ArticleNature biotechnology2026
Detection of viral sequences at single-cell resolution identifies novel viruses associated with host gene expression changes.
Article in Nature biotechnology, 2026. 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
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.
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.
Who cites it
6 citing papers in PubMed.
- Article
- Metatranscriptomic discovery of a novel viral class from the Yangshan deep-water port virosphere.Archives of virology · 2026Article
- A protocol for high-quality single-cell RNA sequencing with cell surface protein quantification.Blood science (Baltimore, Md.) · 2026Article
- Uniform pre-processing of bacterial single-cell RNA-seq.bioRxiv : the preprint server for biology · 2026Article
- Description of bacterial RNA transcripts detected inVirulence · 2025Article
- The respiratory tract virome: unravelling the role of viral dark matter in respiratory health and disease.European respiratory review : an official journal of the European Respiratory Society · 2025Review
Corrections and comments
- Update of
Authors and funding
7 authors.
Funding
Abstract
The increasing use of high-throughput sequencing methods in research, agriculture and healthcare provides an opportunity for the cost-effective surveillance of viral diversity and investigation of virus-disease correlation. However, existing methods for identifying viruses in sequencing data rely on and are limited to reference genomes or cannot retain single-cell resolution through cell barcode tracking. We introduce a method that accurately and rapidly detects viral sequences in bulk and single-cell transcriptomics data based on the highly conserved RdRP protein, enabling the detection of over 100,000 RNA virus species. The analysis of viral presence and host gene expression in parallel at single-cell resolution allows for the characterization of host viromes and the identification of viral tropism and host responses. We apply our method to peripheral blood mononuclear cell data from rhesus macaques with Ebola virus disease and describe previously unknown putative viruses. Moreover, we are able to accurately predict viral presence in individual cells based on macaque gene expression.
Indexed as
Identifiers
40263451What OpenQuestion holds
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.