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Clinical Genomics and Genetic Variant Analysis Training
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Clinical Genomics and Genetic Variant Analysis Training

Detect genetic variants from NGS data, perform their annotation, and evaluate their clinical significance using bioinformatics tools.

12 WeeksBeginner
All courses
100+ graduates96% satisfaction4.8Overall Average Rating
Yasin Polat
Instructor
Yasin Polat
Bioinformatics and Computational Biology Specialist
01

Graduates of bioengineering, genetics, biology, and biotechnology

02

Researchers working or seeking to specialize in medical genetics and clinical genomics

What You'll Learn

Skills and knowledge you will gain from this course.

Effectively use biological and clinical genomics databases such as NCBI, Ensembl, UCSC, and ClinVar
Detect and annotate genetic variants using bioinformatics tools such as GATK, VEP, and ANNOVAR
Learn the principles of clinical classification of genetic variants according to ACMG/AMP criteria
Investigate and interpret genomic findings through databases such as ClinVar, gnomAD, and OMIM
Create scientific analysis reports by examining the relationships between genetic variants and diseases

Term selection

Choose the term that works for you.

Select term

Selected term

November

Monday and Wednesday
8:00 PM – 10:00 PM (TR Time)
Location & Access
Online

About This Course

A comprehensive look at what this course offers.

Master the analysis of genetic variants using powerful bioinformatics tools and clinical genomics databases. This comprehensive training focuses on the scientific and clinical evaluation of genetic variants by practically covering NGS data processing, variant calling, annotation, filtering, and classification by clinical significance.

Curriculum

A detailed breakdown of everything covered in this course.

5 bölüm · 14 konu

1
Introduction to Clinical Genomics and Genetic Variant Analysis
120 dk
2
NGS Technologies and Genomic Data Formats (FASTQ, BAM, VCF)
120 dk
3
Using NCBI, Ensembl, UCSC, and ClinVar Databases
120 dk
1
Quality Control and Preprocessing in NGS Data
120 dk
2
Sequence Alignment to the Reference Genome and Alignment Quality Assessment
120 dk
3
Genetic Variant Detection: Variant Calling and VCF Analysis
120 dk
1
Genetic Variant Annotation: VEP and ANNOVAR
120 dk
2
Variant Filtering and Prioritization: gnomAD, ClinVar, and OMIM
120 dk
3
Functional Impact Analysis of Genetic Variants and Disease Association
120 dk
1
Classification of Genetic Variants According to ACMG/AMP Criteria
120 dk
2
Clinical Genomics Case Analysis: Evaluation of Disease-Associated Variants
120 dk
1
End-to-End Variant Analysis on an NGS Dataset
120 dk
2
Clinical Variant Interpretation and Case Evaluation
120 dk
3
Preparing a Clinical Genomics Analysis Report and Project Presentation
120 dk

Requirements

What you need before starting this course.

  • Have basic knowledge of molecular biology and genetics
  • Have basic computer usage skills

Who This Is For

This course is perfect for you if...

  • Graduates of bioengineering, genetics, biology, and biotechnology
  • Researchers working or seeking to specialize in medical genetics and clinical genomics
  • Undergraduate and graduate students studying bioinformatics, molecular biology, and genetics
  • Academics and scientists who want to gain competence in NGS and genomic data analysis

Instructor

Your guide throughout this course.

Yasin Polat

Yasin Polat

Bioinformatics and Computational Biology Specialist

Designs advanced scientific data science and software automation solutions to manage the massive data load of modern biological research. Skilled in building reproducible analysis architectures that prioritize computability and transparency in multi-omics projects.

Course Details

Key information about this course at a glance.

LevelBeginner
Total Duration12 Weeks
Course TypeLive Course
LanguageEnglish
CertificateIncluded

Frequently Asked Questions

Find answers to the most common questions about this course.

Our platform offers both live and pre-recorded training; you can check the specific 'Course Type' at the top of the course page. Our live courses are fully interactive and conducted simultaneously with the instructor.

While many of our live sessions are recorded, this may vary depending on the specific course. If a course is recorded, you will have access to the recordings through your profile. Please check the course description for exact details.

You can ask your questions directly to the instructor during the live sessions. Additionally, you can stay in constant touch with the instructor and other participants through course-specific WhatsApp communication groups.

Yes, upon successful completion of the live training program, a personalized, verifiable certificate of completion is issued to you. You can add this certificate to your resume and LinkedIn profile with a single click.

Depending on the course, the installation of required software (Python, VS Code, etc.) is usually demonstrated step-by-step during the first session. For courses with specific hardware requirements, these are detailed in the 'Requirements' section on the course page.

To put the theoretical knowledge into practice, hands-on projects and assignments are given at the end of each week or module. You will receive instructor feedback by completing these assignments.

Student Reviews

What our graduates say about our courses

AI in Scientific Research

A very clear, example-driven course. Thank you to everyone who put in the effort.

5

Selin G.

Biology Student

Applied Genomic Data Analysis with Bioinformatics Tools

We walked through pipeline setup from start to finish. Working with real datasets helped me go beyond theory.

5

Mert K.

Industry Professional

AI in Scientific Research

I took the course to build on my basics and I'm very happy with it. It was informative, not boring, and the interactive parts were great. I liked how common AI tools for researchers were explained simply and quickly.

4

Lane Ö.

Undergraduate Student

Introduction to Bioinformatics and Omics Data Structures

Core concepts are covered in a logical order. I saw omics data structures explained clearly for the first time. Reinforcing them with examples was really useful.

5

Zeynep A.

Graduate Student

Applied Genomic Data Analysis with Bioinformatics Tools

Real-world examples made genomic data analysis click for the first time. I could take the outputs from lab sessions straight into my workflow.

5

Ahmet D.

Industry Professional

Introduction to Bioinformatics and Omics Data Structures

The instructor explained the topic in a very clear way. I understood the material much better here than when it was covered mixed together in class.

5

Yiğit Ç.

Bioinformatics Student

AI in Scientific Research

It's a packed pace but the content is well structured. You learn a concrete tool or method in each section, so you can keep going without getting lost.

4

Deniz T.

Molecular Biology Student

Applied Genomic Data Analysis with Bioinformatics Tools

I now have a much clearer sense of which tools to use and when. The step-by-step structure in genomic analysis was exactly what I was looking for.

5

Ece Y.

Data Analyst

AI in Scientific Research

As a first-time learner I struggled with some parts beyond the presentations. Still, the instructor explained everything in a very clear way. I don't have enough background on the topic to offer suggestions.

4

Hilal D.

Physiotherapy Student

Introduction to Bioinformatics and Omics Data Structures

The lessons are clear and helpful. My only suggestion is to solve more examples together during the session to understand better.

5

Arden A.

Biology Student

1 / 10
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