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Nkambule, L. L.

Publications and source records attributed to Nkambule, L. L..

2 recordsLinked to original sources

A harmonized public resource of deeply sequenced diverse human genomes

Underrepresented populations are often excluded from genomic studies due in part to a lack of resources supporting their analyses. The 1000 Genomes Project (1kGP) and Human Genome Diversity Project (HGDP), which have recently been sequenced to high coverage, are valuable genomic resources because of the global diversity they capture and their open data sharing policies. Here, we harmonized a high quality set of 4,094 whole genomes from HGDP and 1kGP with data from the Genome Aggregation Database (gnomAD) and identified over 153 million high-quality SNVs, indels, and SVs. We performed a detailed ancestry analysis of this cohort, characterizing population structure and patterns of admixture across populations, analyzing site frequency spectra, and measuring variant counts at global and subcontinental levels. We also demonstrate substantial added value from this dataset compared to the prior versions of the component resources, typically combined via liftover and variant intersection; for example, we catalog millions of new genetic variants, mostly rare, compared to previous releases. In addition to unrestricted individual-level public release, we provide detailed tutorials for conducting many of the most common quality control steps and analyses with these data in a scalable cloud-computing environment and publicly release this new phased joint callset for use as a haplotype resource in phasing and imputation pipelines. This jointly called reference panel will serve as a key resource to support research of diverse ancestry populations.

genomics↗

gwaRs: an R shiny web application for visualizing genome-wide association studies data

SummaryAlthough there is an exponential increase and extensive availability of genome-wide association studies data, the visualization of this data remains difficult for non-specialist users. Current software and packages for visualizing GWAS data are intended for specialists and have been developed to accomplish specific functions, favouring functionality over user experience. To facilitate this, we have developed an R shiny web application, gwaRs, that allows any general user to visualize GWAS data efficiently and effortlessly. The gwaRs web-browser interface allows users to visualize GWAS data using SNP-density, quantile-quantile, Manhattan, and Principal Component Analysis plots. AvailabilityThe gwaRs web application is publicly hosted at https://gwasviz.shinyapps.io/gwaRs/ and R source code is released under the GNU General Public License and freely available at GitHub: https://github.com/LindoNkambule/gwaRs. Contactlindonkambule116@gmail.com

bioinformatics↗