The SciLifeLab National Genomics Infrastructure is one of the largest sequencing facilities in Europe. We are an accredited facility providing library preparation, sequencing, basic analysis and quality control for Swedish research groups. Our sample throughput requires a highly automated and robust bioinformatics platform. Until recently, we had multiple analysis pipelines built with a range of different workflow tools for each data type. This made development work difficult and led to inevitable technical debt. In this talk I will describe how we have migrated to Nextflow for a range of our data types, the difficulties that we faced and how we hope to leverage Nextflow to migrate to the cloud in coming years.

1. Standardising Swedish
genomics analyses
using nextflow
Phil Ewels
@ewels
@tallphil
Nextflow Meeting
2017-09-14
CRG, Barcelona

2. 2 x MiSeq 5 x HiSeq 2500 5 x HiSeq X10 NovaSeq
RNA-Seq
WG Re-Seq
Targeted Re-Seq
Metagenomics
Others
0 2000 4000 6000 8000 10000 12000 14000
1,265
2,580
3,214
8,934
12,017
Number of
Samples in 2016
1141 Gbp/day
1X Human Genome
every 4 minutes
NGI stockholmstockholm
SciLifeLab NGI

3. CumulativeOutput(MBp)
0
250,000,000
500,000,000
750,000,000
1,000,000,000
Jan
2012
Sep
2012
M
ay
2013
Jan
2014
Sep
2014
M
ay
2015
Jan
2016
Sep
2016
M
ay
2017
NGI stockholmstockholm - sequencing output
SciLifeLab NGI

4. NGI bioinformatics
• Initial data analysis for major protocols
• Internal QC and standardised starting
point for users
• Team of 10 bioinformaticians
• Accredited facility

5. analysis requirements
Automated
Reliable
Easy for others to run
Reproducible results
icons: the noun project

6. NGI pipelines
NouGAT (de-novo)

7. what have we learnt?

8. sharing is caring

9. sharing is caring
• Open-source on GitHub from day one
• Easier help and feedback from others
• Other people may help to develop your code
• https://github.com/nextflow-io/awesome-nextflow

10. use containers

11. use containers
• Create a docker image, even if you don’t think you
need to
• Makes local and automated testing possible
• Future proof for cloud / singularity / other people

12. test, test and test again

13. test, test and test again
• Find a small test dataset
• Make a bash script to fetch data and launch pipeline
• Different flags to launch with different parameters
• Use Travis build matrix to launch parallel test runs

14. use versioned releases

15. use versioned releases

16. minimal configs

17. minimal configs
• Build config files around blocks of function
• Hardware / software deps / genome references
• Use nextflow profiles
• Even if only using ‘standard’ default
• Don’t be afraid to use multiple configs per profile
• Build on a base profile and be clever with
limits

18. minimal configs
def check_max(obj, type) {
if(type == 'memory'){
if(obj.compareTo(params.max_memory))
return params.max_memory
else
return obj
} else if(type == 'time'){
if(obj.compareTo(params.max_time))
return params.max_time
else
return obj
} else if(type == 'cpus'){
return Math.min( obj, params.max_cpus )
}
}
nextflow.config
process {
cpus = { check_max(16, 'cpus') }
memory = { check_max(128.GB, 'memory') }
time = { check_max(10.h, 'time') }
}
conf/base.config
profiles {
standard {
includeConfig 'conf/base.config'
includeConfig 'conf/igenomes.config'
includeConfig 'conf/uppmax.config'
}
devel {
includeConfig 'conf/base.config'
includeConfig 'conf/igenomes.config'
includeConfig 'conf/uppmax.config'
includeConfig 'conf/uppmax-dev.config'
}
}
nextflow.config
params {
max_cpus = 1
max_memory = 16.GB
max_time = 1.h
}
conf/uppmax-dev.config

19. reference genomes

20. reference genomes
params {
genomes {
'GRCh37' {
fasta = '/refs/human/genome.fasta'
gtf = '/refs/human/genes.gtf'
}
'GRCm38' {
fasta = '/refs/mouse/genome.fasta'
gtf = '/refs/mouse/genes.gtf'
}
}
}
conf/references.conf
params.fasta = params.genome ? params.genomes[ params.genome ].fasta ?: false : false
params.gtf = params.genome ? params.genomes[ params.genome ].gtf ?: false : false
main.nf
$ nextflow run main.nf --genome GRCh37
$ nextflow run main.nf --fasta /path/to/my/genome.fa

21. reference genomes
• illumina iGenomes is a great resource for this
• Standard organisation allows easy use of multiple
genomes
• Use AWS iGenomes for free on AWS S3
• See https://ewels.github.io/AWS-iGenomes/

22. problems we’ve hit

23. dodgy file patterns

24. dodgy file patterns
Channel
.fromFilePairs(
params.reads,
size: -1
)
Channel
.fromFilePairs(
params.reads,
size: params.singleEnd ? 1 : 2
)
If glob pattern doesn’t use {1,2}
then all PE files are run in SE mode
If glob pattern doesn’t use {1,2}
then pipeline exits with no matching files

