Sketching the SRA: experiment-wide similarity search across 4.8 million metagenomes
Recent efforts have demonstrated that systematic analysis of the millions of metagenomes in the Sequence Read Archive (SRA) enables groundbreaking biological discoveries. However, SRA-scale comparison of whole metagenomes has remained elusive. Here, we introduce the most comprehensive resource to date for experiment-to-experiment analysis of all SRA metagenomes, comprising FracMinHash sketches…
Systematic analysis of millions of metagenomes in the Sequence Read Archive (SRA) has led to groundbreaking biological discoveries. However, comparing whole metagenomes on such a massive scale has been difficult until now. A team of researchers has now unveiled the most comprehensive resource for experiment-to-experiment analysis of all SRA metagenomes.
The resource comprises three key components - FracMinHash sketches (470GB), hypergen sketches (19GB), and an all-pairs Jaccard similarity matrix (90GB), which are available online at https://github.com/RolandFaure/SRA-metagenome-sketches-databases.
These resources pave the way for a wide range of analyses. The FracMinHash sketches were used to uncover temporal trends in the SRA data, revealing that the amount of newly discovered microbial sequence continues to grow. The hypergen sketches, which facilitate nearest-neighbor search, were employed to identify co-assembly candidates, leading to improved assembly quality. Using the similarity matrix, researchers identified duplicated submissions and over 50,000 candidates for metadata correction across all SRA metagenomes.
In essence, these resources revolutionize the way metagenomic data is analyzed, enabling systematic analysis at an unprecedented scale.
Written by urgent.news from bioRxiv's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
