-Seqera, the leading software provider for complex data analysis in the life sciences space, announced the launch of Seqera Containers, a no-cost, streamlined bioinformatics container solution, during their second annual Nextflow SUMMIT in Boston. This publicly available project creates a simplified experience, allowing developers and researchers to effortlessly assemble containers tailored to their needs without having to build and upload custom container images.

Powered by Amazon Web Services (AWS), this solution assembles on-demand containers via Wave, Seqera’s open-source, next-generation container provisioning service. Wave handles all of the heavy lifting, ensuring seamless image creation and availability. With access to Conda and Python Package Index’s (PyPi) collection of packages, scientists can now generate a container at the easy click of a button, eliminating the need to sift through existing container images or push local ones to a remote location.

“Scientific research can be a daunting task, full of slow and frustrating processes that can waste valuable time and energy that could otherwise be put toward discovery and innovation,” said Evan Floden, Founder and CEO of Seqera. “Seqera Containers enable reproducibility, scalability, and collaboration in bioinformatics research, easing the burden of software management so researchers can focus on core scientific endeavors. With the inclusion of this solution into our platform, we’re on track to create a centralized hub for scientists’ every analytical need, supporting them with access to a community of their peers to enhance research and accelerate the pace of discoveries.”

Containers assembled on-demand through Seqera are publicly accessible to the entire user community, empowering scientists with seamless access to bioinformatics resources. Images requested through the Seqera Containers web interface can be accessed instantly with consistent reuse across organizations by anyone in the community. This solution optimizes analyses and pipelines, significantly saving time and costs in production. It also ensures the reproducibility that is so crucial to scientific research while minimizing the burden of creating custom containers.