University of Colorado Anschutz Medical Campus
Explore lipid-related molecular changes across biological samples using untargeted LC-MS analysis of the hydrophobic fraction. Our analytical approach supports lipid discovery and comparative profiling in biomedical and basic research.
What the data can provide
Untargeted analysis emphasizes detected molecular features and differences in relative abundance. Lipid-class coverage and structural identification depend on sample composition, extraction, chromatography, ionization, fragmentation information and available references.
Potentially detected families include glycerolipids, glycerophospholipids, sphingolipids, sterol-related lipids and fatty-acyl species. These are examples of relevant lipid classes, not a guaranteed list of compounds detected or identified in each sample.
Feature detection is not equivalent to confirmed compound identification. Some signals can be assigned to candidate formulas, lipid classes or putative structures; others remain unidentified. Isomer resolution and exact structural assignments require additional analysis.
Data analysis and interpretation
Our data analysis services support statistical comparisons, unsupervised pattern discovery, feature prioritization, and biological interpretation. PCA, heatmaps and clustering can highlight sample-level trends; univariate analyses can help prioritize signals for additional annotation and confirmation.
Biological interpretation is constrained by annotation confidence. Pathway-level conclusions are more limited when many significant molecular features cannot be assigned to sufficiently specific structures.
We can help select an analytical approach based on the biological question, sample matrix and desired coverage.