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Authors: Obi Griffith  or Charlotte Soneson @charlott... 


Informatics for RNA-Seq Analysis 2018 Module 3-Expression and Differential Expression

Course providing an introduction to RNA-seq data analysis followed by integrated tutorials demonstrating the use of popular RNA-seq analysis packages.

Informatics for RNA-Seq Analysis 2018 Module 3-Expression and Differential Expression https://tess.elixir-europe.org/materials/informatics-for-rna-seq-analysis-2018-module-3-expression-and-differential-expression Course providing an introduction to RNA-seq data analysis followed by integrated tutorials demonstrating the use of popular RNA-seq analysis packages. Researchers Biologists, Genomicists, Computer Scientists Graduate Students Post-Doctoral Fellows
Informatics for RNA-Seq Analysis 2017 Module 3-Expression and Differential Expression

Course providing an introduction to RNA-seq data analysis followed by integrated tutorials demonstrating the use of popular RNA-seq analysis packages.

Informatics for RNA-Seq Analysis 2017 Module 3-Expression and Differential Expression https://tess.elixir-europe.org/materials/informatics-for-rna-seq-analysis-2017-module-3-expression-and-differential-expression Course providing an introduction to RNA-seq data analysis followed by integrated tutorials demonstrating the use of popular RNA-seq analysis packages. Researchers Graduate Students Biologists, Genomicists, Computer Scientists Post-Doctoral Fellows
High-Throughput Biology 2017 Module 9-Expression and Differential Expression

Course covers the key bioinformatics concepts and tools required to analyze DNA- and RNA- sequence reads using a reference genome.

High-Throughput Biology 2017 Module 9-Expression and Differential Expression https://tess.elixir-europe.org/materials/high-throughput-biology-2017-module-9-expression-and-differential-expression Course covers the key bioinformatics concepts and tools required to analyze DNA- and RNA- sequence reads using a reference genome. Graduate students Post-Doctoral Fellows Researchers Biologists, Genomicists, Computer Scientists
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
Differential expression analysis

This lecture covers the process from count matrix to statistical analysis results (differential expression). More specifically, it covers experimental design, normalization, statistical modeling and parameter estimation, multiple hypothesis testing and a more detailed look at some of the most...

Keywords: Differential-expression, Statistical-model

Differential expression analysis https://tess.elixir-europe.org/materials/differential-expression-analysis This lecture covers the process from count matrix to statistical analysis results (differential expression). More specifically, it covers experimental design, normalization, statistical modeling and parameter estimation, multiple hypothesis testing and a more detailed look at some of the most common differential expression methods as well as a comparison between them. Differential-expression, Statistical-model
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