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18 materials found

Authors: David Wishart  or Eija Korpelainen 


Single cell RNA-seq data analysis using Chipster

This course introduces single cell RNA-seq data analysis methods, tools and file formats. It covers the processing of transcript counts from quality control and filtering to dimensional reduction, clustering, and differential expression analysis. You will also learn how to do integrated analysis...

Keywords: scRNA-seq

Resource type: Slides, Training materials

ELIXIR eLearning definitions

Materials from the asynchronous learning course "ELIXIR eLearning definitions"

Keywords: eLearning, training, EeLP

Resource type: course materials, Training materials, Documentation

RNA-seq data analysis using Chipster

Materials from the ELIXIR tutorial “RNA-seq data analysis using Chipster”, Jan 31, 2017

Scientific topics: Transcriptomics, Genomics

Keywords: transcriptomics, RNA-Seq, eLearning, EeLP

Resource type: course materials, Training materials, Slides, Video

Single cell RNA-seq data analysis with Chipster

This course introduces single cell RNA-seq data analysis methods, tools and file formats. It covers the preprocessing steps of DropSeq data from raw reads to a digital gene expression matrix (DGE), and how to find sub-populations of cells using clustering with the...

Scientific topics: RNA-Seq

Keywords: RNA-Seq, Single Cell technologies, scRNA-seq

Resource type: course materials, Video

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.

Community analysis of amplicon sequencing data (16S rRNA)

This course introduces community analysis of amplicon sequencing data (16S rRNA). It covers preprocessing, taxonomic classification, and statistical analysis for marker gene studies. The user-friendly Chipster software is used in the exercises, so no Unix or R experience is required and the...

Resource type: course materials, Video

Virus detection using small RNA-seq

This course introduces the VirusDetect pipeline covering all the analysis steps and file formats. VirusDetect allows you to detect known viruses and identify news ones by sequencing small RNAs (siRNA) in host samples. siRNA sequences are assembled to contigs and compared to known virus sequences....

Scientific topics: RNA-Seq

Resource type: course materials, Video

RNA-seq data analysis

This course introduces RNA-seq data analysis methods, tools and file formats. It covers all the steps from quality control and alignment to quantification and differential expression analysis, and also experimental design is discussed. The user-friendly Chipster software is used in the exercises,...

Scientific topics: RNA-Seq

Resource type: course materials, Video

Metagenomics data analysis

Metagenomics investigates the composition and function of microbial communities in different environments based on direct isolation of genetic material. It has been accelerated by the advances in high-throughput sequencing technologies, and the increasing data sizes require efficient analysis...

Scientific topics: Metagenomics

Resource type: Video, course materials

RNA-seq data analysis: from raw reads to differentially expressed genes

This course material introduces the central concepts, analysis steps and file formats in RNA-seq data analysis. It covers the analysis from quality control to differential expression detection, and workflow construction and several data visualizations are also practised. The material consists of...

Scientific topics: Sequencing, RNA, Data architecture, analysis and design, Bioinformatics

Keywords: Bioinformatics, Differential expression, Ngs, Rna seq