Andrew Carroll

Andrew Carroll

@acarroll.bsky.social

Product lead Genomics Google Research

2.7K followers222 following27 posts

Andrew Carroll reposted

How good is MiniBWA, the successor to BWA? To test it, I ran MiniBWA on sequencing from 76 different species, comparing mapping speed, rate and accuracy with BWA MEM. In short, it's really good. If you map short reads, it's well worth your time. andrewcarroll.github.io/2026/06/30/t...

andrewcarroll.github.ioThe Best of Both Worlds - Assessing MiniBWARecently, Heng Li released MiniBWA (GitHub) alongside a paper by Heng Li and Nils Homer describing the method (paper). MiniBWA builds on the approaches in Minimap2 (also by Heng Li), but falls back on...

Release of DeepVariant v1.10 Phased VCF output for long-reads Accuracy improvements for multi-allelic variants Pangenome accuracy improvements (18% fewer errors) Most technologies ~10% faster RNA-seq is a full supported mode DeepSomatic is 12-40% faster github.com/google/deepv...

github.comRelease DeepVariant 1.10.0 · google/deepvariantDeepVariant: Continuous phasing: Long-read variant calls (PacBio and ONT) are now natively phased and phased output is generated for both vcf and gvcf formats. Fuzzy channels: Added “fuzzy channel...

Release led by Kishwar Shafin. Special thanks to Ehud Amitai and Ultima Genomics for a contribution that improves accuracy (~4% error reduction) for all technologies. Core team: Alexey Kolesnikov, Daniel Cook, Lucas Brambrink & manager Pi-Chuan Chang. 20%er work in release notes

Andrew Carroll reposted

What if you could improve small variant accuracy, CNV inference, and interpretability of your HiFi WGS data by taking a different approach to read mapping? Our new preprint describes portello, a method which demonstrates the potential for such improvements. (1/5)

Andrew Carroll reposted

The killing of Alex Pretti is a heartbreaking tragedy. It should also be a wake-up call to every American, regardless of party, that many of our core values as a nation are increasingly under assault.

Andrew Carroll reposted

Release of DeepVariant and DeepSomatic v1.9 DV: Now train on HG002 T2T-Q100. Error reduction of 12% for Illumina and 30% for PacBio on this truth set. 25% faster. DeepTrio is 5x faster (20h -> 4h). DS: New models FFPE_TUMOR_ONLY for {WGS, WES}. Much improved WGS models. github.com/google/deepv...

github.comRelease DeepVariant 1.9.0 · google/deepvariantDeepVariant: In this version we have updated our training scheme for the HG002 sample with the newly released HG002-T2T truth set which improves accuracy against that truth set. Our labeling metho...

Release led by Kishwar Shafin, contributions by Daniel Cook, Alexey Kolesnikov, Lucas Brambrink, and Pi-Chuan Chang as engineering manager. Thanks to student researcher contributions from Farica Zhuang and Mobin Asri. DeepSomatic release page: github.com/google/deeps...

github.comRelease DeepSomatic 1.9.0 · google/deepsomaticDeepSomatic: In this release, we are introducing FFPE_WGS_TUMOR_ONLY and FFPE_WES_TUMOR_ONLY models. The WGS and WGS_TUMOR_ONLY models have been retrained with all datasets described in the manusc...

Also thanks to 20% contributors: Ben Soudry, Mike Kruskal, Sowmiya Nagarajan, Suchismita Tripathy, Francisco Unda, Vasiliy Strelnikov And community contributions from Sam Yadav and Seraj Ahmad at Roche improving the code for custom model training

Andrew Carroll reposted

Incredibly moving Justin Trudeau remarks: "We have fought and died alongside you....During your darkest hours...we were always there. Standing with you, grieving with you, the American people....Canadians are a little perplexed as to why our closest friends and neighbors are choosing to target us."

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

Release led by DeepVariant tech lead Kishwar Shafin. Team Engineering manager Pi-Chuan Chang. Small model work led by Lucas Brambrink. Pangenome-aware led by Mobin Asri and Juan Carlos Mier. Fast pipeline by Alexey Kolesnikov. Kinnex/MAS-Seq model by Daniel Cook and Shiyi Yin from Verily. 3/3

Release of DeepVariant v1.6. Support for haploid regions, chrX/Y. Workflow for Pangenome FASTQ-to-VCF. Major DeepTrio improvements for de novo variants. Models for CompleteGenomics T7, G400 Add NovaSeqX to training data Release by Kishwar Shafin github.com/google/deepv...

github.comRelease DeepVariant 1.6.0 · google/deepvariantImproved support for haploid regions, chrX and chY. Users can specify haploid regions with a flag. Updated case studies show usage and metrics. Added pangenome workflow (FASTQ-to-VCF mapping with V...
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Release of DeepVariant v1.6. Support for haploid regions, chrX/Y. Workflow for Pangenome FASTQ-to-VCF. Major DeepTrio improvements for de novo variants. Models for CompleteGenomics T7, G400 Add NovaSeqX to training data Release by Kishwar Shafin github.com/google/deepv...

github.comRelease DeepVariant 1.6.0 · google/deepvariantImproved support for haploid regions, chrX and chY. Users can specify haploid regions with a flag. Updated case studies show usage and metrics. Added pangenome workflow (FASTQ-to-VCF mapping with V...

TThanks to Jimin Park and Benedict Paten from UCSC, Mikhail Kolmogorov from NCI for analysis and testing. This group has also developed Severus for somatic SV calling, and we've worked closely with them (github.com/KolmogorovLa...) Thanks to Khi Pin Chua and Billy Rowell from PacBio

github.comGitHub - KolmogorovLab/Severus: A tool for somatic structural variant calling using long readsA tool for somatic structural variant calling using long reads - GitHub - KolmogorovLab/Severus: A tool for somatic structural variant calling using long reads

Andrew Carroll reposted

Best resource for getting extracellular domain localization from Ensembl gene/protein IDs? I tried the subcellular locations in HPA but the membrane annotation is mostly fully intracellular proteins. 🧪🧬🖥️🔬

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