Power of QTL detection using association tests with family controls

Jules Hernández-Sánchez1, Chris S Haley, Peter M Visscher

  • 1Roslin Institute (Edinburgh), Roslin, Midlothian EH25 9PS, Scotland, UK. jules.Hernandez@bbsrc.ac.uk

Related Concept Videos

Detection of Gross Error: The Q Test01:00

Detection of Gross Error: The Q Test

When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
Cochran's Q Test01:17

Cochran's Q Test

Cochran's Q Test is a nonparametric statistical test used to determine if there are potential differences in the outcomes of three or more related groups on a binary (yes/no) or dichotomous outcome. It is essentially an extension of the McNemar Test, which is limited to two related samples - Cochran's Q test can handle three or more related samples, making it more versatile in scenarios where subjects are measured under multiple conditions. The test statistic follows a Chi-Square distribution,...
Significance Testing: Overview01:04

Significance Testing: Overview

Significance testing is a set of statistical methods used to test whether a claim about a parameter is valid. In analytical chemistry, significance testing is used primarily to determine whether the difference between two values comes from determinate or random errors. The effect of a particular change in the measurement protocol, analyst, or sample itself can cause a deviation from the expected result. In the case of a suspected deviation/outlier, we need to be able to confirm mathematically...
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...
Pedigree Analysis02:21

Pedigree Analysis

A pedigree is a diagram displaying a family’s history of a trait. Analyzing pedigrees can reveal (1) whether a trait is dominant or recessive, (2) the type of chromosome, autosomal or sex, a trait is linked to, (3) genotypes of family members, and (4) probabilities of phenotypes in future generations. For families with a history of autosomal or sex-linked diseases, this information can be crucial to family planning.Pedigrees Display Family HistoriesIn various plant and animal species,...
Punnett Squares01:53

Punnett Squares

A Punnett square displays the possible genotypes offspring can inherit from two parental genotypes. If a trait’s inheritance pattern (e.g., dominant or recessive) is known, Punnett squares can also be used to determine the probability of inheriting a phenotype. Punnett squares are applicable in situations where trait inheritance is determined by a single gene locus and traits are independently inherited. However, they cannot predict trait probabilities for more complex genetic inheritance...