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.
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Expérience recommandée
Ce que vous apprendrez
Basics of R
Basics of Python
How to analyze bulk RNAseq count data
How to analyze single cell RNAseq count data
Compétences que vous acquerrez
- Catégorie : Bioinformatics
- Catégorie : Python Programming
- Catégorie : R Programming
Détails à connaître
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Il y a 4 modules dans ce cours
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.
Inclus
17 vidéos2 lectures4 devoirs
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.
Inclus
20 vidéos1 lecture2 devoirs6 devoirs de programmation
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.
Inclus
19 vidéos1 lecture4 devoirs4 devoirs de programmation1 laboratoire non noté
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.
Inclus
19 vidéos2 lectures3 devoirs4 devoirs de programmation
Instructeurs
Recommandé si vous êtes intéressé(e) par Data Analysis
University of California, Irvine
Johns Hopkins University
University of Minnesota
University of Cape Town
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