Research Support: Innovation, engineering and data analysis



Rhonda displaying the results of a successful incubation experiment at Station Papa SeaFlow data collected along the Pacific Northwest showing Synechococcus distributions in surface waters Gwenn tending to her Thalassiosira pseudonana chemostats, grown under high and low carbon dioxide levels

In the Armbrust lab, we have a team of research scientists, engineers, bioinformaticists and software developers who work on data acquisition and analysis, from extensive lab culturing projects to bioinformatics pipelines and instrumentation. Over the past several years, our lab has tackled the ongoing challenge of processing, managing and interpreting large-scale data sets, including (e.g.): SOLiD sequence reads, assembled for (meta)genomic and (meta)transcriptomic analysis, basin-wide flow cytometry data that maps temporal and spatial variability in phytoplankton communities, and additional sequence databases generated from various EST and tiling array projects, as well as collaborations with external lab groups.

Specific areas of innovation:
  1. Bioinformatics analysis pipelines and cluster computing infrastructure (led by Chris Berthiaume).
  2. Mathematical/Statistical modeling of diatom genomes and mathematical graph-based representation of
    metagenomic data (led by Tony Chiang).
  3. Development of in-house tools for SOLiD read assembly and analysis (led by Vaughn Iverson).
  4. Management of laboratory procedures and SOLiD sequencing engineer, including preparation of SOLiD sequencing libraries and instrument operation (led by Rhonda Morales).
  5. R software development for real-time analysis of flow cytometry data (led by Francois Ribalet).
  6. Development of the SeaFlow instrumentation (led by Jarred Swalwell).
  7. Culture maintenance and support for laboratory experiments (led by Irina Oleinikov).
  8. Office management and herder of cats (led by Rita Peterson).
In-house tools:
  1. SEAStAR for quantifying SOLiD read coverage in metagenomes and (meta)transcriptomes.
  2. The R package flowPhyto used to analyze high-throughout SeaFlow data.
  3. MANTA, an R package for conducting comparative metatranscriptomics.