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Related Concept Videos

Single Nucleotide Polymorphisms-SNPs01:05

Single 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,...
Comparing Copy Number Variations and SNPs02:26

Comparing 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%...
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
Principles of Pharmacogenetics: Types of Genetic Variants01:27

Principles of Pharmacogenetics: Types of Genetic Variants

The human genome is over 99.9% identical between individuals, yet genetic differences exist at millions of bases. The human genome contains approximately 3 million variant positions per individual, many of which are heterozygous, contributing to genetic diversity and individual traits. Genetic variations include single-nucleotide polymorphisms (SNPs), insertions, deletions, and copy number variations (CNVs).SNPs, the most common variation, involve single-base changes in DNA. These can be...
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...

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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Picking single-nucleotide polymorphisms in forests.

Daniel F Schwarz1, Silke Szymczak, Andreas Ziegler

  • 1Institut für Medizinische Biometrie und Statistik, Universität zu Lübeck, Universitätsklinikum Schleswig-Holstein, Campus Lübeck, Ratzeburger Allee 160, 23538 Lübeck, Germany. schwarz@imbs.uni-luebeck.de

BMC Proceedings
|May 10, 2008
PubMed
Summary
This summary is machine-generated.

This study introduces a two-stage method using random forests (RFs) to screen single-nucleotide polymorphisms (SNPs) for genome-wide association studies. This approach effectively identifies candidate SNPs for complex diseases like rheumatoid arthritis.

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Area of Science:

  • Genetics
  • Statistical Genetics
  • Bioinformatics

Background:

  • High-throughput single-nucleotide polymorphism (SNP) technologies generate vast data, challenging classical statistical methods in genetic association studies.
  • A two-stage approach, involving initial SNP screening followed by logistic regression, is a potential solution for analyzing case-control data.

Purpose of the Study:

  • To introduce and evaluate a novel two-stage method for selecting candidate SNPs using random forests (RFs) for permutation importance.
  • To apply this method to simulated data for genome-wide association studies (GWAS) of complex diseases.

Main Methods:

  • A two-stage strategy was employed: Stage 1 involved using RFs to pre-select important SNPs from simulated data.
  • Haplotype tagging further reduced the selected SNPs.
  • Stage 2 utilized logistic regression (logReg) to estimate the effects of the selected SNPs.

Main Results:

  • The RF-based screening identified significant SNPs, with the highest effect estimates for five simulated loci.
  • Key covariates such as smoking, gender, and parental DR alleles were identified.
  • Two out of four simulated genes with direct effects on rheumatoid arthritis risk were identified, along with all covariates, without false positives.

Conclusions:

  • A two-stage approach incorporating RF-based SNP screening is effective for identifying candidate SNPs in GWAS for complex diseases.
  • This method demonstrates suitability for handling large SNP datasets and detecting relevant genetic associations.