Description Usage Arguments Value Author(s) References Examples
This function finds the relationship between most abundant taxa and numerical environmental variables based on correlation. The abundance of each feature/taxa is correlated with each of the environmental variables. A correlation test is performed and associated p-values are adjusted for multiple testing. The scheme of adjustment is elaborated in the arguments section. The function returns a data.frame with raw p-values, corrected p-values, and correlation results.
1 2 3 | taxa.env.correlation(physeq, grouping_column, method = "pearson",
pvalue.threshold = 0.05, padjust.method = "BH", adjustment = 1,
num.taxa = 50, select.variables = NULL)
|
physeq |
(Required). A |
grouping_column |
(Required). Character string specifying name of a categorical variable that is preffered for grouping the information. information, this should be one of the components of grouping vector. |
method |
A character string indicating which correlation coefficient is to be computed, available options are "pearson" which is also the default, "kendall" and "spearman". |
adjustment |
(optional). An integer to specify how the p-values should be adjusted;
|
select.variables |
(optional). Character string for the names(s) of environmental variables to be considered in correlation compution. if not given, all numerical variables are considered. |
pvalue.threshold. |
Cut off p-value for significance of correlation between taxa abundance and environmental variables, default is 0.05. |
padjust.method. |
Method for adjusting p-values. |
A data.frame
of correlation results.
Alfred Ssekagiri assekagiri@gmail.com, Umer Zeeshan Ijaz Umer.Ijaz@glasgow.ac.uk
http://userweb.eng.gla.ac.uk/umer.ijaz/, Umer Ijaz, 2015
1 2 3 4 5 | data(pitlatrine)
physeq <- pitlatrine
physeq <- taxa_level(physeq, "Phylum")
tax_env_cor <- taxa.env.correlation(physeq,"Country")
plot_taxa_env(tax_env_cor)
|
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