Register training material
23 materials found

Authors: David Wishart  or Martin Morgan 


Evening session: Efficient 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: Big data

Lab 9-1: Efficient and Parallel Evaluation

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: Big data

Lecture 20-1: Working with Large Data

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: Big data

Lecture 19: Gene Set Enrichment 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...

Keywords: GSEA

Lab 1: Introduction to R and 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: introduction

Lecture 1: Introduction to R and 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: introduction

06: Gene Set Enrichment 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...

Keywords: Intro

05: Bioconductor Annotation Resources

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: Intro

06: Gene Set Enrichment -- Introduction

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: Intro

04: Practical: Organizing data with SummarizedExperiment

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: Intro

03: Core approaches in 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: Intro

02: Practical: R / Bioconductor and Reproducible Research

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: Intro

01: Introduction to R and 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: Intro

Developing robust and efficient code

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: Workshop

Informatics and Statistics for Metabolomics 2018 Module 6-Future of Metabolomics

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2018 Module 3-Databases for Chemical, Spectral, and Biological Data

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2018 Module 2-Metabolite Identification and Annotation

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2018 Module 1-Introduction to Metabolomics

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2017 Module 6-Future of Metabolomics

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2017 Module 5-MetaboAnalyst

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2017 Module 3-Databases for Chemical, Spectral, and Biological Data

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2017 Module 2-Metabolite Identification and Annotation

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases.

Informatics and Statistics for Metabolomics 2017 Module 1-Introduction to Metabolomics

Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases.