MetaFun

MetaFun performs integrative functional meta-analysis of transcriptomic omics datasets to detect and characterize sex-based differences.

Key Features:

• Sex-Based Analysis: Emphasizes sex as a biological variable to detect and analyze sex-specific differences across omics datasets.
• Integration and Functional Characterization: Integrates omics datasets and performs functional characterization to interpret biological relevance.
• Comprehensive Functional Meta-Analysis: Performs meta-analyses that increase statistical power by combining data from multiple transcriptomic studies.
• Case-Control Meta-Analyses: Supports case-control meta-analysis to compare groups across multiple studies.

Scientific Applications:

• Genetics: Facilitates analysis of sex-related genetic variation and gene expression patterns.
• Genomics: Enables meta-analysis of transcriptomic datasets to identify genome-level expression differences between sexes.
• Personalized Medicine: Supports identification of sex-specific biomarkers and therapeutic targets to inform precision medicine.
• Biomarker and Therapeutic Target Identification: Enables discovery of biomarkers and therapeutic targets by integrating sex-specific meta-analytic results.

Methodology:

Backend computations are implemented primarily in R and Java and perform functional meta-analysis by integrating transcriptomic datasets across multiple studies.