Evidence map›Paper›PMID 39127634›Full record

ArticleBMC genomics2024

Utility analyses of AVITI sequencing chemistry.

Silvia Liu, Caroline Obert, Yan-Ping Yu, Junhua Zhao, Bao-Guo Ren, Jia-Jun Liu, Kelly Wiseman, Benjamin J Krajacich, Wenjia Wang, Kyle Metcalfe and 3 more

Abstract read
In one paragraph

Article in BMC genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. BCAR: a fast and indel-tolerant barcode-sequence mapper.Bioinformatics (Oxford, England) · 2026
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Silvia LiuDepartment of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15261, USA. shl96@pitt.edu.
Caroline ObertElement Biosciences Inc, 10055 Barnes Canyon Road, Suite 100, San Diego, CA, 92121, USA.
Yan-Ping YuDepartment of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15261, USA.
Junhua ZhaoElement Biosciences Inc, 10055 Barnes Canyon Road, Suite 100, San Diego, CA, 92121, USA.
Bao-Guo RenDepartment of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15261, USA.
Jia-Jun LiuDepartment of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15261, USA.
Kelly WisemanElement Biosciences Inc, 10055 Barnes Canyon Road, Suite 100, San Diego, CA, 92121, USA.
Benjamin J KrajacichElement Biosciences Inc, 10055 Barnes Canyon Road, Suite 100, San Diego, CA, 92121, USA.
Wenjia WangDepartment of Biostatistics, University of Pittsburgh School of Public Health, Pittsburgh, USA.
Kyle MetcalfeElement Biosciences Inc, 10055 Barnes Canyon Road, Suite 100, San Diego, CA, 92121, USA.
Mat SmithElement Biosciences Inc, 10055 Barnes Canyon Road, Suite 100, San Diego, CA, 92121, USA.
Tuval Ben-YehezkelElement Biosciences Inc, 10055 Barnes Canyon Road, Suite 100, San Diego, CA, 92121, USA.
Jian-Hua LuoDepartment of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15261, USA. luoj@upmc.edu.

Funding

University of Pittsburgh Clinical and Translational Science InstituteUL1TR001857 · NCATS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI REIS, STEVEN E · 2016 to 2025
$129.3M
Pittsburgh Liver Research CenterP30DK120531 · NIDDK · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Shuchang Silvia Liu · 2019 to 2026
$10.9M
Genome targeting of liver cancerR56CA229262 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI LUO, JIANHUA · 2018 to 2019
$705k
High-Throughput Computing for Genomics and Bioinformatics ResearchS10OD028483 · OD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI LEE, ADRIAN V · 2021 to 2021
$574k
Innovation in Cancer Informatics N/ANational Cancer Institute, United States 1R56CA229262-01NCATS NIH HHS UL1 TR001857NCI NIH HHS 1R56CA229262-01NCI NIH HHS R56 CA229262NIDDK NIH HHS P30 DK120531NIDDK NIH HHS P30- DK120531-01NIH HHS S10 OD028483NIH HHS UL1TR001857 and S10OD028483University of Pittsburgh Clinical and Translational Science Institute N/A
6 · The paper itself

Abstract

backgroundDNA sequencing is a critical tool in modern biology. Over the last two decades, it has been revolutionized by the advent of massively parallel sequencing, leading to significant advances in the genome and transcriptome sequencing of various organisms. Nevertheless, challenges with accuracy, lack of competitive options and prohibitive costs associated with high throughput parallel short-read sequencing persist.

resultsHere, we conduct a comparative analysis using matched DNA and RNA short-reads assays between Element Biosciences' AVITI and Illumina's NextSeq 550 chemistries. Similar comparisons were evaluated for synthetic long-read sequencing for RNA and targeted single-cell transcripts between the AVITI and Illumina's NovaSeq 6000. For both DNA and RNA short-read applications, the study found that the AVITI produced significantly higher per sequence quality scores. For PCR-free DNA libraries, we observed an average 89.7% lower experimentally determined error rate when using the AVITI chemistry, compared to the NextSeq 550. For short-read RNA quantification, AVITI platform had an average of 32.5% lower error rate than that for NextSeq 550. With regards to synthetic long-read mRNA and targeted synthetic long read single cell mRNA sequencing, both platforms' respective chemistries performed comparably in quantification of genes and isoforms. The AVITI displayed a marginally lower error rate for long reads, with fewer chemistry-specific errors and a higher mutation detection rate.

conclusionThese results point to the potential of the AVITI platform as a competitive candidate in high-throughput short read sequencing analyses when juxtaposed with the Illumina NextSeq 550.

Indexed as

High-Throughput Nucleotide SequencingGene LibraryHumansSequence Analysis, DNASequence Analysis, RNASingle-Cell AnalysisAVITINextSeqNucleic acid sequencing

Identifiers

PMID39127634
PMCPMC11316309

What OpenQuestion holds

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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.