Services

The Bioinformatics Unit’s services are structured in three main lines: Help Desk, Common Services and Personalised Services. Each of these three lines have different requirements, access protocols, and queuing systems.

Help Desk

The Bioinformatics Unit Help Desk is designed to attend quick and short questions that can be resolved easily. We can address questions about statistics, bioinformatics methods and tools, some results we produced earlier, etc. It should be possible to reply by email, or in a short meeting. Questions should be ideally addressed by email, although you can come and visits us if you think it will be easier and quicker. Questions will be attended in a “first come – first serve” basis.

Common Services

Common services are those that are frequent and for which we have standard pipelines in place.These include:

• Micro arrray data analysis, including differential expression analysis, functional enrichment, and common figures like PCA, volcano plots, etc.
• RNA-seq, including differential expression analysis, functional enrichment, and common figures like PCA, volcano plots, etc.
• ATAC-aeq analysis, including peak identification, differential analysis, peak annotation, functional analysis and common figures.
• Single-cell RNA-seq, ATAC-seq or Multiomics, including running standard 10x pipelines and loupe browser files generation.

This list will grow and change according to the CABD’s necessities and the Unit’s available resources.

To access these services send us an email,, describing in detail what you need, or come and visit us, and we will have a meeting to discuss all the details and deliverables, required working time form you and us, and estimated delivery date.

All services in this track are queued by arrival time, time of execution, available resources, etc. Different projects are normally interleaved to optimise resource so no-one have to wait too much.

Personalized Services

We consider personalised services everything that is not included above, including, but not exclusively:

• Data analysis for genomic experiments not included above.
• Complex differential analyses: multi-class designs, interactions studies, etc.
• Meta-analysis, re-analysis of publicly available data, etc.
• Scientific programming: custom scripts in R, python, bash, etc., pipelines, parallelisation, adaptation to the UPO cluster, etc.
• Visualization: custom figures, diagrames, presentations, web pages, etc.
• Data release: submission to public repositories, custom databases and/or public interfaces, etc.
• Custom infrastructures: Custom galaxy servers or pipelines, Custom RStudio Servers, etc.

These services are by far the ones that take more resources, and thus have to be carefully planned in order not to halt the other tracks, and requiere the approval from the Unit scientific coordinator. Send us an email, and we will arrange a meeting with the scientific coordinator and the unit manager.