CLAM is a general toolkit for re-aligning multi-mapped reads in CLIP/RIP-seq data and calling peaks.
For details, please read our NAR paper.
CLAM v1.1 works under Python 2. Please click and download the latest version from the releases. Once unzip the file, type
$ python setup.py install
in your terminal and this will automatically install CLAM in your currently working python.
You should have already installed "pysam" using pip/conda for your python interpreter. If not, you can check the detailed requirements in the file "requirements.txt", or type
pip install -r requirements.txt
to install those requirements manually.
The input for CLAM is a sorted or unsorted BAM file of CLIP-seq alignment and a gene annotation file in GTF format.
In the case of RIP-seq or eCLIP, a BAM file for IP experiment and a BAM file for Control/input experiment are taken together as input.
Note: As in the released version v1.1.0, the
read_gtf function had a bug and required the Gencode format GTF (i.e. last column of GTF
matches gene_id "(xx)" ) to proceed the peak calling. This bug has been fixed in the github repository and has been fixed in later releases/patches.
CLAM is run through issueing subcommands. Currently there are four subcommands available: preprocessor, realigner, peakcaller and permutation_callpeak.
usage: CLAM [-h] [--version]
{preprocessor,realigner,peakcaller,permutation_callpeak} ...
CLAM -- CLip-seq Analysis of Multi-mapped reads
positional arguments:
{preprocessor,realigner,peakcaller,permutation_callpeak}
preprocessor CLAM Preprocessor: tag read alignments to specific
locus
realigner CLAM Realigner: realign multi-mapped reads using
expectation-maximization
peakcaller CLAM Peakcaller: negative binomial model-based peak
calling combining unique- and multi-reads
permutation_callpeak
CLAM permutation peakcaller: call peaks using
permutation (as in v1.0.0)
optional arguments:
-h, --help show this help message and exit
--version show program's version number and exit
For command line options of each sub-command, type: CLAM COMMAND -h
Below we briefly describe what each subcomand does and provide an example command-line run.
This subcommand (new v1.1) will prepare the input files for CLAM pipeline. As of the current version (v1.1), it looks for
reads passing QC, splits the input bam file by sorting them into unique.sorted.bam and multi.sorted.bam,
and adding an additional tag "RT" (short for Read Tag) to each alignment based which read tagger function the user supplied.
Note that you can also run CLAM realigner directly, which will call preprocessor and automatically determine
if preprocessor has been called in the output folder.
If you don't want to run realigner, you can also run peakcaller directly after preprocessor.
Example run:
CLAM preprocessor -i path/to/input/Aligned.out.bam -o path/to/clam/outdir/ --read-tagger-method median
This subcommand will run expectation-maxmization to assign the multi-mapped reads in a probablistic framework. More details about the EM model is described in our NAR paper.
Note when --retag is specified, realigner will re-run preprocessor regardless; otherwise, it will use
the prepared files in outdir if available.
Example run:
CLAM realigner -i path/to/input/Aligned.out.bam -o path/to/clam/outdir/ --read-tagger-method start --retag
This subcommand (new in v1.1) will call peaks by looking for bins enriched with IP reads over control, specifying a Negative-binomial model on observed read counts.
Note we can specify both unique.sorted.bam (from preprocessor) and realigned.sorted.bam (from realigner) and
separte the two file paths by a space, to call peaks using the combination of uniquely- and multi-mapped reads.
Alternatively, we can also only input unique.sorted.bam; this will allow CLAM to call peaks using only uniquely-
mapped reads.
Example run:
CLAM peakcaller -i path/to/IP/outdir/unique.sorted.bam path/to/IP/outdir/realigned.sorted.bam \
-c path/to/CTRL/unique.sorted.bam path/to/CTRL/realigned.sorted.bam \
-o path/to/peaks/outdir --unstranded --binsize 100 \
--gtf path/to/gencode.v19.annotation.gtf
This subcommand will call peaks using permutation by randomly placing reads along the gene. More details about the permutation procedure is described in our NAR paper.
Example run:
CLAM permutation_callpeak -i path/to/outdir/unique.sorted.bam path/to/outdir/realigned.sorted.bam \
-o path/to/peaks/outdir -p 8 \
--gtf path/to/gencode.v19.annotation.gtf
The output of the re-aligner is "realigned.sorted.bam" (previously "assigned_multimapped_reads.bam" in v1.0), which is a customized BAM file following SAM format. Note that the re-aligned weights are stored in "AS:" tag, so please be aware and do not change/omit it. Output of re-aligner could also be seen as an intermediate file for CLAM pipeline.
The output of the peak-caller is a bed file following NarrowPeak format. It is a 10-column BED format file.
If you run permutation peak caller (as in v1.0), there will be only one output file called "narrow_peak.permutation.bed". Hence a peak with "combined" but no "unique" on the fifth column indicates this is a rescued peak; both "unique" and "combined" as common peak; or lost peak otherwise.
If you run model-based peak caller (new in v1.1), depending on the specified paramter (whether you turned on --unique-only),
the output will be either "narrow_peak.unique.bed" for peaks called using only uniquely-mapped reads; or
"narrow_peak.combined.bed" for peaks called when adding realigned multi-mapped reads.
Once downloaded the CLAM source code, please download the hnRNPC iCLIP dataset from here.
Then run CLAM by using realigner and permutation_peakcaller on the dataset; if finished correctly, you should have rescued peaks at these two loci:
chr11:82,624,179-82,626,008
chr20:37,054,180-37,055,310
Zijun Zhang zj.z@ucla.edu
Yi Xing yxing@ucla.edu
If you found a bug or mistake in this project, we would like to know about it.
Copyright (C) 2016-2017 University of California, Los Angeles (UCLA) Zijun Zhang and Yi Xing
Authors: Zijun Zhang and Yi Xing
This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.