Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2016:2016:7983236.
doi: 10.1155/2016/7983236. Epub 2016 Dec 14.

A Survey of Computational Tools to Analyze and Interpret Whole Exome Sequencing Data

Jennifer D Hintzsche  1 , William A Robinson  2 , Aik Choon Tan  3
Affiliations
Review

A Survey of Computational Tools to Analyze and Interpret Whole Exome Sequencing Data

Jennifer D Hintzsche et al. Int J Genomics. 2016.

Abstract

Whole Exome Sequencing (WES) is the application of the next-generation technology to determine the variations in the exome and is becoming a standard approach in studying genetic variants in diseases. Understanding the exomes of individuals at single base resolution allows the identification of actionable mutations for disease treatment and management. WES technologies have shifted the bottleneck in experimental data production to computationally intensive informatics-based data analysis. Novel computational tools and methods have been developed to analyze and interpret WES data. Here, we review some of the current tools that are being used to analyze WES data. These tools range from the alignment of raw sequencing reads all the way to linking variants to actionable therapeutics. Strengths and weaknesses of each tool are discussed for the purpose of helping researchers make more informative decisions on selecting the best tools to analyze their WES data.

PubMed Disclaimer

Conflict of interest statement

The authors declare that there are no competing interests regarding the publication of this paper.

Figures

Figure 1
Figure 1
Trends in Whole Exome Sequencing studies and tools by querying PubMed (2011–2016).
Figure 2
Figure 2
Whole Exome Sequencing data analysis steps. Novel computational methods and tools have been developed to analyze the full spectrum of WES data, translating raw fastq files to biological insights and precision medicine.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Metzker M. L. Sequencing technologies—the next generation. Nature Reviews Genetics. 2010;11(1):31–46. doi: 10.1038/nrg2626. - DOI - PubMed
    1. Goodwin S., McPherson J. D., McCombie W. R. Coming of age: ten years of next-generation sequencing technologies. Nature Reviews Genetics. 2016;17(6):333–351. doi: 10.1038/nrg.2016.49. - DOI - PMC - PubMed
    1. Lek M., Karczewski K. J., Minikel E. V., et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature. 2016;536(7616):285–291. doi: 10.1038/nature19057. - DOI - PMC - PubMed
    1. McKenna A., Hanna M., Banks E., et al. The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Research. 2010;20(9):1297–1303. doi: 10.1101/gr.107524.110. - DOI - PMC - PubMed
    1. DePristo M. A., Banks E., Poplin R., et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nature Genetics. 2011;43(5):491–498. doi: 10.1038/ng.806. - DOI - PMC - PubMed