Bioinformatics expertise and omics analysestailored to your project
UbSeq supports laboratories, research teams, companies, researchers and scientific project leads with their bioinformatics needs.
From defining the analysis strategy to data processing, interpretation and structured reporting, UbSeq provides clear, tailored bioinformatics services adapted to each project.
Expertise available at every stage of a project
Analytical scoping, data processing, modelling, automation and reporting are combined according to the scientific requirements of each project.
Bioinformatics analysis & omics data
Data qualification, fit-for-purpose workflows, statistical analyses and interpretation within the study design.
View service →Consulting & analysis strategy
Analysis-plan design, selection of controls and covariates, methodological review and interpretation strategy.
View service →Pipelines & automation
Versioned, reproducible workflows with explicit management of parameters, dependencies and execution environments.
View service →Reporting & scientific tools
Structured results, figures, reports and analytical provenance documentation to support review, sharing and reuse.
View service →Training & knowledge transfer
Practical training tailored to the participants’ level, data and objectives, individually or in groups.
View service →Scientific & analytical expertise
Human genomics
Germline and somatic variation, CNV/SV, annotation, prioritisation and research-oriented cohort analyses.
Microbial genomics & pathogens
Genomic characterisation, typing, comparative genomics, phylogenomics and resistance or virulence determinants.
Transcriptomics
Quantification, expression modelling, differential analyses, splicing and functional interpretation.
Microbiome & metagenomics
Taxonomic and functional profiling, community structure, compositional analyses and metadata integration.
Biostatistics & data integration
Study design, statistical modelling, covariate control, validation, data integration and visualisation.
Analytical rigour, traceability & reproducibility
Robust analysis relies on a coherent design, qualified data and explicit analytical provenance. Methods, references, versions, parameters and critical decisions are documented to the level required by the project.
Explore the UbSeq approach →Methods guided by study design and scientific hypotheses
Method selection follows from the study design, data structure, available controls and expected level of inference.
A framework designed to produce interpretable, reproducible results
Each engagement is structured around the elements that determine validity, traceability and interpretation of results.View collaboration options →
Study design
Hypotheses, cohorts, contrasts, controls, covariates and interpretation criteria are defined up front.
Data qualification
Quality, provenance, metadata, references and technical factors are assessed before downstream analyses.
Analysis & inference
Processing steps and statistical models are applied with appropriate controls and explicit analytical provenance.
Reproducible reporting
Results, methods, parameters and limitations are structured to facilitate reading, review and reuse.
Do you have data to analyse or an analysis strategy to define?
Briefly describe your need. No file or sensitive data is requested through the public form.