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This course follows on from the introductory course. It goes into more detail on practical guides to filtering and combining complex data sets. It also looks at other core R concepts such as looping with apply statements and using packages. Finally it looks at how to document your R analyses and...

Keywords: R programming, Babraham Institute

Advanced R https://tess.elixir-europe.org/materials/advanced-r This course follows on from the introductory course. It goes into more detail on practical guides to filtering and combining complex data sets. It also looks at other core R concepts such as looping with apply statements and using packages. Finally it looks at how to document your R analyses and generate complete analysis reports. R programming, Babraham Institute

The aim of this course is to help computational biologists with complex data analysis problems. After discussing the theoretical foundations, the course will provide practical advice on how to use the presented methodogies with R.

Advanced regression methods https://tess.elixir-europe.org/materials/advanced-regression-methods The aim of this course is to help computational biologists with complex data analysis problems. After discussing the theoretical foundations, the course will provide practical advice on how to use the presented methodogies with R. 2017-08-22

Introduction to short-read alignments, including a general overview of existing methods (Burrow-Wheeler-Transform, Maximum Mappable Prefix, _etc._) and some cautionary tales.

Scientific topics: RNA-Seq

Keywords: BAM, Populus-tremula, RNA-Seq, QC, Alignment

Alignment https://tess.elixir-europe.org/materials/alignment Introduction to short-read alignments, including a general overview of existing methods (Burrow-Wheeler-Transform, Maximum Mappable Prefix, _etc._) and some cautionary tales. RNA-Seq BAM, Populus-tremula, RNA-Seq, QC, Alignment

This course builds on the core skills introduced in the Introduction to R, Introduction to Unix and Introduction to SeqMonk courses to provide a more in depth look at the analysis of bisulphite sequencing data. The course is a mix of theoretical lectures and hands on practicals which go through...

Analysing bisulfite methylation sequencing data https://tess.elixir-europe.org/materials/analysing-bisulfite-methylation-sequencing-data This course builds on the core skills introduced in the Introduction to R, Introduction to Unix and Introduction to SeqMonk courses to provide a more in depth look at the analysis of bisulphite sequencing data. The course is a mix of theoretical lectures and hands on practicals which go through the whole analysis pipeline, starting from raw sequence data and covering QC, visualisation, quantitation and differential methylation analysis. DNA methylation

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

Keywords: Microbiomes, R

Analysis of community composition data using phyloseq 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

This introduces to the different sources of genomic and genic annotation and to their most commonly used format. It also introduces how to ensure that the used annotation are not a source of bias in downstream analyses.

Scientific topics: RNA-Seq

Keywords: GFF3, Populus-tremula, RNA-Seq, Annotation

Annotation https://tess.elixir-europe.org/materials/annotation This introduces to the different sources of genomic and genic annotation and to their most commonly used format. It also introduces how to ensure that the used annotation are not a source of bias in downstream analyses. RNA-Seq GFF3, Populus-tremula, RNA-Seq, Annotation

The aim of this course is to introduce you to data modelling using R. We focus on linear regression and ANOVA in order to improve your generic statistics knowledge. Please note that we cannot go into the specific data analysis problems of your particular project.

ANOVA and linear regression with R https://tess.elixir-europe.org/materials/linear-models-with-r The aim of this course is to introduce you to data modelling using R. We focus on linear regression and ANOVA in order to improve your generic statistics knowledge. Please note that we cannot go into the specific data analysis problems of your particular project. 2017-08-22

This training gives an introduction to the use of the statistical software language R. R is a language for data analysis and graphics. This introduction to R is aimed at beginners. The training covers data handling, graphics, mathematical functions and some statistical techniques. R is for free...

Basic statistics in R https://tess.elixir-europe.org/materials/basic-statistics-in-r This training gives an introduction to the use of the statistical software language R. R is a language for data analysis and graphics. This introduction to R is aimed at beginners. The training covers data handling, graphics, mathematical functions and some statistical techniques. R is for free and for more information you can visit the site at the CRAN web site. This training is an introduction to the use of R and RStudio and stops at very basic analyses (t-tests and non-parametric equivalents). A full overview of statistical analyses in R including regression, ANOVA will be given in the follow-up training Basic statistics in R, part II Life Science Researchers PhD students post-docs 2016-04-22 2017-08-22

This training builds further on the Basic statistics in R training, showing you how to do statistical analyses in R. Where the Basic statistics in R training is an introduction to the use of R and RStudio and stops at very basic analyses (t-tests and non-parametric equivalents), this training...

