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 with Prokka
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...
Genome Annotation - Genome annotation with Prokka
http://galaxyproject.github.io/training-material/topics/genome-annotation/tutorials/annotation-with-prokka/tutorial.html
http://tess.elixir-uk.org/materials/genome-annotation-genome-annotation-with-prokka
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.
Questions of the tutorial:
- How to annotate a bacterial genome?
- How to visualize annoted genomic features?
Objectives of the tutorial:
- Load genome into Galaxy
- Annotate genome with Prokka
- View annotations in JBrowse
annasyme
tseemann
slugger70
Variant Analysis - Microbial Variant Calling
Exome sequencing means that all protein-coding genes in a genome are sequenced
Questions of the tutorial:
- How do we detect differences between a set of reads from a microorganism and a reference genome
Objectives of the tutorial:
- Find variants between a reference genome and a set of...
Variant Analysis - Microbial Variant Calling
http://galaxyproject.github.io/training-material/topics/variant-analysis/tutorials/microbial-variants/tutorial.html
http://tess.elixir-uk.org/materials/variant-analysis-microbial-variant-calling
Exome sequencing means that all protein-coding genes in a genome are sequenced
Questions of the tutorial:
- How do we detect differences between a set of reads from a microorganism and a reference genome
Objectives of the tutorial:
- Find variants between a reference genome and a set of reads
- Visualise the SNP in context of the reads aligned to the genome
- Determine the effect of those variants on genomic features
- Understand if the SNP is potentially affecting the phenotype
annasyme
slugger70
tseemann
Assembly - Unicycler Assembly
DNA sequence data has become an indispensable tool for Molecular Biology & Evolutionary Biology. Study in these fields now require a genome sequence to work from. We call this a 'Reference Sequence.' We need to build a reference for each species. We do this by Genome Assembly. De novo Genome...
Assembly - Unicycler Assembly
http://galaxyproject.github.io/training-material/topics/assembly/tutorials/unicycler-assembly/tutorial.html
http://tess.elixir-uk.org/materials/assembly-unicycler-assembly
DNA sequence data has become an indispensable tool for Molecular Biology & Evolutionary Biology. Study in these fields now require a genome sequence to work from. We call this a 'Reference Sequence.' We need to build a reference for each species. We do this by Genome Assembly. De novo Genome Assembly is the process of reconstructing the original DNA sequence from the fragment reads alone.
Questions of the tutorial:
- I have short reads and long reads. How do I assemble a genome?
Objectives of the tutorial:
- Perform Quality Control on your reads
- Perform a Small genome Assembly with Unicycler
- Evaluate the Quality of the Assembly with Quast
- Annotate the assembly with Prokka
nekrut
delphine-l
slugger70
Assembly - De Bruijn Graph Assembly
DNA sequence data has become an indispensable tool for Molecular Biology & Evolutionary Biology. Study in these fields now require a genome sequence to work from. We call this a 'Reference Sequence.' We need to build a reference for each species. We do this by Genome Assembly. De novo Genome...
Assembly - De Bruijn Graph Assembly
http://galaxyproject.github.io/training-material/topics/assembly/tutorials/debruijn-graph-assembly/tutorial.html
http://tess.elixir-uk.org/materials/assembly-de-bruijn-graph-assembly
DNA sequence data has become an indispensable tool for Molecular Biology & Evolutionary Biology. Study in these fields now require a genome sequence to work from. We call this a 'Reference Sequence.' We need to build a reference for each species. We do this by Genome Assembly. De novo Genome Assembly is the process of reconstructing the original DNA sequence from the fragment reads alone.
Questions of the tutorial:
- What are the factors that affect genome assembly?
- How does Genome assembly work?
Objectives of the tutorial:
- Perform an optimised Velvet assembly with the Velvet Optimiser
- Compare this assembly with those we did in the basic tutorial
- Perform an assembly using the SPAdes assembler.
slugger70
Assembly - Introduction to Genome Assembly
DNA sequence data has become an indispensable tool for Molecular Biology & Evolutionary Biology. Study in these fields now require a genome sequence to work from. We call this a 'Reference Sequence.' We need to build a reference for each species. We do this by Genome Assembly. De novo Genome...
Assembly - Introduction to Genome Assembly
http://galaxyproject.github.io/training-material/topics/assembly/tutorials/general-introduction/tutorial.html
http://tess.elixir-uk.org/materials/assembly-introduction-to-genome-assembly
DNA sequence data has become an indispensable tool for Molecular Biology & Evolutionary Biology. Study in these fields now require a genome sequence to work from. We call this a 'Reference Sequence.' We need to build a reference for each species. We do this by Genome Assembly. De novo Genome Assembly is the process of reconstructing the original DNA sequence from the fragment reads alone.
Questions of the tutorial:
- How do we perform a very basic genome assembly from short read data?
Objectives of the tutorial:
- assemble some paired end reads using Velvet
- examine the output of the assembly.
slugger70