psiCLIP

Scripts for the pre-processing and figures from "PsiCLIP reveals dynamic RNA binding by DEAH-box helicases before and after exon ligation". The data for this paper is accessible from Array Express: E-MTAB-8895.

Dependencies

To install everything you need to run this code I recommend creating a conda environment. This is done for you in the pre-processing script, but does require that you have Anaconda or miniconda installed.

conda env create -f psiclip_environment.yml

Alternatively, ensure you have the packages in psiclip_environment.yml installed.

Pre-processing

Mapping of demultiplexed fastq files and processing to crosslink sites is performed by a Snakemake workflow. This consists of a Snakefile and config.yaml. The chunks of code are contained in the Snakefile and the sample annotations are in the config.yaml.

Run the demo

I have created a one-sample demo so that you can test the running of the pre-processing pipeline on your machine. This was tested on a 2017 MacBook Pro with 16GB memory, 3.1 GHz Intel Core i7 processor, running macOS Sierra and ran in 11m6.587s. This will run much faster on a computing cluster!
Important: Anaconda or miniconda must be pre-installed to allow the creation of a conda environment to install dependencies.

1. Clone this repository to your computer.

git clone https://github.com/luslab/psiclip.git

2. Run ./prep-for-demo.sh to download some annotation files and create the conda environment.
3. Move to the demo directory and run snakemake:

cd demo
conda activate psiclip
# If you are running on your desktop:
snakemake -k --cores 4 --jobs 200 --latency-wait 60 --rerun-incomplete
# If you are running on a cluster:
snakemake -k --cluster 'sbatch {params.cluster}' --jobs 200 --latency-wait 60 --rerun-incomplete

I want to reproduce the paper

Note: This analysis has been tested and optimised for a SLURM computing cluster. The files are small enough that the analysis could feasibly run on a laptop. In which case the command to run Snakemake should be altered to remove the --cluster flag. For alternative cluster architectures, the cluster paramater for each step would be need to be changed to the correct format.

1. Clone this repository to your computing cluster (note if you are not using a cluster environment, you will need to set cores and memory as in the demo snakemake command, based on the resources you have available).

git clone https://github.com/luslab/psiclip.git

2. Run ./prep-for-preprocessing.sh. This script will download the raw fastq files from Array Express and the metadata information; it will download the yeast genome and annotation from Ensembl; it will create a conda environment called "psiclip" containing all the programs you need.
3. Move to the pre_processing directory and run snakemake:

conda activate psiclip
cd pre_processing
snakemake -k --cluster 'sbatch {params.cluster}' --jobs 200 --latency-wait 60 --rerun-incomplete

I want to modify the code for new substrates or samples

In order to modify this code for new samples, you will need to annotate them as we have for our samples in the config.yaml. If you are using a different pre-mRNA substrate you will need a fasta file with your substrate and the snRNAs to map against and an annotation file with the intron position. You can copy the format we have used for our different substrates. The final step for adding a new substrate is to add a new rule in the Snakemake workflow to generate the index for your substrate, and add a new line to the mapping rule, such that it will know to check for your new substrate. The format is straightforward to copy from the substrates available already. Note that post-"substratome" mapping is done to the yeast genome in this script, but this could be modified if your sample was in human extract for example.

Scripts for downstream analysis

The main concept for the downstream analysis is that cDNAs mapping to the substratome are normalised to the total cDNAs that map to the yeast genome, because we found that this behaved a lot like a spike-in. We also gaussian smooth the signal and subtract the FLAG-tagged experimental condition from the non-tagged condition.

I want to reproduce the paper

1. Run the steps for pre-processing.
2. Run relevant script from figure_scripts folder. Ensure you are in your psiclip conda environment/ or have the relevant R packages installed.

Contact

Charlotte Capitanchik, charlotte.capitanchik@crick.ac.uk if you have questions.