MGFM

MGFM identifies marker genes associated with specific tissues and cell types from microarray gene expression datasets to support cell identity and tissue-specific function analyses.

Key Features:

• Marker Gene Prediction: Groups samples of similar types based on their expression levels to predict marker genes specific to tissues or cell types.
• Data Integration and Analysis: Leverages publicly available microarray datasets from NCBI's Gene Expression Omnibus (GEO) and was validated using two GEO datasets covering five human tissues: brain, heart, kidney, liver, and lung.
• Validation and Comparison: Compares predictions with literature-derived tissue markers and another tissue-specific gene identification tool, with top-ranked markers experimentally validated by reverse transcriptase-polymerase chain reaction (RT-PCR).

Scientific Applications:

• Cell identity determination: Identification of marker genes to discriminate and characterize distinct cell types.
• Tissue-specific gene function analysis: Discovery of genes with specific expression patterns across brain, heart, kidney, liver, and lung for functional studies.
• Investigation of molecular mechanisms in complex diseases: Detection of tissue- and cell-type-specific markers relevant to disease-associated molecular pathways.

Methodology:

Groups samples by similar expression levels to identify marker genes from microarray data, uses publicly available microarray datasets from NCBI GEO, and compares predictions to literature-derived markers and another tissue-specific gene identification tool.