BING: Biomedical informatics pipeline for Next Generation Sequencing |
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Authors: | Jeffrey Kriseman Christopher Busick Szabolcs Szelinger Valentin Dinu |
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Affiliation: | 1. Department of Biomedical Informatics, Arizona State University, Phoenix, AZ, USA;2. The Translational Genomic Research Institute, Phoenix, AZ, USA;3. Department of Basic Medical Sciences, University of Arizona College of Medicine-Phoenix, AZ, USA;1. Center for Biomedical Informatics; UC Institute for Translational Medicine; Institute for Genomics and Systems Biology; University of Chicago, Chicago, IL 60634, USA;2. Departments of Pediatrics and Medicine, Stanford University, Stanford, CA 94305, USA;3. Center for Computational Pharmacology, Computational Bioscience Program; Departments of Pharmacology, Preventive Medicine & Biometrics, Computer Science, and Biology; University of Colorado Health Sciences Center, Denver, CO 80262, USA |
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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 (<2%). This approach has the potential of increasing the density and throughput of NGS technologies. |
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