Single Cell ATAC-seq (scATAC-seq )

scATAC-seq (Single-cell Assay for Transposase-Accessible Chromatin using sequencing) is a genomics technique that profiles chromatin accessibility at the single-cell level. This method allows researchers to identify regulatory elements (like enhancers and promoters) that are active in individual cells, providing insight into gene regulation and cellular heterogeneity.

scATAC-seq detects regions of open chromatin, where DNA is not tightly wound around nucleosomes and is accessible to regulatory proteins. These regions are typically associated with:
Active gene promoters
Enhancers
Transcription factor binding sites

Why Use scATAC-seq?
Cell type identification based on chromatin accessibility
Study of epigenetic regulation in development and disease
Integration with scRNA-seq for combined transcriptomic and epigenomic profiling
Discovery of cell-specific regulatory elements

IMG
You will learn how gene expression is controlled at the chromatin level. It shows which regulatory elements and transcription factors are active in different cell types or during development, offering insight into cell identity, differentiation, and disease mechanisms.

👉 Enroll now and take the first step toward a future in data-driven biology and beyond.

## 10% Discount if you register before 15th October, 2025. Hurry up!!

  • RNASeq [R]
  • RNASeq [D]
  • scRNA-Seq
  • lncRNA-Seq
  • miRNA-Seq
  • PSI-Seq
  • ChipSeq
  • ATAC-Seq
  • scATA-Seq
  • Spatial Transcriptome
  • DNASeq
  • MethylSeq
  • Whole Genome de novo Assembly
  • Targeted metagenomics
  • Whole Genome Metagenomics
  • Metatranscriptomics
  • RAD-Seq
  • SNAP-ChIP

Course Information
Course Single Cell ATAC-seq Data Analysis
Duration online 7 Days Training [ 2 Hours Daily [ Monday To Friday ] ]

Slots

Our working Time is 9:00 AM to 6:00 PM Indian Time Available slots - 9:00 AM to 11:00 AM / 11:00 AM to 1:00 PM / 2:00 PM to 4:00 PM / 4:00 PM to 6:00 PM
For training slots after 6 PM or before 9 am as well as weekends training kindly mention during registration accordingly it will be scheduled.

Mode

👉 For online training candidate have to install ZOOM (with remote control on candidate system which makes 100% interactive)
👉 Run time video recording candidate can make as well as pdf manual will be provided for future reference.
👉 All our training is 100% practical and 100% industrial and 100% interactive which provides same as offline learning.
👉 For doubt clear there will be extra support will be provided based on the requirement.
👉 Certificate will be provided
Sequencing Platform genome10x
Raw data Candidate can include maximum 4 datasets of their own during training. Publication standards figures and tables will be generated.
Training Fees
Module-NGS Single Cell ATAC-seq Data Analysis
    📘 Introduction to scATAC-seq
    - What is scATAC-seq and how it works
    - Comparison with bulk ATAC-seq and scRNA-seq
    - Workflow and Understanding Algorithm for scATAC-seq

    📘 Linux Basics & Environment Setup
    - Linux Command Line Basics
    - Installing Tools (FastQC, Bowtie2, Cellranger, R, MACS2, etc.)
    - Using Conda and Shell Scripting

    📘 Data Preprocessing
    - Overview of sequencing formats (FASTQ, SAM, BAM, etc.)
    - Cell/nuclei quality filtering and barcode selection
    - TSS enrichment, fragment count thresholds

    📘 Peak Calling and Fragment Matrix Construction
    - Peak calling
    - Constructing peak-cell and bin-cell matrices
    - Generation of fragment files and accessibility matrices

    📘 Dimensionality Reduction and Clustering
    - TF-IDF normalization or latent semantic indexing
    - UMAP/t-SNE embedding for visualization
    - Clustering cells based on chromatin accessibility profiles

    📘 Transcription Factor Motif Analysis
    - Motif enrichment in accessible peaks
    - Inferring transcription factor (TF) activity
    - Linking TF activity to cell types or conditions

    📘 Gene Score Calculation
    - Estimating gene activity from nearby accessible regions
    - Visualizing gene scores in dimensionality-reduced space
    - Heatmaps of accessibility per cell cluster

    📘 Pseudotime and Trajectory Inference
    - Inferring developmental trajectories
    - Analyzing dynamic changes in accessibility over pseudotime
    - Mapping lineage progression (e.g., stem cell → mature state)

    📘 Visualization and Interpretation
    - Peak and motif heatmaps
    - Coverage tracks (e.g., IGV browser)
    - UMAP plots of clusters, trajectories, or TF activity

    📘 Biological Interpretation and Reporting
    - Identifying cell-type–specific regulatory elements
    - Inferring gene regulatory networks
    - Reporting reproducible workflows using R

Preparation

- scATAC-seq : https://en.wikipedia.org/wiki/ATAC-seq
- NCBI : https://pmc.ncbi.nlm.nih.gov/articles/PMC7910485/

Instructor

Industry Experienced

Target Audiance

This course is designed for graduate students, postdoctoral researchers, and professionals working in the fields of conservation biology, evolutionary genomics, and population genetics or any life sciences who are interested in applying genomic tools to real-world conservation challenges.

Contact

Please write us at info@arraygen.com or call or whatsapp us on mobile +91-9673625446 if you need any clarification or for any custom training based on candidate reference paper or candidate own content/tools.

