Insights, opportunities, and challenges provided by large cell atlases

Area of Science:

• Single-cell biology
• Computational biology
• Data science

Background:

• Rapid advancements in single-cell biology generate large, diverse datasets across species and conditions.
• Coordinated initiatives like CZI CELLxGENE, HuBMAP, DISCO, and the Broad Institute Single Cell Portal provide access to curated single-cell data beyond scRNA-seq.
• These data repositories offer opportunities for computational biology to develop novel tools and extract biological insights.

Purpose of the Study:

• To review the current achievements in leveraging large-scale single-cell datasets.
• To identify areas requiring further development in the computational biology ecosystem.
• To outline specific challenges hindering the full utilization of single-cell data.

Main Methods:

• Review of existing coordinated data access efforts (CZI CELLxGENE, HuBMAP, DISCO, Broad Institute Single Cell Portal).
• Analysis of the current state of computational tools for single-cell data reuse.
• Identification of challenges and future directions in the field.

Main Results:

• Significant progress has been made in curating and accessing diverse single-cell datasets.
• The computational biology ecosystem is expanding to support data reuse and insight generation.
• Key challenges include data integration, tool development, and standardization.

Conclusions:

• The growing volume of single-cell data presents a critical opportunity for computational biology.
• Further development is needed to create robust tools for data analysis and biological discovery.
• Overcoming specific challenges will enhance the reuse of single-cell data and accelerate scientific breakthroughs.