Basic statistics in R, part II https://tess.elixir-europe.org/materials/basic-statistics-in-r-part-ii This training builds further on the Basic statistics in R training, showing you how to do statistical analyses in R. Where the Basic statistics in R training is an introduction to the use of R and RStudio and stops at very basic analyses (t-tests and non-parametric equivalents), this training gives you a full overview of statistical analyses in R including regression, ANOVA... Emphasis will be placed on practical applications. To this end, theory will be complemented with hands-on exercises in R, a free software environment for statistical computing and graphics. Topics include distributions, plots, confidence intervals, hypothesis testing... beginner bioinformaticians Life Science Researchers PhD students post-docs 2016-04-22 2017-08-22

This training gives an introduction to the use of statistics for basic analyses of life sciences data. This training is a prerequisite introduction to a series of hands-on trainings on the statistical analysis of life sciences data: 'Basic statistics in R' and 'Basic statistics in Graphpad...

Basic statistics theory https://tess.elixir-europe.org/materials/basic-statistics-theory This training gives an introduction to the use of statistics for basic analyses of life sciences data. This training is a prerequisite introduction to a series of hands-on trainings on the statistical analysis of life sciences data: 'Basic statistics in R' and 'Basic statistics in Graphpad Prism'. If you want to follow one of these trainings, you have to follow this introduction. Ít will give you all the theoretical background that you need. Those that already have a strong statistical background may register directly for the 'Basic statistics in R, part II' training. post-docs Life Science Researchers PhD students 2016-04-22 2017-08-22

A short training session with Dr. Ian Handel at The Roslin Institute, April 2015

Keywords: R language, Roslin Institute

A Brief Introduction to R https://tess.elixir-europe.org/materials/a-brief-introduction-to-r A short training session with Dr. Ian Handel at The Roslin Institute, April 2015 R language, Roslin Institute

ChIP-seq is the most commonly used technique to study binding profiles of chromatin proteins, such as TFs or histone modification patterns. This course is an introduction to ChIP-seq data, and data analysis mainly using R, some command line based peak-callers and online software. It provides a...

Keywords: ChIP-Seq, Experimental-design, Peak-calling, Differential-binding, Visualisation, Annotation, Homo-sapiens, R-programming

ChIP-seq analysis using R https://tess.elixir-europe.org/materials/chip-seq-analysis-using-r-5049bc9c-9bbb-4a6b-9244-37ed3980da0e ChIP-seq is the most commonly used technique to study binding profiles of chromatin proteins, such as TFs or histone modification patterns. This course is an introduction to ChIP-seq data, and data analysis mainly using R, some command line based peak-callers and online software. It provides a theoretical background and the means to perform peak calling and differential binding analysis. ChIP-Seq, Experimental-design, Peak-calling, Differential-binding, Visualisation, Annotation, Homo-sapiens, R-programming

ChIP-seq is the most commonly used technique to study binding profiles of chromatin proteins, such as TFs or histone modification patterns. This course is an introduction to ChIP-seq data, and data analysis mainly using R, some command line based peak-callers and online software. It provides a...

Keywords: ChIP-Seq, Experimental-design, QC, Data-format, Alignment, Peak-calling, Differential-binding, Visualisation, Annotation

ChIP-seq analysis using R https://tess.elixir-europe.org/materials/chip-seq-analysis-using-r ChIP-seq is the most commonly used technique to study binding profiles of chromatin proteins, such as TFs or histone modification patterns. This course is an introduction to ChIP-seq data, and data analysis mainly using R, some command line based peak-callers and online software. It provides a theoretical background and the means to perform peak calling and differential binding analysis. ChIP-Seq, Experimental-design, QC, Data-format, Alignment, Peak-calling, Differential-binding, Visualisation, Annotation

This lecture is an introduction to ChIP-seq experiments and data. It provides a theoretical background to experimental design and peak calling.

