Related Experiment Video
Updated: May 25, 2026
10:36
Rare Event Detection Using Error-corrected DNA and RNA Sequencing
Published on: August 3, 2018
Sample size determination for classifiers based on single-nucleotide polymorphisms
Xinyu Liu1, Yupeng Wang, Romdhane Rekaya
1Department of Statistics, University of Georgia, Athens, GA 30602, USA.
Biostatistics (Oxford, England)
|January 31, 2012
Summary
Determining adequate sample sizes for disease risk prediction using single-nucleotide polymorphisms (SNPs) is crucial. This study presents a cost-effective algorithm for sample size determination, minimizing study costs while ensuring accurate classification.
Area of Science:
- Genetics and Bioinformatics
- Statistical Genetics
- Computational Biology
Background:
- Single-nucleotide polymorphisms (SNPs) are key genetic markers used for predicting disease risk and understanding human variation.
- High costs and limited availability of clinical samples pose significant challenges in genetic association studies.
- Efficient sample size determination is essential for cost-effective and statistically robust genomic research.
Purpose of the Study:
- To develop a method for determining the optimal sample size for building accurate SNP-based classifiers.
- To minimize study costs by reducing the number of samples required for reliable disease risk prediction.
- To derive and validate an approximation for the probability of correct classification (PCC) for SNP data.
Main Methods:
- Derivation of an optimal classifier and its approximate probability of correct classification (PCC) for two-class SNP data.
- Construction of a linear classifier and derivation of its approximate PCC.
- Validation of PCC approximations using Monte Carlo simulations.
- Development of a sample size determination algorithm based on a PCC difference threshold.
Main Results:
- The study successfully derived and validated approximations for PCC using linear classifiers and simulations.
- A novel sample size determination algorithm was developed and demonstrated to be effective.
- Application to HapMap data for Chinese and Japanese populations showed that a total sample size of 166 (83 per population) is sufficient for a threshold of 0.05 with 51 independent SNPs.
Conclusions:
- The developed algorithm provides a reliable and cost-effective approach for sample size determination in SNP-based disease risk studies.
- This method facilitates the design of efficient genetic studies, balancing accuracy with resource constraints.
- The findings have significant implications for future research in personalized medicine and genetic epidemiology.
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,...
01:19Sample Size Calculation
Knowledge of the sample size is the first requirement to conduct random sampling or an experiment. The sample size is the total number of units, observations, or groups (in some cases) used to get the data to estimate a population parameter. As the name suggests, the sample size is that of the sample drawn from the population and differs from the population size.
The sample size for the given experiment or sampling effort is fundamental to any study design. Sample size decides the number of...
The sample size for the given experiment or sampling effort is fundamental to any study design. Sample size decides the number of...
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%...