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Keywords: Exploratory-analysis  or metagenomics  or Chip-seq  or life-sciences  or Genomics 


PanelApp Reviewer’s Guide

This presentation provides a guide to how to make reviews of gene-disease evidence in the PanelApp database.

Scientific topics: Rare diseases, Genomics

Keywords: Gene lists, Genomics, human disease, Biocuration

Resource type: knowledgebase

PanelApp Reviewer’s Guide https://tess.elixir-europe.org/materials/panelapp-reviewer-s-guide This presentation provides a guide to how to make reviews of gene-disease evidence in the PanelApp database. Rare diseases Genomics Gene lists, Genomics, human disease, Biocuration Clinical Scientists clinicians and informaticians interested in cancer genetics Researchers
Plant Bioinformatics

The past 15 years have been exciting ones in plant biology. Hundreds of plant genomes have been sequenced, RNA-seq has enabled transcriptome-wide expression profiling, and a proliferation of "-seq"-based methods has permitted protein-protein and protein-DNA interactions to be determined cheaply...

Keywords: life-sciences, health-informatics

Plant Bioinformatics https://tess.elixir-europe.org/materials/plant-bioinformatics The past 15 years have been exciting ones in plant biology. Hundreds of plant genomes have been sequenced, RNA-seq has enabled transcriptome-wide expression profiling, and a proliferation of "-seq"-based methods has permitted protein-protein and protein-DNA interactions to be determined cheaply and in a high-throughput manner. These data sets in turn allow us to generate hypotheses at the click of a mouse. For instance, knowing where and when a gene is expressed can help us narrow down the phenotypic search space when we don't see a phenotype in a gene mutant under "normal" growth conditions. Coexpression analyses and association networks can provide high-quality candidate genes involved in a biological process of interest. Using Gene Ontology enrichment analysis and pathway visualization tools can help us make sense of our own 'omics experiments and answer the question "what processes/pathways are being perturbed in our mutant of interest?" Structure: each of the 6 week hands-on modules consists of a ~2 minute intro, a ~20 minute theory mini-lecture, a 1.5 hour hands-on lab, an optional ~20 minute lab discussion if experiencing difficulties with lab, and a ~2 minute summary. Tools covered: Module 1: GENOMIC DBs / PRECOMPUTED GENE TREES / PROTEIN TOOLS. Araport, TAIR, Gramene, EnsemblPlants Compara, PLAZA; SUBA4 and Cell eFP Browser, 1001 Genomes Browser Module 2: EXPRESSION TOOLS. eFP Browser / eFP-Seq Browser, Araport, Genevestigator, TravaDB, NCBI Genome Data Viewer for exploring RNA-seq data for many plant species other than Arabidopsis, MPSS database for small RNAs Module 3: COEXPRESSION TOOLS. ATTED II, Expression Angler, AraNet, AtCAST2 Module 4: PROMOTER ANALYSIS. Cistome, Athena, ePlant Module 5: GO ENRICHMENT ANALYSIS AND PATHWAY VIZUALIZATION. AgriGO, AmiGO, Classification SuperViewer, TAIR, g:profiler, AraCyc, MapMan (optional: Plant Reactome) Module 6: NETWORK EXPLORATION. Arabidopsis Interactions Viewer 2, ePlant, TF2Network, Virtual Plant, GeneMANIA [Material updated in March 2019] life-sciences, health-informatics
ELIXIR TtR course: Basic genomics using advanced analysis tools

Materials from the ELIXIR workshop “ELIXIR TtR course: Basic genomics using advanced analysis tools”, Nov 5-6 2018 at the University of Ljubljana, Faculty of Medicine, Ljubljana, Slovenia

Scientific topics: Genomics

Keywords: Galaxy, training, Genomics, eLearning, EeLP

Resource type: course materials, Training materials, Slides

ELIXIR TtR course: Basic genomics using advanced analysis tools https://tess.elixir-europe.org/materials/elixir-ttr-course-basic-genomics-using-advanced-analysis-tools Materials from the ELIXIR workshop “ELIXIR TtR course: Basic genomics using advanced analysis tools”, Nov 5-6 2018 at the University of Ljubljana, Faculty of Medicine, Ljubljana, Slovenia Christophe Antoniewski Olivier Inizan Genomics Galaxy, training, Genomics, eLearning, EeLP life scientists beginner bioinformaticians Postgraduate students
Chip-seq: Motif Analysis Tutorial

Introduction Goal The aim is to : Get familiar with motif analysis of ChIP-seq data. Learn de novo motif discovery methods. In practice : Motif discovery with peak-motifs Differential analysis Random controls

Keywords: Chip-seq, Motif analysis, NGS, Pattern recognition

Chip-seq: Motif Analysis Tutorial https://tess.elixir-europe.org/materials/chip-seq-motif-analysis-tutorial Introduction Goal The aim is to : Get familiar with motif analysis of ChIP-seq data. Learn de novo motif discovery methods. In practice : Motif discovery with peak-motifs Differential analysis Random controls Chip-seq, Motif analysis, NGS, Pattern recognition
Chip-seq: Functional Annotation tutorial

Global Objective Given a set of ChIP-seq peaks annotate them in order to find associated genes, genomic categories and functional terms.

