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Programmes & specializations videos

Postgraduate Programme | 1 Year | FULL-TIME

For whom?

Consider one additional year of research training after your Master’s, if you’d like to acquire more research experience or increase your chances of qualifying for a PhD research project.

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  • Public Health Epidemiology
  • Epidemiology
  • Genetic & Molecular Epidemiology
  • Clinical Epidemiology
  • Erasmus Summer Programme (ESP)

    For more information about the Erasmus Summer Programme (ESP), please go to:

    www.erasmussummerprogramme.nl

    Master

    Master of Science in Health Sciences | 1 Year | FULL-TIME | 70 EC points

    For whom?

    This MSc programme focuses on training students who are already educated in research methodology, but wish to take a step further in developing a successful career in health science research. This programme is also interesting if you want to enhance your chances of pursuing a PhD.

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  • Public Health Epidemiology
  • Biostatistics
  • Medical Psychology
  • Epidemiology
  • Genetic & Molecular Epidemiology
  • Clinical Epidemiology
  • Research Master in Clinical Research | 2 Years | FULL-TIME | 120 EC points

    For whom?

    This Research Master programme provides a unique opportunity for ambitious students with a Bachelor degree in Medicine or Biomedical Sciences.There is a great need for clinicians who can combine patient care and research. This Research Master programme helps medical students to become clinical investigators and pursue an academic career simultaneously.

    If you are a medical student of Erasmus MC, we have accustomed the Research Master programme to your Master in Medicine.

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    Research Master in Health Sciences | 2 Years | FULL-TIME | 120 EC points

    For whom?

    Just graduated with a Bachelor Degree in clinical, public health or biomedical sciences and want to start making substantial contributions to future developments in medicine as a researcher? Then this Research Master is for you! With a wide range of specialisations and guidance from some of the greatest minds in these fields, you will be well on your way to a very successful research career.


    If you are a medical student of Erasmus MC, we have accustomed the Research Master programme to your Bachelor and Master in Medicine.

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  • Public Health Epidemiology
  • Health Economic Analysis
  • Biostatistics
  • Medical Psychology
  • Epidemiology
  • Genetic & Molecular Epidemiology
  • Clinical Epidemiology
  • Doctorate

    Postgraduate Programme | 1 Year | FULL-TIME

    For whom?

    Consider one additional year of research training after your Master’s, if you’d like to acquire more research experience or increase your chances of qualifying for a PhD research project.

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  • Public Health Epidemiology
  • Epidemiology
  • Genetic & Molecular Epidemiology
  • Clinical Epidemiology
  • Executive Education

    Executive Master of Science in Health Sciences | 2(+)years | Part-time | 70 EC points

    For whom?

    This Executive Master programme focuses on training individuals who have already  authored scientific publications, but wish to take a step further in developing a successful career in health science research. The programme is ideal for working professionals since you can fully customize it to fit your busy schedule.

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  • Public Health Epidemiology
  • Biostatistics
  • Medical Psychology
  • Epidemiology
  • Genetic & Molecular Epidemiology
  • Clinical Epidemiology
  • Health Decision Sciences
  • Courses

    30 Oct 2019 - 15 Nov 2019
    Clinical Epidemiology [CE02]

    About this course

    Research questions in clinical epidemiology originate from clinical practice. Caring for patients commonly triggers the research-minded clinician to question his/her knowledge and decisions. Questions may revolve around risk factors, prevention, diagnosis, prognosis and/or interventions. Results from clinical epidemiological research are used in patient management decisions. Concepts from decision sciences are used to translate clinical research results to application in day-to-day clinical practice.

    In this course, the principles and practice of clinical epidemiology and the application of the results to clinical decision making will be considered, using examples from the literature and from ongoing studies.

    We will be using blended learning: a combination of web-based materials, interactive lectures, workshops and practicums.

    The course is divided into 3 parts:

    1. Diagnosis
    2. Prognosis
    3. Interventions

    Assignments for each part need to be completed prior to the next part.

