Bioinformatcs HOW-TOs

This is an outline of a series of blogs that I plan to write in 2020 that will share many tools and code snippets that I find useful in Bioinformatics.

RNA-seq

• Alignment (hisat2)
• Get read counts (feature counts)
• Differential expression (DESeq), volcano plot, heatmaps
• PCA plot, including scatter plot of how genes contribute to PC1 and PC2
• Batch effect correction
• Projecting other people’s datasets onto your dataset (or vice versa) using PCA
• Pathway enrichment

ChIP-seq

• Call peaks
• Peak set enrichment using GREAT
• Annotate peaks to genes using ChIPpeakAnno
• Differential peaks using diffReps
• Visualization using ngs.plot
• Integration with RNA-seq data

Metabolic network analysis

• mCADRE
• Metabolic pathway enrichment
• Visualize transcriptomics and metabolomics data together in KEGG pathway maps

Data wrangling in R

Data visualization in R