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You are here: Moseley Bioinformatics Lab>Main Web>LabServices (26 Apr 2025, HunterMoseley)Edit wiki text | Edit Attach
Lab Services
Through shared resource facilities, service cores, and grant-funded collaboration, we provide a range of bioinformatics and systems biology services. We develop many of the tools that we use and can provide customized analyses, tailored to the specific experimental design, analytical technique, and scientific question.Contact Information
- Hunter Moseley - hunter.moseley@uky.edu
- Robert Flight - robert.flight@uky.edu
Major Services
Omics Data Analysis
We have analyzed datasets derived from all major omics technologies including epigenomics, genomics, transcriptomics, proteomics, and especially metabolomics.Differential Abundance Analysis
We perform differential abundance analyses on various types of omics datasets, especially transcriptomics, proteomics, and metabolomics datasets.- In transcriptomics, these analyses are referred to as differential expression analysis.
- These analyses are quite popular, especially when combined with annotation enrichment analysis.
Annotation Enrichment Analysis
categoryCompare
We have implemented categoryCompare, a flexible framework for enrichment of feature annotations and comparisons between enrichment of annotations across two or more experimental groups.- Available on GitHub: https://github.com/rmflight/categoryCompare2
- Flight et al., "CATEGORYCOMPARE, an analytical tool based on feature annotations" Frontiers in Genetics 5, 98 (2014)
GOcats
We have implemented a novel tool that organizes GO into subgraphs representing user-defined concepts, while ensuring that all appropriate relations are congruent with respect to scoping semantics.- Available on GitHub: https://github.com/MoseleyBioinformaticsLab/GOcats
- Eugene W. Hinderer III and Hunter N.B. Moseley. "GOcats: A tool for categorizing Gene Ontology into subgraphs of user-defined concepts" PLOS One 15, e0233311 (2020).
- Eugene W. Hinderer III, Robert M. Flight, Rashmi Dubey, James N. MacLeod, and Hunter N.B. Moseley. "Advances in Gene Ontology Utilization Improve Statistical Power of Annotation Enrichment" PLOS One 14, e0220728 (2019).
Lipid Annotation Enrichment Analysis
We have developed multiple approaches to detect lipid characteristics of interest in lipidomics datasets.- Jing Li, Liping Yang, Jun Song, Baoxiang Yan, Andrew J. Morris, Hunter N.B. Moseley, Robert M. Flight, Chi Wang, Jinpeng Liu, Heidi L. Weiss, Edward F. Morris, Ilyes Abdelhamid, Mathias J. Gerl, Olle Melander, Susan Smyth, B. Mark Evers. "Neurotensin accelerates atherosclerosis and increases circulating levels of short-chain and saturated triglycerides" Atherosclerosis 117479 (2024).
- Joshua M. Mitchell, Robert M. Flight, and Hunter N.B. Moseley. "Untargeted lipidomics of non-small cell lung carcinoma demonstrates differentially abundant lipid classes in cancer vs non-cancer tissue" Metabolites 11, 740 (2021).
Interaction Network Analysis
We provide a range of interaction network analyses utilizing custom-built interaction networks using molecular interaction data derived from public repositories.Biomarker Analysis
We can perform a variety of biomarker analyses, including (but not limited to):- Principal Component Analysis for visualization of systematic variance and quality control.
- Correlation Matrix Analysis for quality control.
- Classification using machine learning methods, especially Random Forest.
Metabolomics Data Analyses
We have extensive expertise in analyzing both NMR and mass spectrometry metabolomics datasets.Small Molecule Isotope Resolved Formula Enumerator (SMIRFE)
This is a completely untargeted, data-driven isotopically-resolved metabolite assignment methodology.- Joshua M. Mitchell, Robert M. Flight, and Hunter N.B. Moseley. "Small Molecule Isotope Resolved Formula Enumeration: a Methodology for Assigning Isotopologues and Metabolites in Fourier Transform Mass Spectra" Analytical Chemistry 91, 8933 (2019).
- Joshua M. Mitchell, Robert M. Flight, and Hunter N.B. Moseley. "Untargeted lipidomics of non-small cell lung carcinoma demonstrates differentially abundant lipid classes in cancer vs non-cancer tissue" Metabolites 11, 740 (2021).
Natural Abundance Correction
We have implemented a unique deisotoping method that corrects for isotopic labeling derived from natural abundance in multi-labeling experiments.- Carreer et al., "A computational framework for high-throughput isotopic natural abundance correction of omics-level ultra-high resolution FT-MS datasets" Metabolites 3, 853-866 (2013)
- Hunter N.B. Moseley. "Correcting for the Effects of Natural Abundance in Stable Isotope Resolved Metabolomics Experiments Involving Ultra-High Resolution Mass Spectrometry." BMC Bioinformatics 11, 139-144 (2010).
Metabolic Relative Flux Analysis
This advanced metabolomic flux analysis method called moiety modeling is under development and we hope to offer it as a service soon.- Huan Jin and Hunter N.B. Moseley. "Moiety Modeling Framework for Deriving Moiety Abundances from Mass Spectrometry Measured Isotopologues" BMC Bioinformatics 20, 524 (2019).
- Hunter N.B. Moseley, Andrew N. Lane, Alex C. Belshoff, Richard M. Higashi, and Teresa W-M. Fan. "A novel method for deconvoluting metabolic subunits from mass isotopologues in stable isotope resolved metabolomic experiments under non steady-state conditions: application to the biosynthesis of UDP-GlcNAc" BMC Biology, 9, 37 (2011).
- Moseley et al., "A novel method for deconvoluting metabolic subunits from mass isotopologues in stable isotope resolved metabolomic experiments under non steady-state conditions: application to the biosynthesis of UDP-GlcNAc" BMC Biology 9, 37 (2011)
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