SMapper: visualizing spatial prevalence data of all types, including sparse and incomplete datasets

Abstract Motivation We introduce SMapper, a novel web and software tool for visualizing spatial prevalence data of all types including those suffering from incomplete geographic coverage and insufficient sample sizes. We demonstrate the benefits of our tool in overcoming interpretational issues with...

Full description

Saved in:
Bibliographic Details
Published in:Bioinformatics advances 2023, Vol.3 (1), p.vbad176-vbad176
Main Authors: Khellaf, Lynn, Ralf, Arwin, Nguyen, Khanh Toan, Kayser, Manfred, Nothnagel, Michael
Format: Article
Language:English
Subjects:
Application Note
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Abstract Motivation We introduce SMapper, a novel web and software tool for visualizing spatial prevalence data of all types including those suffering from incomplete geographic coverage and insufficient sample sizes. We demonstrate the benefits of our tool in overcoming interpretational issues with existing tools caused by such data limitations. We exemplify the use of SMapper by applications to human genotype and phenotype data relevant in an epidemiological, anthropological and forensic context. Availability and implementation A web implementation is available at https://rhodos.ccg.uni-koeln.de/smapper/. A stand-alone version, released under the GNU General Public License version 3 as published by the Free Software Foundation, is available from https://rhodos.ccg.uni-koeln.de/smapper/software-download.php as a Singularity container (https://docs.sylabs.io/guides/latest/user-guide/index.html) and a native Linux Python installation.
ISSN:2635-0041
2635-0041
DOI:10.1093/bioadv/vbad176