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.

Target Audience

Everybody using Bioinformatics methods is implicitly using statistical methods. Moreover, proper judgment 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.

Detailed Program

Days Lectures Exercises & Script examples
Day 1 Guides
  • Probability Review (exercise)
    • Random variables
    • Parameters
    • Discrete Distributions
    • Continuous Distributions
  • Simulation (exercise)
    • Monte Carlo simulation
    • Parametic/Non-parametric Boostrap estimation
    • Boostrap Confidence Intervals
    • Bootstrap Hypothesis Tests for one sample/two independent samples
Day 2
Day 3
Day 4

Course Pre-requisites


The source for this course webpage is on github.

Creative Commons License
ABSTAT18 by GTPB is licensed under a Creative Commons Attribution 4.0 International License