Bioinformatic; Learn Bulk RNA-Seq Data Analysis From Scratch

Focused View

Muhammad Dujana

4:40:29

202 View

1. Course Introduction And Disclaimer

1. Course Introduction, Disclaimer And Important Message to Our Learners.mp4

01:53

2. Module-1 Basics of Molecular Biology (Optional)

1. What is DNA.mp4

02:10

2. Where is DNA Located in Our Cells.mp4

00:56

3. What is Role of DNA.mp4

03:10

4. Difference Between Eukaryotic and Prokaryotic Genes.mp4

06:48

5. What is Inside of Gene (Coding Regions of DNA).mp4

05:11

6. Post Transcriptional Modifications.mp4

02:06

3. Introduction of RNA-Seq

1. Why There is Need of RNA-Seq Analysis.mp4

02:27

2. Basic Workflow of RNA-Seq Analysis.mp4

02:11

3. Next Generation Sequencing Workflow.mp4

03:58

4. Basic File Obtained During RNA-Seq Analysis.mp4

06:00

4. Practical Demonstration of RNA-Seq Reads To Feature Count Matrix In Linux

1. Basic Workflow of RNA-Seq Data Analysis.mp4

01:49

2. Installation of Linux in Your Windows (WSL).mp4

05:16

3.1 Commands to Install Necessary Programs In Linux Environment.pdf

3. Installation of Necessary Programs In Linux Environment (Part-1).mp4

01:06

4. Installation of Necessary Programs In Linux Environment (Part-2).mp4

04:21

5. Installation of SAM Tools in Linux (Part-3).mp4

01:46

6. Downloading of Timmomatic Tool.mp4

03:14

7.1 Command to Perform FASTQC Analysis.txt

7. Quality Check of the Reads with FASTQC (Part-1).mp4

04:10

8.1 test udemy.zip

8. Quality Check of the Reads with FASTQC (Part-2).mp4

09:06

9. Assignment 1 FASTQC Analysis of test udemy.fastq File.html

10.1 Command to Perform Trimming Analysis.txt

10. Use of Timmomatic Tool to Remove Poor Quality Reads.mp4

07:00

11. Assignment-2 Trimming of Poor Quality Reads.html

12.1 Command to Perform Alignment Using HISAT2.txt

12. Use of HISAT2 for Alignment of Reads with Reference Genome.mp4

05:58

13. Assignment-3 Performing Alignment of Reads with Reference Genome.html

14. Downloading of GTF File to Build the Feature Count Matrix.mp4

03:14

15.1 Command to Build The Feature Count Matrix.txt

15. Building of Feature Count Matrix With Subread Tool.mp4

05:33

16. Assignment-4 Building Feature Count Matrix.html

17.1 script1.zip

17.2 script2.zip

17.3 script3.zip

17.4 script4.zip

17. How to Process Multipipe FastQ Files Using Bash Scripts.mp4

13:08

18. Experimental Design of Airway Cell Line Study That will Use In DEG Analysis.mp4

04:39

5. Basic Concepts of R and R-Studio

1. Introduction of the Section.mp4

01:06

2. Installation of R and R-Studio.mp4

06:00

3. Setting Working Directory in R-Studio.mp4

02:23

4. Basic Data Types Used in R.mp4

03:19

5. Creating a Variable.mp4

02:50

6. What is Package And Function in R.mp4

05:55

7.1 R-Code to Bioconductor and DESeq2 in R-Studio.txt

7. Brief Introduction of Bioconductor.mp4

05:00

6. Differential Expression of Gene Analysis in R Using DESeq2 Package

1. Installation of DESeq2 in R-Studio For DEGs Analysis.mp4

02:31

2. What is CSV format And Saving MetaData File in CSV format.mp4

02:42

3. Uploading of Feature Count Matrix and Meta Data in R-Studio.mp4

08:09

4. Assignment-5 Uploading Feature Count Matrix and Meta Data in R-Studio.html

5. Basic Quality Check of Feature Count Matrix and Meta Data.mp4

04:07

6. Assignment-6 Basic Quality Check of Data.html

7. Use of DESeq2 for DEG Analysis (Part-1).mp4

03:56

8. Assignment-7 Creating Design for Differentially Expressed Genes.html

9. DESeq2 Concept of Leaky Expression Part-2).mp4

03:32

10. DESEq2 Removing Low Counts Reads Genes (Part-3).mp4

03:39

11. Assignment-8 Dropping Rows with Low Count.html

12. DESeq2 Use of DESeq2 Function for DEG Analysis (Part-3).mp4

07:32

13. Assignment-9 Use of DESeq Function.html

14. What is Size Factor Estimation in DESEq2 .mp4

05:52

15. What is dispersion Estimation in DESeq2.mp4

02:35

16. Hypothesis testing in DESeq2 for DEG Analysis.mp4

03:57

17. Concept of P-value and P-Adjusted values.mp4

03:26

18. Getting Differentially Expressed Gene at Different Alpha Value.mp4

04:29

19. Assignment-10 Getting DEGs at 0.05 Alpha Value.html

20. Converting Gene IDs to Gene Name.mp4

10:06

21. Assignment-11 Converting Genes IDs to Gene Name.html

7. Quality Checking of RNA-Seq Data

1. Basic Quality Check Parameters.mp4

00:40

2. Basic Concepts of PCA Plot.mp4

04:49

3. Building PCA Plot of RNA-Seq Data.mp4

05:01

4. Assignment-12 Generation of PCA Plot.html

5. Size Factor Estimation and Its Calculation.mp4

02:05

6. Assignment-13 Estimating Size Factor.html

7. Dispersion Estimates and Building of Dispresion Plot.mp4

02:59

8. Assignment-14 Building Dispersion Plot.html

8. Analysis of Gene Expression Data

1. Basic Understanding of Tidyverse And ggplo2.mp4

01:41

2. Installation of Tidyverse And ggplot2 and Sample Dataset.mp4

04:09

3. Basic Functionality of Tidyverse Functions; Filter, Arrange, and Mutate.mp4

11:23

4. Basic Functionality of ggplot2 to Build the Plots.mp4

04:39

5. Building MA Plot.mp4

03:20

6. Assignment-15 Building MA Plot for DEGs.html

7. Getting Idea About Best Genes.mp4

04:39

8. Assignment-16 Extraction of top 30 Best Genes.html

9. Building Volcano Plot-Part1.mp4

01:08

