News

AddToAny

Google+ Facebook Twitter Twitter

Large-scale data integration

A Chinese research team has proposed a new algorithm (NetMoss) for efficient integration of large-scale microbiome data and biomarker identification.

The algorithm uses microbial interaction networks to effectively integrate data from different populations. It can quantify the topological differences between different network modules by comparing the perturbations of microbial networks in different states, thus enabling the identification of disease-associated biomarkers.

Compared with previous methods, NetMoss can unbiasedly integrate different batches of microbial data more efficiently, mine disease-associated biomarkers, and identify microbial dysbiosis covariation patterns that drive the occurrence of multiple diseases.

The study is based on 11,377 sequencing samples of gut microbiome from diseased and healthy controls, covering 78 studies, 37 diseases, and 13 countries or regions. The algorithm was applied to simulated and real datasets.

It was highly accurate and robust both in the integrated dataset and in the single dataset.

go.nature.com/3MqfFnq

Image credit | iStock

Related Articles

3D culture-images cellvoyager high content analysis system cq3000

Tech news: March 2024

This month's top tech news stories

Healthcare workers performing surgery at hospital - Image credit | iStock-1145212202

Iodine antiseptic and surgical-site infections

A large multicentre clinical trial found that an antiseptic containing iodine resulted in about one-quarter fewer post-surgical infections in patients with limb fractures compared to another frequently used skin antiseptic.

est Blood Glucose For Diabetes stock photo-CREDIT-istock-836372378

Point-of-care testing

Point of Care Project Manager Rakhee Surti outlines a unique project to enhance patient health outcomes in the community.

Top