Pipeline development is the process of designing, creating, testing, and maintaining software pipelines. Our company has extensive experience in pipeline development for any type of analysis and has specialists with computational background and experience in Machine learning algorithms and programming languages such as R, Python, Perl, Bash programming, etc. We have created pipelines with the help of Snakemake and Nextflow tools that are both workflow management systems designed to facilitate the creation, execution, and management of bioinformatics pipelines. These tools aim to simplify the complexity of organizing and executing computational workflows, particularly in the context of high-throughput data analysis, such as genomics, transcriptomics, and proteomics.

An effective pipeline development depends on different factors, such as an organisation’s technology stack, the level of expertise and the available budget. It is very important to have a comprehensive understanding of both development and operations, including coding, infrastructure management, system administration, in order to build an effective pipeline. 

What is a pipeline?

Pipelines are a series of interconnected steps that allow software to be developed from source code to a running executable.

Pipeline can minimise human error and maintain a consistent process for how software is released. Some of the tools included in the pipeline are compiling code, unit tests, code analysis, security, and binaries creation. 

Pipeline development stages

A pipeline development consists of four primary stages:

Version Control: This is the initial stage and it takes place after the new code was written and saved to a source control repository. After the code is verified it is now prepared for the following stage in the deployment pipeline.

Acceptance Tests: This stage consists of a series of tests that the new code is going through, in order  to check it against the team pre-established acceptance criteria. At this point, it’s important to have these assessments tailored to the organisation’s objectives and user requirements for the product. 

Independent Deployment: After acceptance testing and verification stage, the next stage that the code will go through is the independent deployment stage. Basically, the code is automatically deployed to a development environment that should closely mirror the production environment to enable accurate functionality testing.  This stage is very important as it will ensure that the final product is free of bugs that could potentially affect the live user experience.

Production Deployment: The last phase of the deployment pipeline is production deployment, where the code is launched for the end-user instead of a separate development environment.