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bioRxiv · 10.64898/2026.08.06.743046

Flex-sweep 2.0: more flexible and faster selective sweeps detection

Murga-Moreno, J.·Enard, D.
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Abstract

Flex-sweep is a convolutional neural network-based method able to detect a wide range of selective sweeps, including those thousands of generations old, from single population genomic data, while robust to background selection. Here we present a substantial update that streamlines the entire workflow. The new version vastly reduces memory needs and vastly speeds up summary-statistic computation over fully customizable statistics combinations and genomic regions, relaxes CNN constraints by supporting custom architectures and haplotype matrix sorting methods. Domain-Adaptive Neural Network (DANN) training is now supported, as well as ancestral-state polarization and a robust, clustering and confounder-aware gene set sweep enrichment pipeline robust for downstream analysis. Flex-sweep 2.0 scales to hundreds of thousands of training simulations, and enables genome-wide inference on a standard workstation.

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Murga-Moreno, J., Enard, D.. 2026-08-07. Flex-sweep 2.0: more flexible and faster selective sweeps detection. https://doi.org/10.64898/2026.08.06.743046

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