Statistical analysis of 16S rRNA data using Chipster (Jarno Tuimala)
Chipster Tutorials・2 minutes read
Statistical analysis of 16s rRNA data sets in Chipster involves visualization and tools based on R packages. The presentation covers tools like rarefaction curves, rank abundance curves, and ordination analysis for interpreting and analyzing data sets with examples and references.
Insights
- Chipster offers a range of statistical tools based on R packages for analyzing 16s rRNA data sets, including rarefaction curves, rank abundance curves, and ordination analysis like PCA and RDA.
- The presentation emphasizes the importance of interpreting ordination analysis results, highlighting the distinction between unconstrained PCA and constrained RDA methods, and provides guidance on utilizing explanatory variables effectively while cautioning against excessive use for clearer interpretation.
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Recent questions
What is the purpose of rarefaction curves in statistical analysis?
Rarefaction curves estimate species richness in a sample.
How are rank abundance curves used in analyzing species richness?
Rank abundance curves show species richness and evenness in samples.
What is the significance of ordination analysis in ecological studies?
Ordination analysis displays and analyzes multidimensional data sets.
How does Chipster aid in statistical analysis of metagenomics data sets?
Chipster offers tools for visualization and statistical analysis.
What are the key statistical tests available in Chipster for group differences?
Chipster offers permutation tests and multivariate homogeneity tests.
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