Email updates

Keep up to date with the latest news and content from BMC Research Notes and BioMed Central.

Open Access Technical Note

ASAP: an environment for automated preprocessing of sequencing data

Eric S Torstenson1, Bingshan Li12 and Chun Li134*

Author Affiliations

1 Center for Human Genetics Research, Vanderbilt University, Nashville, USA

2 Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, USA

3 Department of Biostatistics, Vanderbilt University, Nashville, USA

4 Center for Human Genetics Research, Vanderbilt University Medical Center, 519 Light Hall, Nashville, TN, 37212-0700, USA

For all author emails, please log on.

BMC Research Notes 2013, 6:5  doi:10.1186/1756-0500-6-5

Published: 4 January 2013

Abstract

Background

Next-generation sequencing (NGS) has yielded an unprecedented amount of data for genetics research. It is a daunting task to process the data from raw sequence reads to variant calls and manually processing this data can significantly delay downstream analysis and increase the possibility for human error. The research community has produced tools to properly prepare sequence data for analysis and established guidelines on how to apply those tools to achieve the best results, however, existing pipeline programs to automate the process through its entirety are either inaccessible to investigators, or web-based and require a certain amount of administrative expertise to set up.

Findings

Advanced Sequence Automated Pipeline (ASAP) was developed to provide a framework for automating the translation of sequencing data into annotated variant calls with the goal of minimizing user involvement without the need for dedicated hardware or administrative rights. ASAP works both on computer clusters and on standalone machines with minimal human involvement and maintains high data integrity, while allowing complete control over the configuration of its component programs. It offers an easy-to-use interface for submitting and tracking jobs as well as resuming failed jobs. It also provides tools for quality checking and for dividing jobs into pieces for maximum throughput.

Conclusions

ASAP provides an environment for building an automated pipeline for NGS data preprocessing. This environment is flexible for use and future development. It is freely available at http://biostat.mc.vanderbilt.edu/ASAP webcite.

Keywords:
Next-generation sequencing; Data processing; Automation; Computer cluster