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Information
| Unit | INSTITUTE OF MEDICAL SCIENCES |
| BIOSTATISTICS (MEDICINE) (MASTER) (WITHOUT THESIS) (EVENING EDUCATION) | |
| Code | BIST527 |
| Name | Analysis of Genetic Data |
| Term | 2025-2026 Academic Year |
| Term | Spring |
| Duration (T+A) | 1-2 (T-A) (17 Week) |
| ECTS | 5 ECTS |
| National Credit | 2 National Credit |
| Teaching Language | Türkçe |
| Level | Lisansüstü Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Doç. Dr. YAŞAR SERTDEMİR |
| Course Instructor |
The current term course schedule has not been prepared yet.
|
Course Goal / Objective
The aim of this course is to enable students to understand the basic structure of genetic data, become familiar with fundamental genetic data analysis methods used in health sciences, and interpret analysis results from clinical and epidemiological perspectives.
Course Content
This course covers genetic and genomic data types used in health sciences, basic molecular genetics concepts, genotype–phenotype relationships, types of genetic variation (SNPs, indels), genetic data formats, quality control steps, basic genetic statistics, univariate and multivariate analysis approaches, association analyses, and interpretation of results in clinical and epidemiological contexts. Applications are conducted using real or example genetic datasets.
Course Precondition
No prerequisites. (Basic knowledge of biostatistics is recommended.)
Resources
Bush, W. S., Moore, J. H. Genome-Wide Association Studies Lewis, C. M. Statistical Genetics Hartl, D. L., Clark, A. G. Principles of Population Genetics
Notes
Recent genetic epidemiology research articles
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Explain types of genetic data used in health sciences. |
| LO02 | Define the basic statistical properties of genetic data. |
| LO03 | Describe basic quality control steps for genetic datasets. |
| LO04 | Evaluate associations between genetic variants and diseases using basic analytical methods. |
| LO05 | Interpret genetic analysis results within clinical and epidemiological contexts. |
| LO06 | Explain ethical and privacy principles in genetic data analysis. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Explain basic biostatistics, probability, and demographic concepts used in health sciences. | |
| PLO02 | Bilgi - Kuramsal, Olgusal | Define research designs, sampling methods, and data types used in health research. | |
| PLO03 | Bilgi - Kuramsal, Olgusal | Explain the foundations of statistical approaches used in healthcare decision-making processes. | |
| PLO04 | Bilgi - Kuramsal, Olgusal | Explain the basic logic of regression, modeling, and advanced statistical methods used in health sciences. | 2 |
| PLO05 | Beceriler - Bilişsel, Uygulamalı | Analyze and interpret data obtained from health research using appropriate statistical methods. | 3 |
| PLO06 | Beceriler - Bilişsel, Uygulamalı | Perform statistical analyses and generate outputs using statistical software packages. | 2 |
| PLO07 | Beceriler - Bilişsel, Uygulamalı | Apply basic data science, artificial intelligence, and machine learning applications in health sciences. | |
| PLO08 | Beceriler - Bilişsel, Uygulamalı | Evaluate multiple regression and survival analysis results in a clinical context. | |
| PLO09 | Beceriler - Bilişsel, Uygulamalı | Analyze genetic and biomedical data using basic analytical approaches. | 5 |
| PLO10 | Beceriler - Bilişsel, Uygulamalı | Apply scale development, validity, and reliability analyses. | |
| PLO11 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Conduct data analysis and reporting within the scope of a term project. | |
| PLO12 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Apply and manage sampling procedures in health studies. | |
| PLO13 | Yetkinlikler - Öğrenme Yetkinliği | Critically evaluate scientific studies from a statistical perspective. | 1 |
| PLO14 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Present analysis results in accordance with ethical principles. | 2 |
| PLO15 | Yetkinlikler - Alana Özgü Yetkinlik | Applies fundamental concepts of epidemiology and health statistics to clinical and field settings. | 2 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Course introduction; overview of genetic data analysis | Reading | Öğretim Yöntemleri: Anlatım |
| 2 | Basic molecular genetics concepts | Reading | Öğretim Yöntemleri: Anlatım |
| 3 | Types of genetic variation | Reading | Öğretim Yöntemleri: Anlatım |
| 4 | Genetic data formats | Reading | Öğretim Yöntemleri: Anlatım |
| 5 | Quality control in genetic data | Reading | Öğretim Yöntemleri: Anlatım |
| 6 | Basic genetic statistics | Reading | Öğretim Yöntemleri: Anlatım |
| 7 | Genotype–phenotype relationships | Reading | Öğretim Yöntemleri: Anlatım |
| 8 | Mid-Term Exam | Ölçme Yöntemleri: Sözlü Sınav |
|
| 9 | Introduction to association analyses | Reading | Öğretim Yöntemleri: Anlatım |
| 10 | Univariate genetic analyses | Reading | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 11 | Introduction to multivariate genetic analyses | Reading | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 12 | Genetic epidemiology and interpretation | Reading | Öğretim Yöntemleri: Anlatım, Tartışma |
| 13 | Ethics, privacy, and data security | Reading | Öğretim Yöntemleri: Anlatım |
| 14 | General review | Reading | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 15 | Evaluation of applications | Reading | Öğretim Yöntemleri: Soru-Cevap, Tartışma |
| 16 | Term Exams | Ölçme Yöntemleri: Ödev, Proje / Tasarım |
|
| 17 | Term Exams | Ölçme Yöntemleri: Ödev, Proje / Tasarım |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 3 | 42 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 1 | 15 | 15 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 15 | 15 |
| Final Exam | 1 | 15 | 15 |
| Total Workload (Hour) | 129 | ||
| Total Workload / 25 (h) | 5,16 | ||
| ECTS | 5 ECTS | ||