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sRNAnalyzer-a flexible and customizable small RNA sequencing data analysis pipeline.
Wu, Xiaogang; Kim, Taek-Kyun; Baxter, David; Scherler, Kelsey; Gordon, Aaron; Fong, Olivia; Etheridge, Alton; Galas, David J; Wang, Kai.
Afiliación
  • Wu X; Institute for Systems Biology, Seattle, WA 98109, USA.
  • Kim TK; Institute for Systems Biology, Seattle, WA 98109, USA.
  • Baxter D; Institute for Systems Biology, Seattle, WA 98109, USA.
  • Scherler K; Institute for Systems Biology, Seattle, WA 98109, USA.
  • Gordon A; Institute for Systems Biology, Seattle, WA 98109, USA.
  • Fong O; Pacific Northwest Research Institute, Seattle, WA 98122, USA.
  • Etheridge A; Pacific Northwest Research Institute, Seattle, WA 98122, USA.
  • Galas DJ; Pacific Northwest Research Institute, Seattle, WA 98122, USA.
  • Wang K; Institute for Systems Biology, Seattle, WA 98109, USA.
Nucleic Acids Res ; 45(21): 12140-12151, 2017 Dec 01.
Article en En | MEDLINE | ID: mdl-29069500
ABSTRACT
Although many tools have been developed to analyze small RNA sequencing (sRNA-Seq) data, it remains challenging to accurately analyze the small RNA population, mainly due to multiple sequence ID assignment caused by short read length. Additional issues in small RNA analysis include low consistency of microRNA (miRNA) measurement results across different platforms, miRNA mapping associated with miRNA sequence variation (isomiR) and RNA editing, and the origin of those unmapped reads after screening against all endogenous reference sequence databases. To address these issues, we built a comprehensive and customizable sRNA-Seq data analysis pipeline-sRNAnalyzer, which enables (i) comprehensive miRNA profiling strategies to better handle isomiRs and summarization based on each nucleotide position to detect potential SNPs in miRNAs, (ii) different sequence mapping result assignment approaches to simulate results from microarray/qRT-PCR platforms and a local probabilistic model to assign mapping results to the most-likely IDs, (iii) comprehensive ribosomal RNA filtering for accurate mapping of exogenous RNAs and summarization based on taxonomy annotation. We evaluated our pipeline on both artificial samples (including synthetic miRNA and Escherichia coli cultures) and biological samples (human tissue and plasma). sRNAnalyzer is implemented in Perl and available at http//srnanalyzer.systemsbiology.net/.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Análisis de Secuencia de ARN / MicroARNs / Secuenciación de Nucleótidos de Alto Rendimiento Tipo de estudio: Evaluation_studies Límite: Humans Idioma: En Revista: Nucleic Acids Res Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Análisis de Secuencia de ARN / MicroARNs / Secuenciación de Nucleótidos de Alto Rendimiento Tipo de estudio: Evaluation_studies Límite: Humans Idioma: En Revista: Nucleic Acids Res Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos