Applied Bioinformatics 2019

Topics covered will include:

• Introduction to R and UNIX command line environments
• Command line tools such as FastQC, HISAT2 and HTSeq for dealing with RNA-seq data
• R Bioconductor tools like edgeR for analysis of differential gene expression
• Web-based tools such as Galaxy, UCSC Genome Browser and IGV for general genomics
• A survey of publicly available experimental data and gene annotation resources
• R packages for dimensional reduction, visualization, gene ontology and pathway analysis
• Introduction to cloud computing technology relevant to biomedical research
• An introduction to machine learning using CART models, random forests and support vector machines

Additionally, the course will include evening workshops to address topics of interest to course participants.

Applicants may be interested in taking the Environmental Genomics course held immediately after this one.  Though the two courses are independent, participants may benefit from taking both courses. Applied Bioinformatics, offered first, offers experiences in bioinformatics that pave the way for the more complex experimental designs used in Environmental Genomics. Students enrolled in both courses receive complimentary on-campus housing to enjoy Acadia National Park and the Bar Harbor area between courses.