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Chapter 4 - Using R for Genomic Data Analysis
R Basics
Chapter 1 - Using the Terminal
1.1 Terminal Basics
1.2 Shell Script Basics
1.3 High Power Computing (HPC) at the CCB
1.4 VSCode
1.5 Folder Structures
1.6 BED format and BEDtools
1.7 Mamba and Conda Environments
Chapter 2 - File Formats
2.1 FASTQ Format
2.2 SAM/BAM Format
2.3 IGV for BAM Visualising
2.4 GFF Format
2.5 GTF Format
Chapter 3 - Analysis Pipelines
General Steps
STEP 1 - Quality Checks with FastQC
STEP 2: Trimming and Adapter Removal
General Aligning reads
ATAC/ChIP-seq Pipeline
ATAC/ChIP-seq Overview
STEP 3/4 Alignments
STEP 5: Visualization
STEP 6: Peak Calling
STEP 7: Quality Checks
STEP 8: Analysis
RNA-seq Pipeline
RNA-seq Pipeline Overview
STEP 3/4 - RNA-seq Alignments
STEP 5 - RNA-seq Counts
STEP 6: Visualization
STEP 7: Analysis
STEP 7: Analysis Example Notebook
Capture-C Pipeline
Capture-C Pipeline Overview
Capture-C Analysis Example Notebook
Hi-C Pipeline
Hi-C Pipeline Overview
Hi-C Visualisation Example
Single-cell RNA analysis
Single Cell RNA Analysis Overview
Chapter 4 - Using R for Genomic Data Analysis
R Basics
Plotgardener in R
Chapter 5 - Making it Public
Public Resources
UCSC Genome Browser
UCSC Track Hubs
Downloading Data
Upload to GEO
Chapter 6 - Additional Resources
Citing Bioinformatics Tools and Resources
Using Shell Scripts for Sequence Processing
CGAT Pipeline Basics
How to maintain the training documentation
Why use quarto for GitHub Pages docs?
Chapter 4 - Using R for Genomic Data Analysis
R Basics
R Basics
R Basics
Content about R basics for genomic data analysis will go here.