Keywords: Chip-seq, Functional Annotation, NGS

Chip-seq: Functional Annotation tutorial https://tess.elixir-europe.org/materials/chip-seq-functional-annotation-tutorial Global Objective Given a set of ChIP-seq peaks annotate them in order to find associated genes, genomic categories and functional terms. Chip-seq, Functional Annotation, NGS
Galaxy: Initiation II

Galaxy II: common tools, quality control; alignment; data managment

Keywords: Genomics

Galaxy: Initiation II https://tess.elixir-europe.org/materials/galaxy-initiation-ii Galaxy II: common tools, quality control; alignment; data managment Genomics
Differential analysis of RNA-Seq data

Design, describe, explore and model

Keywords: Genomics, RNA-seq

Differential analysis of RNA-Seq data https://tess.elixir-europe.org/materials/differential-analysis-of-rna-seq-data Design, describe, explore and model Genomics, RNA-seq
Variant Filtering

Some use cases : - Extract a subset of variants (localization, type) - Combine variants from several analyses - Compare obtained variants from several data types (RNA ...

Keywords: Genomics

Variant Filtering https://tess.elixir-europe.org/materials/variant-filtering-98171288-9eb3-49d3-b627-8ae1ead26885 Some use cases : - Extract a subset of variants (localization, type) - Combine variants from several analyses - Compare obtained variants from several data types (RNA ... Genomics
DNA-seq analysis: From raw reads to processed alignments

Objectives: Mapping the DNA-seq data to the reference genome Process the alignments for the variant calling

Keywords: Alignment, DNA-seq, Genomics, Variant calling

DNA-seq analysis: From raw reads to processed alignments https://tess.elixir-europe.org/materials/dna-seq-analysis-from-raw-reads-to-processed-alignments Objectives: Mapping the DNA-seq data to the reference genome Process the alignments for the variant calling Alignment, DNA-seq, Genomics, Variant calling
Chip-seq: Pattern Analysis tutorial

Goal The aim is to : Get familiar with motif analysis of ChIP-seq data. Learn de novo motif discovery methods. In practice : Motif discovery with peak-motifs Differential analysis Random controls

Keywords: Chip-seq, NGS, Pattern recognition

Chip-seq: Pattern Analysis tutorial https://tess.elixir-europe.org/materials/chip-seq-pattern-analysis-tutorial Goal The aim is to : Get familiar with motif analysis of ChIP-seq data. Learn de novo motif discovery methods. In practice : Motif discovery with peak-motifs Differential analysis Random controls Chip-seq, NGS, Pattern recognition
Variants: alignment and pre-treatment; GATK

Variant calling practical session

Keywords: Genomics

Variants: alignment and pre-treatment; GATK https://tess.elixir-europe.org/materials/variants-alignment-and-pre-treatment-gatk-d2d0443e-60d2-48f0-bbec-53b94eb5b003 Variant calling practical session Genomics
Third generation sequencing : the revolution of long reads

Introduction on sequencing: available technologies, library types, applications ...

Keywords: Genomics

Third generation sequencing : the revolution of long reads https://tess.elixir-europe.org/materials/third-generation-sequencing-the-revolution-of-long-reads Introduction on sequencing: available technologies, library types, applications ... Genomics
Exploring Microscope Platform

How to use the Microscope Platform to annotate and analyze microbial genomes.

Keywords: Annotation, Genomics, Metabolomics, Microbial evolution, Sequence analysis, Transcriptomics

Exploring Microscope Platform https://tess.elixir-europe.org/materials/exploring-microscope-platform How to use the Microscope Platform to annotate and analyze microbial genomes. Annotation, Genomics, Metabolomics, Microbial evolution, Sequence analysis, Transcriptomics
Variant Filtering

Some use cases : - Extract a subset of variants (localization, type) - Combine variants from several analyses - Compare obtained variants from several data types (RNA ...

