Register training material
19 materials found

Keywords: Exploratory-analysis  or FAIR  or Statistical-model 


FAIRsharing Educational Material

Whether you are a researcher, standard/database developer, funder, journal editor, librarian or data manager, FAIRsharing can help you understand which standards are mature and appropriate to your use case. By mapping the relationships between standards and the databases that implement them, or...

Keywords: Databases, Standards, Data Policies, FAIR

Resource type: Metadata Registry

FAIRsharing Educational Material https://tess.elixir-europe.org/materials/fairsharing-educational-material Whether you are a researcher, standard/database developer, funder, journal editor, librarian or data manager, FAIRsharing can help you understand which standards are mature and appropriate to your use case. By mapping the relationships between standards and the databases that implement them, or the policies that recommend them, FAIRsharing enables you to make an informed decision as to which standard or database to use or endorse. In this training, educational material, we describe the FAIRsharing resource and explain how you can use it to find the appropriate resource for your work. Databases, Standards, Data Policies, FAIR Researchers data managers data stewards Policy makers database managers biocurators standard developers
InterMine user tutorial

A tutorial for end users of InterMine

Keywords: Data querying, Data analysis, Data download, FAIR

Resource type: Tutorial

InterMine user tutorial https://tess.elixir-europe.org/materials/intermine-user-tutorial A tutorial for end users of InterMine Data querying, Data analysis, Data download, FAIR Life Science Researchers Bioinformaticians
InterMine user manual

Documentation for end users on how to search for data, run simple and complex queries, analyse results and download data from any instance of InterMine.

Keywords: Data querying, data visualization, Data download, FAIR

Resource type: Documentation

InterMine user manual https://tess.elixir-europe.org/materials/intermine-user-manual Documentation for end users on how to search for data, run simple and complex queries, analyse results and download data from any instance of InterMine. Data querying, data visualization, Data download, FAIR Life Science Researchers Bioinformaticians
InterMine operator manual

Documentation on how to install, configure and operate an InterMine instance.

Keywords: Data integration, Data analysis, Data publishing, FAIR

Resource type: Documentation

InterMine operator manual https://tess.elixir-europe.org/materials/intermine-operator-manual Documentation on how to install, configure and operate an InterMine instance. Data integration, Data analysis, Data publishing, FAIR Bioinformaticians software engineers
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
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
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
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
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
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
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
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
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
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
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