Keywords: ChIP-Seq, Experimental-design, Peak-calling, Visualisation

ChIP-seq analysis using R - Experimental design and peak calling. https://tess.elixir-europe.org/materials/chip-seq-analysis-using-r-experimental-design-and-peak-calling This lecture is an introduction to ChIP-seq experiments and data. It provides a theoretical background to experimental design and peak calling. ChIP-Seq, Experimental-design, Peak-calling, Visualisation

This lecture is an introduction to ChIP-seq experiments and data. It provides a theoretical background to experimental design and peak calling.

Keywords: ChIP-Seq, Experimental-design, Peak-calling, Visualisation

ChIP-seq analysis using R - Experimental design and peak calling. https://tess.elixir-europe.org/materials/chip-seq-analysis-using-r-experimental-design-and-peak-calling-cfd4c18f-6c86-45ae-ab0b-630422c76af6 This lecture is an introduction to ChIP-seq experiments and data. It provides a theoretical background to experimental design and peak calling. ChIP-Seq, Experimental-design, Peak-calling, Visualisation

This lecture introduces the file formats of sequencing data before alignment and covers the general quality control of sequencing data focussing on RNA-Seq and ChIP-Seq.

Scientific topics: RNA-Seq

Keywords: ChIP-Seq, RNA-Seq, QC, Data-format, Experimental-design

ChIP-seq analysis using R - File formats and QC https://tess.elixir-europe.org/materials/chip-seq-analysis-using-r-file-formats-and-qc This lecture introduces the file formats of sequencing data before alignment and covers the general quality control of sequencing data focussing on RNA-Seq and ChIP-Seq. RNA-Seq ChIP-Seq, RNA-Seq, QC, Data-format, Experimental-design

This lecture introduces the principles behind alignment, different tools and de-novo assembly. It also covers post mapping data format and quality control

Scientific topics: Sequence assembly, RNA-Seq

Keywords: ChIP-Seq, RNA-Seq, Alignment, Data-format, Assembly, QC

ChIP-seq analysis using R - Mapping and file formats https://tess.elixir-europe.org/materials/chip-seq-analysis-using-r-mapping-and-file-formats This lecture introduces the principles behind alignment, different tools and de-novo assembly. It also covers post mapping data format and quality control Sequence assembly RNA-Seq ChIP-Seq, RNA-Seq, Alignment, Data-format, Assembly, QC

ChIP-seq is the most commonly used technique to study binding profiles of chromatin proteins, such as TFs or histone modification patterns. This practical is an introduction to ChIP-seq data analysis mainly using R, some command line based peak-callers and online software. It provides means to...

Keywords: ChIP-Seq, Peak-calling, Differential-binding, Visualisation, Annotation, Homo-sapiens, R-programming

ChIP-seq analysis using R - Practical https://tess.elixir-europe.org/materials/chip-seq-analysis-using-r-practical ChIP-seq is the most commonly used technique to study binding profiles of chromatin proteins, such as TFs or histone modification patterns. This practical is an introduction to ChIP-seq data analysis mainly using R, some command line based peak-callers and online software. It provides means to perform peak calling, annotation, motif search and differential binding analysis. ChIP-Seq, Peak-calling, Differential-binding, Visualisation, Annotation, Homo-sapiens, R-programming

ChIP-seq is the most commonly used technique to study binding profiles of chromatin proteins, such as TFs or histone modification patterns. This practical is an introduction to ChIP-seq data analysis mainly using R, some command line based peak-callers and online software. It provides means to...

Keywords: ChIP-Seq, Peak-calling, Differential-binding, Visualisation, Annotation, Homo-sapiens, R-programming

ChIP-seq analysis using R - Practical talk https://tess.elixir-europe.org/materials/chip-seq-analysis-using-r-practical-talk ChIP-seq is the most commonly used technique to study binding profiles of chromatin proteins, such as TFs or histone modification patterns. This practical is an introduction to ChIP-seq data analysis mainly using R, some command line based peak-callers and online software. It provides means to perform peak calling, annotation, motif search and differential binding analysis. ChIP-Seq, Peak-calling, Differential-binding, Visualisation, Annotation, Homo-sapiens, R-programming

This practical illustrates steps that can be undertaken to assess the quality of the sequencing data. We will start from the fastq files and assess their quality in respect to potential contamination and technical artifacts.

