Evidence map›Paper›PMID 39345401›Full record

ArticlebioRxiv : the preprint server for biology2024

Highly accurate assembly polishing with DeepPolisher.

Mira Mastoras, Mobin Asri, Lucas Brambrink, Prajna Hebbar, Alexey Kolesnikov, Daniel E Cook, Maria Nattestad, Julian Lucas, Taylor S Won, Pi-Chuan Chang and 3 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Mira MastorasUC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA.ORCID 0000-0001-6897-0116
Mobin AsriUC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA.ORCID 0000-0002-7194-5138
Lucas BrambrinkGoogle Inc, Mountain View, CA, USA.
Prajna HebbarUC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA.ORCID 0009-0008-9817-5330
Alexey KolesnikovGoogle Inc, Mountain View, CA, USA.
Daniel E CookGoogle Inc, Mountain View, CA, USA.ORCID 0000-0003-3347-562X
Maria NattestadGoogle Inc, Mountain View, CA, USA.ORCID 0000-0002-4796-2894
Julian LucasUC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA.ORCID 0000-0001-9163-2756
Taylor S WonUC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA.ORCID 0000-0002-4821-0854
Pi-Chuan ChangGoogle Inc, Mountain View, CA, USA.ORCID 0000-0003-3021-6446
Andrew CarrollGoogle Inc, Mountain View, CA, USA.ORCID 0000-0002-4824-6689
Benedict PatenUC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA.ORCID 0000-0001-8863-3539
Kishwar ShafinGoogle Inc, Mountain View, CA, USA.ORCID 0000-0001-5252-3434

Funding

The AnVIL Data Ecosystem DACReS SupplementU24HG010262 · NHGRI · BROAD INSTITUTE, INC. · PI Robert J Carroll, Jonathan Lawson · 2018 to 2026
$40.5M
Dockstore: The Community Platform for Reproducible Biomedical Workflows and ApplicationsU24HG011853 · NHGRI · UNIVERSITY OF CALIFORNIA SANTA CRUZ · PI Jonathan Lawson, Benedict Paten · 2021 to 2026
$5.7M
Comprehensive, Flexible and FAIR Tools for the HuBMAP HIVEOT2OD026682 · OD · CARNEGIE-MELLON UNIVERSITY · PI PATEN, BENEDICT, RUFFALO, MATTHEW · 2018 to 2021
$3.4M
The construction and utility of reference pan-genome graphsU01HG010961 · NHGRI · DANA-FARBER CANCER INST · PI LI, HENG, PATEN, BENEDICT · 2020 to 2023
$3.2M
Enabling Comparative PangenomicsR01HG010485 · NHGRI · UNIVERSITY OF CALIFORNIA SANTA CRUZ · PI HAUSSLER, DAVID H, MARTIN, FERGAL JAMES · 2020 to 2023
$2.6M
UCSC Graduate Program in Genome SciencesT32HG012344 · NHGRI · UNIVERSITY OF CALIFORNIA SANTA CRUZ · PI Angela Norie Brooks, Christopher Vollmers · 2022 to 2026
$1.5M
NHGRI NIH HHS T32 HG012344NHGRI NIH HHS U01 HG010961NHGRI NIH HHS U24 HG010262NHGRI NIH HHS U24 HG011853NIH HHS OT2 OD026682
6 · The paper itself

Abstract

Accurate genome assemblies are essential for biological research, but even the highest quality assemblies retain errors caused by the technologies used to construct them. Base-level errors are typically fixed with an additional polishing step that uses reads aligned to the draft assembly to identify necessary edits. However, current methods struggle to find a balance between over-and under-polishing. Here, we present an encoder-only transformer model for assembly polishing called DeepPolisher, which predicts corrections to the underlying sequence using Pacbio HiFi read alignments to a diploid assembly. Our pipeline introduces a method, PHARAOH (Phasing Reads in Areas Of Homozygosity), which uses ultra-long ONT data to ensure alignments are accurately phased and to correctly introduce heterozygous edits in falsely homozygous regions. We demonstrate that the DeepPolisher pipeline can reduce assembly errors by half, with a greater than 70% reduction in indel errors. We have applied our DeepPolisher-based pipeline to 180 assemblies from the next Human Pangenome Reference Consortium (HPRC) data release, producing an average predicted Quality Value (QV) improvement of 3.4 (54% error reduction) for the majority of the genome.

Identifiers

PMID39345401
PMCPMC11429912

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.