CLIPSeqTools is a collection of command line applications used for the analysis of CLIP-Seq datasets. CLIP-Seq stands for UV cross-linking and immunoprecipitation coupled with high-throughput sequencing.
CLIPSeqTools has applications for a wide range of analyses that will give an in depth view of the analysed dataset. Examples of such analyses are: genome read coverage, distibution of reads on genic elements, motif enrichment, relative position of reads of two datasets, differential gene counts, etc).
CLIPSeqTools is grouped in 4 toolboxes each of which performs a specific set of analyses:
Application to analyse a single CLIP-Seq library.
Application to compare two CLIP-Seq libraries. (Can be used after
clipseqtoolsis run on each dataset).
Helper application to create plots for the output of
clipseqtools-compare. (Note: Usually the plotting functions are called from the analysis scripts themselves using the
Application to process a FastQ file into files that are compatible with
clipseqtools. (Among other things, it aligns the reads on the reference genome, annotate the alignments with genic, repeat masker and phastCons conservation information).
CLIPSeqTools is a Perl module and should be compatible with any Unix style operating system with the Perl programming language installed. Chances are that if you are working on a Mac or a Linux operating system you already have Perl installed.
Although the installation is straighforward for people that have some experience with command line installations it can be slightly cumbersome for people with no such experience. For this, we suggest to contact your IT department or someone able to help you with the installation process.
CLIPSeqTools relies on a few external programs for things like the alignment and the plotting functionality. To successfully install and use CLIPSeqTools you will need to have the following tools installed and available in the users path:
Language for statistical computing. To download R statistical package and for installation instructions refer to http://www.r-project.org/
To remove 5' end adaptor sequence from reads (only if you use clipseq-tools preprocess). To download cutadapt and for installation instructions refer to https://code.google.com/p/cutadapt/
For the alignment of reads on a reference genome (only if you use clipseqtools-preprocess). To download STAR and for installation instructions refer to https://code.google.com/p/rna-star/
If you plan on using
clipseqtools-preprocessto do the alignment of reads on a reference genome you will need a machine with at least 16 GB of RAM. The reason is that this is the amount of memory required by the STAR aligner. The amount of required memory might be smaller for smaller genomes but don't take our word for it.
The simplest way to install CLIPSeqTools is to use CPAN which is the a package manager for Perl modules. If you are the system administrator and want to install the module system-wide, you need to switch to your root user.
To fire up the CPAN module, just get to your terminal (Command Line) and run the following command:
perl -MCPAN -e shell
If this is the first time you've run CPAN, it's going to ask you a series of questions - in most cases the default answer is fine.
Once you find yourself staring at the
cpan> command prompt type:
CPAN should take it from there and install CLIPSeqTools.
Download required files
CLIPSeqTools relies on certain data and annotation files to function properly. For the user's convenience, we provide the required files for 3 species - human (assembly: hg19), mouse (assembly: mm9) and fly (assembly: dm3) on our public server.
You may access these file at this link
Prepare your working directory
To keep things simple, in the following we assume you are using a working
clip and that you work for human (hg19) species.
Create a new directory named
This creates the path
hg19.tgzfrom our public server using the link given previously
Put the downloaded file into the new directory
clip/data/and unzip it.
This creates the path
clip/data/hg19/. To save disk space you can now remove file
Assuming your CLIP-Seq data are for proteinA, create a new directory named
This creates the path
Move/Copy the FastQ file with the CLIP-Seq reads into
clip/proteinA/and rename it to reads.fastq.
Important: Unzip it, if it is zipped.
Open a terminal and navigate to your working directory.
List all directories and files with the following command.
You should now have a working directory that looks like this:
clip/ clip/data/ clip/data/hg19/ clip/proteinA/ clip/proteinA/reads.fastq
Verify that everything is in place.
Align and process FastQ files with
To process the fastq file, align the reads on the reference genome, annotate
the alignments with genic, repeat masker and phastCons conservation
information run the following command substituting
<PLACEHOLDER> with the
If you are running on a machine with more than 32GB RAM.
clipseqtools-preprocess all \ --adaptor <3_END_ADAPTOR> \ --fastq proteinA/reads.fastq \ --gtf data/hg19/annotation/UCSC_gene_parts_genename.gtf \ --rmsk data/hg19/annotation/rmsk.bed \ --star_genome data/hg19/STAR/index/ \ --cons_dir data/hg19/phastCons/ \ --rname_sizes data/hg19/chrom.sizes \ --o_prefix clip/proteinA/ \ -v
If you are running on a machine with more than 16GB RAM.
clipseqtools-preprocess all \ --adaptor <3_END_ADAPTOR> \ --fastq proteinA/reads.fastq \ --gtf data/hg19/annotation/UCSC_gene_parts_genename.gtf \ --rmsk data/hg19/annotation/rmsk.bed \ --star_genome data/hg19/STAR/index-sparsed2/ \ --cons_dir data/hg19/phastCons/ \ --rname_sizes data/hg19/chrom.sizes \ --o_prefix clip/proteinA/ \ -v
The command above is doing a lot of things and it's going to take quite some
time. Most likely it will take at least a few hours, so be patient and do
NOT close the terminal. When it finishes you will find all files required to
clipseqtools in the next step under
Analyse a library with
clipseqtools all \ --database proteinA/reads.adtrim.star_Aligned.out.single.sorted.db \ --gtf data/hg19/annotation/UCSC_gene_parts_genename.gtf \ --rname_sizes data/hg19/chrom.sizes \ --o_prefix clip/proteinA/ \ --plot \ -v
The command above is doing many things and is going to take some time,
probably a few hours so be patient and do NOT close the terminal. When
it finishes you will find the result files (tables and figures) in
To view the table files (those with .tab extension) you can open them with a spreadsheet program like MS Excel or copy & paste their content directly into a spreadsheet.
Compare two libraries with
Assuming you have two libraries on which you have previously run
clipseqtools you can now use
clipseqtools-compare to compare their
results. For simplicity, we assume the two directories containing the
clipseqtools results for these two libraries are
clip/proteinB/. To compare the results for the two libraries run the
clipseqtools-compare all \ --database clip/proteinA/reads.adtrim.star_Aligned.out.single.sorted.db \ --res_prefix clip/proteinA/ \ --r_database clip/proteinB/reads.adtrim.star_Aligned.out.single.sorted.db \ --r_res_prefix clip/proteinB/ \ --rname_sizes data/hg19/chrom.sizes \ --o_prefix clip/proteinA_vs_B/ \ --plot \ -v
Note that with the above command we are comparing library proteinA against the reference library proteinB.
The command is going to take some time so be patient. When it finishes you
will find the result files for the analyses in