Keywords: Genomics

Variant Filtering https://tess.elixir-europe.org/materials/variant-filtering Some use cases : - Extract a subset of variants (localization, type) - Combine variants from several analyses - Compare obtained variants from several data types (RNA ... Genomics
REPET: TEdenovo tutorial

The TEdenovo pipeline follows a philosophy in three first steps: Detection of repeated sequences (potential TE) Clustering of these sequences Generation of consensus sequences for each cluster, representing the ancestral TE

Keywords: Annotation, Genomics

REPET: TEdenovo tutorial https://tess.elixir-europe.org/materials/repet-tedenovo-tutorial The TEdenovo pipeline follows a philosophy in three first steps: Detection of repeated sequences (potential TE) Clustering of these sequences Generation of consensus sequences for each cluster, representing the ancestral TE Annotation, Genomics
Chip-seq: Peak calling tutorial

The aim is to : Understand how to process reads to obtain peaks (peak-calling). Become familiar with differential analysis of peaks In practice : Obtain dataset from GEO Analyze mapped reads Obtain set(s) of peaks, handle replicates Differential analysis of peak

Keywords: Chip-seq, NGS, Peak calling

Chip-seq: Peak calling tutorial https://tess.elixir-europe.org/materials/chip-seq-peak-calling-tutorial The aim is to : Understand how to process reads to obtain peaks (peak-calling). Become familiar with differential analysis of peaks In practice : Obtain dataset from GEO Analyze mapped reads Obtain set(s) of peaks, handle replicates Differential analysis of peak Chip-seq, NGS, Peak calling
NGS data exploration with the MicroScope Platform

Exploring data annotation on the genomics and transcriptomics levels with the MicroScope Platform and its tools

Keywords: Genomics, NGS, RNA-seq, SNP, Transcriptomics

NGS data exploration with the MicroScope Platform https://tess.elixir-europe.org/materials/ngs-data-exploration-with-the-microscope-platform Exploring data annotation on the genomics and transcriptomics levels with the MicroScope Platform and its tools Genomics, NGS, RNA-seq, SNP, Transcriptomics
Chip Seq: Annotation and visualization Lesson

How to add biological meaning to peaks

Keywords: Annotation, Chip-seq, Data Visualization, NGS

Chip Seq: Annotation and visualization Lesson https://tess.elixir-europe.org/materials/chip-seq-annotation-and-visualization-lesson How to add biological meaning to peaks Annotation, Chip-seq, Data Visualization, NGS
Variants: alignment and pre-treatment; GATK

Variant calling practical session

Keywords: Genomics

Variants: alignment and pre-treatment; GATK https://tess.elixir-europe.org/materials/variants-alignment-and-pre-treatment-gatk Variant calling practical session Genomics
RGP finder: prediction of Genomic Islands

Prediction of Region of Genomic Plasticity (RGPs) and CoDing Sequences (CDSs) and visualization

Keywords: CDS, Data visualization, Genomics, RGP

RGP finder: prediction of Genomic Islands https://tess.elixir-europe.org/materials/rgp-finder-prediction-of-genomic-islands Prediction of Region of Genomic Plasticity (RGPs) and CoDing Sequences (CDSs) and visualization CDS, Data visualization, Genomics, RGP
PASTEClassifier Tutorial

The PASTEClassifier (Pseudo Agent System for Transposable Elements Classification) is a transposable element (TE) classifier searching for structural features and similarity to classify TEs ( Hoede C. et al. 2014 )

Keywords: Genomics, Transposons

PASTEClassifier Tutorial https://tess.elixir-europe.org/materials/pasteclassifier-tutorial The PASTEClassifier (Pseudo Agent System for Transposable Elements Classification) is a transposable element (TE) classifier searching for structural features and similarity to classify TEs ( Hoede C. et al. 2014 ) Genomics, Transposons
Chip-seq Analysis

Quality, normalisation and peak calling

Keywords: Chip-seq, Genomics

Chip-seq Analysis https://tess.elixir-europe.org/materials/chip-seq-analysis Quality, normalisation and peak calling Chip-seq, Genomics
Exploring microbiomes with the MicroScope Platform

This module is separated in different courses: MicroScope: General overview, Keyword search and gene cart functionalities Functional annotation of microbial genomes Functional annotation of microbial genomes: Prediction of enzymatic functions Relational...

