Example Workflow

We will be working with the first published Ribo-seq dataset GSE13750 from Ingolia et al. (2009) which has samples for both mRNA-seq and Ribo-seq from Yeast grown in starved and nutrient rich media.

At this point, we assume you have already completed all the steps under “Installing dependencies” section of the README.

Step 1: Downloading datasets

We will download all SRA files corresponding to GSE13750.

cd riboraptor
download_sra_data --sradb=../riboraptor-data/SRAmetadb.sqlite \
--geodb=../riboraptor-data/GEOmetadb.sqlite GSE13750

GEO IDs are automatatiicaly converted to corresponding SRP IDs. GSE13750 corresponds to SRP000637.

There are 6 experiments in total (SRX003184-SRX003191), but we will be working with only two: SRX003187`and `SRX003191 one of which is mRNA-seq while other is Ribo-seq. (We will figure out which is which later.) You can delete are SRX directories except the above two. We will be using sacCerR64 as our reference.

We will now use Snakemake to run all the downstream steps. Here is what the overall workflow looks like:

Step 2: Copy template

cd snakemake
cp configs/SRP000637.py.sample configs/SRP000637.py

Edit the paths inside SRP000637.py to point to your RAW data, GTF and BED files. BED files for a lot of assemblies are inbuilt into riboraptor. In most cases, those should suffice. However, you stil need to provide paths to fasta, chromosome sizes and the GTF. The BED files are created from a particular version of the GTF, so if you are using your own GTF, you should ideally be using your own BED files too.

An example of a config would be:

## Path to SRP directory
RAWDATA_DIR = '/staging/as/skchoudh/SRA_datasets/SRP000637'

## Output directory (will be created if does not exist)
OUT_DIR = '/staging/as/skchoudh/riboraptor-analysis/SRP000637'

## Genome fasta location
GENOME_FASTA = '/home/cmb-06/as/skchoudh/genomes/sacCerR64/fasta/Saccharomyces_cerevisiae.R64-1-1.dna.toplevel.fa'

## Chromosome sizes location
CHROM_SIZES = '/home/cmb-06/as/skchoudh/genomes/sacCerR64/fasta/Saccharomyces_cerevisiae.R64-1-1.dna.toplevel.sizes'

## Path to STAR index (will be generated if does not exist)
STAR_INDEX = '/home/cmb-06/as/skchoudh/genomes/sacCerR64/star_annotated'

## GTF path
GTF = '/home/cmb-06/as/skchoudh/genomes/sacCerR64/annotation/Saccharomyces_cerevisiae.R64-1-1.91.gtf'


## Path to bed file containing Intron coordinates
INTRON_BED = '/home/cmb-panasas2/skchoudh/github_projects/riboraptor/riboraptor/annotation/sacCerR64/intron.bed'

## Path to bed file containing CDS coordinates
CDS_BED = '/home/cmb-panasas2/skchoudh/github_projects/riboraptor/riboraptor/annotation/sacCerR64/cds.bed'

## Path to bed file containing 5'UTR coordinates
UTR5_BED = '/home/cmb-panasas2/skchoudh/github_projects/riboraptor/riboraptor/annotation/sacCerR64/utr5.bed'

## Path to bed file containing 3'UTR coordinates
UTR3_BED = '/home/cmb-panasas2/skchoudh/github_projects/riboraptor/riboraptor/annotation/sacCerR64/utr3.bed'

Step 3 : Change your miniconda path

Edit Line4 snakemake/jobscript.sh pointing to your conda root directory.

An example path would be:

export PATH="/home/cmb-panasas2/wenzhenl/miniconda3/bin:$PATH"

Step 4: Edit snakemake/cluster.yaml

Edit Line6 snakemake/cluster.yaml and Line7 snakemake/cluster.yaml to point to your log directory error log file.

An example path would be:

logout: '/home/cmb-06/as/skchoudh/logs/{rule}.{wildcards}.out'
logerror: '/home/cmb-06/as/skchoudh/logs/{rule}.{wildcards}.err'

You would want to just edit the directory path leading to /home/cmb-06/as/skchoudh/logs/ and leave the rest as it is.

Step 5: Submit job

bash submitall.sh SRP000637

The submitall.sh looks for a file named SRP000637.py in the configs directory, so make sure SRP000637.py exists inside configs/ directory.

Visualizing Results

When the entire pipeline as run, it will create an html file riboraptor_report.html as output. You can copy it locally to visualize metagene profiles and read length distribution for all samples.