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DeepConsensus

By Google Health & PacBio →

Transformer-based neural consensus caller for Pacific Biosciences HiFi sequencing

DeepConsensus applies deep learning to correct errors in Pacific Biosciences (PacBio) circular consensus sequencing (CCS), significantly improving yield of Q30+ and Q40+ high-accuracy reads.

Deep learning consensus calling across subreads to correct systematic sequencing errorsIncreases the yield of Q30 (>99.9% accurate) and Q40 (>99.99% accurate) HiFi reads by up to 40%Integrated into standard PacBio SMRT Link secondary analysis pipelinesOptimized with GPU acceleration for high-throughput sequencing facilities
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Overview

DeepConsensus applies deep learning to correct errors in Pacific Biosciences (PacBio) circular consensus sequencing (CCS), significantly improving yield of Q30+ and Q40+ high-accuracy reads.

Information checked against an official source; not a hands-on test. Source · Last reviewed: 20/09/2026, 11:09:40

Key Features

  • Deep learning consensus calling across subreads to correct systematic sequencing errors
  • Increases the yield of Q30 (>99.9% accurate) and Q40 (>99.99% accurate) HiFi reads by up to 40%
  • Integrated into standard PacBio SMRT Link secondary analysis pipelines
  • Optimized with GPU acceleration for high-throughput sequencing facilities

Academic Context & Research Evidence

Biological & Workflow Fit

Biological Application
De novo genome assembly, structural variant discovery, and pangenomics
Research Workflow
Raw PacBio subreads -> DeepConsensus inference -> high-accuracy HiFi BAM/FASTQ
Compute & Hardware
Multi-core CPU or NVIDIA GPU (CUDA)
Licensing & Academic Use
BSD-3-Clause
Documented Evidence
View validation publication / source ↗

Cite this Tool

Use this citation format when referencing DeepConsensus in scientific publications and benchmark papers.

@software{deepconsensus_2026,
  title = {{DeepConsensus}},
  author = {{Google Health & PacBio}},
  year = {2026},
  url = {https://github.com/google/deepconsensus},
  note = {Indexed on aibioatlas - AI for Biology and Drug Discovery}
}

Peer-Reviewed Literature & Preprints

Live scientific citations streamed from Europe PMC and PubMed for DeepConsensus.

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Technical / Product Information

Missing values mean the catalog has no recorded information. They do not mean a feature is absent.

Entry typeSoftware Tool
Access modeOpen Source
AI roleSignal & Sequence Error Correction
Input dataNot recorded
Output dataNot recorded
Licence conditionsBSD-3-Clause
Commercial eligibilityOpen source release
Compute requirementsMulti-core CPU or NVIDIA GPU (CUDA)
ValidationNot recorded
TypeNeural sequencing consensus caller
Intended useNot recorded
CompatibilityNot recorded
ManufacturerGoogle LLC & PacBio
Biological applicationDe novo genome assembly, structural variant discovery, and pangenomics
Research workflowRaw PacBio subreads -> DeepConsensus inference -> high-accuracy HiFi BAM/FASTQ
Evidence levelPeer-reviewed publication (Nature Biotechnology 2022)
Integration evidencehttps://github.com/google/deepconsensus
Laboratory handoffGenerates ready-to-assemble reads for clinical and population genomics
AvailabilityAvailable on GitHub and Bioconda
Price / accessFree Open Source

Research fit & compatibility

No software–hardware integration has been verified for this entry yet. Explore documented research workflows.

Gallery & resources

No licensed product photograph recorded for DeepConsensus yet. Visit the official resource below for manufacturer imagery.

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FAQ

Where is this product available?

Available on GitHub and Bioconda

How is pricing handled?

Prices reflect the source at its last check. Confirm current pricing and regional availability on the official site.

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Peer Reviews & Community Ratings

Feedback from researchers and computational biologists evaluating DeepConsensus.

5.0
★★★★★Based on 0 researcher evaluations
Biological Accuracy
4.8/5
Ease of Installation
4.3/5
Documentation & Code
4.6/5