Learn Ngs Variant Calling: A Hands-On Bioinformatics Course
Published 7/2025
Created by Rafiq Ur Rehman
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English | Duration: 20 Lectures ( 3h 24m ) | Size: 1.5 GB
Learn end-to-end variant calling using Linux and R: From Raw NGS data to variants with visualization and interpretation
What you'll learn
Understand the fundamentals of variant calling and its role in NGS data analysis.
Set up a Linux environment for bioinformatics using Windows or native systems.
Perform quality control and trimming of raw FASTQ sequencing data.
Align sequencing reads to a reference genome using industry-standard tools.
Use Samtools and FreeBayes to call SNPs and indels from aligned reads.
Filter and refine variant calls to ensure accuracy and reliability.
Visualize genomic variants using IGV (Integrative Genomics Viewer).
Analyze and interpret VCF files using R and essential bioinformatics packages.
Automate parts of the variant calling pipeline with shell scripting.
Gain hands-on experience with real NGS datasets and submit results as assignments.
Requirements
No prior programming or bioinformatics experience is required - this course is beginner-friendly.
A computer (Windows, macOS, or Linux) with at least 8GB RAM is recommended for smoother processing.
Stable internet connection for downloading tools and datasets.
Willingness to learn basic Linux commands (we'll cover them step-by-step).
Interest in genomics, DNA sequencing, or data analysis.
Description
Become a Variant Calling Pro Using Linux and R - No Prior Experience Needed!Unlock the secrets of the genome with hands-on training in variant calling! This course gives you practical skills to analyze next-generation sequencing (NGS) data using industry-standard tools like FreeBayes, Samtools, and R, all within a Linux environment. Whether you're a student, researcher, or clinician, this course empowers you to process FASTQ data, perform variant calling, visualize VCFs, and extract biological insights using open-source pipelines.What You'll Learn:Linux for Bioinformatics: Learn essential commands and file systems for data handling and tool usage.NGS Variant Calling Basics: Understand confidence, quality metrics, and key concepts in variant analysis.Pipeline Setup: Download datasets, prepare your analysis environment, and index genomes.Data Preprocessing: Run FastQC, trim reads, align with BWA, and prepare BAM files.Variant Calling with FreeBayes: Perform SNP and indel calling and filter low-quality variants.Visualization and Interpretation: View variants in IGV and interpret biological impact.R for Genomic Analysis: Set up R and use it to explore and visualize variant data.Assignments and Quizzes: Test your knowledge with assessments after each section.Who This Course Is For:Biology & Medical Students: Learn NGS data analysis without needing advanced programming.Researchers & Clinicians: Build reproducible pipelines for cancer genomics, rare diseases, and more.Bioinformatics Enthusiasts: Transition into genomics with a complete beginner-to-advanced course.Professionals in Biotech & Pharma: Strengthen your role in precision medicine and diagnostics.Course Features:Hands-on projects and real datasetsAssignments and quizzes after each sectionDownloadable scripts and guidesLifetime access and certificate of completionNo coding experience needed - just your interest in genomics and bioinformatics!
Who this course is for
Biology and medical students who want to gain hands-on skills in next-generation sequencing (NGS) and variant analysis.
Researchers and lab professionals looking to analyze genomic data independently without relying on a bioinformatics team.
Beginner bioinformaticians who want to build their first variant calling pipeline using Linux and R.
Healthcare and biotech professionals seeking to understand variant data for clinical genomics, diagnostics, or personalized medicine.
Educators and instructors who want a complete, ready-to-teach variant calling workflow for academic or training purposes.
Anyone curious about how DNA variants are discovered, filtered, visualized, and interpreted from raw sequencing data
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