74 research outputs found
H3ABioNet Data Support Workshop - 8th H3Africa Meeting Training Material Archive
No full textThis is an archive containing training materials for the H3ABioNet course: “H3ABioNet Data Support Workshop - 8th H3Africa Meeting”.Brief description of the course: his interactive workshop will provide an overview of data management, analysis and submission for H3Africa projects. It also provides an opportunity for Data Support Working Group members, who represent the H3Africa projects to engage with H3ABioNet and discuss their needs.Intended Audience: This workshop is aimed at Data Support Working Group members who should be the H3Africa project data managers, data analysts or bioinformaticians. It is important that the attendees have knowledge of the data being generated by their H3Africa projects and information about the project’s data analysis plan.Syllabus: Participants discussed their data plans and challenges. Lectures were be given on Clinical data collection & storage, overview of GWAS/NGS/microbiome processing, downstream analysis (Variant annotation, meta-analysis, structure, ancGWAS), Data transfer considerations, security, data processing options, and H3Africa Archive and EGA submission. This was followed by discussion on developing data management plans (with reference to the article: Michener WK (2015) Ten Simple Rules for Creating a Good Data Management Plan. PLoS Comput Biol 11(10): e1004525), and interactive sessions discussing specific projects.Course trainers/authors: Nicola Mulder, Sumir Panji, Ayton Meintjes, Scott Hazelhurst, Fourie Joubert, Alia Benkahla and Faisal FadlelmolaCourse sponsor/organisers:H3ABioNet, NIH Common FundCourse level: IntermediateThe archive contains the following items:Trainer/creator file containing the names of the person/s responsible for organising and delivering the courseCourse information file - which contains the original information about the course and includes a course scheduleLecture materialsThis upload was performed by: Verena Ras | H3ABioNet Training and Outreach Coordinator</p
Genotype calling from chip data - Lecture 3 H3ABioNet 2018 GWAS Lecture series
No full text
Genotype calling from Illumina files
The third of a series of seven H3ABioNet online lectures for Genome
Wide Association Studies (GWAS) will introduce genotyping SNP array
chips with particular emphasis on the H3Africa genotype chip. The
lecture will cover common file formats when obtaining genotyping chip
data from a service provider such as Illumina and software used for
genotype calling. This lecture will also cover genotype calling, sample
and probe quality control, probe viewing and exporting of data using
GenomeStudio. Converting the data to PLINK format and some tips on
troubleshooting and common pitfalls will be discussed.
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A second book of Aesop's Fables
No full textA small version--with twelve fables--of the later Ladybird large-format book Aesop's Fables (1975). It looks like the illustrations are the same. The Wolves and the Dogs is here but not in the larger-format book.Marie Stuar
A web-based protein interaction network visualizer
No full textAbstract
Background
Interaction between proteins is one of the most important mechanisms in the execution of cellular functions. The study of these interactions has provided insight into the functioning of an organism’s processes. As of October 2013, Homo sapiens had over 170000 Protein-Protein interactions (PPI) registered in the Interologous Interaction Database, which is only one of the many public resources where protein interactions can be accessed. These numbers exemplify the volume of data that research on the topic has generated. Visualization of large data sets is a well known strategy to make sense of information, and protein interaction data is no exception. There are several tools that allow the exploration of this data, providing different methods to visualize protein network interactions. However, there is still no native web tool that allows this data to be explored interactively online.
Results
Given the advances that web technologies have made recently it is time to bring these interactive views to the web to provide an easily accessible forum to visualize PPI. We have created a Web-based Protein Interaction Network Visualizer: PINV, an open source, native web application that facilitates the visualization of protein interactions (
http://biosual.cbio.uct.ac.za/pinv.html
). We developed PINV as a set of components that follow the protocol defined in BioJS and use the D3 library to create the graphic layouts. We demonstrate the use of PINV with multi-organism interaction networks for a predicted target from Mycobacterium tuberculosis, its interacting partners and its orthologs.
