9 materials found

**Keywords**:
R

Introduction to R (slides)
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an...

Introduction to R (slides)
https://bioconductor.org/help/course-materials/2014/Epigenomics/IntroductionToR.html
https://tess.elixir-europe.org/materials/introduction-to-r-slides
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an active user community.
Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images.
Martin Morgan
R

Introduction to R
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an...

Introduction to R
https://bioconductor.org/help/course-materials/2014/SeattleOct2014/A01.1_IntroductionToR.html
https://tess.elixir-europe.org/materials/introduction-to-r-05a4bc85-7d88-4b09-aa40-8cf33e7b1af7
Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data.
Bioconductor uses the R statistical programming language, and is open source and open development.
It has two releases each year, 1560 software packages, and an active user community.
Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images.
Martin Morgan
R

Statistics with RStudio
Introduction to statistics with R

Statistics with RStudio
https://www.france-bioinformatique.fr/en/training_material/statistics-rstudio
https://tess.elixir-europe.org/materials/statistics-with-rstudio
Introduction to statistics with R
R

A Quick and focused overview of R data types and ggplot2 syntax
R and RStudio overview.

** Keywords: **Graphical analysis, R, Statistics

A Quick and focused overview of R data types and ggplot2 syntax
https://www.france-bioinformatique.fr/en/node/1966
https://tess.elixir-europe.org/materials/a-quick-and-focused-overview-of-r-data-types-and-ggplot2-syntax-b0aa7b0d-f355-44d7-baed-93d124c0f3ba
R and RStudio overview.
Graphical analysis, R, Statistics

Analysis of community composition data using phyloseq
Learn about and become familiar with phyloseq R package for the analysis of microbial census data

Analysis of community composition data using phyloseq
https://www.france-bioinformatique.fr/en/node/1967
https://tess.elixir-europe.org/materials/analysis-of-community-composition-data-using-phyloseq
Learn about and become familiar with phyloseq R package for the analysis of microbial census data
Microbiomes, R

Statistics with R
The aim of this course is to teach you how to perform basic statistical analysis using R. First we review the foundations (sampling theory, discrete and continuous distributions), then we focus on classical hypothesis testing. This course will improve your generic statistics knowledge....

** Scientific topics: **Statistics and probability

** Keywords: **Biostatistics, R

Statistics with R
https://www.mygoblet.org/training-portal/materials/statistics-r
https://tess.elixir-europe.org/materials/statistics-with-r
The aim of this course is to teach you how to perform basic statistical analysis using R. First we review the foundations (sampling theory, discrete and continuous distributions), then we focus on classical hypothesis testing. This course will improve your generic statistics knowledge.
Topics:
Sampling theory: obtaining information about a population via sampling.
Sample characteristics (location, dispersion, skewness), estimation of the mean, standard error of the mean.
Discrete and continuous probability distributions. Central limit theorem.
Hypothesis testing. Basic principles, one- and two-sided testing, types of errors, power calculations.
"Cookbook of tests": location testing, normality, variance comparisons,
counting statistics, contingency tables, regression tests.
András Aszódi
Statistics and probability
Biostatistics, R
2016-04-21
2017-10-09

Working with Affymetrix CEL files in R
This tutorial shows how to download some public Affymetrix microarray data, load the data into R, calculate expression values and do some very simple plotting

** Keywords: **Affymetrix, Microarrays, R

Working with Affymetrix CEL files in R
https://www.mygoblet.org/training-portal/materials/working-affymetrix-cel-files-r
https://tess.elixir-europe.org/materials/working-with-affymetrix-cel-files-in-r
This tutorial shows how to download some public Affymetrix microarray data, load the data into R, calculate expression values and do some very simple plotting
Mick Watson
Affymetrix, Microarrays, R
Beginners
PhD students
Researchers
2014-01-14
2017-10-09

Simple plotting in R
This quick and simple tutorial demonstrates some of the easy plotting tools in the R core software.
the data are in the "data" directory and come from an old two-colour microarray experiment where spots on the array were printed with different buffers, in different concentrations and with...

** Keywords: **Bioinformatics, Microarray data analysis, Plotting data, R, Visualisation

Simple plotting in R
https://www.mygoblet.org/training-portal/materials/simple-plotting-r
https://tess.elixir-europe.org/materials/simple-plotting-in-r
This quick and simple tutorial demonstrates some of the easy plotting tools in the R core software.
the data are in the "data" directory and come from an old two-colour microarray experiment where spots on the array were printed with different buffers, in different concentrations and with different pins. Also, both channels Cy5 and Cy3 were spotted identically, and so the fold ratio for all spots should be 1 - this helps us see bias in the data
Mick Watson
Bioinformatics, Microarray data analysis, Plotting data, R, Visualisation
Beginners
PhD students
Researchers
Scientists
2014-01-14
2017-10-09

Flow Cytometry 2013 Module 2 - Exploring FCM data in R
Loading a single or groups of FCS files into R
flowFrame and flowSet objects and their attributes
Exploring sample annotation and keywords stored within the FCS file format, searching for specic samples (such as controls) using grep, highlighting the importance of correct sample annotation...

** Keywords: **Fcs files, Plotting data, R

Flow Cytometry 2013 Module 2 - Exploring FCM data in R
https://www.mygoblet.org/training-portal/materials/flow-cytometry-2013-module-2-exploring-fcm-data-r
https://tess.elixir-europe.org/materials/flow-cytometry-2013-module-2-exploring-fcm-data-in-r
Loading a single or groups of FCS files into R
flowFrame and flowSet objects and their attributes
Exploring sample annotation and keywords stored within the FCS file format, searching for specic samples (such as controls) using grep, highlighting the importance of correct sample annotation at point of acquisition
Simple dot plots and density plots
Michelle Brazas
Fcs files, Plotting data, R
2013-06-26
2017-10-09