iQTL-F2

iQTL-F2 maps imprinted quantitative trait loci (iQTL) in F2 experimental crosses using maximum likelihood inference and an EM algorithm implemented in R to detect and estimate imprinted genetic effects genome-wide.

Key Features:

• R implementation: The analysis is implemented in R code for execution of the described statistical methods.
• Maximum likelihood inference: Uses a maximum likelihood approach to estimate and test imprinted genetic effects.
• EM algorithm: Employs the Expectation-Maximization (EM) algorithm to enable efficient parameter estimation during genome scans.
• Genome-wide scanning: Performs scans across the genome to detect locations of iQTL in F2 crosses.
• Statistical significance testing: Provides procedures for assessing the statistical significance of detected iQTL.
• Imprinted-effect estimation: Estimates parent-of-origin (imprinted) effects, including detection of paternally expressed alleles affecting traits.

Scientific Applications:

• Genetic research: Identifies and characterizes the contribution of imprinting to quantitative trait variation.
• Developmental biology: Aids studies on imprinting-mediated regulation of developmental traits across organisms.
• Trait analysis: Facilitates analysis of how iQTL influence specific quantitative traits, such as body weight.
• Cross-species studies: Applicable to imprinting studies beyond mice due to the general nature of imprinting effects.

Methodology:

Reanalyzes genotype–phenotype data from F2 families (e.g., LG/S × SM/S) using R code to perform genome-wide scans with maximum likelihood estimation implemented via an EM algorithm and accompanying statistical significance testing of imprinted effects.