Proteomics is the investigation of the protein composition of cells, tissues, organisms, or other biological systems in a high throughput manner. We offer a complete proteomics data analysis pipeline from raw protein or peptide information to publication-grade visualisations and textual summaries.
What We Offer
Fios Genomics offers established, cost-efficient, and rapid turnaround proteomics data analysis for data from a range of platforms including tandem mass spectrometry, and protein immunoassays. Additionally, we regularly process both labelled and unlabelled LC-MS/MS experimental data from a wide array of mass spectrometry instruments, as well as data sets from other proteomics methods like Olink or PISA.
Our proteomics data analysis service may include the following:
Processing data from mass spectrometry experiments
We can harmonise multiple mass spectrometry runs or replicate experiments to analyse them together. We also normalise and impute values if needed before displaying the results using publication-grade visualisations in our reports. Furthermore, this process is supported by rigorous quality control to make sure any subsequent statistical analysis can deliver its full potential. Our pipelines are compatible with a multitude of data providers. Additionally we can also design novel, custom pipelines for the latest methods.
Acquiring proteomics data from public or private repositories
We can search for, collate, and reanalyse publicly available proteomic datasets, such as those available from the PRoteomics IDEntifications database (PRIDE) public repository, or apply for access to some private repositories such as the UK BioBank (UKBB), to help confirm results, uncover new information from existing data sets, or compare to results of other studies.
Statistical analysis of protein-level information
Proteomics experiments often yield large data sets of peptides or proteins with abundances in each sample. However, we can use state-of-the-art statistical methods to find proteins with significantly different abundances between samples. This can then lead to discovering new biomarkers when comparing diseased samples to controls, or identifying targets of treatments.
Pathway-level analysis of proteome changes
Generating a list of proteins that are expressed differently between samples is often not sufficient to explain all effects observed. A pathway analysis groups key proteins into functional groups and assigns them to common pathways, therefore aiding the understanding of the biology underlying an observed result. We offer multiple statistical methods and visualisations to help find the relevant pathways or keywords that define the differences between sample groups.
Integrating results from multi-omics studies
Proteomics data is often supplemented with RNA sequencing or other omics data sets. We can bring together and compare the results from multiple omics data analyses to find patterns common in some or all of them. We can also compare results from one study to another to identify common themes.
Benefits of Working with Fios Genomics
Compared to other omics data types, proteomic data, especially mass spectrometry data sets, are prone to exhibit a high amount of variance between technical replicates, and often contain a high number of missing values. However, we use the latest methods and algorithms, and build on our ever-growing list of successfully delivered projects to ensure a robust analysis is performed in each study.
When you work with us you will benefit from:
Dedicated Bioinformatician
A dedicated bioinformatician, backed by an experienced bioinformatics team, will curate all data, identify the most appropriate statistical approach to take and provide a biological interpretation of results
Interactive Data Analysis Report
Receive a searchable data analysis report that includes interactive visualisations of the data. Our reports are internally peer-reviewed and include analysis methods and results (particularly helpful if you plan to publish your research results)
Post-Report Follow-Up
Upon receipt of our data analysis report, we arrange a review call so that your project’s dedicated bioinformatician can talk you through the results and answer any questions you have about the report
Dedicated Project Manager
Your dedicated Project Manager will act as your single point of contact throughout the project. They will ensure everything from data transfer to report delivery runs smoothly and efficiently for you
Large Capacity Computing
When you choose Fios Genomics, you benefit from our large capacity computing and secure data storage facilities, where we store all your raw data, analysed data and your data analysis report
Proteomics Data Analysis Applications
There are many useful applications of proteomics data analysis, including:
Profiling of proteomes between normal and diseased tissues
Identifying key differences between healthy and diseased tissues may lead to the discovery of novel biomarkers or potential therapeutic targets. Our analyses pinpoint such differentially expressed proteins.
Identification and quantification of protein biomarkers and post-translational modifications associated with drug response or survival
The latest treatments often rely on the careful modulation of cellular pathways to achieve the desired therapeutical effect. In this regard, we can extract both PTM-level, protein-level, and pathway-level changes between treated and control samples in order to identify the mechanistic effect of treatments.
Identification of direct targets and indirect effects of drugs and other active molecules
Knockout experiments or treatments targeting specific factors are often expected to have a profound effect on the target protein. We validate these through proteomics and can also identify off-target or knock-on effects resulting from a particular treatment.
Identifying spatial or temporal changes in proteomes
Whether it is a treatment monitored over time or a tissue sample from a tumour, temporal and spatial changes can explain why living systems are dynamic and heterogeneous. We can analyse time series data of proteins and compare samples from different tissue regions in order to identify gradual changes in protein levels in space and time.
Our Experience in Proteomics Data Analysis
Some projects we have helped with:
- Measuring response of Atlantic salmon to oxidative stress
- Studying lignin biosynthesis in aspen trees
- Uncovering the effect of blood parasites on the host proteome
- Extending signalling networks to better explain the mechanism of apoptosis
- Investigation of drug or gene knockout-induced changes to proteome of cancer cells or tissues from various model organisms
- Identification of protein response to drug treatment in blood samples taken from cancer clinical trial patients
- Investigation of protein abundance and identification of differentially present proteins in exosomes from serum and urine samples to identify potential biomarkers for rare disease
- Integration of RNAseq and proteomics data to assess congruence
- Correlation of protein levels with patient response to treatment to identify predictive biomarkers
- Data mining public proteomics data sets from a neurological condition to find proteomic data sets of relevance as a baseline for a study
- Analysing publicly available cancer proteome data sets to confirm the existence of relevant biomarkers for an upcoming treatment
Our Reports
Our analysis reports come as an HTML link hosted on our secure server. This secure link contains a password-protected HTML document that is clickable, searchable, and dynamic. This allows you to easily interrogate and explore your data. Our reports always include all analysis methods, tools and thresholds.
Example Proteomics Data Analysis Report
To demonstrate what you can expect from a Fios Genomics clinical data analysis report, we have an example report available: Proteomic profiling of human colon segments. This data analysis report evaluates mass spectrometry-based proteomics data from human colon segments obtained from the PRoteomics IDEntifications database (PRIDE) public repository. To view this report contact us and ask for our ‘Proteomics’ example report.
Our Testimonials
We have utilized the Bioinformatics team at FIOS Genomics for many of our drug discovery projects, as they provide expertise in the analysis of complex bioinformatic datasets. This includes large scale datasets from public sources as well as internally generated datasets. In many instances, at the start of a project, we have planned our large scale transcriptomic/proteomic studies with the FIOS team, to ensure that the data generated would provide the information we need, and that our projects had the highest chance of success. We have been consistently impressed with the rigor of FIOS’ work, their communication throughout the projects, and the rapid speed at which they complete their analyses.
Companies We Have Worked With
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Further Information
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 by 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 Reactome pathway knowledgebase and the Gene Ontology (GO) database.
Where required we can also 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.
