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Fiona Howat, Kate Tatton-Brown, Katie Snape, and Amy Frost (Mentor)

Most FutureLearn courses run multiple times. Every run of a course has a set start date but you can join it and work through it after it starts. Find out more This course is designed for scientists and healthcare professionals with an interest in obtaining a postgraduate-level understanding of genomic sequencing technologies. If you are completing both Genomic Technologies in Clinical Diagnostics courses, we recommend that you complete Genomic Technologies in Clinical Diagnostics: Molecular Techniques first. And if you are new to the field, we recommend that before you start either course, you complete The Genomics Era: the Future of Genetics in Medicine – the first in the Genomics in Healthcare program from St George’s. You can use the hashtag #FLgentechNGS to talk about this course on social media.

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Most FutureLearn courses run multiple times. Every run of a course has a set start date but you can join it and work through it after it starts. Find out more This course is designed for scientists and healthcare professionals with an interest in obtaining a postgraduate-level understanding of genomic sequencing technologies. If you are completing both Genomic Technologies in Clinical Diagnostics courses, we recommend that you complete Genomic Technologies in Clinical Diagnostics: Molecular Techniques first. And if you are new to the field, we recommend that before you start either course, you complete The Genomics Era: the Future of Genetics in Medicine – the first in the Genomics in Healthcare program from St George’s. You can use the hashtag #FLgentechNGS to talk about this course on social media.

Topics Covered

  • The changing landscape of genomics: From Sanger sequencing to Next Generation Sequencing
  • Overview of Next Generation Sequencing platforms and their methodology
  • Targeted resequencing
  • Alignment, variant calling and annotation
  • Other applications of Next Generation Sequencing beyond DNA sequencing
  • Next Generation Sequencing in gene discovery
  • Gene discovery in the research and diagnostics
  • Next Generation Sequencing in clinical diagnostics: Single gene, gene panel sequencing, exome and genome sequencing
  • How to design a gene panel
  • The 100 000 Genomes project
  • The transforming NHS: Genomics in mainstream practice

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Reviews summary

In-depth genomics for clinical diagnostics

According to learners, this course provides an in-depth and relevant exploration of Genomic Technologies in Clinical Diagnostics, focusing heavily on Next Generation Sequencing (NGS). Many appreciate its comprehensive coverage of topics from NGS platforms to variant calling and gene panel design. Students find the content highly relevant for healthcare professionals and scientists aiming for a postgraduate-level understanding. However, some learners note the course's demanding nature and the crucial need for strong prerequisites, emphasizing that prior knowledge in molecular techniques is highly beneficial to fully grasp the complex subjects presented.
Focuses on the theoretical underpinnings of genomic technologies.
"The course provides a solid theoretical background, which is essential for understanding the nuances of NGS."
"I appreciated the deep dive into the methodology behind various sequencing platforms."
"While comprehensive, I felt it could benefit from more hands-on or practical examples."
Highly relevant for professionals in clinical diagnostics.
"The content directly applies to my work in clinical diagnostics, especially gene panel design."
"I found the discussions on the transforming NHS and clinical utility invaluable."
"It effectively bridges the gap between theoretical genomic science and real-world clinical application."
Offers a deep dive into genomic technologies & applications.
"I really gained a comprehensive understanding of Next Generation Sequencing and its clinical applications."
"The course covers a broad range of genomic technologies, from fundamental platforms to advanced variant analysis."
"It provides an excellent overview of current genomic projects like the 100,000 Genomes project."
Requires strong prior knowledge for optimal understanding.
"I found the course challenging without having completed the recommended prerequisite molecular techniques course."
"It assumes a significant level of existing knowledge in genetics and molecular biology."
"To truly benefit, I recommend having a solid foundation before diving into this advanced material."

