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This article is part of the supplement: Selected articles from The Second Workshop on Data Mining of Next-Generation Sequencing in conjunction with the 2012 IEEE International Conference on Bioinformatics and Biomedicine

Open Access Research

Efficient digest of high-throughput sequencing data in a reproducible report

Zhe Zhang1*, Jeremy Leipzig1, Ariella Sasson1, Angela M Yu1, Juan C Perin1, Hongbo M Xie1, Mahdi Sarmady1, Patrick V Warren1 and Peter S White123

Author Affiliations

1 Center for Biomedical Informatics, The Children's Hospital of Philadelphia, PA, USA

2 Division of Oncology, The Children's Hospital of Philadelphia, PA, USA

3 Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, PA, USA

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BMC Bioinformatics 2013, 14(Suppl 11):S3  doi:10.1186/1471-2105-14-S11-S3

Published: 13 September 2013

Abstract

Background

High-throughput sequencing (HTS) technologies are spearheading the accelerated development of biomedical research. Processing and summarizing the large amount of data generated by HTS presents a non-trivial challenge to bioinformatics. A commonly adopted standard is to store sequencing reads aligned to a reference genome in SAM (Sequence Alignment/Map) or BAM (Binary Alignment/Map) files. Quality control of SAM/BAM files is a critical checkpoint before downstream analysis. The goal of the current project is to facilitate and standardize this process.

Results

We developed bamchop, a robust program to efficiently summarize key statistical metrics of HTS data stored in BAM files, and to visually present the results in a formatted report. The report documents information about various aspects of HTS data, such as sequencing quality, mapping to a reference genome, sequencing coverage, and base frequency. Bamchop uses the R language and Bioconductor packages to calculate statistical matrices and the Sweave utility and associated LaTeX markup for documentation. Bamchop's efficiency and robustness were tested on BAM files generated by local sequencing facilities and the 1000 Genomes Project. Source code, instruction and example reports of bamchop are freely available from https://github.com/CBMi-BiG/bamchop webcite.

Conclusions

Bamchop enables biomedical researchers to quickly and rigorously evaluate HTS data by providing a convenient synopsis and user-friendly reports.