A bioinformatics practice grounded in methodological rigour
UbSeq designs analyses in which study design, data quality, analytical provenance, statistical inference and interpretation are treated as a coherent whole.
From the scientific question to an interpretable, reproducible analysis
The objective is to build an analytical strategy suited to the real project context, using justifiable methods, sufficient traceability and results whose limitations can be examined explicitly.
Support can cover a targeted analysis, a complete project or recurring needs, with documentation and automation proportional to the scientific and technical stakes.
Methodological principles
- Hypothesis, design and interpretation criteria defined before analysis
- Methods selected according to technology, controls and data structure
- Quality, bias, confounders and inference limits examined explicitly
- References, versions, parameters and analytical provenance documented to the required level
- Results, assumptions and uncertainties reported in a readable and verifiable form
A collaboration structured around the scientific requirements of the project
Scientific scoping
Question, design, data, metadata, controls and evaluation criteria are clarified before methodological choices are made.
Analytical provenance
Methods, references, versions, parameters and critical transformations are documented to enable review of the analysis.
Proportionate reproducibility
The level of automation, versioning, testing and documentation is adjusted to the workflow’s lifespan and criticality.
Reporting & limitations
Results are accompanied by the elements needed for interpretation: assumptions, controls, diagnostics, uncertainties and limitations of use.
Discuss a bioinformatics project
Present the scientific question, available data and expected outcome. The initial discussion helps assess the analytical scope and methodological points that need clarification.