Next Generation Sequencing Technology in the Clinic and Its Challenges

Data analysis has become a crucial aspect in clinical oncology to interpret output from next-generation sequencing-based testing. NGS being able to resolve billions of sequencing reactions in a few days has consequently increased the demand for tools to handle and analyze such large data sets. Many...

Full description

Saved in:
Bibliographic Details
Published in:Cancers 2021-04, Vol.13 (8), p.1751
Main Authors: Vestergaard, Lau K, Oliveira, Douglas N P, Høgdall, Claus K, Høgdall, Estrid V
Format: Article
Language:English
Subjects:
Cancer
Drug delivery
Genes
Genomes
Genomics
Incorporation
Medical prognosis
Mutation
Next-generation sequencing
Nucleotide sequence
Nucleotides
Oncology
Precision medicine
Review
Tumorigenesis
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Data analysis has become a crucial aspect in clinical oncology to interpret output from next-generation sequencing-based testing. NGS being able to resolve billions of sequencing reactions in a few days has consequently increased the demand for tools to handle and analyze such large data sets. Many tools have been developed since the advent of NGS, featuring their own peculiarities. Increased awareness when interpreting alterations in the genome is therefore of utmost importance, as the same data using different tools can provide diverse outcomes. Hence, it is crucial to evaluate and validate bioinformatic pipelines in clinical settings. Moreover, personalized medicine implies treatment targeting efficacy of biological drugs for specific genomic alterations. Here, we focused on different sequencing technologies, features underlying the genome complexity, and bioinformatic tools that can impact the final annotation. Additionally, we discuss the clinical demand and design for implementing NGS.
ISSN:2072-6694
2072-6694
DOI:10.3390/cancers13081751