Data Carpentry’s aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain. This workshop uses Data Carpentry’s approach to teach data management and analysis for genome mining research including: best practices for organization of bioinformatics projects and data, use of command-line utilities, use of command-line tools to analyze sequence quality, use of R studio and use of R libraries to compare diversity between samples, and connecting to and using cloud computing.
Prerequisitos
FIX ME
Data
This worksop uses data from experiment: Genome analysis of multiple pathogenic isolates of Streptococcus agalactiae: Implications for the microbial “pan genome”, by Hervé Tettelin, Vega Masignani, Michael J. Cieslewicz, Claire M et al.
All of the data used in this workshop can be downloaded from:
More information about this data is available on the Data page.