Evidence map›Paper›PMID 37986916›Full record

ArticlemedRxiv : the preprint server for health sciences2023

Crykey: Rapid Identification of SARS-CoV-2 Cryptic Mutations in Wastewater.

Yunxi Liu, Nicolae Sapoval, Pilar Gallego-García, Laura Tomás, David Posada, Todd J Treangen, Lauren B Stadler

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2023. 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, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 2 countries.

Yunxi LiuDepartment of Computer Science, Rice University, Houston, TX, 77005, USA.
Nicolae SapovalDepartment of Computer Science, Rice University, Houston, TX, 77005, USA.ORCID 0000-0002-0736-5075
Pilar Gallego-GarcíaCINBIO, Universidade de Vigo, 36310 Vigo, Spain.ORCID 0000-0001-8531-9851
Laura TomásCINBIO, Universidade de Vigo, 36310 Vigo, Spain.ORCID 0000-0001-9848-002X
David PosadaCINBIO, Universidade de Vigo, 36310 Vigo, Spain.ORCID 0000-0003-1407-3406
Todd J TreangenDepartment of Computer Science, Rice University, Houston, TX, 77005, USA.ORCID 0000-0002-3760-564X
Lauren B StadlerDepartment of Civil and Environmental Engineering, Rice University, Houston, TX, 77005, USA.ORCID 0000-0001-7469-1981
Rice University · USGalicia Sur Biomedical Foundation · ES

Funding

Project 3: Functional Microbiome and Host Signatures in Transition from Commensal to pathogenP01AI152999 · NIAID · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI HAAG, ANTHONY · 2020 to 2025
$12.0M
NIAID NIH HHS P01 AI152999
6 · The paper itself

Abstract

We present Crykey, a computational tool for rapidly identifying cryptic mutations of SARS-CoV-2. Specifically, we identify co-occurring single nucleotide mutations on the same sequencing read, called linked-read mutations, that are rare or entirely missing in existing databases, and have the potential to represent novel cryptic lineages found in wastewater. While previous approaches exist for identifying cryptic linked-read mutations from specific regions of the SARS-CoV-2 genome, there is a need for computational tools capable of efficiently tracking cryptic mutations across the entire genome and for tens of thousands of samples and with increased scrutiny, given their potential to represent either artifacts or hidden SARS-CoV-2 lineages. Crykey fills this gap by identifying rare linked-read mutations that pass stringent computational filters to limit the potential for artifacts. We evaluate the utility of Crykey on >3,000 wastewater and >22,000 clinical samples; our findings are three-fold: i) we identify hundreds of cryptic mutations that cover the entire SARS-CoV-2 genome, ii) we track the presence of these cryptic mutations across multiple wastewater treatment plants and over a three years of sampling in Houston, and iii) we find a handful of cryptic mutations in wastewater mirror cryptic mutations in clinical samples and investigate their potential to represent real cryptic lineages. In summary, Crykey enables large-scale detection of cryptic mutations representing potential cryptic lineages in wastewater.

Identifiers

PMID37986916
PMCPMC10659477
OpenAlexW4381330541

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.