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  • BioSimSpace – filling the gaps between molecular simulation codes

    27 June 2018

    BioSimSpace – filling the gaps between molecular simulation codes 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 2

    22 August 2018

    H3ABioNet 2018 Genotyping Chip Data Analysis and GWAS lecture series - Lecture 2 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 info@h3abionet.org 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
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