edX
Free Online Course (Audit)
English
4 weeks long, 4-10 hours a week
selfpaced
Overview
Are you interested in analyzing biological datasets but don’t have a strong computational background? Do you want to focus on the biology and learn how to use modern best-practice pipelines that use existing tools? This introductory course, geared towards non-computational biologists, will introduce a specific biological problem each week centered around next generation sequencing and teach you how to use Illumina’s BaseSpace platform to run workflows conveniently and in a user-friendly manner.
You will learn current best-practice workflows for Genome Assembly, Variant Calling, Trio Analysis, and Differential Expression Analysis as well as the types of biological problems that motivate them.
You will learn current best-practice workflows for Genome Assembly, Variant Calling, Trio Analysis, and Differential Expression Analysis as well as the types of biological problems that motivate them.
Syllabus
- Week 1: Assembling Genomes
- Given raw whole genome sequence data, you will learn how to perform genome assembly, assess the quality of the assembled genome, perform annotation and gene prediction, and perform basic comparative genomics
- Week 2: Searching for Disease-Causing Mutations
- Given raw whole genome sequence data as well as raw whole exome sequence data, you will learn how to perform variant calling and will dive into comparing and contrasting the pros and cons of each sequencing method
- Week 3: Will Modifications of Embryos Treat Genetic Diseases?
- Given raw whole genome sequence data from parents and a child, you will learn how to perform variant calling on each and how to perform “trio analysis” (e.g. finding which parent was the source of each of the child’s SNVs, searching for rare de novo mutations, and finding compound heterozygous traits)
- Week 4: Analyzing Gene Expression
- Given raw RNA-Seq data from different samples, you will learn how to align the reads, count the number of transcripts of each gene in either sample, and perform pairwise differential expression across the samples to determine which genes underwent the most significant expression changes
Taught by
Pavel Pevzner , Phillip Compeau and Niema Moshiri
