Introduction to R and Bioconductor lecture
This reference handout goes over how to read and parse a line of complex R code.
Introduction to R and Bioconductor lecture
https://microasp.upsc.se/ngs_trainers/Materials/tree/master/Content/Prerequisite/Jenny_Drnevich/Understanding_R_code_Mar2015.md
http://tess.elixir-uk.org/materials/introduction-to-r-and-bioconductor-lecture-990e00de-2241-49f5-9577-5c110cc06a64
This reference handout goes over how to read and parse a line of complex R code.
Jenny Drnevich @jenny
R-programming
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://microasp.upsc.se/ngs_trainers/Materials/tree/master/Content/ChIP-Seq/Bori_Mifsud/README.md
http://tess.elixir-uk.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.
Bori Mifsud
Kathi Zarnack
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://microasp.upsc.se/ngs_trainers/Materials/tree/master/Content/ChIP-Seq/Bori_Mifsud/EMBO_Oct_2014_ChIP_seq_practical_talk.md
http://tess.elixir-uk.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.
Bori Mifsud
Kathi Zarnack
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://microasp.upsc.se/ngs_trainers/Materials/tree/master/Content/ChIP-Seq/Bori_Mifsud/EMBO_Oct_2014_ChIP_seq_practical.md
http://tess.elixir-uk.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.
Bori Mifsud
Kathi Zarnack
ChIP-Seq, Peak-calling, Differential-binding, Visualisation, Annotation, Homo-sapiens, R-programming
Guide to R swirl interactive lessons
This handout describes how to download the swirl package and start the basic interactive lessons to learn R.
Guide to R swirl interactive lessons
https://microasp.upsc.se/ngs_trainers/Materials/tree/master/Content/Prerequisite/Jenny_Drnevich/R_swirl_guide.md
http://tess.elixir-uk.org/materials/guide-to-r-swirl-interactive-lessons
This handout describes how to download the swirl package and start the basic interactive lessons to learn R.
Jenny Drnevich @jenny
R-programming
Introduction to R practice codes
These codes give an overview of R object types and programming language structure.
Introduction to R practice codes
https://microasp.upsc.se/ngs_trainers/Materials/tree/master/Content/Prerequisite/Jenny_Drnevich/introR.md
http://tess.elixir-uk.org/materials/introduction-to-r-practice-codes
These codes give an overview of R object types and programming language structure.
Jenny Drnevich @jenny
R-programming
Nicolas Delhomme and Bastian Schiffthaler
This merely lists the various courses at which we taught RNA-Seq data
Scientific topics: RNA-Seq
Keywords: FASTQ, GFF3, BAM, Populus-tremula, RNA-Seq, Pre-processing, QC, Alignment, Annotation, Expression-estimation, Differential-expression, R-programming
Nicolas Delhomme and Bastian Schiffthaler
https://microasp.upsc.se/ngs_trainers/Materials/tree/master/Content/RNA-Seq/Nicolas_Delhomme/README.md
http://tess.elixir-uk.org/materials/nicolas-delhomme-and-bastian-schiffthaler
This merely lists the various courses at which we taught RNA-Seq data
@delhomme
@bastian
RNA-Seq
FASTQ, GFF3, BAM, Populus-tremula, RNA-Seq, Pre-processing, QC, Alignment, Annotation, Expression-estimation, Differential-expression, R-programming
Tutorial
This file describes the main tutorial PDF file. Almost all tutorials and hands-on practices are indeed collated in a single document. In addition to this PDF, R code excerpts and installation instructions are also provided.
Scientific topics: RNA-Seq
Keywords: FASTQ, GFF3, BAM, Populus-tremula, RNA-Seq, Pre-processing, QC, Alignment, Annotation, Expression-estimation, R-programming
Tutorial
https://microasp.upsc.se/ngs_trainers/Materials/tree/master/Content/RNA-Seq/Nicolas_Delhomme/EMBO-Oct-2014/00_EMBO-October-2014-Tutorial.md
http://tess.elixir-uk.org/materials/tutorial
This file describes the main tutorial PDF file. Almost all tutorials and hands-on practices are indeed collated in a single document. In addition to this PDF, R code excerpts and installation instructions are also provided.
Nicolas Delhomme @delhomme
Bastian Schiffthaler @bastian
RNA-Seq
FASTQ, GFF3, BAM, Populus-tremula, RNA-Seq, Pre-processing, QC, Alignment, Annotation, Expression-estimation, R-programming
Prerequisite
No description available
Scientific topics: Statistics and probability
Keywords: Unix, Linux, R-programming, Statistics
Prerequisite
https://microasp.upsc.se/ngs_trainers/Materials/tree/master/Content/Prerequisite/README.md
http://tess.elixir-uk.org/materials/prerequisite
No description available
Statistics and probability
Unix, Linux, R-programming, Statistics
Nicolas Delhomme - Bastian Schiffthaler - October 2014 EMBO course material
Material for the course held on EBI Campus, Welcome Trust Center, Hinxton, UK on 20-26th, October 2014. The material cover general RNA-Seq data pre-processing as described in these [guidelines](http://www.epigenesys.eu/en/protocols/bio-informatics/1283-guidelines-for-rna-seq-data-analysis) and...
