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Keywords: Exploratory-analysis  or metagenomics  or Roslin Institute 


Gut metagenomics in cardiometabolic diseases

Cardio-metabolic and Nutrition-related diseases (CMDs) represent an enormous burden for health care. They are characterized by very heterogeneous phenotypes progressing with time. It is virtually impossible to predict who will or will not develop cardiovascular comorbidities. There is a clear...

Keywords: metagenomics

Gut metagenomics in cardiometabolic diseases https://tess.elixir-europe.org/materials/gut-metagenomics-in-cardiometabolic-diseases-339bc8b2-0c05-4f21-9aba-2ae647a5178c Cardio-metabolic and Nutrition-related diseases (CMDs) represent an enormous burden for health care. They are characterized by very heterogeneous phenotypes progressing with time. It is virtually impossible to predict who will or will not develop cardiovascular comorbidities. There is a clear need to intervene earlier in the natural cycle of the disease, before irreversible tissue damages develop. Predictive tools still remain elusive and environmental factors (food, nutrition, physical activity and psychosocial factors) play major roles in the development of these interrelated pathologies. Poor nutritional environment and lifestyle also promote health deterioration resulting in CMD progression. In the last few years, the characterization of the gut microbiome (i.e. collective bacteria genome) and gut-derived molecules (i.e. metabolites, lipids, inflammatory molecules) has opened up new avenues for the generation of fundamental knowledge regarding putative shared pathways in CMD. The gut microbiome is likely to have an even greater impact than genetic factors given its close relationship with environmental factors. In metabolic disorders, the discoveries that low bacterial gene richness associates with cardiovascular risks stimulate encourage these developments. Due to the complexity of the gut microbiome, and its interactions with human (host) metabolism as well as with the immune system, it is only through integrative analyses where metabolic network models are used as scaffold for analysis that it will be possible to identify markers and shared pathways, which will contribute to improve patient stratification and develop new modes of patient care. metagenomics 2016-12-15 2017-01-11
Fast filtering, mapping and assembly of 16S ribosomal RNA

The application of next-generation sequencing technologies to RNA orDNA directly extracted from a community of organisms yields a mixtureof nucleotide fragments. The task to distinguish amongst these and tofurther categorize the families of ribosomal RNAs (or any other givenmarker) is an...

Keywords: metagenomics

Fast filtering, mapping and assembly of 16S ribosomal RNA https://tess.elixir-europe.org/materials/fast-filtering-mapping-and-assembly-of-16s-ribosomal-rna-83398e0f-76de-4945-b0a8-8274413a6a47 The application of next-generation sequencing technologies to RNA orDNA directly extracted from a community of organisms yields a mixtureof nucleotide fragments. The task to distinguish amongst these and tofurther categorize the families of ribosomal RNAs (or any other givenmarker) is an important step for examining the phylogeneticclassification of the constituting species. In thisperspective, we have developed a complete bioinformatics suite, called MATAM, capable of handling large sets of reads in a fast and accurate way. MATAM covers all steps of the analysis, from the identificationof reads of interest in the raw sequencing data to the reconstructionof the full-length sequences of the marker and alignment to areference database for taxonomic assignment. Part of MATAM is basedon the SortMeRNA software, also developed by the team. metagenomics 2016-12-16 2017-01-11
Exploiting collisions between DNA molecules to characterize the genomic structures of complex communities

Meta3C is an experimental and computational approach that exploits the physical contacts experienced by DNA molecules sharing the same cellular compartments. These collisions provide a quantitativeinformation that allows interpreting and phasing the genomes present within complex mixes of species...

Keywords: metagenomics

Exploiting collisions between DNA molecules to characterize the genomic structures of complex communities https://tess.elixir-europe.org/materials/exploiting-collisions-between-dna-molecules-to-characterize-the-genomic-structures-of-complex-communities-e13ff1e3-f218-4367-b445-2a8e18bb7834 Meta3C is an experimental and computational approach that exploits the physical contacts experienced by DNA molecules sharing the same cellular compartments. These collisions provide a quantitativeinformation that allows interpreting and phasing the genomes present within complex mixes of species without prior knowledge. Not only the exploitation of chromosome physical 3D signatures hold interesting premises regarding solving the genome sequences from discrete species, but it also allows assigning mobile elements such as plasmids or phages to their hosts. metagenomics 2016-12-15 2017-01-11
Dr Jekyll and Mr Hyde: The dual face of metagenomics in phylogenetic analysis

The aim of this lecture is to present the impact of metagenomics and single-cell genomics on public databases. These new powerful approches allow us to have access to the diversity of life on our planet. However, care has to be taken when using these data for posterior analyses, such as...