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    28 Oct 2019 - 1 Nov 2019
    Public Health Research: Analysis of Determinants [HS02b]

    About this course

    Public Health Research: from Epidemiology to Health Promotion

    Module: Analysis of Determinants

    This module elaborates on research of the analysis of determinants of and inequalities in population health and risk factors of disease. Students will be introduced in:

    • current insights in the main determinants of population health and risk factors of disease;
    • determinants of inequalities in population health;
    • research methods for the analysis of these determinants and
    • challenges for future research in these issues.

    Note: HS02a, HS02b and HS02c will be tested after the HS02c course! If you are taking all three courses, you need to pass all three courses separately.

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    27 Nov 2019 - 5 Feb 2020
    Scientific Writing in English for Publication [SC07]

    About this course

    Course days in 2018-2019 will be: Wednesday November 28, Wednesday December 12, Monday January 16 and Wednesday February 6.The first 3 sessions will be on mornings or afternoons depending on your group.

    The last session on the 6th will be in the morning, afternoon or evening depending on your group and other course schedule.


    Writing to be read

    This course will focus on:

    • Communicating the point and importance of your research;
    • Writing a clear and readable scientific article.The course consists of 4 half-day sessions and 3 writing assignments that will receive individual feedback from the instructor as well as other course participants. Attending all 4 sessions and completing all writing assignments is compulsory.

    The course will be intensive—writing takes time—so we suggest that participants reserve considerable time for this course.

    Participants will be guided through the writing process in 3 assignments:

    1. Clarifying the point of the research;
    2. Completing the Hourglass Template with the main messages for the Introduction, Methods, Results, and Discussion of your research;
    3. Writing the Abstract and Title.

    Part of the work will be peer reviewing. Participants will critically discuss each of the three assignments with a peer-review partner (i.e. another course participant). The remaining members of the peer-review group will review and critique each assignment as well. This implies that participants must be willing to work closely with a peer-review partner during the course and meet deadlines for peer reviewing. After revising texts based on these reviews, participants then send them to the instructor, who will provide both substantive and language tips.

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    27 Jan 2020 - 31 Jan 2020
    Advanced Topics in Decision-making in Medicine [EWP02]

    About this course

    This course deals with intermediate- to advanced level topics in the field of medical decision making. Topics that will be addressed include building decision models, evaluation of diagnostic tests, utility assessment, multi-attribute utility theory, Markov cohort models, microsimulation state-transition models, calibration and validation of models, probabilistic sensitivity analysis, value of information analysis, and behavioral decision making. The course will focus on the practical application of techniques and will include published examples and a computer practicum. Students will learn to apply state-of-the-art modeling methods using freely available open source software to evaluate the comparative effectiveness and cost-effectiveness of health interventions. While the primary emphasis is on application, essential underlying theoretical concepts will also be discussed. During the course you will have the opportunity to work on a decision problem which you select yourself. Many students use the course as a way to start writing a paper on a decision model in the field of their interest.

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    25 Nov 2019 - 6 Dec 2019
    Biostatistical Methods II: Classical Regression Models [EP03]

    About this course

    The aim of this course is to introduce several important statistical regression models for non-normal and censored outcomes that are widely applied in clinical and epidemiological research. The course starts with a brief presentation of the basic principles behind likelihood theory, followed by a detailed discussion of logistic regression for dichotomous data, Poisson regression for count data, and closes with an extended presentation of regression models for time-to-event data, including the Cox proportional hazards model and the accelerated failure time model.The course will be explanatory rather than mathematically rigorous, with emphasis given on application such that participants will obtain a clear view on the different modeling approaches, and how they should be used in practice.


    To this end, the course includes several computer sessions during which participants will be asked to implement in practice the methods discussed in the theory sessions.

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    24 Feb 2020 - 28 Feb 2020
    Using R for Statistics in Medical Research [BST02]

    About this course

    R has recently become one of the most popular languages for data analysis and statistics. This course teaches students the basics syntax and data types of this statistical programming language. The aim of this course is to equip students with the R knowledge needed to explore their own data, make data visualizations and perform basic statistical analysis.


