Applied Next Generation Sequencing (SBI127)

10 credits

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.

  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.  
Number Work-based learning outcome Title Knowledge
1 1

Produce a functional FastQ file from multiple NGS platforms.

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2 1

Generate an aligned Binary Alignment/Map (BAM)/Sequence Alignment/Map (SAM) file.

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3 1

Produce a written report, oral, or poster presentation on outcomes and recommendations for tool usage.

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4 2

Perform quality control, data validation (on eukaryotic and prokaryotic data) using open-source and or commercial tools.

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5 2

Perform appropriate analysis, e.g. mapping to reference, de novo assembly.

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6 2

Identify and visualise target genomic regions.

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7 2

Communicate findings to technical and non-technical audiences.

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8 3

Perform sequence interpretation/reporting within quality control parameters, responding to clinical queries as appropriate.

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9 3

Assign interpreted and called mutations with regard to clinically actionable events and assist in multidisciplinary direction of clinical pathway.

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10 3

Produce data in a common format compatible with NHS data standards and data-sharing protocols.

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11 1,2,3

Compare workflows specifically for the requirements of NGS data.

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You must complete
2 Case-based discussion(s)
2 of the following DOPS / OCEs
Assessment Title Type
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

Important information

The academic parts of this module will be detailed and communicated to you by your university. Please contact them if you have questions regarding this module and its assessments. The module titles in your MSc may not be exactly identical to the work-based modules shown in the e-portfolio. Your modules will be aligned, however, to ensure that your academic and work-based learning are complimentary.

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