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STAVE stands for Spatial-Temporal Aggregated Variant Encoding.

It is a lightweight data schema for organising aggregate counts of non-synonymous mutations, which is a data type commonly found in malaria molecular surveillance (MMS) studies. STAVE provides a consistent way to link genetic measurements to precise space–time coordinates, and to estimate the prevalence of particular genetic variants even when mixtures or ambiguous calls are present.

What STAVE is designed to do

STAVE focuses on a small number of key tasks that commonly cause errors or inconsistencies in MMS workflows:

  • Provide a simple, relational data structure for storing study metadata, survey-level space–time information, and aggregated genetic counts.
  • Encode haplotypes of non-synonymous mutations (i.e. changes in amino acid) in a compact, human-readable format using the variantstring format.
  • Support robust prevalence estimation, even when variants represent subsets of longer haplotypes or when mixed calls introduce uncertainty.

STAVE is deliberately minimal: it does not attempt to handle individual-level data, nucleotide-level data, or downstream spatial modelling. Instead, it aims to slot cleanly into broader analysis workflows by providing a reliable and unambiguous foundation on which those steps can build.

Getting started

To learn how the STAVE data structure works, see How it works.

When you’re ready to start working with the package, visit: