Coverage bias and sensitivity of variant calling for four whole-genome sequencing technologies

• Verfasst von: Rieber, Nora [VerfasserIn]
• Verfasst von: Zapatka, Marc [VerfasserIn]
• Verfasst von: Lasitschka, Bärbel [VerfasserIn]
• Verfasst von: Jones, David T. W. [VerfasserIn]
• Verfasst von: Northcott, Paul [VerfasserIn]
• Verfasst von: Hutter, Barbara [VerfasserIn]
• Verfasst von: Jäger, Natalie [VerfasserIn]
• Verfasst von: Kool, Marcel [VerfasserIn]
• Verfasst von: Taylor, Michael [VerfasserIn]
• Verfasst von: Lichter, Peter [VerfasserIn]
• Verfasst von: Pfister, Stefan [VerfasserIn]
• Verfasst von: Wolf, Stephan [VerfasserIn]
• Verfasst von: Brors, Benedikt [VerfasserIn]
• Verfasst von: Eils, Roland [VerfasserIn]
• Titel: Coverage bias and sensitivity of variant calling for four whole-genome sequencing technologies
• Verf.angabe: Nora Rieber, Marc Zapatka, Bärbel Lasitschka, David Jones, Paul Northcott, Barbara Hutter, Natalie Jäger, Marcel Kool, Michael Taylor, Peter Lichter, Stefan Pfister, Stephan Wolf, Benedikt Brors, Roland Eils
• E-Jahr: 2013
• Jahr: June 11, 2013
• Umfang: 11 S.
• Fussnoten: Gesehen am 11.01.2022
• Titel Quelle: Enthalten in: PLOS ONE
• Ort Quelle: San Francisco, California, US : PLOS, 2006
• Jahr Quelle: 2013
• Band/Heft Quelle: 8(2013), 6, Artikel-ID e66621, Seite 1-11
• ISSN Quelle: 1932-6203
• DOI: doi:10.1371/journal.pone.0066621
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Cancer genomics
• Sach-SW: DNA methylation
• Sach-SW: Genome analysis
• Sach-SW: Genome sequencing
• Sach-SW: Genomics
• Sach-SW: Next-generation sequencing
• Sach-SW: Nucleotide sequencing
• Sach-SW: Single nucleotide polymorphisms
• K10plus-PPN: 1785422529

Abstract

The emergence of high-throughput, next-generation sequencing technologies has dramatically altered the way we assess genomes in population genetics and in cancer genomics. Currently, there are four commonly used whole-genome sequencing platforms on the market: Illumina’s HiSeq2000, Life Technologies’ SOLiD 4 and its completely redesigned 5500xl SOLiD, and Complete Genomics’ technology. A number of earlier studies have compared a subset of those sequencing platforms or compared those platforms with Sanger sequencing, which is prohibitively expensive for whole genome studies. Here we present a detailed comparison of the performance of all currently available whole genome sequencing platforms, especially regarding their ability to call SNVs and to evenly cover the genome and specific genomic regions. Unlike earlier studies, we base our comparison on four different samples, allowing us to assess the between-sample variation of the platforms. We find a pronounced GC bias in GC-rich regions for Life Technologies’ platforms, with Complete Genomics performing best here, while we see the least bias in GC-poor regions for HiSeq2000 and 5500xl. HiSeq2000 gives the most uniform coverage and displays the least sample-to-sample variation. In contrast, Complete Genomics exhibits by far the smallest fraction of bases not covered, while the SOLiD platforms reveal remarkable shortcomings, especially in covering CpG islands. When comparing the performance of the four platforms for calling SNPs, HiSeq2000 and Complete Genomics achieve the highest sensitivity, while the SOLiD platforms show the lowest false positive rate. Finally, we find that integrating sequencing data from different platforms offers the potential to combine the strengths of different technologies. In summary, our results detail the strengths and weaknesses of all four whole-genome sequencing platforms. It indicates application areas that call for a specific sequencing platform and disallow other platforms. This helps to identify the proper sequencing platform for whole genome studies with different application scopes.