 ##### Introduction to R for the beginners (Poznań/2-days workshops)

###### Course content:

• Introduction to R and RStudio
• Basic operators in R, mathematical and statistical functions, R as a calculator
• Basic objects in R: vectors, matrices, data frames, lists
• Introduction to programming: loops, conditional statements, functions
• Introduction to data analysis: basic descriptive statistics, statistical tests: t test, anova, tests for checking equality of variance, testing for normal distribution
• Basic charts: histogram, boxplot, scatter plot, heatmaps, dendrograms

• ##### Introduction to R for the beginners (Poznań/2-days workshops)

###### Course content:

• Introduction to R and RStudio
• Basic operators in R, mathematical and statistical functions, R as a calculator
• Basic objects in R: vectors, matrices, data frames, lists
• Introduction to programming: loops, conditional statements, functions
• Introduction to data analysis: basic descriptive statistics, statistical tests: t test, anova, tests for checking equality of variance, testing for normal distribution
• Basic charts: histogram, boxplot, scatter plot, heatmaps, dendrograms
• ##### Statistical data analysis in R for the beginners (Poznań/2-days workshops)

###### Course content:

• Introduction to R and RStudio
• Basic descriptive statistics: measures of central tendency, measures of dispersion, analysis of data distribution
• Basic operators in R, mathematical and statistical functions, R as a calculator
• Basic objects in R: vectors, matrices, data frames, lists
• Introduction to programming: loops, conditional statements, functions
• Introduction to data analysis: t test, anova, Kruskal-Wallis, Friedman’s rank test, Wilcoxon signed rank test, post – hoc tests
• Basic charts: histogram, boxplot, scatter plot, heatmaps, dendrograms
• Regression analysis
• Principial component analysis
• ##### Statistical data analysis in R for the beginners (Poznań/2-days workshops)

###### Course content:

• Introduction to R and RStudio
• Basic descriptive statistics: measures of central tendency, measures of dispersion, analysis of data distribution
• Basic operators in R, mathematical and statistical functions, R as a calculator
• Basic objects in R: vectors, matrices, data frames, lists
• Introduction to programming: loops, conditional statements, functions
• Introduction to data analysis: t test, anova, Kruskal-Wallis, Friedman’s rank test, Wilcoxon signed rank test, post – hoc tests
• Basic charts: histogram, boxplot, scatter plot, heatmaps, dendrograms
• Regression analysis
• Principial component analysis
• ##### RNA-seq Data Analysis in R (Poznań/2-days workshop)

###### Course content:

• Brief introduction to R. Package dplyr.
• Basic descriptive statistics: measures of central tendency, measures of dispersion, analysis of data distribution
• Basic plots
• Basics of data visualization: the ggplot2 package
• Introduction to RNA-seq and Bioconductor
• Quality analysis, mapping, counts
• Chi-square independence tests
• Basic statistical tests for NGS data: edgeR, deseq, limma.
• GO and KEGG analysis
• Visualization of results
• Case study

• ##### RNA-seq Data Analysis in R (Poznań/2-days workshop)

###### Course content:

• Brief introduction to R. Package dplyr.
• Basic descriptive statistics: measures of central tendency, measures of dispersion, analysis of data distribution
• Basic plots
• Basics of data visualization: the ggplot2 package
• Introduction to RNA-seq and Bioconductor
• Quality analysis, mapping, counts
• Chi-square independence tests
• Basic statistical tests for NGS data: edgeR, deseq, limma.
• GO and KEGG analysis
• Visualization of results
• Case study