ArticleCancer informatics2026
MGDB: A Novel Bioinformatics Quality Control Tool for Clinical Next-Generation Sequencing.
Article in Cancer informatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
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
Background and Objectives: Next-generation sequencing (NGS) is transforming clinical diagnostics by enabling the detection of genetic variation with unprecedented precision. However, successful implementation of NGS workflows necessitates stringent quality control. This study introduces Molecular Genetics Dashboard (MGDB), a novel bioinformatics tool designed to enhance quality control in clinical NGS workflows. Methods: Using the Python dash framework for visualizations and MySQL databases, we have developed a novel tool for variant-level monitoring of clinical NGS sequencing runs. MGDB uses a docker-compose containerization for improved portability and can flexibly include or exclude samples from accumulated statistics with notes from interpreters. Results: MGDB facilitates variant-level run-to-run monitoring, ensuring the consistency of variant detection across sequencing cycles. The tool provides an interactive platform for visualizing and assessing variant data, identifying potential inconsistencies or outliers and improving data management and interpretation compared to traditional methods. MGDB was tested using samples sequenced with Oncomine Focus/Comprehensive Plus assays on S5 sequencers and analyzed via IonReporter software. Conclusions: MGDB offers a robust and user-friendly solution for enhancing quality control in clinical NGS workflows, contributing to greater accuracy and reliability in variant detection. The tool is freely available on GitHub: https://github.com/acri-nb/GeneticVariantsDB.
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.