the dataset. The idea is from:

Chen, Yiwen, Nicolas Negre, Qunhua Li, Joanna O. Mieczkowska, Matthew Slattery, Tao Liu, Yong Zhang, et al. 2012. Systematic evaluation of factors influencing ChIP-seq fidelity. Nature Methods 9(6): 609-614.(http://www.nature.com/nmeth/journal/v9/n6/full/nmeth.1985.html)

Required libraries before compiling:

1. The Boost library v1.56 or newer

2. Pthread

3. g++

4. zlib

Install any missing items via apt-get install . Once all the libraries are installed, go to the root path of the unzipped package and type:

make

This will generate bin/peakranger. Compilation in other Linux distributions is similar.

We suggest that you modify the STATIC variable in the makefile:

STATIC = -static

This will produce a stand-alone binary file that is easier to use.

Required libraries before compiling:

1. Xcode developer tool kit from Apple

2. The Boost library v1.56 or newer

3. zlib

4. Pthread

The Xcode kit can be installed using the OSX installation disk. If you dont have the installation disk, you can also get it for free from Apple Developer. The tool kit installs essential command line tools such as make and C++ compilers. The Boost library can be installed by following the instructions on its website. If you do not have root access, modify the BOOST_PATH variable in the make file:

BOOST_PATH = -I/path/to/your/boost/header -L/path/to/your/boost/library

Once all the libraries are installed, go to the root path of the unzipped package and type:

make

If the compilation failed, double check the BOOST_PATH variable is correctly set. The resulting binaries require dynamic boost library files, to make sure peakranger can find these files, type :

export DYLD_LIBRARY_PATH=$DYLD_LIBRARY_PATH:/path/to/your/boost/library

please change the path accordingly.

Not supported but should be possible.

peakranger lc sample.bam

peakranger nr --format bam sample.bam control.bam

peakranger wig --format bam sample.bam sample.bam_coverage

peakranger wig --format bed sample.bed sample.bed_coverage

peakranger wigpe sample.bam sample.bam_coverage

peakranger wigpe sample.bam sample.bam_coverage_splitted -s

peakranger wigpe sample.bam sample.bam_coverage_splitted_by_strand -sx

peakranger wigpe sample.bam sample.bam_coverage_gzipped -z

peakranger wigpe sample.bam sample.bam_coverage_splitted_by_strand_gzip -sxz

peakranger wigpe sample.bam sample.bam_coverage_read_extend_to_200 -l 200

peakranger ranger --format bam sample.bam control.bam ranger_result

peakranger ranger --format bam sample.bam control.bam ranger_result_threaded_faster -t 3

peakranger ccat --format bam sample.bam contro.bam ccat_result

peakranger ccat --format bam sample.bam contro.bam ccat_result_with_HTML_report --report --gene_annot_file hg19refGene.txt

peakranger ccat --format bam sample.bam contro.bam ccat_result_with_HTML_report_5kb_region --report --gene_annot_file hg19refGene.txt --plot_region 10000

peakranger bcp --format bam sample.bam contro.bam bcp_result

peakranger bcp --format bam sample.bam contro.bam bcp_result_with_HTML_report_5kb_region --report --gene_annot_file hg19refGene.txt --plot_region 10000

input

-d,--data

data file.

-c,--control

control file.

--format

the format of the data file, can be one of : bowtie, sam, bam and bed.

Qualities

-l,--ext_length

read extension length

Other

-h,--help

show the usage

--verbose

show progress

--version

output the version number

input

-d,--data

data file.

Other

-h,--help

show the usage

--verbose

show progress

--version

output the version number

input

-d,--data

data file.

--format

the format of the data file, can be one of : bowtie, sam, bam and bed.

Output

-o,--output

the output location

-s,--split

generate one wig file per chromosome

-z,--gzip

compress the output

-x,--strand

generate one wig file per strand

Qualities

-l,--ext_length

read extension length

Other

-h,--help

show the usage

--verbose

show progress

--version

output the version number

input

-d,--data

data file.

