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Updated: Jun 10, 2026

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
Published on: April 4, 2018
pfSNP: An integrated potentially functional SNP resource that facilitates hypotheses generation through knowledge
Jingbo Wang1, Mostafa Ronaghi, Samuel S Chong
1Department of Biochemistry Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
The pfSNP database integrates over 40 resources to identify potentially functional single nucleotide polymorphisms (SNPs) from millions of variants. This tool aids researchers in generating hypotheses for association studies and SNP functionality experiments.
Area of Science:
- Genetics
- Bioinformatics
- Computational Biology
Background:
- Over 14 million single nucleotide polymorphisms (SNPs) have been reported, presenting a significant challenge in identifying those that affect phenotypes.
- Existing web resources for SNP functionality are primarily annotation databases and lack comprehensiveness.
Purpose of the Study:
- To present pfSNP, a comprehensive, integrated web resource for potentially functional SNPs (pfSNPs).
- To facilitate hypothesis generation by integrating diverse data and providing a user-friendly interface for exploring SNP functionality.
Main Methods:
- Integrated over 40 algorithms and resources to analyze >14 million SNPs from dbSNP.
- Identified potentially functional SNPs based on published reports, genetic inference, and sequence motif prediction.
- Developed a customizable query interface with an 'auto-complete, prompt-as-you-type' feature and Boolean logic support.
Main Results:
- The pfSNP resource provides comprehensive, well-annotated data on potentially functional SNPs.
- The user interface is highly customizable, supporting complex Boolean queries.
- Results pages include gene/pathway information with text clouds for enriched tissues/pathways, aiding understanding and hypothesis generation.
Conclusions:
- pfSNP offers a valuable, integrated resource for scientists studying SNP functionality.
- The tool is expected to be of significant interest to researchers in association studies and experimental validation of SNP function.
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