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 6-Future of Metabolomics
https://bioinformaticsdotca.github.io/metabolomics_2018
http://tess.elixir-uk.org/materials/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.
David Wishart
Researchers
Post-Doctoral Fellows
Graduate students
Biologists, Genomicists, Computer Scientists
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 3-Databases for Chemical, Spectral, and Biological Data
https://bioinformaticsdotca.github.io/metabolomics_2018
http://tess.elixir-uk.org/materials/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.
David Wishart
Researchers
Post-Doctoral Fellows
Graduate Students
Biologists, Genomicists, Computer Scientists
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 2-Metabolite Identification and Annotation
https://bioinformaticsdotca.github.io/metabolomics_2018
http://tess.elixir-uk.org/materials/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.
David Wishart
Researchers
Graduate students
Post-Doctoral Fellows
Biologists, Genomicists, Computer Scientists
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 2018 Module 1-Introduction to Metabolomics
https://bioinformaticsdotca.github.io/metabolomics_2018
http://tess.elixir-uk.org/materials/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.
David Wishart
Researchers
Graduate Students
Post-Doctoral Fellows
Biologists, Genomicists, Computer Scientists
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 6-Future of Metabolomics
https://bioinformaticsdotca.github.io/metabolomics_2017
http://tess.elixir-uk.org/materials/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.
David Wishart
Researchers
Graduate students
Biologists, Genomicists, Computer Scientists
Post-Doctoral Fellows
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 5-MetaboAnalyst
https://bioinformaticsdotca.github.io/metabolomics_2017
http://tess.elixir-uk.org/materials/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.
David Wishart
Researchers
Graduate Students
Biologists, Genomicists, Computer Scientists
Post-Doctoral Fellows
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 3-Databases for Chemical, Spectral, and Biological Data
https://bioinformaticsdotca.github.io/metabolomics_2017
http://tess.elixir-uk.org/materials/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.
David Wishart
Researchers
Graduate Students
Biologists, Genomicists, Computer Scientists
Post-Doctoral Fellows
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 2-Metabolite Identification and Annotation
https://bioinformaticsdotca.github.io/metabolomics_2017
http://tess.elixir-uk.org/materials/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.
David Wishart
Researchers
Graduate students
Post-Doctoral Fellows
Biologists, Genomicists, Computer Scientists
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.
Informatics and Statistics for Metabolomics 2017 Module 1-Introduction to Metabolomics
https://bioinformaticsdotca.github.io/metabolomics_2017
http://tess.elixir-uk.org/materials/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.
David Wishart
Researchers
Graduate students
Biologists, Genomicists, Computer Scientists
Post-Doctoral Fellows
Genome Annotation - Genome Annotation
Genome annotation is a multi-level process that includes prediction of protein-coding genes, as well as other functional genome units such as structural RNAs, tRNAs, small RNAs, pseudogenes, control regions, direct and inverted repeats, insertion sequences, transposons and other mobile elements.
Genome Annotation - Genome Annotation
http://galaxyproject.github.io/training-material/topics/genome-annotation/tutorials/genome-annotation/tutorial.html
http://tess.elixir-uk.org/materials/genome-annotation-genome-annotation
Genome annotation is a multi-level process that includes prediction of protein-coding genes, as well as other functional genome units such as structural RNAs, tRNAs, small RNAs, pseudogenes, control regions, direct and inverted repeats, insertion sequences, transposons and other mobile elements.
joachimwolff
erxleben
bgruening
ChIP-Seq data analysis - Identification of the binding sites of the Estrogen receptor
ChIP-sequencing is a method used to analyze protein interactions with DNA.
Questions of the tutorial:
- How is raw ChIP-seq data processed and analyzed?
- What are the binding sites of the Estrogen receptor?
Objectives of the tutorial:
- Inspect read quality with FastQC
- Map reads with...
ChIP-Seq data analysis - Identification of the binding sites of the Estrogen receptor
http://galaxyproject.github.io/training-material/topics/chip-seq/tutorials/estrogen-receptor-binding-site-identification/tutorial.html
http://tess.elixir-uk.org/materials/chip-seq-data-analysis-identification-of-the-binding-sites-of-the-estrogen-receptor
ChIP-sequencing is a method used to analyze protein interactions with DNA.
Questions of the tutorial:
- How is raw ChIP-seq data processed and analyzed?
- What are the binding sites of the Estrogen receptor?
