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SNPsnap: a Web-based tool for identification and annotation of matched SNPs
Tune H Pers1, Pascal Timshel1, Joel N Hirschhorn1
1Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA 02115, Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, MA 2142, USA, Department of Systems Biology, Center for Biological Sequence Analysis, Technical University of Denmark, 2800 Lyngby, Denmark and Department of Genetics, Harvard Medical School, Boston, MA 02115, USA Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA 02115, Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, MA 2142, USA, Department of Systems Biology, Center for Biological Sequence Analysis, Technical University of Denmark, 2800 Lyngby, Denmark and Department of Genetics, Harvard Medical School, Boston, MA 02115, USA Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA 02115, Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, MA 2142, USA, Department of Systems Biology, Center for Biological Sequence Analysis, Technical University of Denmark, 2800 Lyngby, Denmark and Department of Genetics, Harvard Medical School, Boston, MA 02115, USA.
SNPsnap provides matched single-nucleotide polymorphism (SNP) sets for accurate enrichment analysis following genome-wide association studies (GWAS). This tool corrects for biases, improving the biological interpretation of genetic associations.
Area of Science:
- Genetics
- Bioinformatics
- Computational Biology
Background:
- Genome-wide association studies (GWAS) identify single-nucleotide polymorphisms (SNPs) associated with diseases or traits.
- Interpreting GWAS results requires assessing if associated SNPs enrich for specific biological annotations.
- Standard enrichment analyses face biases from genomic features like gene density and linkage disequilibrium (LD).
Purpose of the Study:
- To introduce SNPsnap, a web server for SNP-based enrichment analysis.
- To provide a computational tool that generates matched SNP sets for calibrating background expectations in enrichment analyses.
- To address biases inherent in SNP enrichment analyses, improving the reliability of biological interpretations.
Main Methods:
- SNPsnap utilizes query SNPs from GWAS.
- It identifies randomly drawn SNPs matched to query SNPs based on allele frequency, LD, distance to nearest gene, and gene density.
- The server efficiently generates these matched SNP sets for background correction.
Main Results:
- SNPsnap successfully generates matched SNP sets crucial for accurate enrichment analysis.
- The tool accounts for critical biases, including LD, gene density, and SNP location.
- Provides a calibrated background for assessing SNP enrichment in biological annotations.
Conclusions:
- SNPsnap is a valuable computational resource for post-GWAS analysis.
- It facilitates more robust SNP-based enrichment analyses by providing unbiased background SNP sets.
- Enables better biological interpretation of genetic associations identified through GWAS.
Related Concept Videos
01:05Single Nucleotide Polymorphisms-SNPs
02:26Comparing Copy Number Variations and SNPs
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
01:11Genome-wide Association Studies-GWAS
GWAS does not require the identification of the target gene involved in...