Metagenomics Classification

Next-generation sequencing, specifically ‘metagenomics’, has enabled a fundamentally new understanding of the microbial world. The gut microbiome has been implicated in a range of health outcomes from obesity, to Alzheimer’s, to immunotherapy response. R&D groups monitoring bacterial species diversity and discovering microbiome-derived therapeutic candidates need access to large-scale data analysis capabilities from day one.

Manage all metagenomics data

The monitoring of microbial samples over time generates large collections of FastQ files that will only grow in number. Storage and processing infrastructure must flex accordingly.

Latch allow your team monitor your microbial samples as large collections of FastQ files within latch. Import them to Latch Data and then organize/associate them with metadata in Latch Registry

Obtain Amplicon Sequence Variants (ASVs) to find sample composition

Today’s metagenomics sequencing technologies generate a variety of read lengths and outputs. You must stitch reads together and assemble them into genes or organisms. Complex multi-step bioinformatics pipelines are needed for insights like variant identification.

A bioinformatician can use the Latch SDK to develop a variant identification workflow with a user-friendly interface for other scientists/biologists to run. Or they may use common metagenomics tools which are available on Latch:

Explore phylogeny and taxonomy. Identify microbial features for more research.

Generate visualizations from taxonomic classification data in your browser. Explore alpha or beta diversity and phylogenetic relationships. All of this in custom, templated notebooks.

A bioinformatician can develop a Latch Template that serve Shiny applications like Phylo-seq for scientists to track the dynamic evolution of a microbial population over time. The biologists on their team simply click “Use Template” to begin their own analysis, without having to set up an environment or install dependencies.

Elegantly Store Data and Organize for Longitudinal Analyses

Take raw outputs from taxonomic classification pipelines, as well as analysis reports, and attach metadata. Organize samples based on characteristics like time point or Patient ID in Latch Registry.

Query data to assemble comparisons of certain samples based on time point.