ArticleScientific reports2019
DAMIAN: an open source bioinformatics tool for fast, systematic and cohort based analysis of microorganisms in diagnostic samples.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed, 31 citations in OpenAlex.
- Masking recurrent contaminants in reference sequences improves specificity of clinical metagenomic sequencing.Journal of clinical microbiology · 2026Article
- The Potential of Bioinformatics in Revolutionizing Disease Diagnosis in Sub-Saharan Africa: A Narrative Review.Health science reports · 2026Article
- Clinical metagenomics for diagnosis and surveillance of viral pathogens.Nature reviews. Microbiology · 2026Review
- Precursor of H-type II histo-blood group antigen and subterminal sialic acids on gangliosides are significantly implicated in cell entry and infection by a porcine P[11] rotavirus.Emerging microbes & infections · 2025Article
- MetaAll: integrative bioinformatics workflow for analysing clinical metagenomic data.Briefings in bioinformatics · 2024Article
- The effects of sequencing strategies on Metagenomic pathogen detection using bronchoalveolar lavage fluid samples.Heliyon · 2024Article
- Pathogen detection in RNA-seq data with Pathonoia.BMC bioinformatics · 2023Article
- Article
- In the Search of Marine Pestiviruses: First Case of Phocoena Pestivirus in a Belt Sea Harbour Porpoise.Viruses · 2022Article
- Databases, Knowledgebases, and Software Tools for Virus Informatics.Advances in experimental medicine and biology · 2022Article
- Article
- Benchmark of thirteen bioinformatic pipelines for metagenomic virus diagnostics using datasets from clinical samples.Journal of clinical virology : the official publication of the Pan American Society for Clinical Virology · 2021Article
- Biases in Viral Metagenomics-Based Detection, Cataloguing and Quantification of Bacteriophage Genomes in Human Faeces, a Review.Microorganisms · 2021Review
- Genomic and phylogenetic analysis of two guinea pig adenovirus strains recovered from archival lung tissue.Virus research · 2020Article
- From COVID-19 Crisis to Digital Health Care Innovation.Nursing education perspectivesArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We describe DAMIAN, an open source bioinformatics tool designed for the identification of pathogenic microorganisms in diagnostic samples. By using authentic clinical samples and comparing our results to those from established analysis pipelines as well as conventional diagnostics, we demonstrate that DAMIAN rapidly identifies pathogens in different diagnostic entities, and accurately classifies viral agents down to the strain level. We furthermore show that DAMIAN is able to assemble full-length viral genomes even in samples co-infected with multiple virus strains, an ability which is of considerable advantage for the investigation of outbreak scenarios. While DAMIAN, similar to other pipelines, analyzes single samples to perform classification of sequences according to their likely taxonomic origin, it also includes a tool for cohort-based analysis. This tool uses cross-sample comparisons to identify sequence signatures that are frequently present in a sample group of interest (e.g., a disease-associated cohort), but occur less frequently in control cohorts. As this approach does not require homology searches in databases, it principally allows the identification of not only known, but also completely novel pathogens. Using samples from a meningitis outbreak, we demonstrate the feasibility of this approach in identifying enterovirus as the causative agent.
Indexed as
Identifiers
What 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.