Scientific topics: RNA-Seq
Keywords: FASTQ, GFF3, BAM, Populus-tremula, RNA-Seq, Pre-processing, QC, Alignment, Annotation, Expression-estimation, Differential-expression, R-programming
Nicolas Delhomme - Bastian Schiffthaler - October 2014 EMBO course material
https://microasp.upsc.se/ngs_trainers/Materials/tree/master/Content/RNA-Seq/Nicolas_Delhomme/EMBO-Oct-2014.md
http://tess.elixir-uk.org/materials/nicolas-delhomme-bastian-schiffthaler-october-2014-embo-course-material
Material for the course held on EBI Campus, Welcome Trust Center, Hinxton, UK on 20-26th, October 2014. The material cover general RNA-Seq data pre-processing as described in these [guidelines](http://www.epigenesys.eu/en/protocols/bio-informatics/1283-guidelines-for-rna-seq-data-analysis) and reproduces the Differential Expression analysis conducted in Robinson, Delhomme et al., 2014.
Nicolas Delhomme @delhomme
Bastian Schiffthaler @bastian
RNA-Seq
FASTQ, GFF3, BAM, Populus-tremula, RNA-Seq, Pre-processing, QC, Alignment, Annotation, Expression-estimation, Differential-expression, R-programming
Differential expression analysis on the Robinson, Delhomme et al. dataset.
A differential expression analysis conducted on the **[Robinson, Delhomme et al., dataset](https://microasp.upsc.se/ngs_trainers/Materials/blob/master/Datasets/Robinson-Delhomme-Populus-tremula-shows-no-evidence-of-sexual-dimorphism.md)**. The dataset has 17 samples and 2 important meta-data: the...
Scientific topics: RNA-Seq
Keywords: RNA-Seq, Differential-expression, R-programming, Statistical-model
Differential expression analysis on the Robinson, Delhomme et al. dataset.
https://microasp.upsc.se/ngs_trainers/Materials/tree/master/Content/RNA-Seq/Nicolas_Delhomme/EMBO-Oct-2014/06_EMBO-October-2014-Differential-expression.md
http://tess.elixir-uk.org/materials/differential-expression-analysis-on-the-robinson-delhomme-et-al-dataset
A differential expression analysis conducted on the **[Robinson, Delhomme et al., dataset](https://microasp.upsc.se/ngs_trainers/Materials/blob/master/Datasets/Robinson-Delhomme-Populus-tremula-shows-no-evidence-of-sexual-dimorphism.md)**. The dataset has 17 samples and 2 important meta-data: the sample sex and year of collection. The goal is to test whether genes are involved in different processes based on the sex of the tree; _i.e._ is there a sexual dimorphism in _Populus tremula_ trees. It has indeed been hypothesized that male tree should be taller so as to spread their pollen further, whereas female would be more resistant to pests and diseases. The existing literature is contradictory, however it resulted from studies where plants were grown in controlled environment. In the present dataset, plant samples were collected in the wild, at a 2 years interval. The latter is a very important factor in the analysis as the 'year effect' is a strong confounding factor that hides the 'sex effect'. The present tutorial, hence, introduces a differential-expression analysis, but goes further by adressing confounding factors and how to _block_ them in an analysis. It is a good dataset to remind trainees that they should always be critical towards the conclusion they draw from their data.
Bastian Schiffthaler @bastian
Nicolas Delhomme @delhomme
RNA-Seq
RNA-Seq, Differential-expression, R-programming, Statistical-model
Data objects for R practice codes
This RData file contains small R objects to use in the [introR.R practice questions](introR.R)
Data objects for R practice codes
https://microasp.upsc.se/ngs_trainers/Materials/tree/master/Content/Prerequisite/Jenny_Drnevich/Practice.md
http://tess.elixir-uk.org/materials/data-objects-for-r-practice-codes
This RData file contains small R objects to use in the [introR.R practice questions](introR.R)
Jenny Drnevich @jenny
R-programming
EMBO High Throughput Sequencing Data Analysis, Cambridge, UK, 2014
No description available
Scientific topics: RNA-Seq
Keywords: FASTQ, GFF3, BAM, Populus-tremula, RNA-Seq, Pre-processing, QC, Alignment, Annotation, Expression-estimation, Differential-expression, R-programming
EMBO High Throughput Sequencing Data Analysis, Cambridge, UK, 2014
https://microasp.upsc.se/ngs_trainers/Materials/tree/master/Courses/201411-EMBO-High-Throughput-Sequencing-Data-Analysis.md
http://tess.elixir-uk.org/materials/embo-high-throughput-sequencing-data-analysis-cambridge-uk-2014
No description available
RNA-Seq
FASTQ, GFF3, BAM, Populus-tremula, RNA-Seq, Pre-processing, QC, Alignment, Annotation, Expression-estimation, Differential-expression, R-programming