Hands-on ATAC-Seq Data Analysis for Identification of Chromatin Accessibility Using Linux & R

Course Content

In-depth Introduction to ATAC-Seq Data Analysis

In-depth Introduction to ATAC-Seq Data Analysis and Its Biology (Chromatin Accessibility, Nucleosomes, Histones)

59:27
Selection and Retrieval of Raw ATAC-Seq Reads

20:55
What are Raw Reads & What is a FASTQ File
Introduction to Linux for ATAC-Seq Analysis

22:32

Hands-on ATAC-Seq Data Analysis

In-depth Theory: Quality Control

19:37
Hands-on: Preprocess Raw Reads Using FASTQC, FASTP, Trimmomatic & Cutadapt

27:29
In-depth Theory: Mapping (Alignment of Raw Reads)
Hands-on: Mapping Preprocessed Reads Against a Reference Genome Using BOWTIE2, BWA-MEM
Hands-on: Deduplication and Post-Alignment Processing
In-depth Theory: Read Counts & Peak Calling (Chromatin Accessibility Identification)
In-depth Theory: MACS2 & HOMER
Hands-on: Peak Calling Using MACS
Hands-on: Differential Peak Calling Using HOMER
Theory: Downstream Functional Enrichment Analysis

18:39
Hands-on: Gene Ontology Analysis Using topGO & enrichR

14:21
Hands-on: Pathways Analysis Using KEGG, PANTHER, Reactome

07:59

Additional Lectures

Introduction to ArrayExpress

09:55
Introduction to Gene Expression Omnibus Database

09:16
Gene Expression Omnibus – Platforms

05:33
Gene Expression Omnibus – Samples

04:15
Gene Expression Omnibus – Series

04:00
Gene Expression Omnibus – Datasets

04:44
Gene Expression Omnibus – Profiles – How to Search for Gene Expression Profiles

05:55
NCBI Genomes & NCBI Assembly

36:14
Genome Reference Consortium

07:48
Download an Entire Plant Genome & Proteome

26:41
How to retrieve an entire genome & Retrieval of SARS-CoV-2 Viral Genome

09:40
Genome Assembly Retrieval and Analysis

10:23
BED

04:27
GTF/GFF

11:07
SAM

09:07
Introduction to Linux for Bioinformatics

22:32
PWD – Print Working Directory

01:26
CD – Changing Directories

05:03
MKDIR – Making Directories

08:13
MV – Moving Files, Directories and Data

05:11
Which & Whereis – Find Programs You Installed

03:43
RM – Deleting Files and Directories

01:23
Find – Finding User Created Files

03:38
LS – Listing Files and Directories on Linux

06:45
Piping and Redirection of Data

06:34
Cat – Visualization and Inspection of Text Data

03:55
Head – Reading Specified Number of Lines from Top

03:49
Tail- Reading Specified Number of Lines from Bottom

02:23
Touch – Modifying File Statistics and Creating Files

07:04
Stat – Statistics of File & Directories

02:43
Wget – Retrieval of Genome Assemblies

06:48
Curl – Retrieval of Bioinformatics Files

02:25
Vim – Create and Edit Text Files

05:59
Diff – Find Sequence Differences in Files

02:35
GZIP – Compress and Archive Files Efficiently

06:05
Tar – Create Archives of Genome Data

04:19
GUNZIP – Extract Compressed Content

02:14
Grep – Finding Uncharacterized Proteins in Human Genome

08:55
Cut – Subsetting Required Textual Data from Text Files

05:49
Sort – Sorting Data

04:23
Uniq – Finding Unique Data Items

10:33
WC – Statistics of the Data Within File

02:46
CP – Copying Files and Files Contents

03:43
Column – Proper Visualization of Delimited Datasets

04:38

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Student Ratings & Reviews

5.0

Total 1 Rating

1 Rating

0 Rating

Abdullah Al-Zahrani

2 weeks ago

I'd been trying to learn ATAC-seq on my own and was feeling pretty lost, but this course made everything click. The hands-on approach was super helpful for getting comfortable with the Linux and R steps. I finally feel confident enough to analyze my own data.

Course Content

In-depth Introduction to ATAC-Seq Data Analysis

In-depth Introduction to ATAC-Seq Data Analysis and Its Biology (Chromatin Accessibility, Nucleosomes, Histones)

Selection and Retrieval of Raw ATAC-Seq Reads

What are Raw Reads & What is a FASTQ File

Introduction to Linux for ATAC-Seq Analysis

Hands-on ATAC-Seq Data Analysis

In-depth Theory: Quality Control

Hands-on: Preprocess Raw Reads Using FASTQC, FASTP, Trimmomatic & Cutadapt

In-depth Theory: Mapping (Alignment of Raw Reads)

Hands-on: Mapping Preprocessed Reads Against a Reference Genome Using BOWTIE2, BWA-MEM

Hands-on: Deduplication and Post-Alignment Processing

In-depth Theory: Read Counts & Peak Calling (Chromatin Accessibility Identification)

In-depth Theory: MACS2 & HOMER

Hands-on: Peak Calling Using MACS

Hands-on: Differential Peak Calling Using HOMER

Theory: Downstream Functional Enrichment Analysis

Hands-on: Gene Ontology Analysis Using topGO & enrichR

Hands-on: Pathways Analysis Using KEGG, PANTHER, Reactome

Additional Lectures

Introduction to ArrayExpress

Introduction to Gene Expression Omnibus Database

Gene Expression Omnibus – Platforms

Gene Expression Omnibus – Samples

Gene Expression Omnibus – Series

Gene Expression Omnibus – Datasets

Gene Expression Omnibus – Profiles – How to Search for Gene Expression Profiles

NCBI Genomes & NCBI Assembly

Genome Reference Consortium

Download an Entire Plant Genome & Proteome

How to retrieve an entire genome & Retrieval of SARS-CoV-2 Viral Genome

Genome Assembly Retrieval and Analysis

BED

GTF/GFF

SAM

Introduction to Linux for Bioinformatics

PWD – Print Working Directory

CD – Changing Directories

MKDIR – Making Directories

MV – Moving Files, Directories and Data

Which & Whereis – Find Programs You Installed

RM – Deleting Files and Directories

Find – Finding User Created Files

LS – Listing Files and Directories on Linux

Piping and Redirection of Data

Cat – Visualization and Inspection of Text Data

Head – Reading Specified Number of Lines from Top

Tail- Reading Specified Number of Lines from Bottom

Touch – Modifying File Statistics and Creating Files

Stat – Statistics of File & Directories

Wget – Retrieval of Genome Assemblies

Curl – Retrieval of Bioinformatics Files

Vim – Create and Edit Text Files

Diff – Find Sequence Differences in Files

GZIP – Compress and Archive Files Efficiently

Tar – Create Archives of Genome Data

GUNZIP – Extract Compressed Content

Grep – Finding Uncharacterized Proteins in Human Genome

Cut – Subsetting Required Textual Data from Text Files

Sort – Sorting Data

Uniq – Finding Unique Data Items

WC – Statistics of the Data Within File

CP – Copying Files and Files Contents

Column – Proper Visualization of Delimited Datasets

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