BING: Biomedical informatics pipeline for Next Generation Sequencing

  • Authors:

  • Jeffrey Kriseman;Christopher Busick;Szabolcs Szelinger;Valentin Dinu

  • Affiliations:

  • Department of Biomedical Informatics, Arizona State University, Phoenix, AZ, USA and The Translational Genomic Research Institute, Phoenix, AZ, USA;Department of Biomedical Informatics, Arizona State University, Phoenix, AZ, USA;The Translational Genomic Research Institute, Phoenix, AZ, USA;Department of Biomedical Informatics, Arizona State University, Phoenix, AZ, USA and The Translational Genomic Research Institute, Phoenix, AZ, USA and Department of Basic Medical Sciences, Univer ...

  • Venue:
  • Journal of Biomedical Informatics
  • Year:
  • 2010

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Abstract

High throughput parallel genomic sequencing (Next Generation Sequencing, NGS) shifts the bottleneck in sequencing processes from experimental data production to computationally intensive informatics-based data analysis. This manuscript introduces a biomedical informatics pipeline (BING) for the analysis of NGS data that offers several novel computational approaches to 1. image alignment, 2. signal correlation, compensation, separation, and pixel-based cluster registration, 3. signal measurement and base calling, 4. quality control and accuracy measurement. These approaches address many of the informatics challenges, including image processing, computational performance, and accuracy. These new algorithms are benchmarked against the Illumina Genome Analysis Pipeline. BING is the one of the first software tools to perform pixel-based analysis of NGS data. When compared to the Illumina informatics tool, BING's pixel-based approach produces a significant increase in the number of sequence reads, while reducing the computational time per experiment and error rate (