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Comprehensive Outline of Whole Exome Sequencing Data Analysis Tools Available in Clinical Oncology

Authors :
Áron Bartha
Balázs Győrffy
Source :
Cancers, Vol 11, Iss 11, p 1725 (2019), Cancers
Publication Year :
2019
Publisher :
MDPI AG, 2019.

Abstract

Whole exome sequencing (WES) enables the analysis of all protein coding sequences in the human genome. This technology enables the investigation of cancer-related genetic aberrations that are predominantly located in the exonic regions. WES delivers high-throughput results at a reasonable price. Here, we review analysis tools enabling utilization of WES data in clinical and research settings. Technically, WES initially allows the detection of single nucleotide variants (SNVs) and copy number variations (CNVs), and data obtained through these methods can be combined and further utilized. Variant calling algorithms for SNVs range from standalone tools to machine learning-based combined pipelines. Tools for CNV detection compare the number of reads aligned to a dedicated segment. Both SNVs and CNVs help to identify mutations resulting in pharmacologically druggable alterations. The identification of homologous recombination deficiency enables the use of PARP inhibitors. Determining microsatellite instability and tumor mutation burden helps to select patients eligible for immunotherapy. To pave the way for clinical applications, we have to recognize some limitations of WES, including its restricted ability to detect CNVs, low coverage compared to targeted sequencing, and the missing consensus regarding references and minimal application requirements. Recently, Galaxy became the leading platform in non-command line-based WES data processing. The maturation of next-generation sequencing is reinforced by Food and Drug Administration (FDA)-approved methods for cancer screening, detection, and follow-up. WES is on the verge of becoming an affordable and sufficiently evolved technology for everyday clinical use.

Details

ISSN :
20726694
Volume :
11
Database :
OpenAIRE
Journal :
Cancers
Accession number :
edsair.doi.dedup.....a96ecf127fb622bd7e473d8ccaaf200f
Full Text :
https://doi.org/10.3390/cancers11111725