BIO HELP LEARNING COURSE

ATAC-Seq Data Analysis Training

Learn ATAC-seq analysis step by step: QC, alignment, TSS enrichment, MACS3 peak calling, motif discovery and differential chromatin accessibility.

Genomics

◉ Beginner to Advanced◷ 15 Hours / Live▣ Yes — Certificate of Completion

Course Information

Everything you need to know before enrolling.

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Live online classes
Group & college batches
Certificate on completion

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▤ Overview ☷ Curriculum ♙ Instructor ☆ Reviews ▣ FAQs

▤

About This Course

ATAC-seq maps the open, accessible regions of the genome where gene regulation happens. This 15-day training teaches you how to analyse ATAC-seq data correctly, from raw reads to biological interpretation.

You learn read QC and trimming, Bowtie2 alignment, ATAC-specific quality metrics such as fragment size and TSS enrichment, MACS3 peak calling, peak annotation, HOMER motif analysis, deepTools and IGV visualization, and differential accessibility, finishing with a complete project.

Who this course is for

Students and researchers in epigenetics, gene regulation and genomics
Lab scientists who generate ATAC-seq data and want to analyse it themselves
Learners with basic command-line knowledge

◎

What You’ll Learn

✓Understand the principles and applications of ATAC-Seq

✓Understand chromatin accessibility and regulatory genomics

✓Perform quality assessment of ATAC-Seq sequencing data

✓Perform read preprocessing and genome alignment

✓Process and evaluate ATAC-Seq BAM files

✓Perform peak calling to identify accessible chromatin regions

✓Analyze genomic distribution of ATAC-Seq peaks

✓Perform transcription factor motif analysis

✓Visualize accessibility signals using genome browsers

✓Interpret ATAC-Seq results in a biological context

⌘

Tools & Technologies

FastQCBowtie2SamtoolsMACS3deepToolsIGVHOMER

Course Curriculum

What you will learn, day by day

15 days 15 hours of training 60 topics Certificate on completion

- Chromatin structure and gene regulation
- How Tn5 transposase reveals open chromatin
- ATAC-seq vs. DNase-seq and MNase-seq
- Applications in development and disease
- Paired-end reads and FASTQ format
- Expected ATAC-seq read characteristics
- Downloading public datasets
- First look at read quality
- Running FastQC and MultiQC
- Nextera adapter trimming
- Quality filtering
- Comparing reports before and after trimming
- Downloading and indexing the reference genome
- Aligning paired-end reads with Bowtie2
- Alignment rates and what they mean
- Handling multi-mapped reads
- SAM/BAM format explained
- Sorting and indexing with Samtools
- Removing duplicates and mitochondrial reads
- Filtering by mapping quality
- Fragment size distribution and nucleosome patterns
- TSS enrichment score
- Fraction of reads in peaks (FRiP)
- Deciding whether a library passes QC
- How peak callers work
- Running MACS3 for ATAC-seq
- Key parameters and shifting reads
- narrowPeak output format
- Peak counts and widths
- Removing blacklist regions
- Reproducibility between replicates
- Building a consensus peak set
- Promoter, intron and intergenic peaks
- Nearest-gene assignment
- Peak distribution plots
- Linking peaks to candidate genes
- Transcription factor binding motifs
- De novo and known motif analysis with HOMER
- Interpreting motif enrichment
- Introduction to TF footprinting
- Creating bigWig coverage tracks
- Normalization options
- Heatmaps and profile plots around TSS
- Comparing samples visually
- Loading BAM, bigWig and peak files
- Exploring loci of interest
- Comparing conditions in tracks
- Exporting publication-quality snapshots
- Building a peak count matrix
- Statistical testing between conditions
- Volcano plots and MA plots
- Identifying condition-specific regions
- Gene ontology of genes near differential peaks
- Pathway enrichment
- Integration ideas with RNA-seq
- Building a biological story
- End-to-end analysis on a real dataset
- Quality, peaks, motifs and visualization
- Writing the results report
- Presentation and feedback

♙

Your Instructor

Bio Help Learning Educator

Educator | Mentor

Learn from experienced educators and practitioners through practical, career-focused bioinformatics training.

Frequently Asked Questions

10 answers about this course

What is ATAC-Seq?

ATAC-Seq is a sequencing-based method used to identify regions of open or accessible chromatin across the genome.

Who can join this ATAC-Seq training?

The course is suitable for biotechnology, bioinformatics, life science, genetics, genomics and related students, researchers and professionals.

Do I need prior ATAC-Seq experience?

No. The course begins with fundamental concepts and progressively moves toward practical data analysis.

Will this course include hands-on analysis?

Yes. The training focuses on practical ATAC-Seq analysis using sequencing datasets.

Which tools will I learn?

You will work with FastQC, Bowtie2, Samtools, MACS3, deepTools, IGV and HOMER.

Will I learn peak calling?

Yes. You will learn to identify accessible chromatin regions using peak-calling workflows.

Will I learn motif analysis?

Yes. The curriculum includes motif discovery and transcription factor analysis.

Will I learn differential accessibility analysis?

Yes. The course introduces comparison of chromatin accessibility between experimental conditions.

Will I receive a certificate?

Yes, participants can receive a certificate upon successful completion of the training.

Is there a project at the end of the course?

Yes. Day 15 includes a mini project covering the complete ATAC-Seq data analysis workflow.

Still have a question?Our team usually replies within one working day.

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