Evaluating nanopore sequencing data processing pipelines for structural variation identification.
Genome Biol
; 20(1): 237, 2019 11 14.
Article
em En
| MEDLINE
| ID: mdl-31727126
ABSTRACT
BACKGROUND:
Structural variations (SVs) account for about 1% of the differences among human genomes and play a significant role in phenotypic variation and disease susceptibility. The emerging nanopore sequencing technology can generate long sequence reads and can potentially provide accurate SV identification. However, the tools for aligning long-read data and detecting SVs have not been thoroughly evaluated.RESULTS:
Using four nanopore datasets, including both empirical and simulated reads, we evaluate four alignment tools and three SV detection tools. We also evaluate the impact of sequencing depth on SV detection. Finally, we develop a machine learning approach to integrate call sets from multiple pipelines. Overall SV callers' performance varies depending on the SV types. For an initial data assessment, we recommend using aligner minimap2 in combination with SV caller Sniffles because of their speed and relatively balanced performance. For detailed analysis, we recommend incorporating information from multiple call sets to improve the SV call performance.CONCLUSIONS:
We present a workflow for evaluating aligners and SV callers for nanopore sequencing data and approaches for integrating multiple call sets. Our results indicate that additional optimizations are needed to improve SV detection accuracy and sensitivity, and an integrated call set can provide enhanced performance. The nanopore technology is improving, and the sequencing community is likely to grow accordingly. In turn, better benchmark call sets will be available to more accurately assess the performance of available tools and facilitate further tool development.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Alinhamento de Sequência
/
Análise de Sequência de DNA
/
Genômica
/
Variação Estrutural do Genoma
Tipo de estudo:
Diagnostic_studies
/
Evaluation_studies
Limite:
Humans
Idioma:
En
Revista:
Genome Biol
Assunto da revista:
BIOLOGIA MOLECULAR
/
GENETICA
Ano de publicação:
2019
Tipo de documento:
Article
País de afiliação:
Estados Unidos