Proteomics Data Analysis
Novus Genomics offers established, cost-efficient and rapid turnaround analysis services for proteomics data from a range of platforms including labelled or label-free LC-MS/MS, and protein immunoassays. We are able to receive data in various formats for the analysis such as peptide- or protein-specific intensities and spectral count matrices.
Proteomics analyses are relevant for a range of applications such as:
- Profiling of proteomes between normal and diseased tissues
- Identification and quantification of protein biomarkers and PTMs associated with drug response or survival
- Identification of direct targets and indirect effects of drugs and other active molecules
- Exosome research (exosome profiling, identifying exosome signatures and biomarkers etc.)
Proteomics is the investigation of the protein composition of cells, tissues, organisms or other biological systems in a high throughput manner. In addition to steady-state abundances, proteomics can also help to determine the location and rate of protein production and degradation at a specific time. Other proteomics techniques enable the identification of post-translational modifications (PTMs), interactions, and movement between subcellular compartments.
Most analyses of proteomics data are designed to quantify the changes in protein abundance, modification, location or binding specificity between groups of samples that differ with respect to tissue of origin, treatment, experimental condition or outcome.
Our routine proteomics data analysis pipeline includes:
- Assessment of sample metadata to identify associations between biological and technical study variables
- Quality control evaluation of raw protein or peptide 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 tools (e.g. voom/limma, DESeq2, EdgeR)
- Functional enrichment analysis using resources such as the Reactomepathway knowledgebase and the Gene Ontology (GO) database
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 gene expression 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 were very pleased with the service provided by Novus Genomics. In particular, the Novus team were flexible and willing to spend time understanding our specific project needs and the key scientific questions we were asking of the experiments. They tailored the data output in a way that specifically addressed these questions, which was really helpful. The data package was Web-based and interactive and we were delighted with the way it was presented and explained to us. We will certainly work again with the Novus team for any future projects.
