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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
Published on: April 4, 2018
An integrative scoring system for ranking SNPs by their potential deleterious effects
Phil Hyoun Lee1, Hagit Shatkay
1Computational Biology and Machine Learning Lab, School of Computing, Queen's University, Kingston, ON, Canada. lee@cs.queensu.ca
Bioinformatics (Oxford, England)
|February 21, 2009
Summary
This study introduces a new scoring system to identify harmful single nucleotide polymorphisms (SNPs) associated with diseases. The system effectively prioritizes disease-related SNPs, aiding genetic research and analysis.
Area of Science:
- Genomics
- Molecular Epidemiology
- Bioinformatics
Background:
- Identifying single nucleotide polymorphisms (SNPs) linked to complex human diseases is crucial for molecular epidemiology.
- The vast number of SNPs necessitates computational methods for prioritizing those with potentially deleterious effects.
- Quantitative assessment of SNP deleterious effects for association studies remains underdeveloped.
Purpose of the Study:
- To develop and validate an integrative scoring system for prioritizing single nucleotide polymorphisms (SNPs) based on their potential deleterious effects.
- To improve the efficiency of genotyping and analysis in disease association studies.
Main Methods:
- An integrative scoring system was developed within a probabilistic framework.
- The system was applied to 580 disease-susceptibility genes from the Online Mendelian Inheritance in Man (OMIM) database.
- Comparative analysis with existing function-assessment systems was performed.
Main Results:
- The scoring system successfully differentiated between disease-related SNPs and neutral SNPs.
- Potentially deleterious SNPs exhibited distinct features, including specific functional genomic regions and affected bio-molecular functions.
- The proposed system demonstrated superior performance compared to other assessment methods in identifying known disease-related SNPs.
Conclusions:
- The developed scoring system provides an effective method for prioritizing disease-associated SNPs.
- This approach aids in expediting genetic association studies by focusing on potentially deleterious variants.
- The system offers insights into the functional impact of SNPs in human diseases.
Related Concept Videos
01:05Single Nucleotide Polymorphisms-SNPs
A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
02:26Comparing Copy Number Variations and SNPs
Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
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%...
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%...