Master Assignment
Cluster analyses for phytoplankton community fingerprinting
Student project on network analyses on flow cytometry data
Type: Master EE/CS
Period: (TBD)
Student: (Unassigned)
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Description:
Student project on network analyses on flowcytometry data
Our lakes, rivers and oceans harbor a vast variety of microbial life, notably including phytoplankton. This versatile group of photosynthetic microbes play a major role in the global carbon cycle, and are essential for all aquatic life. Phytoplankton substantially vary in their size, from smaller than 1 µm, up to colonies of over 1 mm. Also, they differ in their photosynthetic pigments, and thus their color. Indications of cell size, pigmentation, and many other characteristics can be detected by flow cytometry. At the NIOO-KNAW, we have a custom build FACS flow cytometry system that can detect a broad size range of particles, and can assess up to 19 different parameters based on particle exciting through 5different lasers. With a count rate of up to 10.000 particles per second, this leads to big data libraries that require substantial data analyses protocols. Among the main questions include: 1) analyses of different clusters of algal groups based on different combinations of parameters, and 2) analyses of fluorescence strength as proxies for cell specific characteristics. In this project, the student will help setting up a data analyses pipeline first focusing on cluster analyses, and afterwards possibly assessing the possibilities for acquiring(shifts/differences in) cell specific data following -omics approaches.