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5 materials found

Keywords: RNA-Seq 

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

RNA-seq data analysis using Chipster https://tess.elixir-europe.org/materials/rna-seq-data-analysis-using-chipster Materials from the ELIXIR tutorial “RNA-seq data analysis using Chipster”, Jan 31, 2017 Eija Korpelainen Maria Lehtivaara Transcriptomics Genomics transcriptomics, RNA-Seq, eLearning, EeLP Researchers
Single cell RNA-seq data analysis with R

This hands-on course introduces the participants to single cell RNA-seq data analysis concepts and popular tools and R packages. It covers the preprocessing steps from raw sequence reads to expression matrix as well as clustering, cell type identification, differential expression analysis and...

Scientific topics: RNA-Seq

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

Resource type: course materials

Single cell RNA-seq data analysis with R https://tess.elixir-europe.org/materials/single-cell-rna-seq-data-analysis-with-r This hands-on course introduces the participants to single cell RNA-seq data analysis concepts and popular tools and R packages. It covers the preprocessing steps from raw sequence reads to expression matrix as well as clustering, cell type identification, differential expression analysis and pseudotime analysis. Eija Korpelainen RNA-Seq RNA-Seq, Single Cell technologies, scRNA-seq bioinformaticians Biologists
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 Seurat tools. You will also...

Scientific topics: RNA-Seq

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

Resource type: course materials, Video

Single cell RNA-seq data analysis with Chipster https://tess.elixir-europe.org/materials/single-cell-rna-seq-data-analysis-with-chipster-6cc8f0fb-1c92-444b-ab19-b04fe6454430 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 Seurat tools. You will also learn how to compare two samples and detect conserved cluster markers and differentially expressed genes in them. The user-friendly Chipster software is used in the exercises, so no Unix or R experience is required and the course is thus suitable for everybody. Eija Korpelainen RNA-Seq RNA-Seq, Single Cell technologies, scRNA-seq Biologists bioinformaticians
LXDE RStudio with support for bioconductor tools

An LXDE Rstudio with pre-loaded Bioconductor tools for rna-seq DE analysis & visualisation

Keywords: RNA-Seq, IFR, Institute of Food Research, Quadram Institute

LXDE RStudio with support for bioconductor tools https://tess.elixir-europe.org/materials/lxde-rstudio-with-support-for-bioconductor-tools An LXDE Rstudio with pre-loaded Bioconductor tools for rna-seq DE analysis & visualisation RNA-Seq, IFR, Institute of Food Research, Quadram Institute
IFR Dockerised version of the EBI's Introduction to RNA-seq course

This is basically the EBI RNA-seq course bundled up in a Docker container using LXDE via TightVNC to provide a graphical environment. The material has been repackaged to use an Ipython Notebook as the learning environment which can be annotated by the learner.

Keywords: RNA-Seq, IFR, Institute of Food Research, Quadram Institute

IFR Dockerised version of the EBI's Introduction to RNA-seq course https://tess.elixir-europe.org/materials/ifr-dockerised-version-of-the-ebi-s-introduction-to-rna-seq-course This is basically the EBI RNA-seq course bundled up in a Docker container using LXDE via TightVNC to provide a graphical environment. The material has been repackaged to use an Ipython Notebook as the learning environment which can be annotated by the learner. RNA-Seq, IFR, Institute of Food Research, Quadram Institute