lncRNA-Annotation-NF

A Nextflow implementation of a lncRNA Annotation Pipeline

Quick start

Make sure you have all the required dependencies listed in the last section or run with Docker.

Install the Nextflow runtime by running the following command:

$ curl -fsSL get.nextflow.io | bash

When done, you can launch the pipeline execution with Docker by entering the command shown below:

$ nextflow run skptic/lncRNA-Annotation-nf -profile test

By default the pipeline is executed against the provided example dataset. Check the Pipeline parameters section below to see how enter your data on the program command line.

Pipeline parameters

--reads

• Specifies the location of the reads fastq file(s).
• Multiple files can be specified using the usual wildcards (*, ?), in this case make sure to surround the parameter string value by single quote characters (see the example below)
• It must end in .fastq.gz.
• Involved in the task: mapping.
• By default it is set to the lncRNA-Annotation-NF's location: ./tutorial/reads/*.fastq.gz

Example:

$ nextflow run cbcrg/lncRNA-Annotation-nf --reads '/home/dataset/*.fastq.gz'

This will handle each fastq file as a seperate sample.

Read pairs of samples can be specified using the glob file pattern. Consider a more complex situation where there are three samples (A, B and C) being paired ended reads. The read files could be:

sample_A_1.fastq.gz
sample_A_2.fastq.gz
sample_B_1.fastq.gz
sample_B_2.fastq.gz
sample_C_1.fastq.gz
sample_C_2.fastq.gz

The reads may be specified as below:

$ nextflow run cbcrg/lncRNA-Annotation-nf --reads '/home/dataset/sample_*_{1,2}.fastq.gz'    

--genome

• The location of the genome multi-fasta file.
• It should end in .fa
• Involved in the task: indexing.
• By default it is set to the lncRNA-Annotation-NF's localization: ./tutorial/data/genome/genome.fa

Example

$ nextflow run cbcrg/lncRNA-Annotation.nf --genome /home/genomes/Sscrofa_102.fa

--annotation

• Specifies the location of the input annotation file in GTF format.
• By default it is set to the lncRNA-Annotation-NF's location: ./tutorial/annotation/annotation.gtf

Example:

$ nextflow run cbcrg/lncRNA-Annotation-nf --annotation '/home/annotation/Sscrofa_102.gtf'

--overlap

• Specifies the length of the genomic sequence around the annotated junction to be used in constructing the splice junction database in STAR.
• It should be set to the read length minus one.
• Involved in the task: indexing.
• By default is set to 100.

Example:

$ nextflow run cbcrg/lncRNA-Annotation-nf --overlap 100

--output

• Specifies the folder where the results will be stored for the user.
• It does not matter if the folder does not exist.
• By default is set to lncRNA-Annotation-NF's folder: ./results

Example:

$ nextflow run cbcrg/lncRNA-Annotation-nf --output /home/user/my_results 

Cluster support

lncRNA-Annotation-NF execution relies on the Nextflow framework which provides an abstraction between the pipeline functional logic and the underlying processing system.

Thus it is possible to execute it on your computer or any cluster resource manager without modifying it.

Currently the following platforms are supported:

• Oracle/Univa/Open Grid Engine (SGE)
• Platform LSF
• SLURM
• PBS/Torque

By default the pipeline is parallelized by spanning multiple threads in the machine where the script is launched.

To submit the execution to a SGE cluster create a file named nextflow.config, in the directory where the pipeline is going to be launched, with the following content:

process {
  executor='sge'
  queue='<your queue name>'
}

In doing that, tasks will be executed through the qsub SGE command, and so your pipeline will behave like any other SGE job script, with the benefit that Nextflow will automatically and transparently manage the tasks synchronisation, file(s) staging/un-staging, etc.

Alternatively the same declaration can be defined in the file $HOME/.nextflow/config.

To lean more about the avaible settings and the configuration file read the Nextflow documentation.

Dependencies

• Java 7+
• Nextflow (0.17.4 or higher)
• STAR - https://github.com/alexdobin/STAR
• Cufflinks - http://cole-trapnell-lab.github.io/cufflinks
• FEELnc - https://github.com/tderrien/FEELnc