Objectives of the tutorial:
- Inspect read quality with FastQC
- Map reads with Bowtie2
- Assess the quality of an ChIP-seq experiments
- Extract coverage files
- Call enriched regions or peaks
friedue
erxleben
bebatut
vivekbhr
fidelram
Variant Analysis - Exome sequencing data analysis
Exome sequencing means that all protein-coding genes in a genome are sequenced
Questions of the tutorial:
- How to identify the genetic variation with the use of exome sequencing?
- What is the pipeline of the process of finding genetic variation which caused the disease?
Objectives of the...
Variant Analysis - Exome sequencing data analysis
http://galaxyproject.github.io/training-material/topics/variant-analysis/tutorials/exome-seq/tutorial.html
http://tess.elixir-uk.org/materials/variant-analysis-exome-sequencing-data-analysis
Exome sequencing means that all protein-coding genes in a genome are sequenced
Questions of the tutorial:
- How to identify the genetic variation with the use of exome sequencing?
- What is the pipeline of the process of finding genetic variation which caused the disease?
Objectives of the tutorial:
- Identification of the genetic variation using the exome sequencing
- Using FreeBayes calls for variants generating
- Variant analysis and GEMINI queries
bebatut
torhou
erxleben
bgruening
ChIP-Seq data analysis - Identification of the binding sites of the T-cell acute lymphocytic leukemia protein 1 (TAL1)
ChIP-sequencing is a method used to analyze protein interactions with DNA.
Questions of the tutorial:
- How is raw ChIP-seq data processed and analyzed?
- What are the binding sites of Tal1?
- Which genes are regulated by Tal1?
Objectives of the tutorial:
- Inspect read quality with FastQC
-...
ChIP-Seq data analysis - Identification of the binding sites of the T-cell acute lymphocytic leukemia protein 1 (TAL1)
http://galaxyproject.github.io/training-material/topics/chip-seq/tutorials/tal1-binding-site-identification/tutorial.html
http://tess.elixir-uk.org/materials/chip-seq-data-analysis-identification-of-the-binding-sites-of-the-t-cell-acute-lymphocytic-leukemia-protein-1-tal1
ChIP-sequencing is a method used to analyze protein interactions with DNA.
Questions of the tutorial:
- How is raw ChIP-seq data processed and analyzed?
- What are the binding sites of Tal1?
- Which genes are regulated by Tal1?
Objectives of the tutorial:
- Inspect read quality with FastQC
- Perform read trimming with Trimmomatic
- Align trimmed reads with BWA
- Assess quality and reproducibility of experiments
- Identify Tal1 binding sites with MACS2
- Determine unique/common Tal1 binding sites from G1E and Megakaryocytes
- Identify unique/common Tal1 peaks occupying gene promoters
- Visually inspect Tal1 peaks with Trackster
malloryfreeberg
moheydarian
vivekbhr
joachimwolff
erxleben
Transcriptomics - Reference-based RNA-Seq data analysis
Training material for all kinds of transcriptomics analysis.
Questions of the tutorial:
- What are the effects of Pasilla (PS) gene depletion on splicing events?
- How to analyze RNA sequencing data using a reference genome?
Objectives of the tutorial:
- Analysis of RNA sequencing data using...
Transcriptomics - Reference-based RNA-Seq data analysis
http://galaxyproject.github.io/training-material/topics/transcriptomics/tutorials/ref-based/tutorial.html
http://tess.elixir-uk.org/materials/transcriptomics-reference-based-rna-seq-data-analysis
Training material for all kinds of transcriptomics analysis.
Questions of the tutorial:
- What are the effects of Pasilla (PS) gene depletion on splicing events?
- How to analyze RNA sequencing data using a reference genome?
Objectives of the tutorial:
- Analysis of RNA sequencing data using a reference genome
- Analysis of differentially expressed genes
- Identification of functional enrichment among differentially expressed genes
bebatut
malloryfreeberg
moheydarian
erxleben
pavanvidem
blankclemens
Transcriptomics - Introduction to Transcriptomics
Training material for all kinds of transcriptomics analysis.
Transcriptomics - Introduction to Transcriptomics
http://galaxyproject.github.io/training-material/topics/transcriptomics/slides/introduction.html
http://tess.elixir-uk.org/materials/transcriptomics-introduction
Training material for all kinds of transcriptomics analysis.
bebatut
erxleben
mwolfien