Mantle is a modern data stack in a single platform, built specifically for science.

Mantle’s features and software development kit (SDK) allow you to centralize and structure your data, as well as perform data processing and analysis easily, traceably, and reproducibly.

The Mantle data lake allows you to centralize your data, making it easy to find, whether you are looking for raw data files or results.

Within a Mantle dataset, you can store raw data and metadata together. For example, a sequencing dataset might contain FASTQ files and information about the data, such as a sample ID, tissue or organism type, or CRO who collected the data. You can specify a configuration of a dataset — the file type(s) and metadata fields that are present in a dataset — as a data type, which is applied to all datasets that share that configuration.

Transform, process, and draw insights from raw data using analyses and pipelines.

A Mantle analysis is an ad-hoc or custom computational analysis in a hosted Jupyter Notebook that is launched in a containerized analysis environment. It allows you to jump in and explore your data quickly.

A Mantle pipeline is a pre-defined computational analysis. A pipeline consists of a workflow, defined using Nextflow; an environment, containerized using Docker; and a schema for inputs and outputs. Once a pipeline is configured on Mantle, users can run the pipeline with no code through the Mantle user interface. A Mantle pipeline run generally takes datasets as inputs and may also produce datasets as outputs.

​

Get started