Recent news

19 Jan 2015

WeaveAlign v1.2.1 is released (changelog)

WeaveAlign is available from the Downloads page.

What is WeaveAlign?

WeaveAlign is a framework for combining a collection of multiple sequence alignments into a directed acyclic graph (DAG) structure, so as to permit efficient inference on very large sets of possible alignments.

Due to interchanges and crossovers in the DAG, the number of alignments encoded in the graph is typically many orders of magnitude greater than the number of alignment samples used to generate the DAG, such that the effective sample size is greatly increased by this representation.

This allows for more efficient estimation of the posterior probabilities of each sampled alignment, and enables summary alignments to be generated that maximise the expected accuracy under various different types of score functions.

The DAG structure also facilitates the propagation of alignment uncertainty into downstream inference, allowing for various algorithms to be carried out on the very large space of possible alignments encoded in the graph.

WeaveAlign can be used in conjunction with statistical alignment software such as StatAlign, which generates alignments sampled according to their posterior probability under a probabilistic model of substitution, insertion and deletion.

For more information, please see our papers on the References page.