LTM

LTM infers genetic influences on circadian clock function by leveraging natural variation in gene expression data to link gene expression variation to measures of circadian clock strength without longitudinal sampling.

Key Features:

• In Silico Screening: LTM applies an in silico screening methodology that uses existing gene expression datasets to infer genetic influences on circadian rhythms without requiring longitudinal time-series data.
• Natural Variation Utilization: LTM correlates natural variation in gene expression within human datasets to measures of circadian clock strength.
• Cross-dataset Application: LTM has been applied to three human skin samples, one melanoma dataset, and thousands of tumor samples across 11 cancer types from The Cancer Genome Atlas (TCGA).
• Identification of Clock-Coupled Pathways: LTM identified the cell cycle pathway as a top clock-coupled candidate in healthy skin and extracellular matrix organization pathways as tightly associated with clock strength in multiple tumor types.
• Correlation with Cellular Composition: LTM-associated analyses revealed correlations between tumor clock strength and the proportion of cancer-associated fibroblasts and endothelial cells.
• Prediction and Classification: LTM predicts clock-coupled pathways and classifies factors associated with circadian clock strength.

Scientific Applications:

• Circadian pathway discovery: Identifying non-clock pathways that couple to or influence circadian clock strength across human tissues.
• Cancer circadian biology: Examining circadian dysregulation and associated pathways in tumor datasets from TCGA and specific melanoma samples.
• Microenvironment and cell-type analyses: Relating clock strength to cellular composition, including cancer-associated fibroblasts and endothelial cell proportions.

Methodology:

In silico screening of existing gene expression data that leverages natural variation to correlate gene expression with circadian clock strength, and performing correlation analyses between clock strength and cell-type proportions.