ArticleBMC research notes2024
Sequence-matching adapter trimmers generate consistent quality and assembly metrics for Illumina sequencing of RNA viruses.
Article in BMC research notes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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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.
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Who cites it
6 citing papers in PubMed.
- Preterm birth disrupts nephron progenitor cell dynamics predisposing to renal disease.iScience · 2026Article
- A total infectome framework for resolving complex disease etiology in aquaculture.Advanced biotechnology · 2026Article
- Article
- Integrated Single-Nucleus Multi-Omics Atlases Reveal Lineage Plasticity and Regulatory Networks of Luminal Epithelial Cells During Mammary Gland Lactation and Involution.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Coordinated RNA- and protein-templated synthesis of double-stranded DNA by a dual reverse transcriptase immune system.bioRxiv : the preprint server for biology · 2026Article
- Using pangenome variation graphs to improve mutation detection in a large DNA virus.Microbial genomics · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Trimming adapters and low-quality bases from next-generation sequencing (NGS) data is crucial for optimal analysis. We evaluated six trimming programs, implementing five different algorithms, for their effectiveness in trimming adapters and improving quality, contig assembly, and single-nucleotide polymorphism (SNP) quality and concordance for poliovirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and norovirus paired data sequenced on Illumina iSeq and MiSeq platforms. Trimmomatic and BBDuk effectively removed adapters from all datasets, unlike FastP, AdapterRemoval, SeqPurge, and Skewer. All trimmers improved read quality (Q ≥ 30, 87.8 - 96.1%) compared to raw reads (83.6 - 93.2%). Trimmers implementing traditional sequence-matching (Trimmomatic and AdapterRemoval) and overlapping algorithm (FastP) retained the highest-quality reads. While all trimmers improved the maximum contig length and genome coverage for iSeq and MiSeq viral assemblies, BBDuk-trimmed reads assembled the shortest contigs. SNP concordance was consistently high (> 97.7 - 100%) across trimmers. However, BBDuk-trimmed reads had the lowest quality SNPs. Overall, the two adapter trimmers that utilized the traditional sequence-matching algorithm performed consistently across the viral datasets analyzed. Our findings guide software selection and inform future versatile trimmer development for viral genome analysis.
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Registered trials
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.