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August 19, 2024
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Instructors: Jesper Tegner
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Beginner level
This course does not require prior knowledge, however proficiency in other programming languages than R and python would be helpful.
(58 reviews)
Recommended experience
Beginner level
This course does not require prior knowledge, however proficiency in other programming languages than R and python would be helpful.
Basics of R
Basics of Python
How to analyze bulk RNAseq count data
How to analyze single cell RNAseq count data
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The course provides a broad and mainly practical overview of fundamental skills for bioinformatics (and, in general, data analysis). The aim is to support the simultaneous development of quantitative and programming skills for biological and biomedical students with little or no background in programming or quantitative analysis.
Through the course, the student will develop the necessary practical skills to conduct basic data analysis. Most importantly, participants will learn long-term skills in programming (and data analysis) and the guidelines for improving their knowledge on it. The course will include Programming in R, programming in Python, Unix server, and reviewing basic concepts of statistics.
The first module will explore the basics of programming through R and this will include: working in R and RStudio, understanding data types, loops and ifs. Additionally, the module will provide an introduction to RMarkDown as a tool for sharing code that we will use in the coding lectures.
17 videos2 readings4 assignments
The second module will focus on two aims. Firstly, to master the use of logical values and vectors and its applications in quality control. Secondly, to practice the programming skills while learning how to perform basic statistical analysis. This will include: explorative data analysis, correlation, linear models, T-test, and ANOVA. Finally, we will explore the available resources for R programming.
20 videos1 reading2 assignments6 programming assignments
The third module will provide the basics of the Python programming language. First, the module will compare Python and R language and learn the programming syntax of Python. Second, the module will work with two key Python modules: pandas and numpy.
19 videos1 reading4 assignments4 programming assignments1 ungraded lab
The final module will focus on applying knowledge and understanding of programming in the analysis of real RNA-seq data. R will be used for analysing of bulk RNA-seq and Python for single- cell RNA-seq. The results of both analyses will then be integrated. Finally, the module will provide insights in how to gain deeper knowledge and skills in R.
19 videos2 readings3 assignments4 programming assignments
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
Instructor ratings
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
Peking University
Course
University of California San Diego
Specialization
University of California San Diego
Specialization
Icahn School of Medicine at Mount Sinai
Course
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