ABSTAT

Advanced Biostatistics


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Advanced Biostatistics

for Bioinformatics Tool Users (using R)

Instructors: Lisete Sousa and Carina Silva

Course description: This course is targeted for Biostatistical techniques often employed in analytical tools for high throughput data and multivariate data. Participants can expect to attend a thorough set of lectures that will reveal the conceptual frameworks that are needed to understand the methods. Extensive hands-on practice will be the main vehicle for providing the skills and user independence. To keep things in context, the course is exclusively based on biological examples. We will be using custom-built R scripts and packages that are available from the CRAN and/or Bioconductor repositories. Care has been taken not to use any proprietary data or software, so that the hands-on experience can carry on after the course, providing maximum user independence. We will be using custom-built R scripts and packages that are available from the CRAN and Bioconductor repositories.

Methodology This intensive course will introduce a relatively high number of concepts and methods. To keep it highly practical, we will spend most of the time in hands-on sessions.

Target Audience

Everybody using Bioinformatics methods is implicitly using statistical methods. Moreover, proper judgement of the results often calls for a deeper level of understanding than what is required to solve scholarly exercises. We will look into particular areas such Simulation, Bayesian Inference, Hidden Markov Chains and Multivariate Data Analysis methods with the attitude, eyes and brains of an experienced statistician that wants to understand how the methods work and systematic way. Course Pre-requisites Intermediate level knowledge in Statistics is necessary. There is no time to provide basic knowledge, so we will need to assume that accepted candidates have self-assessed for it in the following areas:

This level can also be obtained by attending another course in GTPB: The IBSTAT course. Basic Familiarity with the R environment will be necessary. Please follow the exercise that we provide. Install R from http://cran.r-project.org/ following the instructions. Download and unzip the Tutorial folder that is made available here.

Additionally, we suggest that candidates acquire familiarity with RStudio by visiting the following resources:

R Studio will be used in the course to ease-up interaction and increase productivity, but people that prefer the original R environment on the command line will be able to follow that preference

Learning objectives:

Learning outcomes:

Exercises