This article is part of a special issue on exome sequencing.

Open Access Method

Effective detection of rare variants in pooled DNA samples using Cross-pool tailcurve analysis

Tejasvi S Niranjan12, Abby Adamczyk1, Héctor Corrada Bravo34, Margaret A Taub5, Sarah J Wheelan56, Rafael Irizarry5 and Tao Wang1*

Author affiliations

1 McKusick-Nathans Institute of Genetic Medicine and Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA

2 Predoctoral Training Program in Human Genetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA

3 Center for Bioinformatics and Computational Biology, Department of Computer Science, University of Maryland, College Park, MD 20742, USA

4 Current address: Center for Bioinformatics and Computational Biology, Department of Computer Science, University of Maryland, College Park, MD 20742, USA

5 Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA

6 Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA

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Citation and License

Genome Biology 2011, 12:R93  doi:10.1186/gb-2011-12-9-r93

Published: 28 September 2011

Abstract

Sequencing targeted DNA regions in large samples is necessary to discover the full spectrum of rare variants. We report an effective Illumina sequencing strategy utilizing pooled samples with novel quality (Srfim) and filtering (SERVIC4E) algorithms. We sequenced 24 exons in two cohorts of 480 samples each, identifying 47 coding variants, including 30 present once per cohort. Validation by Sanger sequencing revealed an excellent combination of sensitivity and specificity for variant detection in pooled samples of both cohorts as compared to publicly available algorithms.