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9 materials found

Authors: Obi Griffith  or Charlotte Soneson  or Anna Goldenberg 


Microbial genomics

Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. It has two releases each year, 1560 software packages, and an...

Keywords: Microbiome

Microbial genomics https://tess.elixir-europe.org/materials/microbial-genomics Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. It has two releases each year, 1560 software packages, and an active user community. Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images. Microbiome
Experimental design

Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. It has two releases each year, 1560 software packages, and an...

Keywords: Experimental design

Experimental design https://tess.elixir-europe.org/materials/experimental-design Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. It has two releases each year, 1560 software packages, and an active user community. Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images. Experimental design
New RNA-seq workflows

Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. It has two releases each year, 1560 software packages, and an...

Keywords: RNAseq

New RNA-seq workflows https://tess.elixir-europe.org/materials/new-rna-seq-workflows Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor uses the R statistical programming language, and is open source and open development. It has two releases each year, 1560 software packages, and an active user community. Bioconductor is also available as an AMI (Amazon Machine Image) and a series of Docker images. RNAseq
Bioinformatics of Genomic Medicine 2018 Module 7-Identifying Integrative Subtypes and Building Classifiers

Course will explore various aspects of genomic medicine, covering and teaching popular tools and methods in the field.

Bioinformatics of Genomic Medicine 2018 Module 7-Identifying Integrative Subtypes and Building Classifiers https://tess.elixir-europe.org/materials/bioinformatics-of-genomic-medicine-2018-module-7-identifying-integrative-subtypes-and-building-classifiers Course will explore various aspects of genomic medicine, covering and teaching popular tools and methods in the field. Researchers Post-Doctoral Fellows Graduate students Biologists, Genomicists, Computer Scientists
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
Bioinformatics for Cancer Genomics 2017 Module 9-Clinical Data Integration

Course covers the bioinformatics tools required to analyze genomic data sets.

Bioinformatics for Cancer Genomics 2017 Module 9-Clinical Data Integration https://tess.elixir-europe.org/materials/bioinformatics-for-cancer-genomics-2017-module-9-clinical-data-integration Course covers the bioinformatics tools required to analyze genomic data sets. Graduate students Researchers Post-Doctoral Fellows Biologists, Genomicists, Computer Scientists
Bioinformatics of Genomic Medicine 2017 Module 7-Patient Similarity Fusion

Course covers various aspects of genomic medicine, covering and teaching popular tools and methods in the field.

Bioinformatics of Genomic Medicine 2017 Module 7-Patient Similarity Fusion https://tess.elixir-europe.org/materials/bioinformatics-of-genomic-medicine-module-7-patient-similarity-fusion Course covers various aspects of genomic medicine, covering and teaching popular tools and methods in the field. Graduate students Researchers 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