Course Information
Course Single Cell ATAC-seq Data Analysis
Duration online 15 Days Training [ 2 Hours Daily [ Monday To Friday ] ]

Slots

Our working Time is 9:00 AM to 6:00 PM Indian Time Available slots - 9:00 AM to 11:00 AM / 11:00 AM to 1:00 PM / 2:00 PM to 4:00 PM / 4:00 PM to 6:00 PM
For training slots after 6 PM or before 9 am as well as weekends training kindly mention during registration accordingly it will be scheduled.

Mode

👉 For online training candidate have to install ZOOM (with remote control on candidate system which makes 100% interactive)
👉 Run time video recording candidate can make as well as pdf manual will be provided for future reference.
👉 All our training is 100% practical and 100% industrial and 100% interactive which provides same as offline learning.
👉 For doubt clear there will be extra support will be provided based on the requirement.
👉 Certificate will be provided
Sequencing Platform illumina,genome10x,Pacbio,ONT
Raw data Candidate can include maximum 4 datasets of their own during training. Publication standards figures and tables will be generated.
Training Fees
Module-I Advanced Bioinformatics & basic programming
Topics
    📘 Introduction to Bioinformatics
    - Overview of bioinformatics and its applications
    - Key concepts in computational biology
    - Role of bioinformatics in genomics, transcriptomics, and proteomics

    📘 Understanding NGS and Genomics Bioinformatics
    - Basics of Next-Generation Sequencing (NGS)
    - Types of NGS data (RNA-seq, WGS, WES)
    - Overview of NGS data formats: FASTQ, BAM, VCF
    - Introduction to pipelines and tools for NGS data analysis

    📘 Databases & Data Retrieval (NCBI and UCSC)
    - Learning how to retrieve biologically correct data
    - Performing complete batch retrieval (e.g., whole exome)
    - NCBI: understanding gene-level data retrieval
    - UCSC: handling large-scale data retrieval
    - UCSC Genome Browser and Table Browser usage
    - Batch Coordinate Retrieval and Genomic Data downloads
    - GFF/GTF gene annotation formats and how to retrieve them
    - Using BLAT for sequence-based search and alignment

    📘 Gene Prediction and Functional Annotation
    - Gene prediction approaches and tools
    - Functional annotation using Gene Ontology (GO)
    - Pathway analysis using KEGG, Reactome
    - Interpreting gene sets and biological relevance

    📘 Standalone/Offline BLAST for Large-Scale Genomic Data
    - Installing and setting up standalone BLAST
    - Running local BLAST for batch sequence alignment
    - Applications in genome-wide homology searches
    - Custom BLAST databases and performance optimization

    📘 PCR Primer Designing and Specificity Check
    - Designing accurate primers for PCR amplification
    - Tools: Primer3, NCBI Primer-BLAST
    - Checking primer specificity using genome-wide BLAST
    - Avoiding non-target amplification through design best practices

    📘 Understanding Python Programming
    - Introduction to Python for bioinformatics
    - Scripting basics: variables, loops, functions
    - Libraries like Biopython, pandas for biological data handling
    - Automating genomic workflows with Python scripts
AND
Module-II Next Generation Sequencing (NGS) - Single Cell ATAC-seq Data Analysis
Topics
    📘 Introduction to scATAC-seq
    - What is scATAC-seq and how it works
    - Comparison with bulk ATAC-seq and scRNA-seq
    - Workflow and Understanding Algorithm for scATAC-seq

    📘 Linux Basics & Environment Setup
    - Linux Command Line Basics
    - Installing Tools (FastQC, Bowtie2, Cellranger, R, MACS2, etc.)
    - Using Conda and Shell Scripting

    📘 Data Preprocessing
    - Overview of sequencing formats (FASTQ, SAM, BAM, etc.)
    - Cell/nuclei quality filtering and barcode selection
    - TSS enrichment, fragment count thresholds

    📘 Peak Calling and Fragment Matrix Construction
    - Peak calling
    - Constructing peak-cell and bin-cell matrices
    - Generation of fragment files and accessibility matrices

    📘 Dimensionality Reduction and Clustering
    - TF-IDF normalization or latent semantic indexing
    - UMAP/t-SNE embedding for visualization
    - Clustering cells based on chromatin accessibility profiles

    📘 Transcription Factor Motif Analysis
    - Motif enrichment in accessible peaks
    - Inferring transcription factor (TF) activity
    - Linking TF activity to cell types or conditions

    📘 Gene Score Calculation
    - Estimating gene activity from nearby accessible regions
    - Visualizing gene scores in dimensionality-reduced space
    - Heatmaps of accessibility per cell cluster

    📘 Pseudotime and Trajectory Inference
    - Inferring developmental trajectories
    - Analyzing dynamic changes in accessibility over pseudotime
    - Mapping lineage progression (e.g., stem cell → mature state)

    📘 Visualization and Interpretation
    - Peak and motif heatmaps
    - Coverage tracks (e.g., IGV browser)
    - UMAP plots of clusters, trajectories, or TF activity

    📘 Biological Interpretation and Reporting
    - Identifying cell-type–specific regulatory elements
    - Inferring gene regulatory networks
    - Reporting reproducible workflows using R

Preparation

- scATAC-seq : https://en.wikipedia.org/wiki/ATAC-seq
- NCBI : https://pmc.ncbi.nlm.nih.gov/articles/PMC7910485/

Instructor

Industry Experienced

Target Audiance

This course is designed for graduate students, postdoctoral researchers, and professionals working in the fields of conservation biology, evolutionary genomics, and population genetics or any life sciences who are interested in applying genomic tools to real-world conservation challenges.

Contact

Please write us at info@arraygen.com or call or whatsapp us on mobile +91-9673625446 if you need any clarification or for offline training or for any custom training based on candidate reference paper or candidate own content/tools.