Learn · Biological data analysis and visualization with R
Lecture 11 of 42Week 3 :
Lecture 11 : Visualization with vioplot and ggplot2
Prof. Riddhiman Dhar · IIT Kharagpur
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- Biological data analysis and visualization with R, IIT Kharagpur (at NPTEL)
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- CC BY-NC-SA, as NPTEL states it. Non-commercial use only.
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- NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge.
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- Tweens profiles and older. How courses are placed
All the lectures
- Lecture 01 : Introduction
- Lecture 02 : Setting up R
- Lecture 03 : Basic functions in R
- Lecture 04 : Basic data structures in R
- Lecture 05 : Data structures and File I/O
- Lecture 06 : Basic statistical tests with R
- Lecture 07 : Correlation analysis
- Lecture 08 : Analysis of variance (ANOVA)
- Lecture 09 : Basic data visualization techniques
- Lecture 10 : Data visualization
- Lecture 11 : Visualization with vioplot and ggplot2
- Lecture 12 : R packages for plotting and data organization
- Lecture 13 : Data transformation in R
- Lecture 14 : Bioconductor packages
- Lecture 15 : Flow cytometry data analysis in R/Bioconductor
- Lecture 16 : Gene expression analysis and co-expression network
- Lecture 17 : WGCNA package and Data Download
- Lecture 18 : WGCNA hands-on: Data preprocessing
- Lecture 19 : WGCNA hands-on: Soft-threshold
- Lecture 20 : WGCNA: Module gene expression
- Lecture 21 : Introduction to ChIP-seq
- Lecture 22 : ChIP-seq data analysis
- Lecture 23 : ChIP-seq data analysis: Peak calling
- Lecture 24 : Peak calling and Visualization
- Lecture 25 : ChIP-seq data analysis: bigWig/bw files
- Lecture 26 : Regression models on Biological data
- Lecture 27 : Predictive models with linear regression
- Lecture 28 : Multicollinearity
- Lecture 29 : Lasso regression
- Lecture 30 : Non-linear regression
- Lecture 31: Dimensionality reduction
- Lecture 32 : Principal Component Analysis (PCA)
- Lecture 33: PCA analysis hands-on
- Lecture 34: PCA analysis using ‘PCAtools’
- Lecture 35 : UMAP analysis
- Lecture 36 : Classification of biological samples
- Lecture 37 : Penalized and Stepwise Logistic regression
- Lecture 38 : Decision trees
- Lecture 39 : Classification and Regression trees
- Lecture 40 : Random Forests
- Live Session 10-03-2025
- Live Session 16-04-2025