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14 materials found

Authors: Jared Simpson  or Levi Waldron 


Meta-analysis of genomics experiments using Bioconductor

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: Meta-analysis

Meta-analysis of genomics experiments using Bioconductor https://tess.elixir-europe.org/materials/meta-analysis-of-genomics-experiments-using-bioconductor 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. Meta-analysis
Trends in Genomic Data Analysis in R

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: R/Bioconductor

Trends in Genomic Data Analysis in R https://tess.elixir-europe.org/materials/trends-in-genomic-data-analysis-in-r 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. R/Bioconductor
Meta-analysis

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...

Scientific topics: Statistics and probability

Meta-analysis https://tess.elixir-europe.org/materials/meta-analysis 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. Statistics and probability
Resampling methods

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...

Scientific topics: Statistics and probability

Resampling methods https://tess.elixir-europe.org/materials/resampling-methods 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. Statistics and probability
Introduction to linear models

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...

Scientific topics: Statistics and probability

Introduction to linear models https://tess.elixir-europe.org/materials/introduction-to-linear-models 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. Statistics and probability
Informatics on High-Throughput Sequencing Data 2018 Module 6-De Novo Assmebly

Course covers the bioinformatics tools available for managing and interpreting high-throughput sequencing data, where the focus is on Illumina reads although information is applicable to all sequencer reads.

Informatics on High-Throughput Sequencing Data 2018 Module 6-De Novo Assmebly https://tess.elixir-europe.org/materials/informatics-on-high-throughput-sequencing-data-2018-module-6-de-novo-assmebly Course covers the bioinformatics tools available for managing and interpreting high-throughput sequencing data, where the focus is on Illumina reads although information is applicable to all sequencer reads. Researchers Post-Doctoral Fellows Biologists, Genomicists, Computer Scientists Graduate students
Informatics on High-Throughput Sequencing Data 2018 Module 1-Introduction to High-Throughput Sequencing

Course covers the bioinformatics tools available for managing and interpreting high-throughput sequencing data, where the focus is on Illumina reads although information is applicable to all sequencer reads.

Informatics on High-Throughput Sequencing Data 2018 Module 1-Introduction to High-Throughput Sequencing https://tess.elixir-europe.org/materials/informatics-on-high-throughput-sequencing-data-2018-module-1-introduction-to-high-throughput-sequencing Course covers the bioinformatics tools available for managing and interpreting high-throughput sequencing data, where the focus is on Illumina reads although information is applicable to all sequencer reads. Researchers Graduate students Post-Doctoral Fellows Biologists, Genomicists, Computer Scientists
Bioinformatics for Cancer Genomics 2018 Module 5-Genome Assembly

Course covers the key bioinformatics concepts and tools required to analyze cancer genomic data sets and access and work with data sets in the cloud.

Bioinformatics for Cancer Genomics 2018 Module 5-Genome Assembly https://tess.elixir-europe.org/materials/bioinformatics-for-cancer-genomics-2018-module-5-genome-assembly Course covers the key bioinformatics concepts and tools required to analyze cancer genomic data sets and access and work with data sets in the cloud. Researchers Graduate students Biologists, Genomicists, Computer Scientists Post-Doctoral Fellows
Bioinformatics for Cancer Genomics 2018 Module 4-Genome Alignment

Course covers the key bioinformatics concepts and tools required to analyze cancer genomic data sets and access and work with data sets in the cloud.

Bioinformatics for Cancer Genomics 2018 Module 4-Genome Alignment https://tess.elixir-europe.org/materials/bioinformatics-for-cancer-genomics-2018-module-4-genome-alignment Course covers the key bioinformatics concepts and tools required to analyze cancer genomic data sets and access and work with data sets in the cloud. Researchers Graduate students Biologists, Genomicists, Computer Scientists Post-Doctoral Fellows
Bioinformatics for Cancer Genomics 2017 Module 3-Genome Alignment and Assembly

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

Bioinformatics for Cancer Genomics 2017 Module 3-Genome Alignment and Assembly https://tess.elixir-europe.org/materials/bioinformatics-for-cancer-genomics-2017-module-3-genome-alignment-and-assembly Course covers the bioinformatics tools required to analyze genomic data sets. Researchers Graduate students Biologists, Genomicists, Computer Scientists Post-Doctoral Fellows
Informatics on High-Throughput Sequencing Data 2017 Module 6-De Novo Assembly

Course covers the bioinformatics tools available for managing and interpreting high-throughput sequencing data with a focus on Illumina reads.

Informatics on High-Throughput Sequencing Data 2017 Module 6-De Novo Assembly https://tess.elixir-europe.org/materials/informatics-on-high-throughput-sequencing-data-2017-module-6-de-novo-assembly Course covers the bioinformatics tools available for managing and interpreting high-throughput sequencing data with a focus on Illumina reads. Researchers Graduate Students Post-Doctoral Fellows Biologists, Genomicists, Computer Scientists
Informatics on High-Throughput Sequencing Data 2017 Module 1-Introduction to High-Throughput Sequencing

Course covers the bioinformatics tools available for managing and interpreting high-throughput sequencing data with a focus on Illumina reads.

Informatics on High-Throughput Sequencing Data 2017 Module 1-Introduction to High-Throughput Sequencing https://tess.elixir-europe.org/materials/informatics-on-high-throughput-sequencing-data-module-1-introduction-to-high-throughput-sequencing Course covers the bioinformatics tools available for managing and interpreting high-throughput sequencing data with a focus on Illumina reads. Researchers Graduate students Biologists, Genomicists, Computer Scientists Post-Doctoral Fellows
High-Throughput Biology 2017 Module 6-De Novo Assembly

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 6-De Novo Assembly https://tess.elixir-europe.org/materials/high-throughput-biology-2017-module-6-de-novo-assembly Course covers the key bioinformatics concepts and tools required to analyze DNA- and RNA- sequence reads using a reference genome. Researchers Graduate students Biologists, Genomicists, Computer Scientists Post-Doctoral Fellows
High-Throughput Biology 2017 Module 1-Introduction to High-Throughput Sequencing

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 1-Introduction to High-Throughput Sequencing https://tess.elixir-europe.org/materials/high-throughput-biology-2017-module-1-introduction-to-high-throughput-sequencing 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