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Updated: Mar 13, 2026

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
Published on: April 4, 2018
Genomic sequencing in clinical practice: applications, challenges, and opportunities
Joel B Krier1, Sarah S Kalia, Robert C Green2
1Genomes2People Research Program, Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA; Harvard Medical School, Boston, Massachusetts, USA.
Genomic sequencing (GS) is transforming clinical medicine for rare disorders, cancer, and prenatal screening. Rapid adoption presents challenges in interpretation and clinician preparedness, marking a pivotal moment for innovation.
Area of Science:
- Genomics
- Clinical Medicine
- Bioinformatics
Background:
- Massively parallel sequencing, also known as next-generation sequencing, has accelerated the clinical application of genomic sequencing (GS).
- GS is integral for diagnosing rare diseases, identifying cancer therapeutic targets, and prenatal aneuploidy screening.
- New applications like preconception carrier screening and predisposition screening are emerging in research and public use.
Purpose of the Study:
- To review the current state and challenges of genomic sequencing (GS) in clinical medicine.
- To highlight the rapid adoption and emerging applications of GS.
- To discuss the implementation hurdles and future potential of clinical GS.
Main Methods:
- Literature review of current applications and challenges in clinical genomic sequencing.
- Analysis of the impact of next-generation sequencing technology.
- Discussion of stakeholder challenges and future directions.
Main Results:
- Genomic sequencing is a crucial tool in various clinical areas, with expanding applications.
- Rapid adoption of GS has led to challenges in variant interpretation and clinician education.
- The field is at a critical juncture, balancing innovation with implementation issues.
Conclusions:
- Clinical genomic sequencing is rapidly evolving, offering significant potential for patient care.
- Addressing standardization and education challenges is vital for successful integration of GS.
- The future of clinical GS involves navigating complex data and implementation questions for further innovation.
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