Bioinformatics & Genomic Data Analysis Resource
Plan before sequencing
Define genome build, assay type, expected coverage, sample identifiers, controls, QC thresholds, variant classes and downstream statistical plan before data generation.
Bioinformatics essentials
Primary and secondary analysis
Primary analysis converts instrument signals to sequence reads. Secondary analysis may include demultiplexing, read QC, alignment/assembly, duplicate handling, recalibration and variant calling. Pipelines should be validated for the intended application.
Quality control
Track read count, base quality, mapping rate, duplication, insert size, depth, coverage uniformity, contamination and assay-specific metrics. A successful sequencing run does not guarantee every sample is analytically adequate.
Variant annotation
Annotate variants against the correct transcript and reference genome. Record software/database versions because annotations and classifications evolve.
Reproducibility
Use scripted workflows, locked environments/containers where feasible, checksums, version control and machine-readable metadata. Preserve raw data and analysis provenance according to policy.
Privacy
Genomic data can be identifying. Access, transfer, cloud processing and data sharing should follow consent, ethics approval, data-use agreements and applicable privacy requirements.
Research-use note: This resource is educational and methodological. Study-specific protocols require scientific review, appropriate ethics approval, validated laboratory methods and a prespecified statistical plan.
Need support with your analysis?
Our bioinformatics team can help with study design, statistical planning, genomic data analysis and reproducible reporting.