ChIP Next Generation Sequencing Analysis: Complete A to Z

ChIPseq Analysis – Bioinformatics – RStudio – Miniconda – Docker – Linux – Epigenomics – Epigenetics

What you’ll learn
You’ll be able to undertake a ChIPseq analysis pipeline in Linux and R environment
You’ll be given a FREE access to ChIPseq-analysis-ready Docker containers
You’ll be given a FREE access to a whole chapter from a review paper worth $31.50
You’ll be able to set up ChIPseq analysis Docker container
You’ll be able to setup ChIPseq analysis conda virtual environment
You’ll be able to manage the working environment of your ChIPseq projects
You’ll be able to evaluate the quality of ChIPseq sequencing data using FastQC
You’ll be able to perform alignment of reads to the genome using Bowtie2
You’ll be able to filter aligned reads based on criteria of your own choosing
You’ll be able to run MACS3 peak calling algorithm
You’ll be able to use your epigenetic knowledge in order to aid interpretation of ChIP data
You’ll be able to use the principles of functional studies and epigenetic lab techniques
You’ll understand the full ChIPseq analysis workflow
You’ll learn about relationship between epigenetics and environment

Requirements
Exposure to R programming language is required but you don’t have to be an R developer!
Familiarity with UNIX command line, conda and docker containers will be advantageous but not necessary
You’ll need 80GB of available disc space or access to external hard drive or cloud storage to comfortably do all the ChIPseq analyses
Having an basic understanding of central dogma of molecular biology
Being open-minded and ready to learn!

Description
Did you know that chromatin immunoprecipitation (ChIP) is one of the most commonly used techniques when assessing the effect of epigenetic modifications on gene expression and hence cell identity? Traditionally ChIP was combined with polymerase chain reaction (PCR), but with the advent of next-generation sequencing (NGS), a far more powerful way to study epigenetic modifications on a genome-wide level is through ChIP followed by sequencing (ChIPseq) which this course is about.

I’m Alexander Abdulkader Kheirallah, PhD and I’ll be your instructor in this course. I have a doctorate in bioinformatics and my project involved analysis of many ChIPseq datasets. My bioinformatic work has been published in peer-reviewed journals. I have worked as a bioinformatician at University of Cambridge and I am also a data scientist. After the success of my first course on RNAseq differential gene expression analysis, I’ve decided to take it further by condensing years of my experience in the form of a concise and practical course about epigenomics and ChIPseq data analysis. The ability to analyse big genomic data gives you a lot of opportunities at the intersection of biology, medicine and computer science.

What makes this course unique is that it combines thorough study of epigenetic biology with deep and practical analytical capabilities.

Not only you’ll gain epigenetic knowledge to aid your ChIPseq analysis endeavors but also you’ll be able to effectively manage your projects, assess their quality, and analyse. You’ll be provided with NGS ChIPseq data and I’ll walk you through the ChIPseq analysis step-by-step.

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The course is split into 11 sections culminating with a capstone project that you can add to your portfolio

Introduction to the course

Epigenetics of gene expression: a thorough view of biology – Part 1

Epigenetics of gene expression: a thorough view of biology – Part 2

Epigenetics and environment

Laboratory techniques of epigenetics and introduction to functional studies

Canonical ChIPseq analysis workflow

Environment setup and ChIPseq project management

Quality assessment with FastQC

Alignment

Filtering

Peak calling

Your capstone project

By the end of this course you will

Be able to manage the working environment of your ChIPseq projects

You’ll be given a FREE access to ChIPseq-analysis-ready Docker containers

You’ll be given a FREE access to a whole chapter from a review paper worth $31.50

Be able to evaluate the quality of ChIPseq sequencing data using FastQC

Be able to perform alignment of reads to the genome using Bowtie2

Be able to filter aligned reads based on criteria of your own choosing

Be able to run MACS3 peak calling algorithm

Understand the full ChIPseq analysis workflow

Be able to use your epigenetic knowledge in order to aid interpretation of ChIP data

Be able to use the principles of functional studies and epigenetic lab techniques

Be able to explain the relationship between epigenetics and environment

Who this course is for
STEM graduates that aspire to become bioinformaticians specialising in the study of epigenetic control of gene expression and ChIPseq
Curious learners that want to gauge the subject of epigenomics and ChIPseq
Individuals seeking an opportunity for a hands on ChIPseq analysis experience
Individuals wanting to learn about epigenomics and epigenetics
Doctoral or post-doctoral researchers who need to expand their ChIPseq experience
Students who want to start a higher degree (Bachelor, Masters or PhD) project related to epigenetics and regulation of gene expression