Conclusions
The resultant tool provides an attractive view of complex, fully interactive networks with components that allow the querying, filtering and manipulation of the visible subset. Moreover, as a web resource, PINV simplifies sharing and publishing, activities which are vital in today’s research collaborative environments. The source code is freely available for download at
https://github.com/4ndr01d3/biosual
H3Africa Genotyping Chip Data Analysis and GWAS workshop 2018 Training Videos
No full textThis is an archive containing training materials for the H3ABioNet course: “H3Africa Genotyping Chip Data Analysis and GWAS workshop, 2018”.Brief description of the course: The H3Africa chip is being used by the H3Africa projects to generate data that will need to be analysed. The course consisted of two components; a series of online lectures provided by experts in that specific domain. These are to introduce the main concepts and theory behind population genetics and GWAS. The second part of the course for selected participants was a practical Bring Your Own Data (BYOD) workshop on the analysis of H3Africa genotyping data using the H3ABioNet GWAS and Imputation workflows.Intended Audience: People who would like to learn more about genotyping, calling, QC and running a GWAS study for the online lectures. H3Africa project members who will be undertaking the analysis of the genotype data from the H3Africa chip, and who had data available for the practical course.Course trainers/authors: Mamana Mbiyavanga | H3ABioNet, University of Cape TownAyton Meintjes | H3ABioNet, University of Cape TownSuresh Maslamoney | H3ABioNet, University of Cape TownGerrit Botha | H3ABioNet, University of Cape TownShaun Aron | H3ABioNet, University of WitwatersrandSumir Panji | H3ABioNet, University of Cape TownScott Hazelhurst | H3ABioNet, University of WitwatersrandCourse level: AdvancedThe archive contains the following items:Trainer/creator file containing the names of the person/s responsible for organising and delivering the courseCourse information file - which contains the original information about the course and includes a course scheduleLecture videos - slides loaded separately</ul
BioJS components for the display of Protein-Protein Interactions
No full text<p>BioJS components for the visualization of protein-protein interaction networks using two different layouts: force-directed and circle.</p>
<p>The upload includes the dependencies and two html examples that can be seen on-line at http://jsfiddle.net/Bvh6k/1/ and http://jsfiddle.net/J4CE7/1/</p>the dependencies files have their own licencs on thei web sites: d3.v2.min.js - https://raw.github.com/mbostock/d3/master/LICENSE
jquery.min.js - https://raw.github.com/jquery/jquery/master/MIT-LICENSE.tx
Invariant Natural Killer T-cell Dynamics in Human Immunodeficiency Virus-associated Tuberculosis.
No full textBACKGROUND: Tuberculosis (TB) is the leading cause of mortality and morbidity in people living with human immunodeficiency virus (HIV) infection (PLWH). PLWH with TB disease are at risk of the paradoxical TB-associated immune reconstitution inflammatory syndrome (TB-IRIS) when they commence antiretroviral therapy. However, the pathophysiology is incompletely understood and specific therapy is lacking. We investigated the hypothesis that invariant natural killer T (iNKT) cells contribute to innate immune dysfunction associated with TB-IRIS. METHODS: In a cross-sectional study of 101 PLWH and HIV-uninfected South African patients with active TB and controls, iNKT cells were enumerated using α-galactosylceramide-loaded CD1d tetramers and subsequently functionally characterized by flow cytometry. In a second study of 49 people with HIV type 1 (HIV-1) and active TB commencing antiretroviral therapy, iNKT cells in TB-IRIS patients and non-IRIS controls were compared longitudinally. RESULTS: Circulating iNKT cells were reduced in HIV-1 infection, most significantly the CD4+ subset, which was inversely associated with HIV-1 viral load. iNKT cells in HIV-associated TB had increased surface CD107a expression, indicating cytotoxic degranulation. Relatively increased iNKT cell frequency in patients with HIV-1 infection and active TB was associated with development of TB-IRIS following antiretroviral therapy initiation. iNKT cells in TB-IRIS were CD4+CD8- subset depleted and degranulated around the time of TB-IRIS onset. CONCLUSIONS: Reduced iNKT cell CD4+ subsets as a result of HIV-1 infection may skew iNKT cell functionality toward cytotoxicity. Increased CD4- cytotoxic iNKT cells may contribute to immunopathology in TB-IRIS
Library of Congress Bibliography on Infrared
No full textAuthor Institution: Library of CongressPresentations without an abstract printed in the proceedings do not have an abstract (image or text) in the Knowledge Bank record
Station and ship person days, 1986-2016
No full textProgress Code: completedStatement: The areas of highest concentration of humans are those where the most extreme direct point pressures are exerted on biological diversity terrestrially and in adjacent marine areas.
