M-GCTA

M-GCTA estimates the proportion of phenotypic variance attributable to maternal, paternal, and offspring genetic effects from genome-wide genotype data.

Key Features:

• Data requirements: Requires genome-wide genotype data from mother-offspring or father-offspring pairs, suitable for large population-based cohorts.
• Data cleaning and quality control: Provides options for data cleaning and quality control, including automated detection and removal of cryptically related individuals.
• Genetic relationship matrices: Constructs genetic relationship matrices that index genome-wide genetic similarity between parents and offspring.
• Variance partitioning: Partitions phenotypic variance into components attributable to maternal or paternal and offspring genotypes.
• Performance evaluation: Performance has been evaluated using data simulations to assess computational efficiency in terms of time and memory requirements.

Scientific Applications:

• Decomposing parental and fetal genetic contributions: Enables quantification of maternal and paternal contributions separately from offspring genetics to complex traits.
• Birth weight analyses (ALSPAC, MoBa): Applied to birth weight data from the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Norwegian Mother and Child Cohort Study (MoBa), showing genetic variation in birth weight is predominantly explained by fetal genetic sources rather than maternal ones.

Methodology:

Constructs genetic relationship matrices capturing genome-wide genetic similarities and uses them to partition phenotypic variance into maternal/paternal and offspring genotype components; includes data cleaning and quality control with automated detection and removal of cryptically related individuals and performance assessment via data simulations measuring time and memory.