    The course covers practical issues in statistical computing which includes reading data into R, bringing them in the correct structure and writing R functions. This course further focuses on the concepts and tools behind reporting data analyses in a reproducible manner and building simple interactive web applications. In particular, useful features will be introduced such as debugging code, version control using git, markdown reports and shiny apps.


    Written exam: during the course students are asked to perform several programming/analysis tasks in R in the computer lab. The exam is open-book.

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    20 Apr 2020 - 24 Apr 2020
    Advanced Decision Modeling [CE15]

    About this course

    This week-long, project-based course aims to provide students with an understanding of advanced methods used in decision-analytic modeling and cost-effectiveness analyses. These include topics like the latest methods for calibration and validation, quantifying uncertainty, and consideration of heterogeneity of patient benefits and equity issues. The course combines lectures and readings to give theoretical foundation and perspectives with in depth project work and presentations to give practical concrete understanding in a way that furthers students’ specific research goals.

    Course Structure: Each day will begin with a lecture by Professor Goldhaber-Fiebert on an advanced methods topic. After the lecture, lab sessions will commence with students working on their projects as Professor Goldhaber-Fiebert circulates through the room and students assist each other in a collaborative environment. Most days Professor Goldhaber-Fiebert will also give an afternoon lecture. In addition, at the end of days 2, 3, and 4, Professor Goldhaber-Fiebert will give an additional, shorter, informal lecture (i.e., "a chalk talk") on a methods topic tailored to specific issues that are arising within students’ projects. Additionally, throughout the week, Professor Goldhaber-Fiebert will have one-on-one meetings with students about their projects.

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    18 Nov 2019 - 22 Nov 2019
    Principles in Causal Inference [EP01]

    About this course

    Epidemiologic research often entails asking and trying to answer questions toward understanding the causes and consequences of health outcomes. Answers to such causal questions require us to combine data (e.g., from observational studies) with assumptions to estimate causal effects. This course will teach students to think critically and rigorously about the implications of study design and analysis toward addressing such causal questions. Students will learn formal causal inference "languages" – including the concept of a target trial, causal diagrams, and counterfactual theory – to articulate research questions, inform an analytic approach, and identify threats to validity such as confounding.

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    18 Nov 2019 - 22 Nov 2019
    SNPs and Human Diseases [GE08]

    About this course

    The analysis of DNAvariations, including Single Nucleotide Polymorphisms (SNPs), is a standardresearch approach to understand causes of disease, in particular the so-called"complex" diseases such as diabetes, osteoporosis, cancer, Alzheimerdisease, etc. The field is changing fast with large scale projects (Humangenome, dbSNP, HapMap, 1000genomes, ENCODE) and novel technology beingcontinuously introduced, including Next Generation Sequencing.

    The course will deal with five main topics, which are in logical order:

    • General Introduction and Study design,
    • Bio informatic tools for SNP finding and analysis,
    • Genotyping techniques and DNA management,
    • Data analysis, and
    • Examples of research in which SNPs are used.
    Every day will cover one topic. The programme for every day will consist of four to six presentations, including international speakers, and there are learning-by-doing sessions. The possibility exists for participants to discuss their own data and work. This course is organized by the Molecular Medicine postgraduate school (MolMed) in collaboration with NIHES.For more information and application check the MolMed website.

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    18 Nov 2019 - 22 Nov 2019
    International Comparison of Health Care Systems [HS03a]

    About this course

    Insight into the structure, process and outcome of health care systems is vital to be able to implement health care reforms that are effective in improving the health system performance. International comparisons of health care systems and the underlying political, organizational and financial arrangements are a multidisciplinary research field with a mixture of quantitative and qualitative methods. This course will present the various methodological approaches and will build on recent national and international experiences with comparative research.


    The course starts with a clear conceptualization and definition of a health care system, definitions of key system components such as the service delivery system (through professionals and institutions), financing, role of the government and role of patients. Health system performance will be discussed in terms of effectiveness, equity and efficiency. Analytical perspectives taken will come from public health as well as from political sciences and economics. The course will also deal with the recent work performed by international organisations such as the WHO and OECD with respect to health system performance measurement and management.

