Offered: Fall Semester (September – December)
Credits: 3
Apply bioinformatics principles to interpret next generation sequencing (NGS) data within a clinical setting. Explore sequencing technologies and omics statistical tools to gain expertise in assessing genomic test data, and an understanding of how clinical bioinformatics pipelines work to identify, filter, annotate and prioritize candidate disease-causing variants.
Learning outcomes:
- Appraise and critique genome wide sequencing technologies, including the benefits, limitations, diagnostic yields and appropriate clinical indications.
- Apply bioinformatics methods to process NGS data, including variant calling pipelines to annotate, filter, and create a candidate list of genomic variants.
- Evaluate bioinformatics algorithms involved in chromosomal microarray analysis, exome capture, standard short-read sequencing, optical mapping, linked-read sequencing, long-read sequencing, RNA-sequencing and other omics tools used for the detection and analysis various kinds of variants.
- Appraise the potential for integration of multi-omics bioinformatic methods in clinical and research setting and apply corresponding statistics.