Introduction to Bioconductor

We learn how to use Bioconductor, one of the most widely used open source toolkits for biological data. Two tracks will be available: 1) Next generation sequencing and 2) microarrays  

About The Course

We will cover some common uses of the software packages within the Bioconductor project. You will get to decide if you learn methods for next generation sequencing, microarrays or both. We will cover a number of normalization, batch correction, and testing methods for high throughput data.

Topics:

  • Intro to Biology
  • Next Generation Sequencing
    •   GRanges, Rsamtools
    •   Statistical modeling of counts
    •   Differential expression of counts
  • Microarrays
    •   eSets
    •   Background correction
    •   Differential expression of arrays
  • Normalization
  • Advanced differential expression
  • Batch effects
  • Gene set testing

This class was supported in part by NIH grant R25GM114818.

This course is part of a larger set of 8 total courses:

PH525.1x: Statistics and R for the Life Sciences

PH525.2x: Introduction to Linear Models and Matrix Algebra

PH525.3x: Advanced Statistics for the Life Sciences

PH525.4x: Introduction to Bioconductor

PH525.5x: Case study: RNA-seq data analysis

PH525.6x: Case study: Variant Discovery and Genotyping

PH525.7x: Case study: ChIP-seq data analysis

PH525.8x: Case study: DNA methylation data analysis

Recommended Background

PH525.1x or intro to statistics and basic programming