cbcrg/kallisto-nf

Name: kallisto-nf

Owner: Notredame Lab

Description: A nextflow implementation of Kallisto & Sleuth RNA-Seq Tools

Created: 2015-11-05 14:19:32.0

Updated: 2017-12-04 14:36:10.0

Pushed: 2017-10-13 19:50:14.0

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Size: 109669

Language: R

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README

Kallisto-NF

A Nextflow implementation of Kallisto & Sleuth RNA-Seq Tools

Quick start

Make sure you have all the required dependencies listed in the last section.

Install the Nextflow runtime by running the following command:

$ curl -fsSL get.nextflow.io | bash

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

$ nextflow run cbcrg/kallisto-nf

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.
• Involved in the task: kallisto-mapping.
• By default it is set to the Kallisto-NF's location: ./tutorial/data/*.fastq

Example:

$ nextflow run cbcrg/kallisto-nf --reads '/home/dataset/*.fastq'

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), with A and B being paired reads and C being single ended. The read files could be:

sample_A_1.fastq
sample_A_2.fastq
sample_B_1.fastq
sample_B_2.fastq 
sample_C_1.fastq

The reads may be specified as below:

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

--transcriptome

• The location of the transcriptome multi-fasta file.
• It should end in .fa
• Involved in the task: kallisto-index.
• By default it is set to the Kallisto-NF's localization: ./tutorial/data/transcriptome/trascriptome.fa

Example:

$ nextflow run cbcrg/kallisto-nf --transcriptome /home/user/my_transcriptome/example.fa

--experiment

• Specifies the location of the experimental design file.
• The experimental design file provides Seulth with a link between the samples, conditions and replicates for abundance testing.
• By default it is set to the Kallisto-NF's location: ./tutorial/experiment/high_seqinfo.txt

Example:

$ nextflow run cbcrg/kallisto-nf --experiment '/home/experiment/exp_design.txt'

The experiment file should be a text file, space delimited, in a format similar to as shown below:

run_accession condition sample
SRR493366 control A
SRR493367 control B
SRR493368 control C
SRR493369 HOXA1KD A
SRR493370 HOXA1KD B
SRR493371 HOXA1KD C

--fragment_len

• Specifies the average fragment length of the RNA-Seq library.
• This is required for mapping single-ended reads.
• Involved in the task: kallisto-mapping.
• By default is set 180.

Example:

$ nextflow run cbcrg/kallisto-nf --fragment_len 180

--fragment_sd

• Specifies the standard deviation of the fragment length in the RNA-Seq library.
• This is required for mapping single-ended reads.
• Involved in the task: kallisto-mapping.
• By default this is set 20.
  

Example:

$ nextflow run cbcrg/kallisto-nf --fragment_sd 180

--bootstrap

• Specifies the number of bootstrap samples for quantification of abundances.
• Involved in the task: kallisto-mapping.
• By default this is set 100.

Example:

$ nextflow run cbcrg/kallisto-nf --bootstrap 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 Kallisto-NF's folder: ./results

Example:

$ nextflow run cbcrg/kallisto-nf --output /home/user/my_results 

Cluster support

Kallisto-NF execution relies on 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 spawning 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>'
}

When 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

• Nextflow (0.24.0 or higher)
• Docker (alternatively you will need to install the software packages listed here)