EEOB/BCB 546: Computational Skills for Biological Data
Offered: Each Fall, MWF, 1:10-2:30pm
Overview of Course:
With the advent of big data across a number of sub-disciplines within biology, there is an increasing need for biologists to be comfortable and competent with command-line data processing and analysis. This course will develop basic skills necessary for biologists working with big data sets. Topics will include UNIX commands, scripting in R and Python, version control using Git and GitHub, use of high performance computing clusters, and writing effective data-management plans. These topics will be taught using a combination of lectures and computational exercises.
EEOB 561: Evolutionary and Ecological Genomics
Offered: Alternate Springs, Even-numbered years, WF, 1:10-2:30pm
Overview of Course:
Following an initial overview of omic data generation platforms and computational tools, the course will focus on how these data are being (or could be) applied to answer novel questions in evolution and ecology. The first two-week unit will survey next-generation sequencing platforms (e.g., 454, HiSeq, MiSeq, PacBio, nanopore) and the manner in which data are generated to study various fractions of the genome (e.g., RNASeq to evaluate the transcriptome and bisulfite sequencing to evaluate the methylome). This will be followed with a brief overview of computational tools for analysis of large, genomic data sets (e.g., scripting languages, software packages for read mapping and genome assembly, and comprehensive platforms for data analysis such as Galaxy and iPlant). The course will then progress through 11 weeklong modules, each tackling a different topic in ecology or evolution. Modules will begin with a lecture overviewing longstanding questions in these fields followed by discussion of 2-3 recent scientific studies in which genomic data have been brought to bear on the topic at hand. Modules will conclude with a consideration of where research is headed in a given field and how omic data will continue to contribute. The final week of the semester will consist of student presentations describing the manner in which they could apply a genomic approach in their own research.