Keywords: metagenomics

Dr Jekyll and Mr Hyde: The dual face of metagenomics in phylogenetic analysis https://tess.elixir-europe.org/materials/dr-jekyll-and-mr-hyde-the-dual-face-of-metagenomics-in-phylogenetic-analysis-2a7d1d11-5a75-4365-b6bd-c48c8ad9a5dd The aim of this lecture is to present the impact of metagenomics and single-cell genomics on public databases. These new powerful approches allow us to have access to the diversity of life on our planet. However, care has to be taken when using these data for posterior analyses, such as phylogenetic studies, as critical errors can still be present in the databases. This course will incorporate examples taken from real studies, and we will investigate methods used for error detection. metagenomics 2016-12-16 2017-01-11
Deciphering the human intestinal tract microbiome using metagenomic computational methods

In 2010, the MetaHIT consortium published a 3.3M microbiota gene catalog generated by whole genome shotgun metagenomic sequencing, representing a mixture of bacteria, archaea, parasites and viruses coming from 124 human stool metagenomic samples [Qin et al, Nature 2010]. However most of the genes...

Keywords: metagenomics

Deciphering the human intestinal tract microbiome using metagenomic computational methods https://tess.elixir-europe.org/materials/deciphering-the-human-intestinal-tract-microbiome-using-metagenomic-computational-methods-5698849a-2061-466c-8dc6-abe487aa2733 In 2010, the MetaHIT consortium published a 3.3M microbiota gene catalog generated by whole genome shotgun metagenomic sequencing, representing a mixture of bacteria, archaea, parasites and viruses coming from 124 human stool metagenomic samples [Qin et al, Nature 2010]. However most of the genes were fragmented, taxonomically and functionally unknown, making it difficult to define and select biomarkers of interest for genome-wide association studies. Since that, this human gene catalog was improved multiple times, with the last update by [Li et al, Nature Biotechnology, 2014], which generated a 10M gene catalog using more than 1000 metagenomic samples and including some prevalent human microbe genome available at that time. Along with the catalog update, the scientific community developed new tools to challenge the complexity of this dataset and provided new ways to assemble, annotate, quantify and classify the genes coming from these catalogs. In this talk we will discuss the main approaches related to the computational treatment of the different gene catalog other the time, illustrated by the different papers that deciphered step by step the hidden information of our microbiota and his link with our health. metagenomics 2016-12-15 2017-01-11
Assessing microbial biogeography by using a metagenomic approach

Soils are highly complex ecosystems and are considered as one of the Earth’s main reservoirs of biological diversity. Bacteria account for a major part of this biodiversity, and it is now clear that such microorganisms have a key role in soil functioning processes. However, environmental factors...

Keywords: metagenomics

Assessing microbial biogeography by using a metagenomic approach https://tess.elixir-europe.org/materials/assessing-microbial-biogeography-by-using-a-metagenomic-approach-2010019e-528d-4947-9056-e67e089ad240 Soils are highly complex ecosystems and are considered as one of the Earth’s main reservoirs of biological diversity. Bacteria account for a major part of this biodiversity, and it is now clear that such microorganisms have a key role in soil functioning processes. However, environmental factors regulating the diversity of below-ground bacteria still need to be investigated, which limits our understanding of the distribution of such bacteria at various spatial scales. The overall objectives of this study were: (i) to determine the spatial patterning of bacterial community diversity in soils at a broad scale, and (ii) to rank the environmental filters most influencing this distribution. This study was performed at the scale of the France by using the French Soil Quality Monitoring Network. This network includes more than 2,200 soil samples along a systematic grid sampling. For each soil, bacterial diversity was characterized using a pyrosequencing approach targeting the 16S rRNA genes directly amplified from soil DNA, obtaining more than 18 million of high-quality sequences. This study provides the first estimates of microbial diversity at the scale of France, with for example, bacterial richness ranging from 555 to 2,007 OTUs (on average: 1,289 OTUs). It also provides the first extensive map of bacterial diversity, as well as of major bacterial taxa, revealing a bacterial heterogeneous and spatially structured distribution at the scale of France. The main factors driving bacterial community distribution are the soil physico-chemical properties (pH, texture...) and land use (forest, grassland, crop system...), evidencing that bacterial spatial distribution at a broad scale depends on local filters such as soil characteristics and land use when regarding the community (quality, composition) as a whole. Moreover, this study also offers a better evaluation of the impact of land uses on soil microbial diversity and taxa, with consequences in terms of sustainability for agricultural systems. metagenomics 2016-12-16 2017-01-11
200 billion sequences and counting: analysis, discovery and exploration of datasets with EBI Metagenomics

