Syllabus
Areas covered: i) basic alignment, indexing and graph algorithms, data structures ii) tumor genomics - tumor purity, ploidy and heterogeneity
(iii) point mutations and 'variant calling' iv) visualization of tumor genomic characteristics
(v) approaches to 'comparing' reading to a reference transcriptome or genome vi) approaches to identifying expressed genes and isoforms approaches to estimating isoform frequency and differential expression
Annotation
The course consists of two parts. The first part presents basic analytical methods and computational approaches for efficient analysis of celene phenomenon sequencing data in the context of human sequencing experiments.
In the second part, basic approaches to the analysis of transcriptomic data will be presented. Great emphasis will be placed on tumor genomics and its limitations.
The course will seek to close the gap between computer science and genetics and will work with real-life examples from the field of tumor re-sequencing, rare diseases and population-genomic studies.