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12 materials found

Keywords: Experimental-design  or RNAseq 


End-to-end RNA-Seq workflow

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

End-to-end RNA-Seq workflow https://tess.elixir-europe.org/materials/end-to-end-rna-seq-workflow 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
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
RNA-seq data analysis and differential expression

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

RNA-seq data analysis and differential expression https://tess.elixir-europe.org/materials/rna-seq-data-analysis-and-differential-expression 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
An RNA-seq work flow

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

An RNA-seq work flow https://tess.elixir-europe.org/materials/an-rna-seq-work-flow 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
ChIP-seq analysis using R - Experimental design and peak calling.

This lecture is an introduction to ChIP-seq experiments and data. It provides a theoretical background to experimental design and peak calling.

Keywords: ChIP-Seq, Experimental-design, Peak-calling, Visualisation

ChIP-seq analysis using R - Experimental design and peak calling. https://tess.elixir-europe.org/materials/chip-seq-analysis-using-r-experimental-design-and-peak-calling-cfd4c18f-6c86-45ae-ab0b-630422c76af6 This lecture is an introduction to ChIP-seq experiments and data. It provides a theoretical background to experimental design and peak calling. ChIP-Seq, Experimental-design, Peak-calling, Visualisation
ChIP-seq analysis using R

ChIP-seq is the most commonly used technique to study binding profiles of chromatin proteins, such as TFs or histone modification patterns. This course is an introduction to ChIP-seq data, and data analysis mainly using R, some command line based peak-callers and online software. It provides a...

Keywords: ChIP-Seq, Experimental-design, Peak-calling, Differential-binding, Visualisation, Annotation, Homo-sapiens, R-programming

ChIP-seq analysis using R https://tess.elixir-europe.org/materials/chip-seq-analysis-using-r-5049bc9c-9bbb-4a6b-9244-37ed3980da0e ChIP-seq is the most commonly used technique to study binding profiles of chromatin proteins, such as TFs or histone modification patterns. This course is an introduction to ChIP-seq data, and data analysis mainly using R, some command line based peak-callers and online software. It provides a theoretical background and the means to perform peak calling and differential binding analysis. ChIP-Seq, Experimental-design, Peak-calling, Differential-binding, Visualisation, Annotation, Homo-sapiens, R-programming
ChIP-seq analysis using R - Experimental design and peak calling.

This lecture is an introduction to ChIP-seq experiments and data. It provides a theoretical background to experimental design and peak calling.

Keywords: ChIP-Seq, Experimental-design, Peak-calling, Visualisation

ChIP-seq analysis using R - Experimental design and peak calling. https://tess.elixir-europe.org/materials/chip-seq-analysis-using-r-experimental-design-and-peak-calling This lecture is an introduction to ChIP-seq experiments and data. It provides a theoretical background to experimental design and peak calling. ChIP-Seq, Experimental-design, Peak-calling, Visualisation
ChIP-seq analysis using R - Quality Control

This practical illustrates steps that can be undertaken to assess the quality of the sequencing data. We will start from the fastq files and assess their quality in respect to potential contamination and technical artifacts.

Scientific topics: RNA-Seq

Keywords: ChIP-Seq, RNA-Seq, QC, Data-format, Experimental-design

ChIP-seq analysis using R - Quality Control https://tess.elixir-europe.org/materials/chip-seq-analysis-using-r-quality-control This practical illustrates steps that can be undertaken to assess the quality of the sequencing data. We will start from the fastq files and assess their quality in respect to potential contamination and technical artifacts. RNA-Seq ChIP-Seq, RNA-Seq, QC, Data-format, Experimental-design
ChIP-seq analysis using R - File formats and QC

This lecture introduces the file formats of sequencing data before alignment and covers the general quality control of sequencing data focussing on RNA-Seq and ChIP-Seq.

Scientific topics: RNA-Seq

Keywords: ChIP-Seq, RNA-Seq, QC, Data-format, Experimental-design

ChIP-seq analysis using R - File formats and QC https://tess.elixir-europe.org/materials/chip-seq-analysis-using-r-file-formats-and-qc This lecture introduces the file formats of sequencing data before alignment and covers the general quality control of sequencing data focussing on RNA-Seq and ChIP-Seq. RNA-Seq ChIP-Seq, RNA-Seq, QC, Data-format, Experimental-design
ChIP-seq analysis using R - Quality Control Walkthrough

This practical illustrates steps that can be undertaken to assess the quality of the sequencing data. We will start from the fastq files and assess their quality in respect to potential contamination and technical artifacts.

Scientific topics: RNA-Seq

Keywords: ChIP-Seq, RNA-Seq, QC, Data-format, Experimental-design

ChIP-seq analysis using R - Quality Control Walkthrough https://tess.elixir-europe.org/materials/chip-seq-analysis-using-r-quality-control-walkthrough This practical illustrates steps that can be undertaken to assess the quality of the sequencing data. We will start from the fastq files and assess their quality in respect to potential contamination and technical artifacts. RNA-Seq ChIP-Seq, RNA-Seq, QC, Data-format, Experimental-design
ChIP-Seq

No description available

Keywords: ChIP-Seq, Experimental-design, QC, ChIP-Seq-QC, Data-format, Alignment, Peak-calling, Differential-binding, Annotation

ChIP-Seq https://tess.elixir-europe.org/materials/chip-seq No description available ChIP-Seq, Experimental-design, QC, ChIP-Seq-QC, Data-format, Alignment, Peak-calling, Differential-binding, Annotation
ChIP-seq analysis using R

ChIP-seq is the most commonly used technique to study binding profiles of chromatin proteins, such as TFs or histone modification patterns. This course is an introduction to ChIP-seq data, and data analysis mainly using R, some command line based peak-callers and online software. It provides a...

Keywords: ChIP-Seq, Experimental-design, QC, Data-format, Alignment, Peak-calling, Differential-binding, Visualisation, Annotation

ChIP-seq analysis using R https://tess.elixir-europe.org/materials/chip-seq-analysis-using-r ChIP-seq is the most commonly used technique to study binding profiles of chromatin proteins, such as TFs or histone modification patterns. This course is an introduction to ChIP-seq data, and data analysis mainly using R, some command line based peak-callers and online software. It provides a theoretical background and the means to perform peak calling and differential binding analysis. ChIP-Seq, Experimental-design, QC, Data-format, Alignment, Peak-calling, Differential-binding, Visualisation, Annotation