Science Daily April 19, 2021
A team of researchers in the US (University of Michigan, The Salk Institute for Biological Studies) has developed online integrative non-negative matrix factorization (iNMF), an algorithm for integrating large, diverse, and continually arriving single-cell datasets. The approach scales to arbitrarily large numbers of cells using fixed memory, iteratively incorporates new datasets as they are generated and allows many users to simultaneously analyze a single copy of a large dataset by streaming it over the internet. Iterative data addition can also be used to map new data to a reference dataset. The improvements in efficiency do not sacrifice dataset alignment and cluster preservation performance. They demonstrated the effectiveness of online iNMF by integrating more than 1 million cells on a standard laptop, integrating large single-cell RNA sequencing and spatial transcriptomic datasets, and iteratively constructing a single-cell multi-omic atlas of the mouse motor cortex…read more. TECHNICAL ARTICLE
Overview of the online iNMF algorithm. Credit: Nature Biotechnology (2021)