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A systematic comparison of two new releases of exome sequencing products: the aim of use determines the choice of product

  • Janine Altmüller EMAIL logo , Susanne Motameny , Christian Becker , Holger Thiele , Sreyoshi Chatterjee , Bernd Wollnik and Peter Nürnberg
Published/Copyright: March 24, 2016

Abstract

We received early access to the newest releases of exome sequencing products, namely Agilent SureSelect v6 (Agilent, Santa Clara, CA, USA) and NimbleGen MedExome (Roche NimbleGen, Basel, Switzerland), and we conducted whole exome sequencing (WES) of several DNA samples with each of these products in order to assess their performance. Here, we provide a detailed evaluation of the original, normalized (with respect to the different target sizes), and trimmed data sets and compare them in terms of the amount of duplicates, the reads on target, and the enrichment evenness. In addition to these general statistics, we performed a detailed analysis of the frequently mutated and newly described genes found in ‘The Deciphering Developmental Disorders Study’ published very recently (Fitzgerald, T.W., Gerety, S.S., Jones, W.D., van Kogelenberg, M., King, D.A., McRae, J., Morley, K.I., Parthiban, V., Al-Turki, S., Ambridge, K., et al. (2015). Large-scale discovery of novel genetic causes of developmental disorders. Nature 519, 223–228.). In our comparison, the Agilent v6 exome performs better than the NimbleGen’s MedExome both in terms of efficiency and evenness of coverage distribution. With its larger target size, it is also more comprehensive, and therefore the better choice in research projects that aim to identify novel disease-associated genes. In contrast, if the exomes are mainly used in a diagnostic setting, we see advantages for the new NimbleGen MedExome. We find a superior coverage here in those genes of high clinical relevance that likely allows for a better detection of relevant, disease-causing mutations.

Acknowledgments

All computations underlying the analyses presented in this review were performed on the CHEOPS high performance compute cluster of the Computing Center of the University of Cologne.

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Received: 2015-12-10
Accepted: 2016-3-16
Published Online: 2016-3-24
Published in Print: 2016-8-1

©2016 Walter de Gruyter GmbH, Berlin/Boston

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