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Related Concept Videos

Multiple Comparison Tests01:13

Multiple Comparison Tests

Multiple comparison test, abbreviated as MCT, is a post hoc analysis generally performed after comparing multiple samples with one or more tests. An MCT will help identify a significantly different sample among multiple samples or a factor among multiple factors.
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...

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Comparison between single-marker analysis using Merlin and multi-marker analysis using LASSO for Framingham simulated

Yun Ju Sung1, Treva K Rice, Gang Shi

  • 1Division of Biostatistics, Washington University School of Medicine, 660 South Euclid Avenue, Box 8067, St, Louis, Missouri 63110-1093, USA. yunju@wubios.wustl.edu.

BMC Proceedings
|December 19, 2009
PubMed
Summary
This summary is machine-generated.

This study compared single-marker and multi-marker genetic analyses for low-density lipoprotein. Both methods identified a major causal SNP, but struggled with weaker polygenic signals, with differences in handling nearby SNPs.

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Area of Science:

  • Genetics
  • Statistical genetics
  • Bioinformatics

Background:

  • Family-based association studies are crucial for understanding genetic contributions to complex diseases.
  • Accurate identification of single-nucleotide polymorphisms (SNPs) influencing phenotypes like low-density lipoprotein (LDL) cholesterol is vital for genetic research.
  • Comparing different analytical approaches is essential for optimizing genetic discovery.

Purpose of the Study:

  • To compare the performance of family-based single-marker association analysis (Merlin) and multi-marker analysis (LASSO) for the low-density lipoprotein (LDL) phenotype.
  • To evaluate the ability of both methods to detect major causal SNPs and polygenic SNPs using simulated genetic data.
  • To identify differences in how Merlin and LASSO handle SNPs in proximity to causal variants.

Main Methods:

  • Utilized 200 replicates of the Genetic Analysis Workshop 16 Framingham simulated data sets.
  • Employed Merlin for family-based single-marker association analysis.
  • Applied LASSO (least absolute shrinkage and selection operator) for multi-marker analysis.
  • Focused on single-nucleotide polymorphisms (SNPs) on chromosome 22 related to the low-density lipoprotein phenotype.

Main Results:

  • Both Merlin and LASSO successfully identified the major causal SNP (rs2294207) on chromosome 22, confirming its significance.
  • Neither single-marker nor multi-marker analyses detected statistically significant associations for the 12 weaker polygenic SNPs.
  • Merlin provided smaller p-values for 14 SNPs near causal variants, while LASSO frequently excluded these non-causal SNPs from models.

Conclusions:

  • Both single-marker and multi-marker analyses are effective in detecting strong genetic effects.
  • Detecting weak polygenic signals remains a challenge for both Merlin and LASSO.
  • The choice of method can influence the handling of SNPs located near causal variants, impacting model selection.