R for data science
31 March - 3 April 2020
Liverpool, United KingdomR for data science https://www.liverpool.ac.uk/computational-biology-facility/events/r-data-science/ https://tess.elixir-europe.org/events/r-for-data-science The course covered content for these learning objectives: To write your own custom functions To use for loops, apply functions and if statements To analyse large matrices of data in a semi-automated way To normalise data To quantify and correct batch effect To undertake the most common clustering algorithms including k-means and hierarchical To perform variable selection and present these results in different plots including heatmaps To do 2-way ANOVA To undertake multivariate modelling A brief introduction to machine learning. The course included brief theoretical introductions followed by hands on exercises based on real life research examples. 2020-03-31 09:00:00 UTC 2020-04-03 17:00:00 UTC Computational Biology Facility University of Liverpool, Liverpool, United Kingdom University of Liverpool Liverpool Merseyside United Kingdom L69 3GH Statistics and probability Bioinformatics University of Liverpool Computational Biology Facility (firstname.lastname@example.org)   20 workshops_and_courses registration_of_interest R ProgrammingStatistical-model Statistics Pre-processingTranscriptomicsMetabolomicsProteomics
R for beginners
1 - 3 April 2020
Liverpool, United KingdomR for beginners https://www.liverpool.ac.uk/computational-biology-facility/events/r-beginners/ https://tess.elixir-europe.org/events/r-for-beginners R is a programming language and free software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. This course covers: Day 1: Foundations of R: get familiar with R, R studio, operators, variables, functions, directories and the script editor Day 2: Visualisation in basic R (boxplots, scatterplots, line graphs and histograms) and ggplot2 (same types of plots and also manipulation of data for use within this package as well as simple linear regression) Day 3: Introduction to statistical analyses in R: univariate statistics (choosing the right test, checking data assumptions, calculating and extracting the values to report in publications) and Principal Component Analysis (calculation and visualisation with ggplot2) Extra materials: Introduction to the Tidyverse, Introduction to for loops All materials have been built using relevant life sciences/clinical examples. The course has been designed to introduce R from the very basics. Therefore applicants do not need any prior experience to attend, just the desire to learn R. Real life examples with bioinformatic applications are included. 2020-04-01 09:00:00 UTC 2020-04-03 17:00:00 UTC Computational Biology Facility University of Liverpool, Liverpool, United Kingdom University of Liverpool Liverpool Merseyside United Kingdom L69 3GH Computational biology Statistics and probability University of Liverpool Computational Biology Facility (email@example.com)   workshops_and_courses first_come_first_served R-programmingbiostatistics Statistics R programminglife sciences, bioinformaticsClinical Bioinformatics
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