ICAR Research Data Repository for Knowledge Management
GapFinder Demo
CSIRO RDS Repository
View Archive Info| Field | Value | |
| Title |
GapFinder Demo
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| Creator |
Xin-Yi Chua
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| Subject |
Phylogeny and comparative analysis
Genomics and transcriptomics Applications in life sciences Bioinformatics and computational biology not elsewhere classified |
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| Description |
GapFinder is a CSIRO-developed web-based visualisation tool that enables the exploration of large distance matrices that have a hierarchical structure to their observations. The tool aims to help us find gaps between different groups of observations or, at least, understand when these gaps do not exist GapFinder Demo demonstrates the application of the GapFinder visualisation to fish metabarcode data. The aim is to help environmental DNA (eDNA) researchers choose PCR primers that allow them to clearly distinguish species of interest in their experiments by their DNA “barcode”. Since these primers yield DNA barcodes from multiple species, this approach is known as metabarcoding. eDNA metabarcoding is a broadly used practical method to determine which species are present in an environment, and measure biodiversity or detect pests, among many other applications of importance in biodiversity and biosecurity. The tool allows users to interactively view and interrogate in-silico generated DNA metabarcoding data that allows researchers to determine the best primer pairs to use to discriminate their species of interest from other similar species. eDNA Researchers face the challenge of determining which genetic targets will allow them to distinguish closely related species relevant to the study system. In practice, this involves selection of PCR primers to produce particular DNA sequence barcodes, entailing intensive in silico and in vitro validation. This tool tackles that challenge in a way that saves computational and experimental resources by centralising the analysis of primer and barcode sequence data. |
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| Publisher |
CSIRO
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| Contributor |
Louise Ord
Stephen Bent David Lovell Annette McGrath |
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| Date |
2023-08-04
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| Type |
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| Identifier |
csiro:57474
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| Language |
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| Coverage |
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