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    18 May 2020 - 20 May 2020
    Cardiovascular Epidemiology [EP20]

    About this course

    Cardiovascular disease remains the leading cause of morbidity and mortality worldwide. The overall objective of the cardiovascular epidemiology course is to produce epidemiologists and other health scientists with the essential knowledge to carry out high quality research in cardiovascular disease.

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    17 Feb 2020 - 20 Feb 2020
    Psychopharmacology [MP03]

    About this course

    Medical psychology is all about the interaction between mind and body: how do physical complaints affect our psychological functioning? But also: how does our psychological functioning affect us physically? When dealing with this interaction in a clinical setting, drug treatments often play an important role. Patients receiving drug treatment for psychiatric disorders frequently suffer physical side-effects, and drugs prescribed for somatic disorders can influence our mental state.


    Therefore, medical psychologists need to know which drugs are prescribed for common psychiatric and somatic disorders, and need to have a basic understanding of how these (psychoactive) drugs work, how and why they invariably lead to side-effects, and how these side-effect affect compliance. We will look at drug treatment for psychiatric disorders such as depression and schizophrenia, but also at drugs like corticosteroids – used in the treatment of somatic conditions such as inflammatory bowel disease – which have been found to increase the risk of suicidal behavior and neuropsychiatric disorders (i.e. depression, panic and manic episodes).

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    17 Feb 2020 - 21 Feb 2020
    Advanced Clinical Trials [EWP10]

    About this course

    The Randomized Controlled Clinical Trial (RCT) is the most reliable method of assessing the efficacy and effectiveness of interventions. In order to provide the best possible evidence-based health care, health professionals must be able to judge the scientific merits and clinical relevance of published RCTs. In addition, they may be involved in designing and performing a RCT and are frequently asked to recruit patients for RCTs.

    Reports published in major medical journals show a surprising variability in methods including choice of study design, blinding, avoidance of bias, outcome measures, effect parameters, sample size calculations, data analysis techniques, presentation of results in tables and figures, and inferences made from the results. Hence, appraising trial reports can be challenging. In designing RCTs many difficult decisions need to be made with respect to these same issues.

    In this course these topics and issues will be addressed and developed through lectures and group practical sessions. A laptop during classroom sessions is required in order to do the practical assignments.


    The final assignment of this course is due 1 March 2019.


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    16 Oct 2019 - 8 Nov 2019
    Genetic-epidemiologic Research Methods [GE02]

    About this course

    The aim of this course is to introduce participants to the basic principles of genetic epidemiological research.The first part of the course is dedicated to binary traits, covering the basics of probability theory, hypothesis testing, risk calculation in families, and principles of complex segregation analysis. The second part of the course focuses on the genetics of quantitative traits, covering the concept and estimation of heritability and basic quantitative trait linkage analysis using modern genetic analysis software such as SOLAR and MERLIN. In the third part of the course design of genetic epidemiological studies will be discussed. This will be illustrated by practical examples and an assignment to develop a study.During the third week of the course, students will work in groups on this assignment, and will prepare a presentation.

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    14 Oct 2019 - 22 Oct 2019
    Clinical Translation of Epidemiology [CE01]

    About this course

    This course aims to bridge the gap between theoretical epidemiological concepts and application in clinical research and medicine. Understanding of basic epidemiological principles is therefore a prerequisite.

    Students will learn how abstract concepts from epidemiological theory can be translated to clinically observable phenomena. Tools and skills taught in this course will be readily applicable in clinical research on etiology, efficacy, diagnosis and prognosis. Successful completion of this course will enable students to continue with more formal training in theoretical causal inference as well as advanced courses in clinical effectiveness and clinical epidemiology.

    The course will consist of interactive lectures, working groups, group presentations and an individual assignment. Through in-class exercises the student will be provided with the opportunity to utilize the knowledge covered in the lectures on a study from the recent literature.

