MamPhEA

MamPhEA performs enrichment analysis of mammalian gene sets using phenotypic data from mouse mutants to elucidate gene function, including analyses restricted to phenotypes caused by null mutations.


Key Features:

  • Enrichment analysis: Performs enrichment analysis of gene sets against phenotype annotations derived from mouse mutants.
  • Mouse mutant phenotypes: Utilizes phenotypic data from mouse mutants, explicitly including annotations for null mutations.
  • Predefined and custom phenotypes: Supports analysis of both predefined phenotype sets and user-defined custom phenotypes.
  • Null-mutation filtering: Offers the ability to restrict analyses to phenotypes resulting specifically from null mutations.
  • Cross-mammalian support: Enables analyses across mammalian species with fully sequenced genomes.
  • Gene-phenotype association detection: Integrates gene sets with phenotypic annotations to identify significant associations between genes and observed phenotypes.

Scientific Applications:

  • Functional annotation: Annotates and elucidates functional properties of mammalian gene sets based on mouse phenotypes.
  • Gene function inference: Infers potential gene functions from phenotypic outcomes of mutations in mouse models.
  • Disease mechanism investigation: Provides insights into mammalian genetics and disease mechanisms through genotype-phenotype associations.
  • Comparative and evolutionary studies: Facilitates comparative analyses and evolutionary biology inquiries across fully sequenced mammalian genomes.

Methodology:

Integrates phenotypic annotations from mouse mutants (optionally filtered for null mutations) with input gene sets to perform enrichment analysis and identify significant gene-phenotype associations.

Topics

Details

Tool Type:
command-line tool
Operating Systems:
Linux, Windows, Mac
Added:
12/18/2017
Last Updated:
11/25/2024

Operations

Publications

Weng M, Liao B. MamPhEA: a web tool for mammalian phenotype enrichment analysis. Bioinformatics. 2010;26(17):2212-2213. doi:10.1093/bioinformatics/btq359. PMID:20605928. PMCID:PMC2922895.

Documentation

Links