Register training material
29 materials found

Keywords: Exploratory-analysis  or R-programming 


Introduction to R and Bioconductor lecture

This reference handout goes over how to read and parse a line of complex R code.

Keywords: R-programming

Introduction to R and Bioconductor lecture https://tess.elixir-europe.org/materials/introduction-to-r-and-bioconductor-lecture-990e00de-2241-49f5-9577-5c110cc06a64 This reference handout goes over how to read and parse a line of complex R code. R-programming
RNA-seq module Frederik Coppens

Material concerning RNA-seq analysis, with an emphasis on the statistical aspects.

Keywords: FASTQ, Alignment, BAM, Differential-expression, Statistical-model, Exploratory-analysis

RNA-seq module Frederik Coppens https://tess.elixir-europe.org/materials/rna-seq-module-frederik-coppens-4a328fa8-0bef-471c-84e4-b0d89d216128 Material concerning RNA-seq analysis, with an emphasis on the statistical aspects. FASTQ, Alignment, BAM, Differential-expression, Statistical-model, Exploratory-analysis
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...

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 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...

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
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...

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
Variant-calling

No description available

Keywords: Alignment, Annotation, BAM, BCF, De-novo-transcriptome-assembly, Exploratory-analysis, FASTQ, Pre-processing, QC, Statistical-model, Variant-calling, VCF

Variant-calling https://tess.elixir-europe.org/materials/variant-calling No description available Alignment, Annotation, BAM, BCF, De-novo-transcriptome-assembly, Exploratory-analysis, FASTQ, Pre-processing, QC, Statistical-model, Variant-calling, VCF
Guide to R swirl interactive lessons

This handout describes how to download the swirl package and start the basic interactive lessons to learn R.

Keywords: R-programming

Guide to R swirl interactive lessons https://tess.elixir-europe.org/materials/guide-to-r-swirl-interactive-lessons This handout describes how to download the swirl package and start the basic interactive lessons to learn R. R-programming
Day 4 - RNA-Seq Analysis

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
Statistics and RNA-Seq

This lecture and optional practical introduce the relevant statistical concepts along with its computational counterparts used on a common RNA-Seq data analysis workflow.

Keywords: FASTQ, Alignment, BAM, Differential-expression, Statistical-model, Exploratory-analysis

Statistics and RNA-Seq https://tess.elixir-europe.org/materials/statistics-and-rna-seq This lecture and optional practical introduce the relevant statistical concepts along with its computational counterparts used on a common RNA-Seq data analysis workflow. FASTQ, Alignment, BAM, Differential-expression, Statistical-model, Exploratory-analysis
Introduction to R practice codes

These codes give an overview of R object types and programming language structure.

Keywords: R-programming

Introduction to R practice codes https://tess.elixir-europe.org/materials/introduction-to-r-practice-codes These codes give an overview of R object types and programming language structure. R-programming
R/Bioconductor installation and upgrade guide

This handout describes how to download R and install add-on packages, both from CRAN and

Keywords: R-programming

R/Bioconductor installation and upgrade guide https://tess.elixir-europe.org/materials/r-bioconductor-installation-and-upgrade-guide This handout describes how to download R and install add-on packages, both from CRAN and R-programming
Material for the course RNA-seq data analysis with Chipster

This material covers the whole RNA-seq data analysis pipeline, from quality control of raw reads to differential expression analysis.

Scientific topics: RNA-Seq

Keywords: RNA-Seq, FASTQ, QC, Pre-processing, Alignment, BAM, Expression-estimation, Feature-summarisation, Differential-expression, Statistical-model, Exploratory-analysis

Material for the course RNA-seq data analysis with Chipster https://tess.elixir-europe.org/materials/material-for-the-course-rna-seq-data-analysis-with-chipster This material covers the whole RNA-seq data analysis pipeline, from quality control of raw reads to differential expression analysis. RNA-Seq RNA-Seq, FASTQ, QC, Pre-processing, Alignment, BAM, Expression-estimation, Feature-summarisation, Differential-expression, Statistical-model, Exploratory-analysis
Nicolas Delhomme and Bastian Schiffthaler

This merely lists the various courses at which we taught RNA-Seq data

Scientific topics: RNA-Seq

Keywords: FASTQ, GFF3, BAM, Populus-tremula, RNA-Seq, Pre-processing, QC, Alignment, Annotation, Expression-estimation, Differential-expression, R-programming

Nicolas Delhomme and Bastian Schiffthaler https://tess.elixir-europe.org/materials/nicolas-delhomme-and-bastian-schiffthaler This merely lists the various courses at which we taught RNA-Seq data RNA-Seq FASTQ, GFF3, BAM, Populus-tremula, RNA-Seq, Pre-processing, QC, Alignment, Annotation, Expression-estimation, Differential-expression, R-programming
Day 3 - RNA-Seq Analysis

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
Tutorial

This file describes the main tutorial PDF file. Almost all tutorials and hands-on practices are indeed collated in a single document. In addition to this PDF, R code excerpts and installation instructions are also provided.