EBI metagenomics (EMG, https://www.ebi.ac.uk/metagenomics/) is a freely available hub for the analysis and exploration of metagenomic, metatranscriptomic, amplicon and assembly data. The resource provides rich functional and taxonomic analyses of user-submitted sequences, as well as analysis of...

Keywords: metagenomics

200 billion sequences and counting: analysis, discovery and exploration of datasets with EBI Metagenomics https://tess.elixir-europe.org/materials/200-billion-sequences-and-counting-analysis-discovery-and-exploration-of-datasets-with-ebi-metagenomics-ea1b32d5-b113-436c-a7da-8c7d29648d36 EBI metagenomics (EMG, https://www.ebi.ac.uk/metagenomics/) is a freely available hub for the analysis and exploration of metagenomic, metatranscriptomic, amplicon and assembly data. The resource provides rich functional and taxonomic analyses of user-submitted sequences, as well as analysis of publicly available metagenomic datasets held within the European Nucleotide Archive (ENA). EMG has recently undergone rapid expansion, with an over 10-fold increase in data volumes in the first 5 months of 2016. It now houses ~ 50k publicly available data sets, and represents one of the largest collections of analysed metagenomic data. As its data content has grown, EMG has increasingly become a platform for data discovery. To support this process, we have made a series of user-interface improvements, including the classification of projects by biome, presentation of results data for better visualisation and more convenient download, and provision of project level summary files. More recently, we have indexed project metadata for use with the EBI search engine, enabling exploration across different datasets. For example, users are able to search with a particular taxonomic lineage or protein function and discover the projects, samples and sequencing runs in which that lineage or function is found. This functionality allows users to explore associations between biomes, environmental conditions and organisms and functions (e.g., discovering protein coding sequences that correspond to certain enzyme families found in aquatic environments at a given temperature range). Here, we give an overview of the EMG data analysis pipeline and web site, and illustrate the use of the new search facility for data discovery. metagenomics 2016-12-16 2017-01-11
RNA-seq module Frederik Coppens

Material concerning RNA-seq analysis, with an emphasis on the statistical aspects.

Keywords: FASTQ, Alignment, BAM, Differential-expression, Statistical-model, Exploratory-analysis

RNA-seq module Frederik Coppens https://tess.elixir-europe.org/materials/rna-seq-module-frederik-coppens-4a328fa8-0bef-471c-84e4-b0d89d216128 Material concerning RNA-seq analysis, with an emphasis on the statistical aspects. FASTQ, Alignment, BAM, Differential-expression, Statistical-model, Exploratory-analysis
Variant-calling

No description available

Keywords: Alignment, Annotation, BAM, BCF, De-novo-transcriptome-assembly, Exploratory-analysis, FASTQ, Pre-processing, QC, Statistical-model, Variant-calling, VCF

Variant-calling https://tess.elixir-europe.org/materials/variant-calling No description available Alignment, Annotation, BAM, BCF, De-novo-transcriptome-assembly, Exploratory-analysis, FASTQ, Pre-processing, QC, Statistical-model, Variant-calling, VCF
Day 4 - RNA-Seq Analysis

Day 4 focuses on the final steps after production of significant gene lists, including gene clustering, visualization, and annotation.

