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TRAPR: R Package for Statistical Analysis and Visualization of RNA-Seq Data

High-throughput transcriptome sequencing, also known as RNA sequencing (RNA-Seq), is a standard technology for measuring gene expression with unprecedented accuracy. Numerous bioconductor packages have been developed for the statistical analysis of RNA-Seq data. However, these tools focus on specifi...

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Detalles Bibliográficos
Autores principales: Lim, Jae Hyun, Lee, Soo Youn, Kim, Ju Han
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korea Genome Organization 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5389949/
https://www.ncbi.nlm.nih.gov/pubmed/28416950
http://dx.doi.org/10.5808/GI.2017.15.1.51
Descripción
Sumario:High-throughput transcriptome sequencing, also known as RNA sequencing (RNA-Seq), is a standard technology for measuring gene expression with unprecedented accuracy. Numerous bioconductor packages have been developed for the statistical analysis of RNA-Seq data. However, these tools focus on specific aspects of the data analysis pipeline, and are difficult to appropriately integrate with one another due to their disparate data structures and processing methods. They also lack visualization methods to confirm the integrity of the data and the process. In this paper, we propose an R-based RNA-Seq analysis pipeline called TRAPR, an integrated tool that facilitates the statistical analysis and visualization of RNA-Seq expression data. TRAPR provides various functions for data management, the filtering of low-quality data, normalization, transformation, statistical analysis, data visualization, and result visualization that allow researchers to build customized analysis pipelines.