Scientific topics: RNA-Seq

Keywords: ChIP-Seq, RNA-Seq, QC, Data-format, Experimental-design

ChIP-seq analysis using R - Quality Control https://tess.elixir-europe.org/materials/chip-seq-analysis-using-r-quality-control This practical illustrates steps that can be undertaken to assess the quality of the sequencing data. We will start from the fastq files and assess their quality in respect to potential contamination and technical artifacts. RNA-Seq ChIP-Seq, RNA-Seq, QC, Data-format, Experimental-design

This practical illustrates steps that can be undertaken to assess the quality of the sequencing data. We will start from the fastq files and assess their quality in respect to potential contamination and technical artifacts.

Scientific topics: RNA-Seq

Keywords: ChIP-Seq, RNA-Seq, QC, Data-format, Experimental-design

ChIP-seq analysis using R - Quality Control Walkthrough https://tess.elixir-europe.org/materials/chip-seq-analysis-using-r-quality-control-walkthrough This practical illustrates steps that can be undertaken to assess the quality of the sequencing data. We will start from the fastq files and assess their quality in respect to potential contamination and technical artifacts. RNA-Seq ChIP-Seq, RNA-Seq, QC, Data-format, Experimental-design

The main ambition of this workshop is that researchers will be able to handle their data in a more reproducible and efficient way. They should be able to retrieve, view, manipulate, process and manage their own and other one's data. The following topics will be covered during the workshop: ...

Data Carpentry Workshop - Data Management beyond Excel https://tess.elixir-europe.org/materials/data-carpentry-workshop-data-management-beyond-excel The main ambition of this workshop is that researchers will be able to handle their data in a more reproducible and efficient way. They should be able to retrieve, view, manipulate, process and manage their own and other one's data. The following topics will be covered during the workshop: How to use spreadsheet programs (e.g. Excel) more efficiently: what you can and can't do Getting data out of spreadsheets and into more powerful tools (e.g. R) Using databases, managing and querying data in SQL Workflows and automating repetitive tasks, including using command line PhD students post-docs Life Science Researchers 2016-04-22 2016-09-13

Data Carpentry’s aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain. The lessons below were designed for those interested in working with ecology data in R. This is an introduction to R designed for...

Data Carpentry: R for data analysis and visualization of Ecological Data https://tess.elixir-europe.org/materials/data-carpentry-r-for-data-analysis-for-ecology Data Carpentry’s aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain. The lessons below were designed for those interested in working with ecology data in R. This is an introduction to R designed for participants with no programming experience. These lessons can be taught in a day (~ 6 hours). They start with some basic information about R syntax, the RStudio interface, and move through how to import CSV files, the structure of data frames, how to deal with factors, how to add/remove rows and columns, how to calculate summary statistics from a data frame, and a brief introduction to plotting. The last lesson demonstrates how to work with databases directly from R. Data Carpentry’s teaching is hands-on, so participants are encouraged to use their own computers to ensure the proper setup of tools for an efficient workflow. These lessons assume no prior knowledge of the skills or tools, but working through this lesson requires working copies of the software described below. To most effectively use these materials, please make sure to download the data and install everything before working through this lesson. Data files for the lesson are available and can be downloaded manually here: http://dx.doi.org/10.6084/m9.figshare.1314459 2017-08-22

This RData file contains small R objects to use in the [introR.R practice questions](introR.R)

Keywords: R-programming

Data objects for R practice codes https://tess.elixir-europe.org/materials/data-objects-for-r-practice-codes This RData file contains small R objects to use in the [introR.R practice questions](introR.R) R-programming

We organize data in spreadsheets in the ways that we as humans want to work with the data, but computers require that data be organized in particular ways. In order to use tools that make computation more efficient, such as programming languages like R or Python, we need to structure our data...

Data Organization in Spreadsheets https://tess.elixir-europe.org/materials/data-carpentry-spreadsheets-for-ecology We organize data in spreadsheets in the ways that we as humans want to work with the data, but computers require that data be organized in particular ways. In order to use tools that make computation more efficient, such as programming languages like R or Python, we need to structure our data the way that computers need the data. Since this is where most research projects start, this is where we want to start too! In this lesson, you will learn: Much of your time as a researcher will be spent in this ‘data wrangling’ stage. It’s not the most fun, but it is necessary. In this lesson you will learn how to think about data organization and some practices for more effective data wrangling. With this approach you can better format current data and plan new data collection so less data wrangling is needed. Data Carpentry’s teaching is hands-on, so participants are encouraged to use their own computers to insure the proper setup of tools for an efficient workflow. These lessons assume no prior knowledge of the skills or tools. To get started, follow the directions in the “Setup” tab to download data to your computer and follow any installation instructions. 2017-08-22

Day 1 starts at the very beginning of a typical RNA-Seq workflow, explaining the sequencing technology and considerations for experimental design, then starts with hands-on application of working with sequencing data fresh off the sequencer.

