Workflows
How DAVnSCI works with clients
Every project follows a structured, five-stage process — from understanding the research objective to supporting final dissemination. The process is designed to be transparent, collaborative, and scientifically sound at every step.
Understand the Research Objective
Every engagement begins with a structured conversation about the research question, context, and intended outcomes. We invest time in understanding the scientific problem before discussing any method or tool.
This step involves understanding the experimental design, the nature of the data, the publication or reporting intent, and any constraints or timelines. Where a project involves complex multi-layered data, we identify the analytical questions that are central versus peripheral to the primary objective.
Stage outputs
Assess Data and Problem Context
We conduct a thorough assessment of the available data — its quality, structure, completeness, and suitability for the intended analysis. This step prevents misaligned analytical choices downstream.
Data assessment includes reviewing raw data formats, identifying quality issues, evaluating sample sizes and statistical power, understanding the experimental variables, and determining whether the data is sufficient to address the stated research question. Where data quality is a concern, we provide specific recommendations before proceeding.
Stage outputs
Design the Analysis and Visualisation Workflow
Based on the objective and data assessment, we design a bespoke analytical and visualisation workflow. This is documented transparently so the client understands the approach and rationale.
The workflow design specifies the statistical methods, bioinformatics tools, and software environments to be used. Visualisation requirements are scoped at this stage — including the number and type of figures, the format specifications for target journals or reports, and any interactive or dashboard outputs. Client approval is sought before analysis begins.
Stage outputs
Deliver Outputs and Interpretations
Analysis is executed according to the agreed workflow. Outputs are delivered with documented interpretation — not as raw results, but as understood findings placed in the context of the research question.
Deliverables at this stage include processed data tables, statistical results, figures, and interpretive commentary. All code and workflows are documented for reproducibility. We provide a first round of revision based on client review, and flag any findings that require scientific discussion or clarification.
Stage outputs
Support Communication, Publication or Dissemination
The final stage involves translating outputs into the appropriate communication format — whether a manuscript, report, presentation, or institutional publication. We remain engaged through the communication phase.
This may include manuscript writing or editing support, structuring the results and discussion sections, preparing figures to journal specification, designing presentations for conferences or stakeholder meetings, or assisting with science communication for broader audiences. The level of involvement is agreed as part of the original scope.
Stage outputs
Process Principles
Three principles that govern every engagement
Transparency before execution
We design and document the analytical workflow before commencing work. Clients understand what will be done, why, and what the expected outputs are.
Interpretation, not just output
Results are delivered with interpretive commentary grounded in the research context. We do not deliver tables of numbers without explanation.
Reproducibility as standard
Every analysis is fully documented and reproducible. Code, workflow files, and parameter notes are provided as part of the standard deliverable package.
Common Questions
Frequently asked
How is a DAVnSCI engagement scoped?
Each project begins with an initial consultation (typically 30–60 minutes) to understand the research context, data, and objectives. Following this, we prepare a detailed scope document outlining the work, methods, deliverables, and timeline. This document is agreed before work commences.
Do you work with clients at early or exploratory stages of a project?
Yes. Some of the most valuable engagements begin before data collection is complete — helping to design analysis frameworks, define analytical questions, or identify potential issues with experimental design before they become costly.
What data formats and types do you work with?
We work with a wide range of biological and scientific data types: NGS data (FASTQ, BAM, VCF), processed omics data tables (CSV, Excel, HDF5), mass spectrometry outputs, image-based data, and standard statistical datasets. Data can be shared via secure transfer methods.
Is the analytical code and workflow shared with the client?
Yes. Reproducibility is a core principle at DAVnSCI. All analytical workflows, code (R, Python, or workflow management systems), and documentation are provided as part of the deliverables. Clients should be able to audit, understand, and extend any analysis we produce.
Can DAVnSCI support an ongoing project rather than a discrete engagement?
Yes. We offer retainer-based arrangements for institutions and research groups requiring sustained analytical or communication support over multiple months or across multiple projects.
Ready to start a project?
Contact us to schedule an initial consultation and discuss your research needs.