This indicator is particularly useful when compared with other indicators of human activities. This provides direct insight into varying levels of population and their impact on the environment.This dataset was originally set up as a "State of the Environment" indicator - however, that application no longer functions at the Australian Antarctic Data Centre, so the data have been extracted and attached to this original metadata record for the indicator.<br/><br/>Information was obtained from the ANARE Health Register. See Metadata record entitled ANARE Health Register.<br/><br/>INDICATOR DEFINITION<br/>Human population in stations and ships expressed in person-days.<br/><br/>RATIONALE FOR INDICATOR SELECTION<br/>It is generally accepted that the potential impact on the natural environment is proportional to the human population. This is the 'human footprint'. Human activities can cause disruption in physical, chemical and biological systems. As stated by the Australian Bureau of Statistics (1996): 'To understand the human impact on the Australian environment, it is necessary to know how many people live here, and how they are distributed across the continent.'<br/><br/>This indicator reveals where the greatest direct pressures related to size of the human population (e.g. fuel usage, sewerage and other waste generation etc) occur.<br/><br/>DESIGN AND STRATEGY FOR INDICATOR MONITORING PROGRAM<br/>Spatial scale: Antarctic and sub-Antarctic stations and ANARE ships travelling to and from these stations.<br/><br/>Frequency: Monthly figures reported annually.<br/><br/>Measurement technique: The Polar Medicine Branch collects data on all expeditioner movements. These data are entered into the Health Register and updated as personnel arrive on or leave a station.<br/><br/>RESEARCH ISSUES<br/>Now that this figure is available, research is required to ascertain the quantitative relationships of station and ship population to other indicators such as fuel usage and waste generation. This measure may be able to deliver a quantitative estimate of human pressure on the Antarctic environment.<br/><br/>The fields in this dataset are:<br/>Location<br/>Date<br/>Population (person-days)<br/>Illness Rate (per 1000 person years)<br/>Injury Rate (per 1000 person years
Computational analysis of candidate disease genes and variants for salt-sensitive hypertension in indigenous Southern Africans
No full textMultiple factors underlie susceptibility to essential hypertension, including a significant genetic and ethnic component, and environmental effects. Blood pressure response of hypertensive individuals to salt is heterogeneous, but salt sensitivity appears more prevalent in people of indigenous African origin. The underlying genetics of salt-sensitive hypertension, however, are poorly understood. In this study, computational methods including text- and data-mining have been used to select and prioritize candidate aetiological genes for salt-sensitive hypertension. Additionally, we have compared allele frequencies and copy number variation for single nucleotide polymorphisms in candidate genes between indigenous Southern African and Caucasian populations, with the aim of identifying candidate genes with significant variability between the population groups: identifying genetic variability between population groups can exploit ethnic differences in disease prevalence to aid with prioritisation of good candidate genes. Our top-ranking candidate genes include parathyroid hormone precursor ( PTH ) and type-1angiotensin II receptor ( AGTR1 ). We propose that the candidate genes identified in this study warrant further investigation as potential aetiological genes for salt-sensitive hypertension
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