Explore a comprehensive series of R tutorials covering a wide range of bioinformatics and statistical analysis techniques. Learn how to perform differential gene expression analysis using DeSeq and EdgeR, analyze microarray data with RMA normalization and annotation, and conduct various statistical tests including linear regression, survival analysis, and Cox proportional hazard models. Master data visualization techniques such as stripchart, histogram, boxplot, and normal QQ plots. Dive into advanced topics like the Chip Analysis Methylation Pipeline, random forest feature selection, and likelihood ratio tests. Gain practical skills in data manipulation, including reading CSV files and converting data types. Perfect for beginners and intermediate R users looking to enhance their bioinformatics and data analysis capabilities.
Overview
Syllabus
DeSeq - Differential Gene Expression Analysis on RNA-seq data - R Tutorial.
Microarray Data Analysis using R - RMA Normalization and Annotation - tutorial.
EdgeR - Differential Gene Expression Analysis using RNA-seq data - R Tutorial.
Linear Regression using R - Tutorial for beginners.
Stripchart using R - Tutorial for beginners.
Histogram using R - Tutorial for Beginners.
Boxplot using R - Tutorial for beginners.
Normal QQ Plots using R - Tutorial for beginners.
The Chip Analysis Methylation Pipeline using R - Installation.
Survival Analysis using R - Tutorial for beginners.
Cox Proportional Hazard Model - R tutorial for Beginners.
How to read CSV and tabular files in R - Tutorial for beginners.
Convert a Character Object to Integer in R - Tutorial for Beginners.
Random Forest - Feature Selection Method - R tutorial.
Likelihood Ratio Test using R - Part 1.
Likelihood Ratio Test using R - Part 2.
Microarray data normalization and annotation - R tutorial.
Microarray Normalization and Differential Expression using R.
Taught by
Farhan Haq