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    14 Oct 2019 - 15 Oct 2019
    Linux for Scientists [GE14]

    About this course

    This course aims to teach users of a Linux/UNIX system how to work with the command line interface. After an introduction to some history and basic concepts the basic commands for file and directory manipulation will be discussed. Subsequently, the students will learn how to manage processes as well as input and output redirection, followed by more advanced text processing utilities like 'sed' and 'gawk'.

    The second half of the course shows how to write Bash shell scripts to automate tasks. This knowledge is then used when discussing the Sun Grid Engine job queue system in use on the epib-genstat servers.

    The course will focus on providing hands-on experience, so those who have been using a Linux system for a longer time will be able to skip the parts they already feel comfortable with and move on to more advanced concepts like regular expressions, version control and advanced use of a text editor. 

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    14 Oct 2019 - 18 Oct 2019
    Public Health Research: Analysis of Population Health [HS02a]

    About this course

    Public Health Research: From Epidemiology to Health Promotion

    Module: Analysis of Population Health

    This module aims to teach methods to assess the health of populations at national and local levels. Students are taught to calculate, apply and interpret population-based measures of mortality, quality of life and disease occurrence. In addition, students learn methods to assess time trends in population health (e.g. APC methods) and to analyse inequalities in health between social groups.


    Note: HS02a, HS02b and HS02c will be tested after the HS02c course! If you are taking all three courses, you need to pass all three courses separately.

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    14 Oct 2019 - 8 Nov 2019
    Psychology in Medicine [MP01]

    About this course

    Medical psychologists study the way somatically ill people think, act and feel. The aim of this course is to teach students about psychological determinants of illness and illness behavior, the psychological consequences of somatic illness and psychological care for somatic patients. First, you’ll learn about ‘normal’ reactions to disease. We’ll then focus on abnormal and pathological reactions to somatic illness and on problems that patients might have in adjusting to their disease.


    We will discuss models that explain why some people find it difficult to adjust to their disease, such as the stress coping model and the stress vulnerability model. Other models that will be discussed in this course include the Health Belief Model, the Theory of Planned Behavior and the Stages of Change Model. These models are widely applied by medical psychologists in interventions for somatic patients. Modern neuroscientific models for understanding behaviour and behavioural disorders will be addressed as well.


    In this course, we will focus on various somatic problems, such as diabetes, inflammatory bowel disease, infertility, organ transplantation and chronic pain.


    Finally, basic theories of doctor-patient communication will be discussed, as communication between doctors and patients has become more and more important.


    The learning method in this course is problem-based learning. Furthermore, you will build a new model for understanding a complex and realistic problem in medical psychology.

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    11 Nov 2019 - 15 Nov 2019
    The Placebo Effect [MP02]

    About this course

    The placebo effect has been studied since the 1950’s, starting with the original 1955 study of Beecher. In this course we will discuss several postulated underlying mechanisms of the placebo effect (e.g. expectancy, conditioning, affect-modulation, and doctor-patient communication). Furthermore we will debate the existence of the placebo effect and discuss the challenges in measuring the effect. Questions that will be addressed are for instance: can you deliver an open label placebo? Is it ethical to prescribe a placebo when a patient doesn’t know he is getting a sugar pill? Does the placebo effect exist outside of pain medication research? You will experience the strength of the placebo effect first hand in an experiment during the course.

    The assessment of the course will exist of the presentation of a research proposal for studying the placebo effect.

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    11 Mar 2020 - 17 Mar 2020
    Advanced Analysis of Prognosis Studies [EWP13]

    About this course

    Prognostic models are increasingly published in the medical literature each year. But are the results relevant for clinical practice? What are the critical elements of a well developed prognostic model? How can we assume that the model makes accurate predictions for our patients, and not only for the sample that was used to develop the model (generalizability, or external validity)?


    In the course we will address these and other questions from a methodological perspective, using examples from the clinical literature.The participants will be encouraged to participate in interactive discussions and in practical computer exercises.

