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Authors: Jared Simpson  or Sorana Morrissy  or Kathi Zarnack  or Eija Korpelainen @eija, eko... 


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 7-Somatic Mutations and Annotations

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 7-Somatic Mutations and Annotations https://tess.elixir-europe.org/materials/bioinformatics-for-cancer-genomics-2018-module-7-somatic-mutations-and-annotations 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 6-Copy Number Variants

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 6-Copy Number Variants https://tess.elixir-europe.org/materials/bioinformatics-for-cancer-genomics-2018-module-6-copy-number-variants 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 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 5-Somatic Mutations and Annotations

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

Bioinformatics for Cancer Genomics 2017 Module 5-Somatic Mutations and Annotations https://tess.elixir-europe.org/materials/bioinformatics-for-cancer-genomics-2017-module-5-somatic-mutations-and-annotations Course covers the bioinformatics tools required to analyze genomic data sets. Researchers Graduate Students Biologists, Genomicists, Computer Scientists Post-Doctoral Fellows
Bioinformatics for Cancer Genomics 2017 Module 4-Copy Number Variants

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

Bioinformatics for Cancer Genomics 2017 Module 4-Copy Number Variants https://tess.elixir-europe.org/materials/bioinformatics-for-cancer-genomics-2017-module Course covers the bioinformatics tools required to analyze genomic data sets. 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
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 - Practical talk

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

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

ChIP-seq analysis using R - Practical talk https://tess.elixir-europe.org/materials/chip-seq-analysis-using-r-practical-talk ChIP-seq is the most commonly used technique to study binding profiles of chromatin proteins, such as TFs or histone modification patterns. This practical is an introduction to ChIP-seq data analysis mainly using R, some command line based peak-callers and online software. It provides means to perform peak calling, annotation, motif search and differential binding analysis. ChIP-Seq, Peak-calling, Differential-binding, Visualisation, Annotation, Homo-sapiens, R-programming
ChIP-seq analysis using R - Practical

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

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

ChIP-seq analysis using R - Practical https://tess.elixir-europe.org/materials/chip-seq-analysis-using-r-practical ChIP-seq is the most commonly used technique to study binding profiles of chromatin proteins, such as TFs or histone modification patterns. This practical is an introduction to ChIP-seq data analysis mainly using R, some command line based peak-callers and online software. It provides means to perform peak calling, annotation, motif search and differential binding analysis. ChIP-Seq, Peak-calling, Differential-binding, Visualisation, Annotation, Homo-sapiens, R-programming
Material for the course RNA-seq data analysis with Chipster

This material covers the whole RNA-seq data analysis pipeline, from quality control of raw reads to differential expression analysis.

Scientific topics: RNA-Seq

Keywords: RNA-Seq, FASTQ, QC, Pre-processing, Alignment, BAM, Expression-estimation, Feature-summarisation, Differential-expression, Statistical-model, Exploratory-analysis

Material for the course RNA-seq data analysis with Chipster https://tess.elixir-europe.org/materials/material-for-the-course-rna-seq-data-analysis-with-chipster This material covers the whole RNA-seq data analysis pipeline, from quality control of raw reads to differential expression analysis. RNA-Seq RNA-Seq, FASTQ, QC, Pre-processing, Alignment, BAM, Expression-estimation, Feature-summarisation, Differential-expression, Statistical-model, Exploratory-analysis
Exercises for the course RNA-seq data analysis with Chipster

This practical covers the whole RNA-seq data analysis pipeline, from quality control of raw reads to differential expression analysis, using the free Chipster software. Material updated in Dec 2015.

Keywords: FASTQ, QC, Pre-processing, Alignment, BAM, Expression-estimation, Feature-summarisation, Differential-expression, Statistical-model, Exploratory-analysis

Exercises for the course RNA-seq data analysis with Chipster https://tess.elixir-europe.org/materials/exercises-for-the-course-rna-seq-data-analysis-with-chipster This practical covers the whole RNA-seq data analysis pipeline, from quality control of raw reads to differential expression analysis, using the free Chipster software. Material updated in Dec 2015. FASTQ, QC, Pre-processing, Alignment, BAM, Expression-estimation, Feature-summarisation, Differential-expression, Statistical-model, Exploratory-analysis
Lecture slides for the course RNA-seq data analysis with Chipster

This material covers the whole RNA-seq data analysis pipeline, from quality control of raw reads to differential expression analysis. It discusses also experimental design. Material updated in Dec 2015.

Keywords: FASTQ, QC, Pre-processing, Alignment, BAM, Expression-estimation, Feature-summarisation, Differential-expression, Statistical-model, Exploratory-analysis

Lecture slides for the course RNA-seq data analysis with Chipster https://tess.elixir-europe.org/materials/lecture-slides-for-the-course-rna-seq-data-analysis-with-chipster This material covers the whole RNA-seq data analysis pipeline, from quality control of raw reads to differential expression analysis. It discusses also experimental design. Material updated in Dec 2015. FASTQ, QC, Pre-processing, Alignment, BAM, Expression-estimation, Feature-summarisation, Differential-expression, Statistical-model, Exploratory-analysis