Seeing Unseen Biological Data — Biotech cover image

Seeing Unseen Biological Data

New tool visualizes hidden structures in complex biological data

Introduction To Complex Biological Data

Modern biology research has entered the era of "big data," generating vast datasets that capture the identities and multidimensional characteristics of cells. However, analyzing and interpreting such complex datasets remains a major challenge. A team at the University of Basel, Switzerland, has developed a new tool that can provide accurate pictures of the structures hiding within highly complex datasets. This tool, called Bonsai, visualizes high-dimensional data on a tree, helping scientists uncover hidden patterns in the data and make new scientific discoveries.

Understanding High-Dimensional Data

High-throughput technologies, such as single-cell RNA sequencing, generate large-scale datasets that capture the activity of tens of thousands of genes in hundreds of thousands or even millions of individual cells. These data promise to provide fundamental new insights into how cells develop, communicate, and change during disease. However, people are not good at recognizing patterns in high-dimensional spaces, and analyzing such complex datasets is a major challenge. Most popular tools force data with thousands of dimensions into a two-dimensional map, which can distort the data and make it impossible to tell whether the displayed relationships between cells are true or artifacts.

Bonsai accurately reconstructs cell relationships from simulated single-cell RNA sequencing data

The Bonsai Tool

Bonsai overcomes the problem of distorting high-dimensional data by building a branching tree, with individual cells at the leaves of the branches. The distances along the branches accurately reflect how closely cells are related in the high-dimensional space. The team tested the software on both simulated and real single-cell RNA sequencing datasets and found that Bonsai reconstructs developmental pathways vastly more accurately, preserves the true relationships between cells, and identifies similar cells much more reliably.

Real-World Implications

When the researchers analyzed human blood cells, Bonsai not only automatically recovered the known relationships between different blood cell types but also uncovered a novel subtype of immune cell known as natural killer (NK) cells. The molecular signature of this new subtype of NK cells revealed new insights into the development and function of these cells. This demonstrates the potential of Bonsai to help scientists make new discoveries and gain a deeper understanding of complex biological systems.

Future Outlook

The development of Bonsai is a significant step forward in the analysis and interpretation of complex biological data. By providing accurate pictures of the structures hiding within high-dimensional datasets, Bonsai has the potential to accelerate scientific discoveries and improve our understanding of complex biological systems. As the field of biology continues to generate large-scale datasets, tools like Bonsai will be essential for uncovering hidden patterns and relationships in the data.

Sources

This is an original synthesis by Qivorane based on reporting from the outlets below.

Qivorane Editorial

Qivorane Editorial summarizes and explains science and technology news from multiple reputable sources. Our articles are original summaries and analysis, researched with AI assistance and reviewed before publishing.