Output

-o,--output

the output location

-s,--split

generate one wig file per chromosome

-z,--gzip

compress the output

-x,--strand

generate one wig file per strand

Qualities

-l,--ext_length

read extension length

Other

-h,--help

show the usage

--verbose

show progress

--version

output the version number

input

-d,--data

data file.

-c,--control

control file.

--format

the format of the data file, can be one of : bowtie, sam, bam and bed.

Output

-o,--output

the output location

--report

generate html reports

--plot_region

the length of the snapshort regions in the HTML report. It also controls the search span for nearby genes.

--gene_annot_file

the gene annotation file

Qualities

-p,--pval

p value cut off

--win_size

Sliding window size

-l,--ext_length

read extension length

Other

-h,--help

show the usage

--verbose

show progress

--version

output the version number

input

-d,--data

data file.

-c,--control

control file.

--format

the format of the data file, can be one of : bowtie, sam, bam and bed.

Output

-o,--output

the output location

--report

generate html reports

--plot_region

the length of the snapshort regions in the HTML report. It also controls the search span for nearby genes.

--gene_annot_file

the gene annotation file

Qualities

-p,--pval

p value cut off

-q,--FDR

FDR cut off

-l,--ext_length

read extension length

-r,--delta

sensitivity of the summit detector

-b,--bandwidth

smoothing bandwidth.

--pad

pad read coverage to avoid false positive summits

Running modes

-t

number of threads.(default: 1)

Other

-h,--help

show the usage

--verbose

show progress

--version

output the version number

input

-d,--data

data file.

-c,--control

control file.

--format

the format of the data file, can be one of : bowtie, sam, bam and bed.

Output

-o,--output

the output location

--report

generate html reports

--plot_region

the length of the snapshort regions in the HTML report. It also controls the search span for nearby genes.

--gene_annot_file

the gene annotation file

Qualities

-q,--FDR

FDR cut off

--win_size

sliding window size

--win_step

window moving step

--min_count

minimum window reads count

--min_score

minimum window reads fold change

-l,--ext_length

read extension length

Other

-h,--help

show the usage

--verbose

show progress

--version

output the version number

lc lc does not generate any files

nr nr does not generate any files

wig wig generates a single file by default. When -x or -s is specified, it generates multiple files depending on the datasets.

wigpe similar to wig

ranger Three files will be geneated:

_summit.bed

_region.bed

_details

The first two bed files can be visualized in IGV. _summit.bed file contains the locations of summits ranked by their FDR. _regions.bed file contains the locations of regions ranked by their FDR. Each summit or region is annotated by the 4th column.

_details file contains both summits and regions as well as the regions's FDR and p values.

When --report is enabled, this file will also contain nearby genes of called peaks.

--report enables HTML reporting that generates a folder named using the data file's name. The folder contains a single index.html visualizable in most browsers.

ccat Similar to ranger

bcp Similar to ranger but it does not provide the _summit.bed file.

PeakRanger: http://ranger.sourceforge.net modENCODE: http://www.modencode.org PeakSeq: http://info.gersteinlab.org/PeakSeq sourceforge: http://ranger.sourceforge.net ChIP-Seq: http://en.wikipedia.org/wiki/Chip-Sequencing GNU Scientific Library (GSL): http://www.gnu.org/software/gsl/ Ubuntu: http://www.ubuntu.com confuse option file parser: http://www.nongnu.org/confuse/ Bowtie: http://bowtie-bio.sourceforge.net Hadoop: http://hadoop.apache.org/ Boost: http://www.boost.org/ IGV: http://www.broadinstitute.org/igv/ Hadoop Streaming: http://hadoop.apache.org/common/docs/r0.15.2/streaming.html NGS: http://en.wikipedia.org/wiki/DNA_sequencing