Scientific topics: RNA-Seq

Keywords: FASTQ, GFF3, BAM, Populus-tremula, RNA-Seq, Pre-processing, QC, Alignment, Annotation, Expression-estimation, R-programming

Tutorial https://tess.elixir-europe.org/materials/tutorial This file describes the main tutorial PDF file. Almost all tutorials and hands-on practices are indeed collated in a single document. In addition to this PDF, R code excerpts and installation instructions are also provided. RNA-Seq FASTQ, GFF3, BAM, Populus-tremula, RNA-Seq, Pre-processing, QC, Alignment, Annotation, Expression-estimation, R-programming
Prerequisite

No description available

Scientific topics: Statistics and probability

Keywords: Unix, Linux, R-programming, Statistics

Prerequisite https://tess.elixir-europe.org/materials/prerequisite No description available Statistics and probability Unix, Linux, R-programming, Statistics
Intro to R and Bioconductor

R is a free, open-source software environment and programming language for statistical computing and graphics. It is available for all computer platforms and is widely used, and many packages have been developed in the Bioconductor project for analysis of genomic data. This module covers the...

Keywords: Prerequisite, R-programming

Intro to R and Bioconductor https://tess.elixir-europe.org/materials/intro-to-r-and-bioconductor R is a free, open-source software environment and programming language for statistical computing and graphics. It is available for all computer platforms and is widely used, and many packages have been developed in the Bioconductor project for analysis of genomic data. This module covers the basic skills that will be needed before using R to analyze NGS data. Prerequisite, R-programming
RNA-Seq Analysis with Biocluster and R

Sequencing of RNA (RNA-Seq) is the latest method to assess global gene expression because it

Scientific topics: RNA-Seq

Keywords: RNA-Seq, Alignment, Annotation, BAM, Differential-expression, Exploratory-analysis, Expression-estimation, FASTA, FASTQ, Feature-summarisation, Pre-processing, QC, Statistical-model

RNA-Seq Analysis with Biocluster and R https://tess.elixir-europe.org/materials/rna-seq-analysis-with-biocluster-and-r Sequencing of RNA (RNA-Seq) is the latest method to assess global gene expression because it RNA-Seq RNA-Seq, Alignment, Annotation, BAM, Differential-expression, Exploratory-analysis, Expression-estimation, FASTA, FASTQ, Feature-summarisation, Pre-processing, QC, Statistical-model
Material provided by Charlotte Soneson

This folder contains material provided by Charlotte Soneson. The following material is included:

Scientific topics: RNA-Seq

Keywords: RNA-Seq, Differential-expression, Statistical-model, Exploratory-analysis

Material provided by Charlotte Soneson https://tess.elixir-europe.org/materials/material-provided-by-charlotte-soneson This folder contains material provided by Charlotte Soneson. The following material is included: RNA-Seq RNA-Seq, Differential-expression, Statistical-model, Exploratory-analysis
RNA-seq module Eija Korpelainen

All material concerning RNA-seq data analysis with Chipster

Keywords: FASTQ, QC, Pre-processing, Alignment, BAM, Expression-estimation, Feature-summarisation, Differential-expression, Statistical-model, Exploratory-analysis

RNA-seq module Eija Korpelainen https://tess.elixir-europe.org/materials/rna-seq-module-eija-korpelainen All material concerning RNA-seq data analysis with Chipster FASTQ, QC, Pre-processing, Alignment, BAM, Expression-estimation, Feature-summarisation, Differential-expression, Statistical-model, Exploratory-analysis
Introduction to R and Bioconductor lecture

This lecture gives an overview of the R and Bioconductor projects, plus the basics of R object types and programming language structure.

Keywords: R-programming

Introduction to R and Bioconductor lecture https://tess.elixir-europe.org/materials/introduction-to-r-and-bioconductor-lecture This lecture gives an overview of the R and Bioconductor projects, plus the basics of R object types and programming language structure. R-programming
Nicolas Delhomme - Bastian Schiffthaler - October 2014 EMBO course material

Material for the course held on EBI Campus, Welcome Trust Center, Hinxton, UK on 20-26th, October 2014. The material cover general RNA-Seq data pre-processing as described in these [guidelines](http://www.epigenesys.eu/en/protocols/bio-informatics/1283-guidelines-for-rna-seq-data-analysis) and...

