A Python Toolkit for Managing a Large Number of Experiments
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Updated
Feb 9, 2024 - Python
A Python Toolkit for Managing a Large Number of Experiments
R package to work on the RuG Peregrine cluster
This is a 16S amplicon analysis for visualizing microbiome data using QIIME, QIIME2R and Phyloseq. DNA was isolated fom both sediment cores and seabird fecal samples for this analysis.
Application for monitoring performance and energy consumption in a computing cluster.
Monitoring parallel file system usage in a high-performance computer cluster
This is a paleolimnological analysis using tidypaleo in R. View the Github page to walk through each step of the analysis.
Day 1 of the UPPMAX intro course
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