Overview
We quantify proteins and their modifications and interpret what changes between conditions.
Salient features
- DDA, DIA and targeted workflows
- Post-translational modification localisation
- Statistical testing and visualisation
Analyses we offer
Protein sequence analysis
Characterises protein sequences: domains, conservation, clustering and language-model embeddings.
Methods: biopython, MMseqs2, esm.
Protein physicochemical analysis
Computes properties such as charge, hydrophobicity, pI and stability for proteins and peptides.
Methods: biopython, Peptides, modlAMP.
NMR-based proteomics analysis
Processes NMR spectra of proteins for assignment and interaction studies.
Methods: nmrglue, nmrpy.
Antibody array analysis
Normalises and analyses antibody microarray data.
Methods: PAA, limma.
MS-based targeted proteomics
Quantifies selected proteins by SRM/PRM with transition-level quality control.
Methods: pwiz, MSstats.
PTM analysis
Identifies and localises post-translational modifications such as phosphorylation and acetylation.
Methods: FragPipe, PTM-Shepherd, alphapept.
RPPA analysis
Quantifies protein levels from reverse-phase protein arrays with spatial correction.
Methods: rppaspace, RPPanalyzer, Rmiracle.
MS-based metaproteomics
Identifies proteins expressed by whole microbial communities.
Methods: unipept, searchgui.
Proteogenomics analysis
Integrates proteomic and genomic data to discover novel peptides and variants.
Methods: pgatk, quantms.
Deep mutational scanning analysis
Scores the effect of thousands of mutations from selection and sequencing data.
Methods: Enrich2, dms_tools2.
DIA mass-spec proteomics
Analyses data-independent acquisition runs for deep, reproducible quantification.
Methods: DiaNN, OpenMS.
What you receive
- A written report with methods, parameters and interpretation
- Processed data tables and publication-quality figures
- Scripts and settings so every result can be reproduced
Not sure which analysis fits your data? Contact us and we will advise.