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Lifebit
The Francis Crick Institute & Lifebit are co-hosting the London Bioinformatics Frontiers Conference on June 17th & 18th. We’re excited to round up the best of the best in terms of speakers covering a variety of topics, including how to standardise and scale analysis using Nextflow, Containers & Cloud.
Day 1 (June 17th) will consist of talks from the experts. And on Day 2, we will be hosting a hackathon which is open to participants who have pipelines they would like to convert to Nextflow, or that have existing Nextflow pipelines that they want to standardise using nf-core guidelines and/or scale over Cloud.
During this conference, speakers will mainly be focusing on the application of these three topics to real-world large-scale bioinformatics challenges rather than covering the basics of the technologies as we believe this will bring conference attendees more actionable knowledge to apply to their own research & work.
Here, we highlight a few of the applications that are tremendously pushing the limits of big data analysis in the Life Science sector.
Nextflow [programming framework which makes pipelines more efficient]
- Challenge: Wasting time waiting for your analyses to finish.
- Solution? By using Nextflow, processes are parallelised and can run at the same time.
- Challenge: Having to run multiple scripts in different programming languages which are difficult to connect.
- Solution? By using Nextflow different processes can be written in different programming languages and seamlessly connected
- Challenge: Not being able to run a script in a different computing environment.
- Solution? Nextflow makes pipelines more portable by providing a level of abstraction between your pipeline’s logic and the execution layer, meaning your pipelines run on the cloud and in HPC with little/no modification
Containers [standardised units of software]
- Challenge: Software sustainability has been identified as one of the key challenges in scientific & engineering software development.
- Solution? Securing software functionality with containers (i.e. Docker) as it ensures that a functional version of the tool can be re-used in the future.
- Challenge: Being unsure about whether a pipeline will work in a certain compute environment.
- Solution? Installing dependencies with Docker. By using Docker, all code dependencies can be installed and the user can benefit from knowing that the pipeline will work regardless of the compute environment.
- Challenge: Being able to reproduce a colleague’s analysis
- Solution? Immutable container tags, along with the ease of portability, allow for an analysis to be quickly reproduced by others, with minimal configuration overhead.
- Challenge: Having different versions of software which leads to run errors.
- Solution? Container modularity ensures that different versions of the same software can be utilised in one unified workflow.
Cloud [on-demand availability of computer system resources]
- Challenge: Having the necessary infrastructure to scale big data analysis.
- Solution? By using Cloud, bioinformaticians can achieve limitless scale on-demand.
Don’t forget to sign up for the conference before places run out!