10. Building Volcano Plot -Part2.mp4

08:45

11. Assignment-17 Volcano Plot of Data.html

12. Building HeatMap of DEGs.mp4

13:52

13. Assignment-18 HeatMap of Best 30 DEGs.html

14. Simple Gene Ontology and Pathway Analysis of Genes.mp4

11:03

Description

Best Bioinformatics course for Students, Academia and Industry Professionals to learn RNA-Seq Data Analysis From Zero

What You'll Learn?

You will be able to understand basic molecular biology; Central Dogma
You will be able to Understand RNA-Seq Experimentation
You will be able to analyze FASTQ files In Linux Environment
You will be able to understand different file formats like SAM, BAM, FASTQ, GTF, etc
You will be able to Use R and R-Studio
You will able to perform Differential analysis of Genes using DESeq2 Package
You will able to generate Different type of visualization to present your Data like PCA, MA, HeatMap and Volcano Plots
You will be able to perform GO and Pathways Analysis

Who is this for?

Molecular Biologist

Biological Data Analyst

Bioinformatics

What You Need to Know?

Although we try to design this course for beginners but it will be great if you will have basic molecular biology understanding

More details

Description
Welcome to our third courseÂ "Learn Bulk RNA-Seq Data Analysis From Scratch," a comprehensive online course designed to equip you with the skills and knowledge needed to harness the power of RNA-Seq data analysis. In this course, we delve into the captivating world of genomics and bioinformatics, empowering you to explore the intricacies of gene expression and unravel the hidden mysteries within the transcriptome.
With the advent of high-throughput sequencing technologies, RNA-Seq has revolutionized the field of molecular biology, allowing us to decipher the intricate dance of gene expression in ways never before possible. This course serves as your gateway to understanding and interpreting the wealth of information contained within RNA-Seq data, transforming it into valuable insights and meaningful discoveries.
Bioinformatics, the multidisciplinary field at the intersection of biology and computer science, plays a pivotal role in deciphering complex biological systems. In this course, we emphasize the importance of bioinformatics methodologies and tools, which form the foundation of modern genomics research. By mastering these techniques, you will gain a competitive edge in the rapidly evolving field of life sciences.
Course Highlights:
Comprehensive Training: From raw FASTQ files to in-depth analysis, this course provides a step-by-step guide to RNA-Seq data analysis, covering the entire workflow with clarity and precision.
Linux and R-Studio: Get hands-on experience with two essential tools in bioinformatics. Learn to navigate the Linux command line environment and utilize R-Studio for data processing, visualization, and statistical analysis.
Theory and Practice: We strike a perfect balance between theoretical concepts and practical application. Understand the underlying principles of RNA-Seq analysis while honing your skills through hands-on exercises and real-world examples.
Cutting-edge Techniques: Stay at the forefront of genomics research by exploring the latest advancements in RNA-Seq analysis techniques, such as differential gene expression analysis, functional enrichment analysis, and pathway analysis.
Expert Guidance: Benefit from the expertise of experienced instructors who have a deep understanding of both bioinformatics and molecular biology. Their guidance and insights will ensure a rewarding learning experience.
Interactive Learning: Engage in interactive assignments, and discussions to reinforce your understanding and interact with a vibrant community of fellow learners, fostering knowledge exchange.
Embark on this transformative journey into the world of RNA-Seq analysis and bioinformatics. Unleash the power of genomics to uncover hidden biological insights and make significant contributions to scientific research. Enroll in "Bioinformatics: Learn Bulk RNA-Seq Data Analysis From Scratch" today and equip yourself with the essential skills needed to excel in the dynamic field of bioinformatics. We assure you that all of the tools that will be used in this course will be Freely available and closely related to the course material. For most of them you do not need to sign up.
Who this course is for:
Molecular Biologist
Biological Data Analyst
Bioinformatics

User Reviews

Rating

average 0

Total votes0

Focused display

Hi, I am Dr Muhammad Dujana. I am a certified instructor and have more than 10-year experience in Bioinformatics and data science. I love to teach and develop new courses. I am currently, teaching in the Department of Biochemistry and Biotechnology at the university level. During my PhD, I have been at the National University of Singapore (NUS) for my research in the Department of Biological Sciences. Teaching is not a profession for me, it's my passion.

Udemy

View courses Udemy

Students take courses primarily to improve job-related skills.Some courses generate credit toward technical certification. Udemy has made a special effort to attract corporate trainers seeking to create coursework for employees of their company.