Mô tả

Welcome to our third course  "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 (NGS). 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 (NGS) 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. This is not limited to RNA-Seq but to all type of NGS data.

  • 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.

Bạn sẽ học được gì

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

Yêu cầu

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

Nội dung khoá học

8 sections

Course Introduction & Disclaimer

1 lectures
Course Introduction, Disclaimer & Important Message to Our Learners
01:53

Module-1: Basics of Molecular Biology (Optional)

6 lectures
What is DNA?
02:10
Where is DNA Located in Our Cells?
00:56
What is Role of DNA?
03:10
Difference Between Eukaryotic and Prokaryotic Genes
06:48
What is Inside of Gene (Coding Regions of DNA)?
05:11
Post Transcriptional Modifications
02:06

Introduction of RNA-Seq

4 lectures
Why There is Need of RNA-Seq Analysis
02:27
Basic Workflow of RNA-Seq Analysis
02:11
Next Generation Sequencing Workflow
03:58
Basic File Obtained During RNA-Seq Analysis
06:00

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

19 lectures
Basic Workflow of RNA-Seq Data Analysis
01:49
Installation of Linux in Your Windows (WSL)
05:16
Installation of Necessary Programs In Linux Environment (Part-1)
01:06
Installation of Necessary Programs In Linux Environment (Part-2)
04:21
Installation of SAM Tools in Linux (Part-3)
01:46
Downloading of Timmomatic Tool
03:14
Quality Check of the Reads with FASTQC (Part-1)
04:10
Quality Check of the Reads with FASTQC (Part-2)
09:06
Assignment 1: FASTQC Analysis of test_udemy.fastq File
4 questions
Use of Timmomatic Tool to Remove Poor Quality Reads
07:00
Assignment-2: Trimming of Poor Quality Reads
2 questions
Use of HISAT2 for Alignment of Reads with Reference Genome
05:58
Assignment-3: Performing Alignment of Reads with Reference Genome
3 questions
Downloading of GTF File to Build the Feature Count Matrix
03:14
Building of Feature Count Matrix With Subread Tool
05:33
Assignment-4: Building Feature Count Matrix
2 questions
How to Process Multipipe FastQ Files Using Bash Scripts
13:08
Experimental Design of Airway Cell Line Study That will Use In DEG Analysis
04:39
Test Your Skill With Large FASTQ File (Optional)
1 question

Basic Concepts of R and R-Studio

7 lectures
Introduction of the Section
01:06
Installation of R and R-Studio
06:00
Setting Working Directory in R-Studio
02:23
Basic Data Types Used in R
03:19
Creating a Variable
02:50
What is Package & Function in R?
05:55
Brief Introduction of Bioconductor
05:00

Differential Expression of Gene Analysis in R Using DESeq2 Package

21 lectures
Installation of DESeq2 in R-Studio For DEGs Analysis
02:31
What is CSV format & Saving MetaData File in CSV format
02:42
Uploading of Feature Count Matrix and Meta Data in R-Studio
08:09
Assignment-5: Uploading Feature Count Matrix and Meta Data in R-Studio
4 questions
Basic Quality Check of Feature Count Matrix and Meta Data
04:07
Assignment-6: Basic Quality Check of Data
2 questions
Use of DESeq2 for DEG Analysis (Part-1)
03:56
Assignment-7: Creating Design for Differentially Expressed Genes
1 question
DESeq2: Concept of Leaky Expression Part-2)
03:32
DESEq2: Removing Low Counts Reads Genes (Part-3)
03:39
Assignment-8: Dropping Rows with Low Count
2 questions
DESeq2: Use of DESeq2 Function for DEG Analysis (Part-3)
07:32
Assignment-9: Use of DESeq Function
3 questions
What is Size Factor Estimation in DESEq2 ?
05:52
What is dispersion Estimation in DESeq2?
02:35
Hypothesis testing in DESeq2 for DEG Analysis
03:57
Concept of P-value and P-Adjusted values
03:26
Getting Differentially Expressed Gene at Different Alpha Value
04:29
Assignment-10: Getting DEGs at 0.05 Alpha Value
2 questions
Converting Gene IDs to Gene Name
10:06
Assignment-11: Converting Genes IDs to Gene Name
1 question

Quality Checking of RNA-Seq Data

8 lectures
Basic Quality Check Parameters
00:40
Basic Concepts of PCA Plot
04:49
Building PCA Plot of RNA-Seq Data
05:01
Assignment-12: Generation of PCA Plot
2 questions
Size Factor Estimation and Its Calculation
02:05
Assignment-13: Estimating Size Factor
1 question
Dispersion Estimates and Building of Dispresion Plot
02:59
Assignment-14: Building Dispersion Plot
2 questions

Analysis of Gene Expression Data

14 lectures
Basic Understanding of Tidyverse & ggplo2
01:41
Installation of Tidyverse & ggplot2 and Sample Dataset
04:09
Basic Functionality of Tidyverse Functions; Filter, Arrange, and Mutate
11:23
Basic Functionality of ggplot2 to Build the Plots
04:39
Building MA Plot
03:20
Assignment-15: Building MA Plot for DEGs
1 question
Getting Idea About Best Genes
04:39
Assignment-16: Extraction of top 30 Best Genes
3 questions
Building Volcano Plot-Part1
01:08
Building Volcano Plot -Part2
08:45
Assignment-17: Volcano Plot of Data
3 questions
Building HeatMap of DEGs
13:52
Assignment-18: HeatMap of Best 30 DEGs
2 questions
Simple Gene Ontology and Pathway Analysis of Genes
11:03

Đánh giá của học viên

Chưa có đánh giá
Course Rating
5
0%
4
0%
3
0%
2
0%
1
0%

Bình luận khách hàng

Viết Bình Luận

Bạn đánh giá khoá học này thế nào?

image

Đăng ký get khoá học Udemy - Unica - Gitiho giá chỉ 50k!

Get khoá học giá rẻ ngay trước khi bị fix.