Keywords: Annotation, Genomics, Metabolomics, Microbial evolution, Transcriptomics

Exploring microbiomes with the MicroScope Platform https://tess.elixir-europe.org/materials/exploring-microbiomes-with-the-microscope-platform This module is separated in different courses: MicroScope: General overview, Keyword search and gene cart functionalities Functional annotation of microbial genomes Functional annotation of microbial genomes: Prediction of enzymatic functions Relational annotation of bacterial genomes: synteny Automatic functional assignation and expert annotation of genes Relational annotation of bacterial genomes: phylogenetic profiles Relational annotation of bacterial genomes: pan-genome analysis Relational annotation of bacterial genomes: metabolic pathways Syntactic re-annotation of public microbial genomes Syntactic annotation of microbial genomes Annotation, Genomics, Metabolomics, Microbial evolution, Transcriptomics
REPET: TEdannot Tutorial

TEannot is able to annote a genome using DNA sequences library. This library can be a predicted TE library built by TEdenovo

Keywords: Annotation, Genomics

REPET: TEdannot Tutorial https://tess.elixir-europe.org/materials/repet-tedannot-tutorial TEannot is able to annote a genome using DNA sequences library. This library can be a predicted TE library built by TEdenovo Annotation, Genomics
Chip Seq: Annotation and visualization Tutorial

Global Objective Given a set of ChIP-seq peaks annotate them in order to find associated genes, genomic categories and functional terms.

Keywords: Annotation, Chip-seq, Data Visualization, NGS

Chip Seq: Annotation and visualization Tutorial https://tess.elixir-europe.org/materials/chip-seq-annotation-and-visualization-tutorial Global Objective Given a set of ChIP-seq peaks annotate them in order to find associated genes, genomic categories and functional terms. Annotation, Chip-seq, Data Visualization, NGS
Visualization of NGS data with IGV

Visualisation of next-gen sequencing data with Integrative Genomics Viewer

Keywords: Data visualization, Genomics, NGS

Visualization of NGS data with IGV https://tess.elixir-europe.org/materials/visualization-of-ngs-data-with-igv Visualisation of next-gen sequencing data with Integrative Genomics Viewer Data visualization, Genomics, NGS
Differential gene expression analysis : Practical part

RNA-seq: Differential gene expression analysis practical session

Keywords: Genomics, RNA-seq

Differential gene expression analysis : Practical part https://tess.elixir-europe.org/materials/differential-gene-expression-analysis-practical-part RNA-seq: Differential gene expression analysis practical session Genomics, RNA-seq
RNA-seq: Differential gene expression analysis

Transcriptome analysis provides information about the identity and quantity of all RNA molecules

Keywords: Genomics, RNA-seq

RNA-seq: Differential gene expression analysis https://tess.elixir-europe.org/materials/rna-seq-differential-gene-expression-analysis Transcriptome analysis provides information about the identity and quantity of all RNA molecules Genomics, RNA-seq
Galaxy III: Visualization

Visualization of Next Generation Sequencing Data using the Integrative Genomics Viewer (IGV)

Keywords: Genomics

Galaxy III: Visualization https://tess.elixir-europe.org/materials/galaxy-iii-visualization Visualization of Next Generation Sequencing Data using the Integrative Genomics Viewer (IGV) Genomics
Who is doing what on the cheese surface? Overview of the cheese microbial ecosystem functioning by metatranscriptomic analyses

Cheese ripening is a complex biochemical process driven by microbial communities composed of both eukaryotes and prokaryotes. Surface-ripened cheeses are widely consumed all over the world and are appreciated for their characteristic flavor. Microbial community composition has been studied for a...

Keywords: metagenomics

Who is doing what on the cheese surface? Overview of the cheese microbial ecosystem functioning by metatranscriptomic analyses https://tess.elixir-europe.org/materials/who-is-doing-what-on-the-cheese-surface-overview-of-the-cheese-microbial-ecosystem-functioning-by-metatranscriptomic-analyses-55c4b5d0-ba6e-4ae0-879f-7bc27c10b3eb Cheese ripening is a complex biochemical process driven by microbial communities composed of both eukaryotes and prokaryotes. Surface-ripened cheeses are widely consumed all over the world and are appreciated for their characteristic flavor. Microbial community composition has been studied for a long time on surface-ripened cheeses, but only limited knowledge has been acquired about its in situ metabolic activities. We used an iterative sensory procedure to select a simplified microbial consortium, composed of only nine species (three yeasts and six bacteria), producing the odor of Livarot-type cheese when inoculated in a sterile cheese curd. All the genomes were sequenced in order to determine the functional capacities of the different species and facilitate RNA-Seq data analyses. We followed the ripening process of experimental cheeses made using this consortium during four weeks, by metatranscriptomic and biochemical analyses. By combining all of the data, we were able to obtain an overview of the cheese maturation process and to better understand the metabolic activities of the different community members and their possible interactions. We next applied the same approach to investigate the activity of the microorganisms in real cheeses, namely Reblochon-style cheeses. This provided useful insights into the physiological changes that occur during cheese ripening, such as changes in energy substrates, anabolic reactions, or stresses. metagenomics 2016-12-15 2017-01-11