Applied Next Generation Sequencing

Module details

Title

Applied Next Generation Sequencing

Type

Specialist

Module code

SBI127

Credits

10

Requirement

Compulsory

Aim of this module

There is a revolution occurring in genome sequencing. The cost of sequencing an entire human genome has dropped dramatically to the point at which it can be applied within the NHS to underpin diagnosis and treatment. Such strategies have also become very important in areas such as understanding the spread of antibiotic-resistant bacteria across hospitals. However, while the cost of generating the data has dropped, the cost of analysing and interpreting such data has become one of the key bottlenecks in deploying this exciting new technology. This module will develop the trainee’s understanding of genome technology. It will also give them an understanding of the techniques needed to follow best practice in assembling genomic data from the current version of these technologies, and will provide the trainee with tools and strategies for converting these data into clinically useful information. A strong emphasis will be placed on understanding the ethical and data governance challenges faced by this new – and very personal – data. This module will enable the trainee to gain experience of the use of Next Generation Sequencing in a clinical setting and apply their theoretical knowledge, developing the trainees’ understanding of genome technology, the techniques needed to follow best practice in assembling genomic data from the current version of these technologies, and the tools and strategies for converting these data into clinically useful information within an ethical and data governance framework.

Competencies

#	Learning outcome	Competency	Action
# 1	Learning outcome 1	Competency Produce a functional FastQ file from multiple NGS platforms.	Action View
# 2	Learning outcome 1	Competency Generate an aligned Binary Alignment/Map (BAM)/Sequence Alignment/Map (SAM) file.	Action View
# 3	Learning outcome 1	Competency Produce a written report, oral, or poster presentation on outcomes and recommendations for tool usage.	Action View
# 4	Learning outcome 2	Competency Perform quality control, data validation (on eukaryotic and prokaryotic data) using open-source and or commercial tools.	Action View
# 5	Learning outcome 2	Competency Perform appropriate analysis, e.g. mapping to reference, de novo assembly.	Action View
# 6	Learning outcome 2	Competency Identify and visualise target genomic regions.	Action View
# 7	Learning outcome 2	Competency Communicate findings to technical and non-technical audiences.	Action View
# 8	Learning outcome 3	Competency Perform sequence interpretation/reporting within quality control parameters, responding to clinical queries as appropriate.	Action View
# 9	Learning outcome 3	Competency Assign interpreted and called mutations with regard to clinically actionable events and assist in multidisciplinary direction of clinical pathway.	Action View
# 10	Learning outcome 3	Competency Produce data in a common format compatible with NHS data standards and data-sharing protocols.	Action View
# 11	Learning outcome 1,2,3	Competency Compare workflows specifically for the requirements of NGS data.	Action View

Assessments

You must complete:

• 2 case-based discussion(s)
• 2 of the following DOPS/ OCEs:

Assess the quality of sequencing from an NGS sequencing run using FastQC or equivalent	DOPS
Create a BAM file from FASTQ sequence	DOPS
View a sequence alignment BAM file in IGV and assess sequence alignment	DOPS
Combining two datasets e.g. HPO and OMIM, output a list of genes associated with a specific functional pathway, annotated with information from both datasets.	DOPS
Perform a literature search and using online resources for a particular variant to determine role in a disease. Abstract decisions only.	DOPS

Learning outcomes

1. Use the tools required for each stage of NGS data analysis.
2. Analyse NGS data through base calling, filtering, quality control, data validation and read mapping (eukaryotic and prokaryotic) in a clinical setting.(The clinical setting could include Clinical Genetics, Microbiology, Virology, Clinical Diagnostics, for example targeted oncology treatments/classical genetics.)
3. In partnership with the relevant clinical specialist interpret NGS data through SNP, InDEL and CNV analysis, and relate to phenotypic data.  

Learning outcomes

1. Describe the main Next Generation Sequencing (NGS) platforms and the methodologies that they use.
2. Discuss the applications of NGS in the clinical setting, including genome-wide association studies, whole-exome sequencing, targeted resequencing and profiling of microbial pathogens.
3. Describe the strengths of each NGS platform to solve different biological problems.
4. Describe how samples are prepared for sequencing.
5. Describe the basic principles of NGS data analysis, bioinformatic approaches, challenges in storage and data transfer.
6. Describe the various data file types, such as FASTQ, Binary Alignment/Map (BAM) and Sequence Alignment/Map (SAM) files, and describe tools available for conversion of file types.
7. Describe the ethical and governance regulations relating to data capture in the NHS.
8. Describe the ethical and governance concerns regarding data integration in the NHS.

Indicative content

• Brief history of sequencing strategies
• Application of next generation data in genetics and medicine and the impact on patient care

Next Generation Sequencing platforms

• The genome science behind NGS – random fragments, sequencing, assembly
• Different sequencing platforms and the physical chemistry they deploy: non-optical (e.g. Ion Torrent, Nanopore and optical e.g. Illumina, 454)
• Applications of NGS

Sequence assembly

• The problems of aligning short reads
• Next generation alignment strategies – Bowtie, BWA, SOAP, Burrows-Wheeler, de Bruijn graphs
• Data formats for next generation data – BAM, SAM, FASTQ
• Sequence interpretation
• SNP detection, CNV detection

Data handling and data governance

• Workflows for next generation analysis
• Data quality in next generation data
• Presenting next generation data
• Models of use of next generation technology within the NHS
• Issues of patient consent and what analyses are ethical
• Current literature and practice around the impact of NGS tools in clinical medicine and genomics

Activities

• Observe the pre- and post-analytical processes from sampling to data generation and critically evaluate the process during discussions with your training officer.
• Observe the use of NGS in a range of NHS and other settings (for example academic, commercial) and evaluate commercial tools versus open-source software for analysing NGS data and the requirement for automated NGS data analysis pipelines.
• Attend a range of clinical settings where patients will be reviewed and the results generated from next generation sequence testing will be discussed with the patient, and evaluate the requirement for best practice, reproducible NGS bioinformatics, reporting workflows and the need to be able to share NGS data in the clinical setting.
• Attend and actively participate in multidisciplinary group meetings to inform and influence decisions on patient care and technology strategy.