📊 Lecture 5: Advanced Statistical Analysis

Interactive notebooks for statistical testing, data visualization, FDR correction, and comprehensive biological data analysis.

🎯 Getting Started

Master statistical testing - Learn to apply appropriate tests to biological data.

Create publication-ready plots - Use Seaborn for professional visualizations.

End-to-end analysis - Complete a full biological data analysis workflow.

Available

🔍 Handling Missing Values

Learn strategies for dealing with missing data in biological datasets

  • ▸Identifying missing values in DataFrames
  • ▸Strategies for handling NaN values
  • ▸Filtering and cleaning datasets
  • ▸Imputation techniques
  • ▸Best practices for biological data
Open in Colab
Available

📊 SciPy Statistical Analysis

Master statistical testing with SciPy for biological data

  • ▸T-tests and statistical significance
  • ▸Correlation analysis
  • ▸Chi-square tests
  • ▸P-values and interpretation
  • ▸Choosing the right statistical test
Open in Colab
Available

🔧 Creating New DataFrames

Build and manipulate DataFrames for custom analyses

  • ▸Creating DataFrames from scratch
  • ▸Combining multiple data sources
  • ▸Adding calculated columns
  • ▸Reshaping and transforming data
  • ▸Building analysis pipelines
Open in Colab
Available

🎯 False Discovery Rate (FDR)

Control for multiple testing in genomic analyses

  • ▸Understanding multiple testing problem
  • ▸Bonferroni correction
  • ▸Benjamini-Hochberg FDR
  • ▸Interpreting adjusted p-values
  • ▸Application to gene expression data
Open in Colab
Available

🎨 Seaborn Visualization

Create publication-ready plots with Seaborn

  • ▸Advanced plotting with Seaborn
  • ▸Statistical visualizations
  • ▸Customizing plot aesthetics
  • ▸Multi-panel figures
  • ▸Publication-quality graphics
Open in Colab
Available

🔢 Working with Sets

Use Python sets for efficient biological data operations

  • ▸Set operations and theory
  • ▸Finding unique elements
  • ▸Set intersections and unions
  • ▸Comparing gene lists
  • ▸Venn diagram analysis
Open in Colab
Apply It!

🧬 End-to-End Analysis Project

Complete biological data analysis from start to finish

  • ▸Full analysis workflow
  • ▸Data cleaning and preparation
  • ▸Statistical testing pipeline
  • ▸Advanced visualizations
  • ▸Interpreting biological results
Open in Colab

🗺️ Learning Path

Data Preparation: Handle missing values and clean datasets

Statistical Testing: Apply SciPy tests to biological data

Visualization: Create publication-ready plots with Seaborn

Integration: Complete end-to-end analysis project

🎓 Skills You'll Master

By completing these notebooks, you'll be able to:

  • ✓Handle and clean messy biological datasets
  • ✓Perform appropriate statistical tests
  • ✓Control for multiple testing with FDR
  • ✓Create publication-quality visualizations
  • ✓Build complete analysis pipelines
  • ✓Interpret and communicate statistical results

📚 Part of the Python for Biologists course by Helfrid Hochegger

University of Sussex | Year 3 Biology, Biochemistry & Neuroscience