Keywords: Exploratory-analysis, Differential-expression, Statistical-model, Annotation

Day 4 - RNA-Seq Analysis https://tess.elixir-europe.org/materials/day-4-rna-seq-analysis Day 4 focuses on the final steps after production of significant gene lists, including gene clustering, visualization, and annotation. Exploratory-analysis, Differential-expression, Statistical-model, Annotation
Statistics and RNA-Seq

This lecture and optional practical introduce the relevant statistical concepts along with its computational counterparts used on a common RNA-Seq data analysis workflow.

Keywords: FASTQ, Alignment, BAM, Differential-expression, Statistical-model, Exploratory-analysis

Statistics and RNA-Seq https://tess.elixir-europe.org/materials/statistics-and-rna-seq This lecture and optional practical introduce the relevant statistical concepts along with its computational counterparts used on a common RNA-Seq data analysis workflow. FASTQ, Alignment, BAM, Differential-expression, Statistical-model, Exploratory-analysis
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
Day 3 - RNA-Seq Analysis

Day 3 focuses on statistical analysis of RNA-Seq data and identification of differentiall expressed genes in multiple comparisons.

Keywords: QC, Exploratory-analysis, Differential-expression, Statistical-model, Pre-processing

Day 3 - RNA-Seq Analysis https://tess.elixir-europe.org/materials/day-3-rna-seq-analysis Day 3 focuses on statistical analysis of RNA-Seq data and identification of differentiall expressed genes in multiple comparisons. QC, Exploratory-analysis, Differential-expression, Statistical-model, Pre-processing
RNA-Seq Analysis with Biocluster and R

Sequencing of RNA (RNA-Seq) is the latest method to assess global gene expression because it

Scientific topics: RNA-Seq

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

RNA-Seq Analysis with Biocluster and R https://tess.elixir-europe.org/materials/rna-seq-analysis-with-biocluster-and-r Sequencing of RNA (RNA-Seq) is the latest method to assess global gene expression because it RNA-Seq RNA-Seq, Alignment, Annotation, BAM, Differential-expression, Exploratory-analysis, Expression-estimation, FASTA, FASTQ, Feature-summarisation, Pre-processing, QC, Statistical-model
Material provided by Charlotte Soneson

This folder contains material provided by Charlotte Soneson. The following material is included:

Scientific topics: RNA-Seq

Keywords: RNA-Seq, Differential-expression, Statistical-model, Exploratory-analysis

Material provided by Charlotte Soneson https://tess.elixir-europe.org/materials/material-provided-by-charlotte-soneson This folder contains material provided by Charlotte Soneson. The following material is included: RNA-Seq RNA-Seq, Differential-expression, Statistical-model, Exploratory-analysis
RNA-seq module Eija Korpelainen

All material concerning RNA-seq data analysis with Chipster

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

RNA-seq module Eija Korpelainen https://tess.elixir-europe.org/materials/rna-seq-module-eija-korpelainen All material concerning RNA-seq data analysis with Chipster 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
Day 2 - RNA-Seq Analysis

Day 2 continues throught the steps in a typical RNA-Seq experiment from alignment to sample QC and count normalization, including a brief overview of the IGV Genome Browser.

Keywords: Alignment, BAM, FASTA, FASTQ, QC, Exploratory-analysis, Feature-summarisation, Pre-processing

Day 2 - RNA-Seq Analysis https://tess.elixir-europe.org/materials/day-2-rna-seq-analysis Day 2 continues throught the steps in a typical RNA-Seq experiment from alignment to sample QC and count normalization, including a brief overview of the IGV Genome Browser. Alignment, BAM, FASTA, FASTQ, QC, Exploratory-analysis, Feature-summarisation, Pre-processing
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
Exploratory analysis and downstream analysis

This lecture gives an overview of exploratory analysis (clustering) and supervised analysis (prediction/classification), as well as visualization methods (heatmaps/PCA) and gene set analysis. It also shows how to transform count data to make it more suitable to apply the traditional methods...

Keywords: Statistical-model, Exploratory-analysis

Exploratory analysis and downstream analysis https://tess.elixir-europe.org/materials/exploratory-analysis-and-downstream-analysis This lecture gives an overview of exploratory analysis (clustering) and supervised analysis (prediction/classification), as well as visualization methods (heatmaps/PCA) and gene set analysis. It also shows how to transform count data to make it more suitable to apply the traditional methods developed (e.g.) for microarray data. Statistical-model, Exploratory-analysis