Scientific topics: RNA-Seq

Keywords: FASTQ, GFF3, BAM, Populus-tremula, RNA-Seq, Pre-processing, QC, Alignment, Annotation, Expression-estimation, Differential-expression, R-programming

Nicolas Delhomme - Bastian Schiffthaler - October 2014 EMBO course material https://tess.elixir-europe.org/materials/nicolas-delhomme-bastian-schiffthaler-october-2014-embo-course-material Material for the course held on EBI Campus, Welcome Trust Center, Hinxton, UK on 20-26th, October 2014. The material cover general RNA-Seq data pre-processing as described in these [guidelines](http://www.epigenesys.eu/en/protocols/bio-informatics/1283-guidelines-for-rna-seq-data-analysis) and reproduces the Differential Expression analysis conducted in Robinson, Delhomme et al., 2014. RNA-Seq FASTQ, GFF3, BAM, Populus-tremula, RNA-Seq, Pre-processing, QC, Alignment, Annotation, Expression-estimation, Differential-expression, R-programming
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...

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
Exercises for the course RNA-seq data analysis with Chipster

This practical covers the whole RNA-seq data analysis pipeline, from quality control of raw reads to differential expression analysis, using the free Chipster software. Material updated in Dec 2015.

Keywords: FASTQ, QC, Pre-processing, Alignment, BAM, Expression-estimation, Feature-summarisation, Differential-expression, Statistical-model, Exploratory-analysis

Exercises for the course RNA-seq data analysis with Chipster https://tess.elixir-europe.org/materials/exercises-for-the-course-rna-seq-data-analysis-with-chipster This practical covers the whole RNA-seq data analysis pipeline, from quality control of raw reads to differential expression analysis, using the free Chipster software. Material updated in Dec 2015. FASTQ, QC, Pre-processing, Alignment, BAM, Expression-estimation, Feature-summarisation, Differential-expression, Statistical-model, Exploratory-analysis
Data objects for R practice codes

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
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.

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
Lecture slides for the course RNA-seq data analysis with Chipster

This material covers the whole RNA-seq data analysis pipeline, from quality control of raw reads to differential expression analysis. It discusses also experimental design. Material updated in Dec 2015.

Keywords: FASTQ, QC, Pre-processing, Alignment, BAM, Expression-estimation, Feature-summarisation, Differential-expression, Statistical-model, Exploratory-analysis

Lecture slides for the course RNA-seq data analysis with Chipster https://tess.elixir-europe.org/materials/lecture-slides-for-the-course-rna-seq-data-analysis-with-chipster This material covers the whole RNA-seq data analysis pipeline, from quality control of raw reads to differential expression analysis. It discusses also experimental design. Material updated in Dec 2015. FASTQ, QC, Pre-processing, Alignment, BAM, Expression-estimation, Feature-summarisation, Differential-expression, Statistical-model, Exploratory-analysis
EMBO High Throughput Sequencing Data Analysis, Cambridge, UK, 2014

No description available

Scientific topics: RNA-Seq

Keywords: FASTQ, GFF3, BAM, Populus-tremula, RNA-Seq, Pre-processing, QC, Alignment, Annotation, Expression-estimation, Differential-expression, R-programming

EMBO High Throughput Sequencing Data Analysis, Cambridge, UK, 2014 https://tess.elixir-europe.org/materials/embo-high-throughput-sequencing-data-analysis-cambridge-uk-2014 No description available RNA-Seq FASTQ, GFF3, BAM, Populus-tremula, RNA-Seq, Pre-processing, QC, Alignment, Annotation, Expression-estimation, Differential-expression, R-programming
Exploratory analysis and downstream analysis

This lecture gives an overview of exploratory analysis (clustering) and supervised analysis (prediction/classification), as well as visualization methods (heatmaps/PCA) and gene set analysis. It also shows how to transform count data to make it more suitable to apply the traditional methods...

Keywords: Statistical-model, Exploratory-analysis

Exploratory analysis and downstream analysis https://tess.elixir-europe.org/materials/exploratory-analysis-and-downstream-analysis This lecture gives an overview of exploratory analysis (clustering) and supervised analysis (prediction/classification), as well as visualization methods (heatmaps/PCA) and gene set analysis. It also shows how to transform count data to make it more suitable to apply the traditional methods developed (e.g.) for microarray data. Statistical-model, Exploratory-analysis