ArticleBMC genomics2025
Sherlock-Genome: an R Shiny application for genomic analysis and visualization.
Article in BMC genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Panorama of Chromosomal Instability in Lung Cancer.medRxiv : the preprint server for health sciences · 2025Article
- A Thiopurine-like Mutagenic Process Defines TGCT Subtypes.bioRxiv : the preprint server for biology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
motivationNext-generation sequencing technologies, such as whole genome sequencing (WGS), have become prominent in cancer genomics. However, managing, visualizing, and integratively analyzing WGS results across various bioinformatic pipelines remains challenging, particularly for non-bioinformaticians, hindering the usability of WGS data for biological discovery.
resultsWe developed Sherlock-Genome, an R Shiny app for data harmonization, visualization, and integrative analysis of WGS-based cancer genomics studies. Following FAIR principles, Sherlock-Genome provides a platform and guidelines for managing and sharing finalized sample-level WGS analysis results, enabling users to upload results, inspect analyses locally, and perform integrative analyses. It includes modules for major cancer genomic analyses, allowing interactive data visualizations and integrative analyses with other data types. Sherlock-Genome supports both local and cloud deployment, facilitating the sharing of results for related publications. This tool has the potential to be widely adopted in cancer genomics, significantly enhancing the accessibility and usability of sample-level WGS analysis results for comprehensive biological discovery and research advancements. AVAILABILITY AND IMPLEMENTATION: The source code and installation instructions for Sherlock-Genome can be accessed via Github https://github.com/xtmgah/Sherlock-Genome . Documentation and data requirements for user project data can also be found on the same GitHub page.
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.