4 events found
BioSimSpace – filling the gaps between molecular simulation codes
27 June 2018BioSimSpace – filling the gaps between molecular simulation codes https://bioexcel.eu/webinar-biosimspace-filling-the-gaps-between-molecular-simulation-codes-2018-06-27/ https://tess.elixir-europe.org/events/biosimspace-filling-the-gaps-between-molecular-simulation-codes [BioSimSpace](https://biosimspace.org) is a flagship software project from the [CCP-BioSim](https://ccpbiosim.ac.uk) and [HEC-BioSim](https://hecbiosim.ac.uk) biomolecular modelling communities. The project aims to make it easier for researchers to develop, share and re-use biomolecular simulation workflow nodes. The software problem in our community is that we have lots of different pieces of software that are all incompatible and are not interoperable. This forces the community to hand-write small scripts for converting between different file formats, or to generate different software input files. The resulting scripts are specific for the software and task performed, leading to the community generating lots of bespoke and brittle workflows. BioSimSpace solves this problem by providing an **interoperability layer** between the major molecular simulation packages. In effect, BioSimSpace provides the shims that fill in the gaps between codes. BioSimSpace Python scripts can be run from the command line, used as workflow nodes in packages such as Knime, or run on the cloud as Jupyter notebooks. In this talk, we will show how BioSimSpace has been implemented, will talk about its capabilities and our future plans, and will demonstrate some BioSimSpace workflow nodes running on the cloud. 2018-06-27 15:00:00 UTC 2018-06-27 16:00:00 UTC BioExcel Molecular modelling Molecular dynamics Workflows University of Manchester  IntermediateBeginners   GROMACSPythonKNIMEJupyter notebook
H3ABioNet 2018 Genotyping Chip Data Analysis and GWAS lecture series - Lecture 1
20 August 2018H3ABioNet 2018 Genotyping Chip Data Analysis and GWAS lecture series - Lecture 1 https://www.youtube.com/watch?v=4_-pxWFUpfU&list=PLcQ0XMykNhCQJPz0amnbz9BPM4Bu0Nkgf https://tess.elixir-europe.org/events/h3abionet-2018-genotyping-chip-data-analysis-and-gwas-lecture-series #### Computational requirements for running the H3ABioNet GWAS workflows The first of a series of seven online lectures for Genome Wide Association Studies (GWAS) will cover the technical requirements for setting up a your computational environment for running the H3ABioNet GWAS workflows. In this inaugural lecture of the series, Prof. Hazelhurst will cover the the following topics: Installing and using Nextflow Installing and using Github Use of containers for packaging and running tools Pulling the GWAS pipeline from Github and running it As this lecture aims to provide attendees with an environment to the run the H3ABioNet GWAS workflow at their own pace, there are some preliminary software requirements: Either a Linux machine or an Apple running macOS Ideally you should have machine with at least 2-4 cores and 8GB of RAM. Java 8 Nextflow installed (see installation instructions at https://www.nextflow.io/) Python 3 Please also install either Docker OR the following dependencies using pip3: Pandas, Matplotlib, Openpyxl, SciPy, NumPy PLINK 1.9 [Please also refer to the following documentation to obtain the H3ABioNet GWAS workflow]: https://github.com/h3abionet/h3agwas/blob/master/README.md 2018-08-20 15:00:00 UTC 2018-08-20 16:30:00 UTC H3ABioNet Population genomics Genotyping experiment Computational biology Workflows GWAS study Bioinformatics H3ABioNet firstname.lastname@example.org H3ABioNet Anyone intersted in GWAS and using the H3Africa genotyping chipAnyone who wants to learn more about GWAS workshops_and_courses  NextflowDockerH3ABioNetGWASWorkflowsGenotyping array analysis bioinformaticsAfricaPopulation GenomicsReproducible ScienceH3Africa genotyping arrayHigh performance computingCloud computingGWAS workflowH3ABioNet GWAS 2018 Lecture Series
H3ABioNet 2018 Genotyping Chip Data Analysis and GWAS lecture series - Lecture 2
