Name: Command-line Based Practical RNA-Seq Data Analysis With Linux & R
Price: 149.99 USD
Availability: InStock
Rating: 5 (1 reviews)

57 Video lessons

7h Total content

≈4 hrs/week Master it in ~2 weeks

About Course

Learning path

Become an RNA-Seq analyst

1 Command-line Based Practical RNA-Seq Data Analysis With Linux & R · you're here
2 End-to-End RNA-Seq Data Analysis With Python-Based Pipeline
3 Hands-on: Single-Cell RNA-Sequencing Data Analysis Using Command-Line and R [Complete Training]
4 Hands-on: Single-Cell RNA-Sequencing Data Analysis Using Python [Complete Training]

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Tools & technologies you'll use

R
Linux
Bash / CLI
DESeq2
edgeR

Course Content

In-Depth Introduction to RNA-Seq

In-depth Introduction to RNA-Seq Data Analysis, Linux Computing and R

44:08
Introduction to Linux for Bioinformatics

22:32
Introduction to ArrayExpress – Getting Started With MicroArray Analysis

09:56

Genomic Databases for Raw Data

BioProject

06:40
BioSystems

04:16
BioSample

02:56
Introduction to Gene Expression Omnibus Database

09:16
Gene Expression Omnibus – Platforms

05:42
Gene Expression Omnibus – Samples

04:16
Gene Expression Omnibus – Series

04:01
Gene Expression Omnibus – Datasets

04:45
Gene Expression Omnibus – Profiles – How to Search for Gene Expression Profiles

05:55
NCBI Genomes & NCBI Assembly

36:14
Genome Reference Consortium

07:48
Introducton to Phytozome

09:39
Download an Entire Plant Genome & Proteome

26:41
Introduction to UCSC Genome Browser

13:40
How to retrieve an entire genome & Retrieval of SARS-CoV-2 Viral Genome

09:41
Introduction to ENSEMBL

07:50
Genome Assembly Retrieval and Analysis

10:24

File Formats

Introduction to Linux for RNA-Seq

Introduction to Linux for Bioinformatics

22:32
PWD – Print Working Directory

01:26
MKDIR – Making Directories

08:13
CD – Changing Directories

05:03
MV – Moving Files, Directories and Data

05:11
RM – Deleting Files and Directories

01:24
Which & Whereis – Find Programs You Installed

03:43
Find – Finding User Created Files

03:39
LS – Listing Files and Directories on Linux

06:46
Cat – Visualization and Inspection of Text Data

03:56
Head – Reading Specified Number of Lines from Top

03:50
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

RNA-Seq Data Analysis Pipeline (Theoretical & Practical)

How to Retreive Raw Reads for RNA-Seq Data Analysis

03:26
Retrieval of Data Required for this Course

08:45
In-depth Theory: Quality Control

19:37
Practical: Preprocess Raw Reads Using FASTQC, FASTP, Trimmomatic & Cutadapt

31:54
In-depth Theory: Mapping & Transcriptome Assembly

48:22
Practical: Mapping Preprocessed Reads Against a Reference Genome Using HISAT2, TOPHAT2, BOWTIE2, STAR

31:51
Practical: Transcriptome Assembly Using StringTie

54:31
Mapping Visualization & Evaluation

36:37
In-depth Theory: Gene Quantification, Expression Estimation & Differential Gene Expression

18:28
In-depth Theory: DeSeq2, Ballgown, edgeR

32:22
Practical: Differential Gene Expression Analysis Using Ballgown, edgeR, DESEQ2 in R

34:39
Theory: Functinal Enrichment Analysis of the DEGs

18:39
Practial: Gene Ontology Analysis

28:02
Practical: Pathways Analysis Using KEGG, PANTHER, Reactome

12:41
Practical: Protein-Protein Interaction Using STRING

13:17

Evaluation

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Student Ratings & Reviews

5.0

Total 1 Rating

1 Rating

0 Rating

Muhammad Abdullah

2 years ago

The course provides a detailed introduction to RNA-seq techniques with hands-on practice. Definitely recommended!

About Course

Become an RNA-Seq analyst

Get the free syllabus & course updates

What Will You Learn?

Tools & technologies you'll use

Course Content

In-Depth Introduction to RNA-Seq

In-depth Introduction to RNA-Seq Data Analysis, Linux Computing and R

Introduction to Linux for Bioinformatics

Introduction to ArrayExpress – Getting Started With MicroArray Analysis

Genomic Databases for Raw Data

BioProject

BioSystems

BioSample

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

Introducton to Phytozome

Download an Entire Plant Genome & Proteome

Introduction to UCSC Genome Browser

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

Introduction to ENSEMBL

Genome Assembly Retrieval and Analysis

File Formats

BED

GTF/GFF

SAM

FASTQ

Introduction to Linux for RNA-Seq

Introduction to Linux for Bioinformatics

PWD – Print Working Directory

MKDIR – Making Directories

CD – Changing Directories

MV – Moving Files, Directories and Data

RM – Deleting Files and Directories

Which & Whereis – Find Programs You Installed

Find – Finding User Created Files

LS – Listing Files and Directories on Linux

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

RNA-Seq Data Analysis Pipeline (Theoretical & Practical)

How to Retreive Raw Reads for RNA-Seq Data Analysis

Retrieval of Data Required for this Course

In-depth Theory: Quality Control

Practical: Preprocess Raw Reads Using FASTQC, FASTP, Trimmomatic & Cutadapt

In-depth Theory: Mapping & Transcriptome Assembly

Practical: Mapping Preprocessed Reads Against a Reference Genome Using HISAT2, TOPHAT2, BOWTIE2, STAR

Practical: Transcriptome Assembly Using StringTie

Mapping Visualization & Evaluation

In-depth Theory: Gene Quantification, Expression Estimation & Differential Gene Expression

In-depth Theory: DeSeq2, Ballgown, edgeR

Practical: Differential Gene Expression Analysis Using Ballgown, edgeR, DESEQ2 in R

Theory: Functinal Enrichment Analysis of the DEGs

Practial: Gene Ontology Analysis

Practical: Pathways Analysis Using KEGG, PANTHER, Reactome

Practical: Protein-Protein Interaction Using STRING

Evaluation

MCQ’s

Earn a certificate

Student Ratings & Reviews

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