Next generation sequencing technology in the clinic and its challenges

Publikation: Bidrag til tidsskrift › Review › Forskning › fagfællebedømt

Standard

Next generation sequencing technology in the clinic and its challenges. / Vestergaard, Lau K.; Oliveira, Douglas N.P.; Høgdall, Claus K.; Høgdall, Estrid V.

I: Cancers, Bind 13, Nr. 8, 1751, 2021.

Publikation: Bidrag til tidsskrift › Review › Forskning › fagfællebedømt

Harvard

Vestergaard, LK, Oliveira, DNP, Høgdall, CK & Høgdall, EV 2021, 'Next generation sequencing technology in the clinic and its challenges', Cancers, bind 13, nr. 8, 1751. https://doi.org/10.3390/cancers13081751

APA

Vestergaard, L. K., Oliveira, D. N. P., Høgdall, C. K., & Høgdall, E. V. (2021). Next generation sequencing technology in the clinic and its challenges. Cancers, 13(8), [1751]. https://doi.org/10.3390/cancers13081751

Vancouver

Vestergaard LK, Oliveira DNP, Høgdall CK, Høgdall EV. Next generation sequencing technology in the clinic and its challenges. Cancers. 2021;13(8). 1751. https://doi.org/10.3390/cancers13081751

Author

Vestergaard, Lau K. ; Oliveira, Douglas N.P. ; Høgdall, Claus K. ; Høgdall, Estrid V. / Next generation sequencing technology in the clinic and its challenges. I: Cancers. 2021 ; Bind 13, Nr. 8.

Bibtex

@article{f464154b3ca04aada790288693dda521,
title = "Next generation sequencing technology in the clinic and its challenges",
abstract = "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.",
keywords = "Alignment, Bioinformatic pipeline, Cancer, Clinical application, Next-generation sequencing, Variant calling",
author = "Vestergaard, {Lau K.} and Oliveira, {Douglas N.P.} and H{\o}gdall, {Claus K.} and H{\o}gdall, {Estrid V.}",
note = "Publisher Copyright: {\textcopyright} 2021 by the authors. Licensee MDPI, Basel, Switzerland.",
year = "2021",
doi = "10.3390/cancers13081751",
language = "English",
volume = "13",
journal = "Cancers",
issn = "2072-6694",
publisher = "M D P I AG",
number = "8",

}

RIS

TY - JOUR

T1 - Next generation sequencing technology in the clinic and its challenges

AU - Vestergaard, Lau K.

AU - Oliveira, Douglas N.P.

AU - Høgdall, Claus K.

AU - Høgdall, Estrid V.

N1 - Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

PY - 2021

Y1 - 2021

N2 - 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.

AB - 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.

KW - Alignment

KW - Bioinformatic pipeline

KW - Cancer

KW - Clinical application

KW - Next-generation sequencing

KW - Variant calling

U2 - 10.3390/cancers13081751

DO - 10.3390/cancers13081751

M3 - Review

C2 - 33916923

AN - SCOPUS:85103617603

VL - 13

JO - Cancers

JF - Cancers

SN - 2072-6694

IS - 8

M1 - 1751

ER -

ID: 302457525