Ref H12
Computational Service
Confidence Reported
Scoped After Feasibility Review
Service Overview
Flow and mass cytometry data frequently arrives with the analysis unfinished: compensation unchecked, gating inconsistent across samples, and high-dimensional panels reduced to a handful of manually drawn populations. We review compensation and quality, apply consistent manual or algorithm-assisted gating, and run dimensionality reduction and clustering on high-parameter panels so that populations are defined by the data rather than by the order in which gates happened to be drawn.
Key Features & Advantages
Compensation And Quality Reviewed First
Spillover, spread and acquisition anomalies are checked before analysis, since a compensation error propagates into every downstream population frequency.
Consistent Gating Across Samples
Gating strategies are applied uniformly and reviewed sample by sample, which removes the operator drift that makes batch comparisons unreliable.
High-Dimensional Analysis Where It Helps
Clustering and dimensionality reduction identify populations that manual gating misses on panels of twenty or more parameters, with clusters mapped back to interpretable phenotypes.
Statistics On Frequencies Done Properly
Population comparisons use tests appropriate to proportional data with paired structure and multiple testing accounted for.
Where This Service Is Used
1Immunophenotyping across treatment groups or clinical timepoints
2Analysing high-parameter spectral or mass cytometry panels
3Reanalysing an existing dataset where the original gating is inconsistent or undocumented
4Quantifying rare populations that require careful gating and statistical treatment
5Producing publication-ready cytometry figures with reproducible analysis
Methods and Techniques Applied
1FCS file quality control, compensation or unmixing review and anomaly detection over acquisition time
2Transformation selection and consistent application across all samples
3Manual gating following an agreed strategy, with per-sample review of every gate
4Automated gating and clustering for high-parameter panels, including self-organising map and graph-based approaches
5Dimensionality reduction for visualisation with cluster-to-phenotype annotation
6Frequency and marker intensity comparison with appropriate statistical testing and effect sizes
What We Need From You
1FCS files with the panel definition, fluorochrome or metal assignment and instrument details
2Compensation or unmixing controls used in the experiment
3Sample metadata including group, timepoint, batch and acquisition date
4Existing gating strategy or workspace if one is to be reproduced or corrected
What You Receive
1Quality control and compensation review report with any problems identified per sample
2Gated population frequencies and marker statistics in tabular form
3Clustering and dimensionality reduction results with annotated populations
4Statistical comparison across groups with plots and effect sizes
5Reproducible analysis scripts and publication-quality figures
What We Compute and Report
1Per-sample quality and compensation assessment with problems identified individually
2Population frequencies and marker intensity statistics under a consistently applied gating strategy
3Cluster assignments with phenotype annotation for high-parameter panels
4Dimensionality reduction coordinates for visualisation and inspection
5Group comparison statistics with effect sizes and multiple-testing correction
Questions We Are Asked Before Scoping
Can you fix data with poor compensation?
▸Sometimes, if the controls are available. Where spillover cannot be corrected reliably, we say which markers are affected and which conclusions they can no longer support.
Manual gating or clustering?
▸Both, usually. Manual gating gives comparability with established literature; clustering finds populations no one thought to gate. Using them together is more informative than choosing.
Do you analyse rare populations?
▸Yes, with attention to the event counts available. Where a population is too rare for reliable statistics at the acquired cell numbers, we state the detection limit rather than report an unstable frequency.
Interpretation and Limitations
Computational predictions prioritise hypotheses; they do not independently establish binding, biological activity, therapeutic efficacy, safety or clinical validity. Performance depends on input quality, target class, the structural evidence available and the applicability domain of the selected methods. Scores used for ranking are comparative devices and should not be read as measured quantities. All deliverables are for research use only and are not intended for diagnostic or therapeutic use.
Is This the Right Service for You?
Choose this when
Gating has been applied inconsistently across samples or operators
A high-parameter panel is being reduced to a handful of manual gates
Rare populations need quantifying with defensible statistics
Consider another service when
Transcriptional state rather than surface phenotype is the question
Bulk & Single-Cell RNA-Seq Analysis Tissue context matters for the populations involved
Spatial Transcriptomics Analysis What Goes Wrong, and How We Handle It
These are the failure modes that produce confident-looking results which do not survive the next experiment. Each one is designed against rather than discovered afterwards.
Compensation errors propagating into every population frequency
Spillover and spread are reviewed before analysis, and affected markers are named rather than silently used.
Operator drift in manual gating across a long study
One gating strategy is applied uniformly with per-sample review, which removes a common source of spurious batch effects.
Rare population frequencies quoted from too few events
Detection limits are computed from acquired event counts, and frequencies below them are reported as unquantifiable.
A Worked Example
Reanalysing a 22-colour panel gated by hand
The situation
Manual gating had produced twelve populations and an unexplained batch difference across acquisition dates.
What the work involved
Compensation and acquisition quality were reviewed, a uniform gating strategy was applied, and clustering was run in parallel on the full parameter space.
What came back
The batch difference traced to a compensation change midway through the study. Clustering also recovered two populations manual gating had missed, one of which separated the treatment groups.
Illustrative of the shape this work takes. Details are generalised, no client or target is identified, and scope and outcome vary with the system in question.
Service Workflow
1
Scientific Consultation
We discuss the objective, the decision it supports and the data you hold. Nothing is quoted before we understand what the result has to answer.
2
Feasibility Review
We check that the data, target class and available structural evidence can support the proposed approach, and say plainly where they cannot.
3
Technical Proposal
Scope, methods, deliverables, timeline and price are confirmed in writing, together with the limitations we expect to report.
4
Computation and QC
The analysis runs on pinned tool versions in a containerised environment, with quality checkpoints and method comparison where that is informative.
5
Report and Follow-Up
You receive the ranked results, the documented methods, the limitations and a proposed validation plan, plus support in interpreting them.
Service Process
1
Online Consultation
›
2
Solution Matching
›
3
Service Contract
›
4
Project Execution
›
5
Data Delivery
Specifications & Turnaround
Note: ICDMO delivers computational (in silico) services. Results prioritise hypotheses for testing; they do not by themselves establish binding, biological activity, efficacy or safety. All deliverables are for research use only and are not intended for diagnostic or therapeutic use. Downstream experimental work is scoped separately and executed through qualified partners.
Get a Custom Quote
Our scientific team responds within 24 hours with a detailed technical proposal and pricing tailored to your project.
Contact Us Online ConsultationStandard Deliverables
✓Sequence-verified final product
✓Full QC documentation
✓Certificate of Analysis (CoA)
✓Electronic data files
✓Project completion report
Why ICDMO?
Computational CDMO Focus
Reproducible, Versioned Pipelines
Confidence & Limitations Reported
Experiment-Aware Recommendations
Response Within One Business Day