Keywords: Alignment, BAM, FASTA, FASTQ, QC

Day 1 - RNA-Seq Analysis https://tess.elixir-europe.org/materials/day-1-rna-seq-analysis Day 1 starts at the very beginning of a typical RNA-Seq workflow, explaining the sequencing technology and considerations for experimental design, then starts with hands-on application of working with sequencing data fresh off the sequencer. Alignment, BAM, FASTA, FASTQ, QC

Day 2 continues throught the steps in a typical RNA-Seq experiment from alignment to sample QC and count normalization, including a brief overview of the IGV Genome Browser.

Keywords: Alignment, BAM, FASTA, FASTQ, QC, Exploratory-analysis, Feature-summarisation, Pre-processing

Day 2 - RNA-Seq Analysis https://tess.elixir-europe.org/materials/day-2-rna-seq-analysis Day 2 continues throught the steps in a typical RNA-Seq experiment from alignment to sample QC and count normalization, including a brief overview of the IGV Genome Browser. Alignment, BAM, FASTA, FASTQ, QC, Exploratory-analysis, Feature-summarisation, Pre-processing

Day 3 focuses on statistical analysis of RNA-Seq data and identification of differentiall expressed genes in multiple comparisons.

Keywords: QC, Exploratory-analysis, Differential-expression, Statistical-model, Pre-processing

Day 3 - RNA-Seq Analysis https://tess.elixir-europe.org/materials/day-3-rna-seq-analysis Day 3 focuses on statistical analysis of RNA-Seq data and identification of differentiall expressed genes in multiple comparisons. QC, Exploratory-analysis, Differential-expression, Statistical-model, Pre-processing

Day 4 focuses on the final steps after production of significant gene lists, including gene clustering, visualization, and annotation.

Keywords: Exploratory-analysis, Differential-expression, Statistical-model, Annotation

Day 4 - RNA-Seq Analysis https://tess.elixir-europe.org/materials/day-4-rna-seq-analysis Day 4 focuses on the final steps after production of significant gene lists, including gene clustering, visualization, and annotation. Exploratory-analysis, Differential-expression, Statistical-model, Annotation

A differential expression analysis conducted on the **[Robinson, Delhomme et al., dataset](https://microasp.upsc.se/ngs_trainers/Materials/blob/master/Datasets/Robinson-Delhomme-Populus-tremula-shows-no-evidence-of-sexual-dimorphism.md)**. The dataset has 17 samples and 2 important meta-data: the...

Scientific topics: RNA-Seq

Keywords: RNA-Seq, Differential-expression, R-programming, Statistical-model

Differential expression analysis on the Robinson, Delhomme et al. dataset. https://tess.elixir-europe.org/materials/differential-expression-analysis-on-the-robinson-delhomme-et-al-dataset A differential expression analysis conducted on the **[Robinson, Delhomme et al., dataset](https://microasp.upsc.se/ngs_trainers/Materials/blob/master/Datasets/Robinson-Delhomme-Populus-tremula-shows-no-evidence-of-sexual-dimorphism.md)**. The dataset has 17 samples and 2 important meta-data: the sample sex and year of collection. The goal is to test whether genes are involved in different processes based on the sex of the tree; _i.e._ is there a sexual dimorphism in _Populus tremula_ trees. It has indeed been hypothesized that male tree should be taller so as to spread their pollen further, whereas female would be more resistant to pests and diseases. The existing literature is contradictory, however it resulted from studies where plants were grown in controlled environment. In the present dataset, plant samples were collected in the wild, at a 2 years interval. The latter is a very important factor in the analysis as the 'year effect' is a strong confounding factor that hides the 'sex effect'. The present tutorial, hence, introduces a differential-expression analysis, but goes further by adressing confounding factors and how to _block_ them in an analysis. It is a good dataset to remind trainees that they should always be critical towards the conclusion they draw from their data. RNA-Seq RNA-Seq, Differential-expression, R-programming, Statistical-model