22 August 2018H3ABioNet 2018 Genotyping Chip Data Analysis and GWAS lecture series - Lecture 2 https://www.youtube.com/watch?v=4_-pxWFUpfU&list=PLcQ0XMykNhCQJPz0amnbz9BPM4Bu0Nkgf https://tess.elixir-europe.org/events/h3abionet-2018-genotyping-chip-data-analysis-and-gwas-lecture-series-4a0ce1cc-f48d-4f1e-98b5-2bfc55abce6a ### Overview of Genome Wide Association Studies and study designs The second of a series of seven online lectures for Genome Wide Association Studies (GWAS) will provide a basic overview on genome-wide association studies (GWAS). This is timely with the H3Africa genotyping data becoming available for several of the H3Africa research groups. To enable genomic research, the H3Africa Consortium had to build some of its own resources. This has involved sequencing whole genomes from selected under-represented African populations, analyzing the data to identify common genetic variation across major groups and developing a unique GWAS array, enriched for common African variation. The H3Africa SNP genotyping array, is currently the best-suited array available for African genome-wide association studies. What does it take to develop a genome study to understand genetic and environmental contributions to complex disease traits? This GWAS lecture will cover the research process from protocol development to data quality control and GWAS analysis approaches. It will include the two main study designs: Case : control (e.g. diabetes, hypertension, kidney disease) Continuous trait (e.g. LDL-Cholesterol, body mass index, height) GWAS. I will discuss the basic building blocks of a GWAS study, the different study designs, power of a study to detect genetic association (based in sample size, allele frequency and expected effect size), and replication studies. The advantages and disadvantages of doing GWAS in African populations will be discussed. 2018-08-22 15:00:00 UTC 2018-08-22 17:00:00 UTC H3ABioNet Genotyping experiment Population genetics Population genomics GWAS study H3ABioNet email@example.com H3ABioNet Anyone intersted in GWAS and using the H3Africa genotyping chip workshops_and_courses  H3ABioNetGWASH3AfricaH3Africa genotyping arrayAfrican populationsStudy designAWI-GENAfrican genomicsPopulations GenomicsGenetic DiversityH3Africa genotyping arrayCase Control studyGenotypesComplex traitsGWAS study designsAllelic associationGenotype associationGWAS workflowQuantitative traitsSample sizeCommon and rare variantsAfrican genome structureH3ABioNet GWAS 2018 Lecture Series
H3ABioNet 2018 Genotyping Chip Data Analysis and GWAS lecture series - Lecture 4
29 August 2018H3ABioNet 2018 Genotyping Chip Data Analysis and GWAS lecture series - Lecture 4 https://www.youtube.com/watch?v=4_-pxWFUpfU&list=PLcQ0XMykNhCQJPz0amnbz9BPM4Bu0Nkgf https://tess.elixir-europe.org/events/h3abionet-2018-genotyping-chip-data-analysis-and-gwas-lecture-series-lecture-4 ### Quality control and its importance in GWAS In the fourth of a series of seven H3ABioNet online lectures for Genome Wide Association Studies (GWAS), the importance of doing good quality control for a GWAS will be discussed. The lecture will cover the types of errors one should control for, the specific bioinformatics tools used for quality control. Specific sample and SNP quality control steps that should be undertaken in a GWAS will be explored using specific examples. 2018-08-29 15:00:00 UTC 2018-08-29 16:30:00 UTC H3ABioNet Genotyping experiment GWAS study Computational biology Bioinformatics Population genomics Population genetics H3ABioNet firstname.lastname@example.org H3ABioNet Anyone intersted in GWAS and using the H3Africa genotyping chip 150 workshops_and_courses  Genome Wide Association StudiesGenotype callingH3Africa genotyping arrayAfrican populationsQuality Control for GWASSample Quality ControlSNP Quality ControlPopulation GenomicsGenotypingPLINK formatPrincipal Component AnalysisLow minor allele frequencyMissingnessGWAS workflowDiscordant Sex informationNextflowGenotyping rate callHeterozygosity rateRelated and duplicate individualsIdentity by DescentHardy Weinberg EquilibriumBioinformaticsH3ABioNet GWAS 2018 Lecture Series
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