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Microbial Ecology Data Analysis
Microbial Ecology Data Analysis
Software Engineering
・
Taiwan
▪ Jun. 2022- Aug. 2022 Data analysis via R studio: Analyzing the microbial ecology of contaminated soils
a. To do a cross-sectional comparison of microbial communities of soils from two contaminated sites, COV (United Kingdom) and CH (Switzerland).
b. The data were analyzed via R studio to elucidate the role played by the environment and reveal key members of the microbial consortia representing these sites to solve the soil contamination problem.
c. The biological data analysis including alpha diversity, beta diversity and regression modelling etc.
• Alpha diversity: Summarize community diversity for a single sample.
• Beta diversity: Compares the similarity between two samples.
• Normalized Stochasticity Ratio(NST): Quantify ecological
stochasticity in different situations.
• Quantitative Process Estimates(QPE): Whether the microbial
samples have an underlying signature of a single environment
or multiple environments.
• Core microbiome heat map: The percentage of
microorganisms present in the sample.
• MA plot (Bland-Altman plot): Compare the differences between
the two sample communities.
• Regression modelling: Subset regression and CODA GLMNET
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