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eRNA: a graphic user interface-based tool optimized for large data analysis from high-throughput RNA sequencing

Tiezheng Yuan1, Xiaoyi Huang1, Rachel L Dittmar1, Meijun Du1, Manish Kohli2, Lisa Boardman2, Stephen N Thibodeau3 and Liang Wang1*

Author Affiliations

1 Department of Pathology and MCW Cancer Center, Medical College of Wisconsin, Milwaukee WI 53226, USA

2 Department of Oncology, Mayo Clinic, Rochester MN 55905, USA

3 Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester MN 55905, USA

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BMC Genomics 2014, 15:176  doi:10.1186/1471-2164-15-176

Published: 5 March 2014

Abstract

Background

RNA sequencing (RNA-seq) is emerging as a critical approach in biological research. However, its high-throughput advantage is significantly limited by the capacity of bioinformatics tools. The research community urgently needs user-friendly tools to efficiently analyze the complicated data generated by high throughput sequencers.

Results

We developed a standalone tool with graphic user interface (GUI)-based analytic modules, known as eRNA. The capacity of performing parallel processing and sample management facilitates large data analyses by maximizing hardware usage and freeing users from tediously handling sequencing data. The module miRNA identification” includes GUIs for raw data reading, adapter removal, sequence alignment, and read counting. The module “mRNA identification” includes GUIs for reference sequences, genome mapping, transcript assembling, and differential expression. The module “Target screening” provides expression profiling analyses and graphic visualization. The module “Self-testing” offers the directory setups, sample management, and a check for third-party package dependency. Integration of other GUIs including Bowtie, miRDeep2, and miRspring extend the program’s functionality.

Conclusions

eRNA focuses on the common tools required for the mapping and quantification analysis of miRNA-seq and mRNA-seq data. The software package provides an additional choice for scientists who require a user-friendly computing environment and high-throughput capacity for large data analysis. eRNA is available for free download at https://sourceforge.net/projects/erna/?source=directory webcite.

Keywords:
RNA sequencing; Bioinformatics tool; Graphic user interface; Parallel processing