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Andrew Carroll

@acarroll.bsky.social

2.8K followers 221 following 27 posts

Product lead Genomics Google Research

Andrew Carroll @acarroll.bsky.social · 02/07/2026

OK, that was indeed interesting. BWA MEM3 is also very fast. MiniBWA is a median of 40% faster than BWA MEM3 and faster in 85% of genomes, with the smallest of genomes favoring BWA MEM3. Thanks for the suggestion. BWA MEM3 is great work as well.

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Andrew Carroll @acarroll.bsky.social · 28/05/2026

This blog shares some thoughts on protein and genome foundation models. The first part explains some of the concepts by training models for example tasks. The second part is opinion on the state of the field. andrewcarroll.github.io/2026/05/26/g...

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Andrew Carroll @acarroll.bsky.social · 05/12/2024

Added SPRQ to PacBio training, reducing Indel error on SPRQ by 26%. Added Platinum Pedigree training data for PacBio model, reducing errors by 34% on more extensive Platinum truth. New model and case study for Kinnex/Mas-Seq/Iso-Seq. Additional speed options for GPU pipelines 2/3

Plots of SNP and Indel error numbers for DeepVariant models. Shows a Indel error reduction of 26% for PacBio and a ~50% SNP error reduction for ONT.

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Andrew Carroll @acarroll.bsky.social · 05/12/2024

Release of DeepVariant 1.8. Large speed improvement (~67% faster) via small model for easy sites. New Pangenome-aware option. Reduces error by ~30% for vg-mapped WGS, ~10% for BWA WGS, ~5% BWA exome. New config for custom model users, see release notes. (github.com/google/deepv...)

Runtime figure for new version of DeepVariant with and without small model. Showing reduction in runtime of 155 minutes to 101 minutes with Illumina, 174 minutes to 71 minutes with PacBio, and 295 minutes to 114 minutes with Oxford Nanopore.

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