Jupyter notebook-based tools for building structured datasets from the Sequence Read Archive.
F1000Res
; 9: 376, 2020.
Article
em En
| MEDLINE
| ID: mdl-32864105
ABSTRACT
The Sequence Read Archive (SRA) is a large public repository that stores raw next-generation sequencing data from thousands of diverse scientific investigations. Despite its promise, reuse and re-analysis of SRA data has been challenged by the heterogeneity and poor quality of the metadata that describe its biological samples. Recently, the MetaSRA project standardized these metadata by annotating each sample with terms from biomedical ontologies. In this work, we present a pair of Jupyter notebook-based tools that utilize the MetaSRA for building structured datasets from the SRA in order to facilitate secondary analyses of the SRA's human RNA-seq data. The first tool, called the Case-Control Finder, finds suitable case and control samples for a given disease or condition where the cases and controls are matched by tissue or cell type. The second tool, called the Series Finder, finds ordered sets of samples for the purpose of addressing biological questions pertaining to changes over a numerical property such as time. These tools were the result of a three-day-long NCBI Codeathon in March 2019 held at the University of North Carolina at Chapel Hill.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Software
/
Sequenciamento de Nucleotídeos em Larga Escala
/
Ontologias Biológicas
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Conjuntos de Dados como Assunto
/
Metadados
Tipo de estudo:
Observational_studies
Limite:
Humans
Idioma:
En
Revista:
F1000Res
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
Estados Unidos