This is what bioinformatics looks like

We offer bioinformatics analysis of next-generation sequencing data so that projects can be done end-to-end and we can be a one-stop shop for investigators. After submitting the next-generation sequencing libraries to the sequencing core, we monitor as they move through their pipeline. When ready, we download the sequences (fastq files) and copy them to our server.

Our standard analysis includes quality assessment of the sequencing data received from the investigator of the sequencing core and generation of summary statistics (i.e. raw and filtered read counts, alignment rates). Moreover we will perform data exploration techniques such as principal component analysis and clustering. Finally, we will perform differential analysis across groups as indicated by the investigator's study design. Besides the result files, we will provide a detailed report describing each step of the data QC and analysis.

Software we commonly use includes:

  • MultiQC
  • DESeq2
  • Limma
  • methylKit
  • ChromHMM

Some projects are more complex than others and require the development of unique bioinformatics pipelines. If you have a project that deviates from the standard analysis, we will work with you to determine an efficient and cost-effective approach.


  • What is a typical turn around time for bioinformatics analysis?
    • The turn around time for the bioinformatics analysis varies greatly depending on the nature of your data, the study design, analysis requested, and also on the overall work load of the service core at the time. A typical project often takes ~3 weeks to finish from the time our bioinformatics team starts the analysis.
  • What data is provided to clients following bioinformatics analysis, and how?
    • The exact results provided depends to the analysis requested. Once the analyses are completed we upload the raw data, along with the results and analysis reports on the secure OHSU-based cloud service called Box. We send you the link to this data and you can easily access your data for downloading.
  • What skills/software are required to handle the results?
    • Proficiency in Microsoft Excel is crucial for exploring the results summary tables. Familiarity with the UCSC genome browser and the igv data visualization tool is extremely helpful in exploring the epigenetic and genetic landscape of regions of interest. Tutorials for these browsers are available online. Moreover, EC personnel can provide some personalized training.
  • What kind of sequencing should I do? 
    • Our assays are based on Illumina sequencing. the specific platform, read length, and coverage will depend on the assay and will be selected by the EC.
  • How can I determine if my project requires a standard or custom analysis?
    • Most projects can be done using our established computational pipelines. However, some projects might require for us to create custom pipelines to address additional questions. The EC will be in constant communication with the investigator in order to find the most cost-efficient but rigorous approach.