MIC training: Modern data analysis in R/RStudio

The first part will demonstrate:

1. Resources with R courses/tutorials,
2. Basic programming concepts,
3. Working with RStudio,
4. Brief intro to data.table & ggplot2,
5. Functions, testing, profiling, debugging,
6. Vectorization,
7. Parallel computations,
8. Command-line parameters

R notebook with the code.

During the second part we will process time-series data from a time-lapse microscopy experiment. We will:

• load data, merge different data sources,
• clean missing data and outliers,
• plot different data cuts,
• perform hierarchical clustering,
• validate clusters.

Intermediate datasets throughout the workshop:

• Milestone 1: complete merged data from all experiments
• Milestone 2: + missing data interpolated
• Milestone 3: + outliers removed
• Milestone 4: + normalised trajectories
• Milestone 5: + cluster numbers assigned to individual time series

PDF with an introduction to datasets.

Notebook with the practical session.

data.table

Extension of base R's data.frame structure.

Fast data manipulation with a concise SQL-like syntax.

Check out the vignette for an introduction and Advanced tips and tricks with data.table for expanding your knowledge.

ggplot2