25. overwriting params

26. overwriting params
// Custom trimming options
params.clip_r1 = 0
params.clip_r2 = 0
params.three_prime_clip_r1 = 0
params.three_prime_clip_r2 = 0
// Preset trimming options
params.pico = false
if (params.pico){
params.clip_r1 = 3
params.clip_r2 = 0
params.three_prime_clip_r1 = 0
params.three_prime_clip_r2 = 3
}
// Custom trimming options
params.clip_r1 = 0
params.clip_r2 = 0
params.three_prime_clip_r1 = 0
params.three_prime_clip_r2 = 0
// Define regular variables
clip_r1 = params.clip_r1
clip_r2 = params.clip_r2
tp_clip_r1 = params.three_prime_clip_r1
tp_clip_r2 = params.three_prime_clip_r2
// Preset trimming options
params.pico = false
if (params.pico){
clip_r1 = 3
clip_r2 = 0
tp_clip_r1 = 0
tp_clip_r2 = 3
}
regular variables
(this now triggers a
warning message)

27. quick-fire round

28. MultiQC in workflows

29. MultiQC in workflows
params.multiqc_config = "$baseDir/conf/multiqc_config.yaml"
multiqc_config = file(params.multiqc_config)
process run_multiqc {
input:
file multiqc_config
file ('fastqc/*') from fastqc_results.collect()
file ('alignment/*') from alignment_logs.collect()
output:
file "*multiqc_report.html" into multiqc_report
file "*_data"
script:
"""
multiqc -f --config $multiqc_config .
"""
}
extra_fn_clean_exts:
- _R1
- _R2
report_comment: >
This report has been generated by the NGI-RNAseq analysis pipeline.
For information about how to interpret these results, please see the docs.
conf/multiqc_config.yaml

30. software versions
process get_software_versions {
output:
file 'software_versions_mqc.yaml' into software_versions_yaml
script:
"""
echo $pipeline_version > v_ngi_methylseq.txt
echo $workflow.nextflow.version > v_nextflow.txt
fastqc --version > v_fastqc.txt
samtools --version > v_samtools.txt
scrape_software_versions.py > software_versions_mqc.yaml
"""
}
main.nf

31. email notifications

32. email notifications
workflow.onComplete {
def subject = 'My pipeline execution'
def recipient = 'me@gmail.com'
['mail', '-s', subject, recipient].execute() << """
Pipeline execution summary
---------------------------
Completed at: ${workflow.complete}
Duration : ${workflow.duration}
Success : ${workflow.success}
workDir : ${workflow.workDir}
exit status : ${workflow.exitStatus}
Error report: ${workflow.errorReport ?: '-'}
"""
}
Nextflow documentation

33. email notifications
workflow.onComplete {
// Render the HTML template
def hf = new File("$baseDir/assets/email_template.html")
def html_template = engine.createTemplate(hf).make(email_fields)
def email_html = html_template.toString()
// Send the HTML e-mail
if (params.email) {
[ 'sendmail', '-t' ].execute() << sendmail_html
log.info "[NGI-MethylSeq] Sent summary e-mail to $params.email (sendmail)"
}
// Write summary e-mail HTML to a file
def output_d = new File( "${params.outdir}/pipeline_info/" )
if( !output_d.exists() ) {
output_d.mkdirs()
}
def output_hf = new File( output_d, "pipeline_report.html" )
output_hf.withWriter { w -> w << email_html }
}
main.nf

34. email notifications
<html>
<head><title>NGI-MethylSeq Pipeline Report</title></head>
<body>
<h1>NGI-MethylSeq: Bisulfite-Seq Best Practice v${version}</h1>
<h2>Run Name: $runName</h2>
<% if (success){
out << """
<div style="color: green;">NGI-MethylSeq execution completed successfully!</div>
"""
} else {
out << """
<div style="color: #red;">
<h4>NGI-MethylSeq execution completed unsuccessfully!</h4>
<p>The exit status of the failed task was: <code>$exitStatus</code>.</p>
<p>The full error message was:</p>
<pre>${errorReport}</pre>
</div>
"""
}
%>
assets/email_template.html

35. [NGI-RNAseq] Successful: Test RNA Run
email notifications

36. email notifications

37. email notifications
[NGI-RNAseq] FAILED: Test RNA Run

38. Groovy syntax highlighting
run-STAR = params.runstar
run-STAR = params.runstar
#!/usr/bin/env nextflow
/*
vim: syntax=groovy
-*- mode: groovy;-*-
*/
main.nf
without highlighting:
with highlighting:

39. saving intermediates
publishDir "${params.outdir}/trim_galore",
mode: 'copy',
saveAs: {fn ->
if (fn.indexOf("_fastqc") > 0) "FastQC/$fn"
else if (fn.indexOf("trimming_report") > 0) "logs/$fn"
else params.saveTrimmed ? fn : null
}
publishDir "${params.outdir}/STAR",
mode: 'copy',
saveAs: {
fn -> params.saveAlignedIntermediates ? fn : null
}

40. future plans
• Use singularity for everything
• Benchmark AWS run pricing for future
planning
• Refine pipelines
• Improve resource requests
• Automate launch and run management

41. Phil Ewels
phil.ewels@scilifelab.se
ewels
tallphil
Acknowledgements
http://github.com/SciLifeLab
http://opensource.scilifelab.se
NGI stockholm
Max Käller
Rickard Hammarén
Denis Moreno
Francesco Vezzi
NGI Stockholm Genomics
Applications Development Group
Paolo Di Tommaso
The nextflow community