Critical assessment of on-premise approaches to scalable genome analysis.
BMC Bioinformatics
; 24(1): 354, 2023 Sep 21.
Article
de En
| MEDLINE
| ID: mdl-37735350
ABSTRACT
BACKGROUND:
Plummeting DNA sequencing cost in recent years has enabled genome sequencing projects to scale up by several orders of magnitude, which is transforming genomics into a highly data-intensive field of research. This development provides the much needed statistical power required for genotype-phenotype predictions in complex diseases.METHODS:
In order to efficiently leverage the wealth of information, we here assessed several genomic data science tools. The rationale to focus on on-premise installations is to cope with situations where data confidentiality and compliance regulations etc. rule out cloud based solutions. We established a comprehensive qualitative and quantitative comparison between BCFtools, SnpSift, Hail, GEMINI, and OpenCGA. The tools were compared in terms of data storage technology, query speed, scalability, annotation, data manipulation, visualization, data output representation, and availability.RESULTS:
Tools that leverage sophisticated data structures are noted as the most suitable for large-scale projects in varying degrees of scalability in comparison to flat-file manipulation (e.g., BCFtools, and SnpSift). Remarkably, for small to mid-size projects, even lightweight relational database.CONCLUSION:
The assessment criteria provide insights into the typical questions posed in scalable genomics and serve as guidance for the development of scalable computational infrastructure in genomics.Mots clés
Texte intégral:
1
Collection:
01-internacional
Base de données:
MEDLINE
Sujet principal:
Génomique
/
Science des données
Type d'étude:
Prognostic_studies
/
Qualitative_research
Langue:
En
Journal:
BMC Bioinformatics
Sujet du journal:
INFORMATICA MEDICA
Année:
2023
Type de document:
Article
Pays d'affiliation:
Émirats arabes unis