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GTX.Digest.VCF: an online NGS data interpretation system based on intelligent gene ranking and large-scale text mining
- Source :
- BMC Medical Genomics, BMC Medical Genomics, Vol 12, Iss S8, Pp 1-10 (2019)
- Publication Year :
- 2019
- Publisher :
- Springer Science and Business Media LLC, 2019.
-
Abstract
- Background An important task in the interpretation of sequencing data is to highlight pathogenic genes (or detrimental variants) in the field of Mendelian diseases. It is still challenging despite the recent rapid development of genomics and bioinformatics. A typical interpretation workflow includes annotation, filtration, manual inspection and literature review. Those steps are time-consuming and error-prone in the absence of systematic support. Therefore, we developed GTX.Digest.VCF, an online DNA sequencing interpretation system, which prioritizes genes and variants for novel disease-gene relation discovery and integrates text mining results to provide literature evidence for the discovery. Its phenotype-driven ranking and biological data mining approach significantly speed up the whole interpretation process. Results The GTX.Digest.VCF system is freely available as a web portal at http://vcf.gtxlab.com for academic research. Evaluation on the DDD project dataset demonstrates an accuracy of 77% (235 out of 305 cases) for top-50 genes and an accuracy of 41.6% (127 out of 305 cases) for top-5 genes. Conclusions GTX.Digest.VCF provides an intelligent web portal for genomics data interpretation via the integration of bioinformatics tools, distributed parallel computing, biomedical text mining. It can facilitate the application of genomic analytics in clinical research and practices.
- Subjects :
- 0301 basic medicine
lcsh:Internal medicine
lcsh:QH426-470
Text mining
Computer science
NGS data interpretation
Genomics
Field (computer science)
Ranking (information retrieval)
03 medical and health sciences
Annotation
0302 clinical medicine
Genetics
Data Mining
lcsh:RC31-1245
Distributed parallel computing
Genetics (clinical)
Information retrieval
business.industry
High-Throughput Nucleotide Sequencing
Biomedical text mining
Neural network
lcsh:Genetics
030104 developmental biology
Workflow
Analytics
Data Interpretation, Statistical
Gene prioritization
Neural Networks, Computer
business
Software
030217 neurology & neurosurgery
Subjects
Details
- ISSN :
- 17558794
- Volume :
- 12
- Database :
- OpenAIRE
- Journal :
- BMC Medical Genomics
- Accession number :
- edsair.doi.dedup.....0a2214c0bd0670e68bf971cb959c1760