Whole-Transcriptome RNA-Seq Data Analysis using Linux

Whole-Transcriptome RNA-Seq Data Analysis using Linux, available at $39.99, has an average rating of 3.1, with 7 lectures, based on 15 reviews, and has 109 subscribers.

You will learn about Differential Gene Expression Analysis Linux CLI Bash Scripting RNA-Seq Data Analysis NGS databases and used software in the pipeline This course is ideal for individuals who are University students/Freelancers working in medicine research, biotech & bioinformatics industry It is particularly useful for University students/Freelancers working in medicine research, biotech & bioinformatics industry.

Enroll now: Whole-Transcriptome RNA-Seq Data Analysis using Linux

Summary

Title: Whole-Transcriptome RNA-Seq Data Analysis using Linux

Price: $39.99

Average Rating: 3.1

Number of Lectures: 7

Number of Published Lectures: 7

Number of Curriculum Items: 7

Number of Published Curriculum Objects: 7

Original Price: $59.99

Quality Status: approved

Status: Live

What You Will Learn

Differential Gene Expression Analysis
Linux CLI Bash Scripting
RNA-Seq Data Analysis
NGS databases and used software in the pipeline

Who Should Attend

University students/Freelancers working in medicine research, biotech & bioinformatics industry

Target Audiences

University students/Freelancers working in medicine research, biotech & bioinformatics industry

This course will develop your bioinformatics skills that how to measure the up-regulated and down-regulated genes called differential gene expression using whole-transcriptome RNA-Seq dataset. This course is the the best suited to the students working on the boundaries of molecular genetics and bioinformatics. Students will come to know that why life sciences researchers are direly needed computation skills, on which type of biological data computation will apply, how Linux/R compute multi-omics problems, and how bioinformatics and computational biology is evolving to circumvent modern genetics problems.

In the time to come, biologists will not restrain to the wet labs only, so let’s come and transform yourselves with bioinformatics data science tools for analysis, visualization, and inferring the crux from your big transcriptomic data. So, this is the right stop, that will help you to overwhelm your transition from wet to dry lab and facilitate you to analyze the whole-transcriptome NGS data using bash scripting in Linux command line interface along with R statistical packages for visualizing resultant files in the form of comprehensive heatmap graphs.

No doubt there are cloud computing and commercial high performance computing cluster facilities available in the world but this course will provide you the insight that how to analyze multi-omics data with limited financial resources without having much expertise in programming and knowhow to computer languages.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Input files & trimming with Trimmomatic (Step 1)

Lecture 2: Quality checks with FastQC (Step 2)

Lecture 3: Indexing and quantification with Salmon (Step 3)

Lecture 4: Making matrices with Trinity (Step 4)

Lecture 5: Counting number of expressed transcripts (Step 5)

Lecture 6: Differentially expressed genes pairwise comparison (Step 6)

Lecture 7: Extracting & clustering differentially expressed transcripts (Step 7)

Instructors

Dr. Rashid Saif
Founder & Director-Research/Diagnostics @ Decode Genomics

Rating Distribution

1 stars: 2 votes
2 stars: 1 votes
3 stars: 4 votes
4 stars: 6 votes
5 stars: 2 votes

Frequently Asked Questions

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