4.6 Article

Snpdat: Easy and rapid annotation of results from de novo snp discovery projects for model and non-model organisms

Journal

BMC BIOINFORMATICS
Volume 14, Issue -, Pages -

Publisher

BIOMED CENTRAL LTD
DOI: 10.1186/1471-2105-14-45

Keywords

SNPs; Annotation; Software; Non-model organisms

Funding

  1. Teagasc Walsh Fellowship Scheme [2009183]
  2. Science Foundation Ireland (SFI) [07/SK/B1236A]
  3. Science Foundation Ireland (SFI) [07/SK/B1236a] Funding Source: Science Foundation Ireland (SFI)

Ask authors/readers for more resources

Background: Single nucleotide polymorphisms (SNPs) are the most abundant genetic variant found in vertebrates and invertebrates. SNP discovery has become a highly automated, robust and relatively inexpensive process allowing the identification of many thousands of mutations for model and non-model organisms. Annotating large numbers of SNPs can be a difficult and complex process. Many tools available are optimised for use with organisms densely sampled for SNPs, such as humans. There are currently few tools available that are species non-specific or support non-model organism data. Results: Here we present SNPdat, a high throughput analysis tool that can provide a comprehensive annotation of both novel and known SNPs for any organism with a draft sequence and annotation. Using a dataset of 4,566 SNPs identified in cattle using high-throughput DNA sequencing we demonstrate the annotations performed and the statistics that can be generated by SNPdat. Conclusions: SNPdat provides users with a simple tool for annotation of genomes that are either not supported by other tools or have a small number of annotated SNPs available. SNPdat can also be used to analyse datasets from organisms which are densely sampled for SNPs. As a command line tool it can easily be incorporated into existing SNP discovery pipelines and fills a niche for analyses involving non-model organisms that are not supported by many available SNP annotation tools. SNPdat will be of great interest to scientists involved in SNP discovery and analysis projects, particularly those with limited bioinformatics experience.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available