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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
Guidelines for this folder

No description available

Guidelines for this folder https://tess.elixir-europe.org/materials/guidelines-for-this-folder No description available
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
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.

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
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
Introduction to NGS and RNA-seq

No description available

Keywords: HTS-introduction, Data-format, Alignment, Differential-expression, Feature-summarisation, QC

Introduction to NGS and RNA-seq https://tess.elixir-europe.org/materials/introduction-to-ngs-and-rna-seq No description available HTS-introduction, Data-format, Alignment, Differential-expression, Feature-summarisation, QC
RNA-seq module Frederik Coppens

All material concerning RNA-seq analysis

Scientific topics: RNA-Seq

Keywords: RNA-Seq, Alignment, BAM, FASTQ, Feature-summarisation, Pre-processing, QC

RNA-seq module Frederik Coppens https://tess.elixir-europe.org/materials/rna-seq-module-frederik-coppens All material concerning RNA-seq analysis RNA-Seq RNA-Seq, Alignment, BAM, FASTQ, Feature-summarisation, Pre-processing, QC
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
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, 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
Alignment

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
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.

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
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
Introduction to HTS

No description available

Keywords: HTS-introduction

Introduction to HTS https://tess.elixir-europe.org/materials/introduction-to-ngs No description available HTS-introduction
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
NGS introduction to file formats

This sub-module gives an overview of the most used file formats in Next Generation Sequencing analysis

Keywords: HTS-introduction, FASTQ, BAM, VCF, WIG, CRAM, GFF3

NGS introduction to file formats https://tess.elixir-europe.org/materials/ngs-introduction-to-file-formats This sub-module gives an overview of the most used file formats in Next Generation Sequencing analysis HTS-introduction, FASTQ, BAM, VCF, WIG, CRAM, GFF3
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
Quality Control

This is an introduction to the tools available for performing the technical QA of RNA-Seq data and to their results, singling out possible common caveats.

Scientific topics: RNA-Seq

Keywords: FASTQ, RNA-Seq, Pre-processing, QC

Quality Control https://tess.elixir-europe.org/materials/quality-control This is an introduction to the tools available for performing the technical QA of RNA-Seq data and to their results, singling out possible common caveats. RNA-Seq FASTQ, RNA-Seq, Pre-processing, QC
NGS introduction to sequencing platforms

This sub-module gives an overview of the most used sequencing platforms and their applications.

Keywords: HTS-introduction

NGS introduction to sequencing platforms https://tess.elixir-europe.org/materials/ngs-introduction-to-sequencing-platforms This sub-module gives an overview of the most used sequencing platforms and their applications. HTS-introduction