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Career center

Learners who complete Genomic Technologies in Clinical Diagnostics: Next Generation Sequencing will develop knowledge and skills that may be useful to these careers:

Reading list

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Provides a practical guide to the analysis of RNA-seq data, a common application of NGS. It covers the workflow from theoretical background to practical examples using various tools, suitable for both bioinformaticians and wet lab scientists.
Provides a comprehensive guide to NGS data analysis, covering various applications like genome assembly, variant discovery, and metagenomics. It's suitable for researchers and graduate students and can serve as a textbook, offering detailed analysis steps rather than just black-box pipelines.
Offers a step-by-step approach to NGS data analysis for a wide range of applications, including RNA-seq, variant discovery, and clinical sequencing. The second edition includes new chapters on single-cell RNA-seq and clinical sequencing, reflecting contemporary topics. It's a practical guide for practitioners in life sciences, bioinformatics, and biostatistics.
This widely-used textbook provides a broad introduction to bioinformatics and genomics, including a chapter on next-generation sequencing in its third edition. It's suitable for advanced undergraduate and graduate students and serves as a valuable resource for researchers.
This practical book focuses on analyzing genomic data using cloud infrastructure and open-source tools like GATK, Docker, and WDL. It's highly relevant for professionals and researchers dealing with large-scale NGS data analysis in a cloud environment, covering contemporary computational approaches.
Presents the foundations of computational molecular biology and bioinformatics, with a focus on computational and statistical principles applied to genomes. While not solely focused on NGS, it provides essential background in the algorithms and statistics necessary for analyzing sequencing data.
Offers a plain-language introduction to the informatics methods and tools for analyzing NGS data. It covers experimental design, data preprocessing, alignment, and assembly, with updated information and new chapters on emerging technologies. It's suitable for students, laboratory scientists, and computing specialists.
Explores recent advances in NGS instrumentation and data analysis, with contributions from experts. It covers current NGS platforms, sequencing chemistries, and applications in various fields, providing a broad overview of the technology and its uses.
Focuses on practical data skills for bioinformatics using open-source tools, which is essential for working with NGS data. While not exclusively about NGS, it provides foundational knowledge in data manipulation, programming, and reproducible research, highly valuable for anyone analyzing sequencing data.
Considered a classic in bioinformatics, this book covers probabilistic models for analyzing biological sequences. While published before the advent of modern NGS, the foundational concepts of sequence analysis are still highly relevant for understanding NGS data processing and interpretation.
Provides a comprehensive introduction to bioinformatics, including sequence and genome analysis. It's a widely recommended textbook for gaining a solid understanding of the fundamental concepts and algorithms used in the field, serving as good background for NGS.
Focuses on the algorithmic foundations of bioinformatics. Understanding these algorithms is crucial for comprehending how NGS data is processed and analyzed. It's a good resource for those wanting to delve deeper into the computational aspects.
Introduces the fundamental concepts of RNA-seq experiments and guides readers through the data analysis process. It covers experimental design, quality control, alignment, quantification, and differential gene expression analysis, valuable for those focusing on transcriptomics.
Focuses specifically on NGS technology in the context of DNA analysis. It likely covers the technical aspects of the sequencing platforms and their applications in DNA sequencing projects.
Compiles chapters on various aspects of NGS, including genomics, transcriptomics, methylomics, platforms, and bioinformatics challenges. It examines advances and challenges of NGS applications in research, providing insights into contemporary topics.
Covers bioinformatics methods ranging from omics technologies to next generation sequencing. It provides a broader context within the 'omics' field and then focuses on methods relevant to NGS data.
Offers an overview of classical bioinformatics concepts. While not solely focused on NGS, it provides essential foundational knowledge in the field, making it useful as a preparatory text for understanding the broader context of NGS data analysis.
Provides an introduction to bioinformatics, covering biological context, classical sequence analysis, and omics. It's a good starting point for those new to the field, offering foundational knowledge relevant to understanding the biological data generated by NGS.
Focuses on the use of NGS in diagnosing diseases. It provides a comprehensive examination of the wide range of clinical applications, highlighting the potential of NGS to optimize healthcare and identify disease-causing variants.

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