Metabolomics Data Analysis
Novus Genomics offers an established, cost-efficient and rapid turnaround analysis services for metabolomic data from a range of platforms including tandem GC-MS, LC-MS and NMR. We are able to receive data in various formats for the analysis such as metabolite abundance tables or spectral data.
Metabolomic analyses are relevant for a range of applications such as:
- Profiling of metabolites in biofluids between normal and diseased subjects
- Identification of metabolites and derivatives associated with drug exposure and toxicity
- Understanding changes in metabolites and metabolic pathways over time
Metabolomics is the study of processes involving metabolites and small molecules within biological systems, typically using high throughput profiling approaches. Metabolic profiling gives a snapshot of ongoing chemical processes within the cell which directly reflects the underlying biochemical activity and state of cells. This can include the evaluation of metabolic processing for both endogenous metabolites (produced by the host organism) as well as exogenous sources, for instance from diet or drug exposure. As such, metabolomics has the potential to link genetic, environmental, and other physiological elements to specific disease states.
Many studies involving metabolomic data are from minimally invasive sources, e.g. plasma, serum, urine and saliva, but can also be extracted from many other tissues. The chemical properties of metabolites can be widely different, from hydrophobic macromolecules such as lipids (lipidomics) to smaller water-soluble metabolites such as sugars. Due to these differences, it is not generally possible to capture all metabolites by a single analytical method and several approaches are commonly used in combination, for instance GC-MS and LC-MS.
How it worksOur routine metabolomic and lipidomic analysis pipelines include:
- Assessment of sample metadata to identify associations between biological and technical study variables
- Quality control evaluation of metabolite abundance data
- Normalisation across samples using appropriate data normalisation techniques
- Identification and correction of batch-related effects
- Assessment, and where appropriate, imputation of missing values
- Exploratory analysis and evaluation of all types of data using unsupervised clustering and dimension reduction techniques to assess overall sample quality and identify possible outliers
- Differential abundance analysis with a range of statistical tools (e.g. limma)
- Functional enrichment analysis using metabolic pathway resources such as MetaCyc™
Where required we can include a range of further bolt-on analyses, for example gene set enrichment analysis (GSEA) to assess functional enrichment, or an integrated congruence analysis with other ‘omics’ data sets such as transcriptomic or proteomic data to obtain a more holistic view of a biological system.
Every time our clients work with us, they benefit from:
- A dedicated analyst backed by an experienced team to curate all data, identify the most appropriate statistical approach to take and provide a biological interpretation of results.
- An interactive data analysis report, internally peer-reviewed, including all analysis methods and results.
- Post-report follow ups: upon receipt of our data analysis report, we arrange a teleconference so that our lead analyst can talk through the results.
Access to large capacity computing and secure data storage facilities.
We found that the package they offered is a very attractive one, compared to other organisations we talked to. Novus provide you with a very nice data package, that is fully interpretable and allows you to draw meaningful conclusions.
