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Helmholtz Munich I Daniela Barreto

Open Source Consortium for Single-Cell Analysis

Featured Publication, ICB,

The technological progress for single-cell research resulted in an increasing amount of data, accordingly big data has become one of the central parts in medical research. “Omics” technologies do not just rely on large scale molecular datasets but also on sufficient computational tools for analysis. Therefore, the multi-institutional open source software scverse was developed with interoperable, scalable and user-friendly tools for storage- and analysis-problems of single-cell profiling data.

The immense growth of new computational analyzing-tools and data structures are intended to simplify single-cell analysis, but users and developers often face challenges such as incompatibilities of data structures or difficult to handle user-interfaces. Hence, researchers coming not only from Helmholtz Munich but from a variety of institutions all around the world founded a new open-source software organization for Python tooling in the single-cell analysis ecosystem, named scverse (https://scverse.org). This enables the joint maintenance and development to ensure interoperability across all single-cell ecosystems while allowing users to attend joint events to learn how to use the fundamental tooling and contribute to the ecosystem.

Scverse Builds on Top of Essential Data Structures for Interoperability

Single-cell technology is becoming more complex every year which is accompanied by a strong demand for scalable and user-friendly data analysis software. Tooling for single-cell in the Python world is built around the researchers’ computational data structures AnnData and MuData, which are computational objects to store and annotate high-dimensional multimodal data. The researchers of scverse built core tooling around the aforementioned data structures that are accompanied by ecosystem tools of other researchers to meet the demand for tooling. The formation of the new organization scverse will allow the researchers to tackle the most pressing issues of the field such as low discoverability and documentation as well as a lack of testing. At the same time the new consortium scverse will promote a healthy, growing and sustainable community.

The Open Community Facilitates Usage and Development

The vision of the founders of scverse is that everyone who is interested can use scverse core tools and become part of the community. All contributions are made on public platforms allowing everyone to participate in the scverse community. Work is done through Github (https://github.com/scverse), development is coordinated in an open Zulip chat (https://scverse.zulipchat.com/) and help is provided in a Discourse forum (https://discourse.scverse.org) to enable close communication between users and developers. The application of the researchers' widely regarded and scalable solutions to single-cell data could lead to novel solutions and discoveries in the single-cell field such as the building of big single-cell atlases, new cell types or disease markers.

 

Original publication

Virshup et al. (2023): scverse: foundational tools for single-cell omics data analysis. Nature Biotechnology. DOI: 10.1038/s41587-023-01733-8

More Information

Open source consortium: https://scverse.org

Contact for scverse: steering-council@scverse.org

Fabian Theis_freigestellt

Prof. Dr. Dr. Fabian Theis

Director of Biomedical AI