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CN EN

Proteomics and metabolomics data analysis

For DIA / DDA / TMT quantitative proteomics, phospho- and other PTM datasets, and targeted or untargeted LC-MS / GC-MS metabolomics. We start from quantification matrices, or from raw spectra if searching is needed.

Standard analysis

  • Database search and quantification (DIA-NN / MaxQuant / Spectronaut) or use of an existing matrix
  • Missing-value handling, normalisation, QC (CV distribution, correlation, PCA)
  • Differential proteins / metabolites with FDR control, volcano and heatmaps
  • GO / KEGG / Reactome enrichment and metabolic pathway maps
  • Protein interaction networks (STRING) and hub nodes
  • PTM site quantification and motif analysis

Optional advanced modules

  • WGCNA and time-series clustering
  • Joint protein–metabolite pathway analysis
  • Machine-learning feature selection for candidate biomarkers, with cross-validation and stated limits
  • Subcellular localisation and domain annotation
  • Integration with transcriptomics

What you send and what comes back

You provideYou receive
Raw spectra or quantification matrixQC report and normalised quantification matrix
Sample sheet: groups, batchesDifferential and enrichment tables with publication-ready figures
Platform and search settings if availableNetwork files (Cytoscape-ready)

Typical turnaround: 7–12 working days for the standard scope; complex designs as stated in the written analysis plan. Quotes are per project, returned within 1 working day.

No public example is available for this analysis yet. Deliverables follow the same structure as our sample reports (report, figures, tables, code, methods text); the specific figures are listed in the written plan.

How are missing values handled in proteomics?

By type: random missingness is imputed; values below detection use a minimum-value approach. The report states the choice and its effect.

How reliable is untargeted metabolite identification?

We report identification levels (standard match, library match, formula only) for every metabolite.

Multi-omics integration

Two or more omics layers from the same samples used to answer one question: transcriptome + proteome, transcriptome + metabolome, genome + transcriptome, microbiome + metabolome, single-cell + spatial. The question comes first, then the integration method.

Standard analysis

  • Unified QC and sample-matching checks across layers
  • Cross-layer correspondence of differential results (e.g. gene–protein concordance, nine-quadrant plots)
  • Correlation analysis and joint heatmaps
  • Joint pathway enrichment with all layers mapped to the same pathways
  • Key-molecule selection and visualisation

Optional advanced modules

  • Multi-omics factor analysis (MOFA+), DIABLO and similar models
  • Microbe–metabolite–host gene association networks
  • Genotype–expression (eQTL) and expression–protein (pQTL) association
  • Joint single-cell and spatial localisation
  • Multi-layer networks and key regulatory nodes

What you send and what comes back

You provideYou receive
Raw data or completed results for each layerIntegration report with joint figures (PDF/SVG/PNG)
Sample mapping table across layersKey molecule and pathway tables
The core questionNetwork files and analysis code

Typical turnaround: 15–25 working days for the standard scope; complex designs as stated in the written analysis plan. Quotes are per project, returned within 1 working day.

No public example is available for this analysis yet. Deliverables follow the same structure as our sample reports (report, figures, tables, code, methods text); the specific figures are listed in the written plan.

Samples do not match one-to-one across layers.

We integrate the overlapping samples and use the rest for single-layer analysis; the plan states the approach.

We already have reports for each layer. Can you do only the integration?

Yes. Send the result tables and the sample mapping.

Public data mining (GEO / TCGA / SRA / single-cell atlases)

Results without new experiments: validate a hypothesis, shortlist candidate genes, add evidence a reviewer asked for, or produce preliminary data for a grant.

Standard analysis

  • Search and selection of suitable datasets with stated inclusion reasons
  • Download, format harmonisation and batch assessment
  • Differential expression, survival analysis (KM curves, Cox regression), correlation
  • Prognostic model building and evaluation (LASSO, nomogram, ROC)
  • Immune infiltration estimation (CIBERSORT, ESTIMATE) and immune-related analysis
  • Cross-validation across datasets

Optional advanced modules

  • Re-analysis of public single-cell data and subpopulation mapping
  • Pan-cancer analysis
  • Drug sensitivity association (GDSC, CTRP)
  • Mendelian randomisation
  • Joint validation with your own data

What you send and what comes back

You provideYou receive
The research question, target genes or pathwaysDataset list with inclusion rationale
Known candidate dataset accessions (optional)Publication-ready figures and result tables
Your own data for validation (optional)Code and a reproducible workflow

Typical turnaround: 5–10 working days for the standard scope; complex designs as stated in the written analysis plan. Quotes are per project, returned within 1 working day.

No public example is available for this analysis yet. Deliverables follow the same structure as our sample reports (report, figures, tables, code, methods text); the specific figures are listed in the written plan.

Can public-data results be published directly?

They can form part of a paper, but reviewers usually ask for experimental validation; the report points out which conclusions need it.

How do you make sure the chosen datasets fit?

At the plan stage we list candidate datasets with sample size, platform and clinical information for you to confirm before analysis.

Custom analysis and manuscript revision

For needs a standard pipeline does not cover: analyses and figures a reviewer asked for, re-plotting existing results, re-analysis across platforms, or a specific analysis designed around your idea.

Standard analysis

  • Point-by-point mapping of reviewer comments to the analyses, figures and statistics required
  • Re-plotting and layout of existing results to journal specifications
  • Review of an existing analysis: is the method appropriate, do the data support the conclusion
  • Single tasks: only enrichment, only survival analysis, only one figure
  • Written description of methods for the response to reviewers

Optional advanced modules

  • Merging and re-analysing data across batches or platforms
  • Custom statistical models and tests
  • Custom visualisations (composite panels, circos, Sankey)
  • Reproducing and comparing published analyses

What you send and what comes back

You provideYou receive
Reviewer comments or a description of the needSupplementary analyses and figures mapped to each comment
Existing data, results and figuresResponse material organised to your needs
Original methods and parameters if availableCode and methods description

Typical turnaround: 3–10 working days for the standard scope; complex designs as stated in the written analysis plan. Quotes are per project, returned within 1 working day.

No public example is available for this analysis yet. Deliverables follow the same structure as our sample reports (report, figures, tables, code, methods text); the specific figures are listed in the written plan.

Do you take on a single figure?

Yes. Describe the data and the requirement and we quote per project.

There is a revision deadline.

Tell us the journal deadline; the plan states the delivery date, and if it cannot be met we say so before quoting.

Tell us the data type and the question you want answered. You will receive a written analysis plan and quote within 1 working day.

Request an analysis plan