Introduction to Bioinformatics Analysis
Bioinformatics converts raw sequencing or imaging outputs into interpretable biological results. Depending on the assay, this may include read quality assessment, alignment, quantification, differential analysis, cell or spatial annotation, regulatory-feature analysis, visualization, and integration with experimental metadata.
Bioinformatic planning should begin before samples are collected. Early consultation is especially valuable for choosing biological replicates, avoiding confounded batches, defining comparisons, estimating sequencing requirements, and ensuring that the assay produces data capable of answering the intended question. Analysis support is also appropriate when investigators need primary processing, standard statistical comparisons, or a collaborative interpretation plan.
Analysis cannot repair a study in which biological groups are confounded with batch, essential controls are absent, replication is inadequate, or the selected assay does not measure the required biology. Highly specialized software development, clinical interpretation, very large custom projects, or analysis without sufficient metadata may fall outside standard service scope and require a separate collaboration or referral. To quote Ronald Fisher, "To consult the statistician after an experiment is finished is often merely to ask him to conduct a s post mortem examination. He can perhaps say what the experiment died of."
For more details, please visit or bioinformatics analysis by assay page.
Compatible sample types
For analysis-only projects, the “sample” is a complete and securely transferable data package. This may include FASTQ files, aligned files, count matrices, platform output, images, sample metadata, the experimental design, reference-genome details, and a description of prior wet bench or computational processing. Data acceptance depends on format, completeness, quality, provenance, security requirements, and the requested analysis.
Genomics CoLab offerings
Experimental-design consultation: Consultations prior to carrying out the experiment including considerations for assay choice, biological replication, batch design, controls, sequencing depth, statistical contrasts, and grant planning.
Primary processing: May include alignment or platform processing, generating quality control metrics, and generation of analysis-ready matrices or files.
Fee-for-service analysis: Assay-appropriate normalization, standardized analysis, differential gene/peak comparisons, standard visualizations, and summarized results.
Collaborative analysis: Project-specific interpretation and exploratory analysis, integration across data types, customized figures, and manuscript or grant support.
Design considerations
When you start your project you will discuss with Genomics CoLab term the following items to assure we can meet your project needs:
- The biological question, primary endpoint, and statistical comparison.
- Biological versus technical replicates and relevant covariates.
- Batch structure and whether it is separable from biological groups.
- Reference genome, annotation version, and required software or pipeline.
- Expected outputs, level of interpretation, visualization needs, and authorship or collaboration expectations.
- Data volume, storage, transfer, access, and security requirements.
- Whether analysis is paired with a CoLab assay or begins from externally generated data.
What the CoLab performs
The CoLab defines the analysis scope with the investigator, reviews data and metadata, performs the agreed processing and statistical analysis, documents relevant methods, and delivers the specified files, tables, figures, or interpretive summaries. The scope of primary processing, standard analysis, and collaborative work is established before analysis begins.
What the investigator supplies
The investigator supplies complete data and metadata, experimental groups and covariates, reference information, prior-processing details, the biological questions and planned comparisons, and timely scientific input during interpretation. The investigator is responsible for confirming that the data can be shared with the CoLab under applicable UCSF and project policies.
Data and analysis delivered
Deliverables are project-specific and may include quality-control reports, processed matrices, statistical result tables, annotations, reproducible analysis outputs, standard or publication-oriented figures, and a methods summary. Raw and intermediate files, code, and long-term storage responsibilities should be agreed upon explicitly.
Pricing and sequencing considerations
Analysis may be included as a defined component of an assay, priced as a standard project package, or scoped separately according to complexity and staff effort. Primary processing should be distinguished from customized biological interpretation. For new experimental projects, sequencing design and analysis planning should be considered together so that the generated data support the intended comparisons.
To start a project
Please download our project description form, fill it in with the as much detail as you can and then send it along with a consultation request to the [email protected] email address.