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    07 Jan 2020 - 24 Jan 2020
    Introduction to Medical Writing [SC02]

    About this course

    During the second semester, full time Master of Science (70 ECTS) students will attend four workshops of three hours and one workshop of six hours on how to write correct and readable scientific articles in English. Each student will be able to bring their own work which will be commented on and corrected by participants and the teacher.

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    06 Jan 2020 - 24 Jan 2020
    Review of Mathematics and Introduction to Statistics [BST01]

    About this course

    Several courses in the NIHES curriculum require a good working knowledge of basic concepts in mathematics and statistics. These courses include Biostatistical Methods I: Basic Principles (CC02), Biostatistical Methods II: Classical Regression Models (EP03), Repeated Measurements (CE08) and Bayesian Statistics (CE09). The course "BST01: Review of Mathematics and Introduction to Statistics" aims to prepare you for these statistical courses by helping you to obtain a sufficient working knowledge of mathematics and statistics. This course is a self-study course based on online material (videos from external sources) and the material in an accompanying reader. There will be no lectures or tutorials, but the organizers of the course are available for questions during the course. A number of exercises and a practice test are included in the course materials. The content of this course is divided into the following topics:

    • Basic mathematical operations
    • Functions
    • Differentiation
    • Integration
    • Vectors and matrices
    • Basic concepts in statistics

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    04 Nov 2019 - 08 Nov 2019
    Public Health Research: Intervention Development and Evaluation [HS02c]

    About this course

    Public Health Research: from Epidemiology to Health Promotion

    Module: Intervention Development and Evaluation.

    This module elaborates on the intervention development, implementation and evaluation phases in the model of planned promotion of public health.

    Students will:

    • be introduced to strategies and opportunities of primary and secondary prevention;
    • learn how to work from determinants to interventions, i.e. how to translate determinants into intervention goals and intervention components and;
    • learn about the opportunities and challenges of evaluation of primary and secondary prevention interventions and;
    • be introduced to theory and challenges in dissemination of prevention interventions.

    The course uses examples from health behaviour change, cancer screening, and vaccination.


    Note: HS02a, HS02b and HS02c will be tested after the HS02c course! If you are taking all three courses, you need to pass all three courses separately.

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    03 Feb 2020 - 07 Feb 2020
    Using R for Decision Modeling in Health Technology Assessment [CE16]

    About this course

    This course aims to teach how to build decision models in R to students who have a basic understanding of health decision science.

    • The course combines lectures with R coding exercise.
    • The course is project-based. You are encouraged to apply the theory and skills you learn during this course to a decision problem you select yourself.

    More detailed information about each session will be provided in the syllabus.

    Attendance of all lectures and practicums is highly recommended in order to be able to complete the assignments and case example successfully. Each day builds on knowledge and skills from the previous day. Clarification of the material taught is best done in the interactive teaching environment provided during classroom sessions.

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    02 Mar 2020 - 06 Mar 2020
    An Introduction to the Analysis of the Next-generation Sequencing Data [GE13]

    About this course

    This course provides an introduction to working with Next-Generation Sequencing (NGS) data. It targets individuals who have access to NGS data and want to learn how to work with this data and what the possibilities and limitations of NGS are. Lectures will be complemented with practical sessions in which the student will gain hands-on experience with various tools and techniques.Subjects that will be covered include:

    • NGS: an introduction to methodology and techniques;
    • Basic statistics of NGS data, e.g. coverage;
    • Aligning the sequence reads;
    • Calling sequence and structural variants;
    • Dealing with various file formats (samtools, VCFtools, GATK);
    • Annotating sequence and structural variants;
    • Evaluating functional effects of the genetic variants on proteins;
    • Conversion to other formats;
    • Single variant and Collapsed genotype analyses with various tools (e.g. seqMeta, RAREMETAL and RVtest);
    • Finding variants with recessive effects and compound heterozygosity;
    • Search for rare variants in families and population based studies for complex phenotypes;
    • Search for rare variants in Mendelian disorders, and
    • Imputation of sequence variants.

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