TN_corr | R Documentation |
This function calculates correlation coefficients for given plant traits and generates a correlation network plot.
TN_corr(traits_matrix, rThres = 0.2, pThres = 0.05, method = "pearson")
traits_matrix |
A numeric matrix where each column represents a plant trait and each row represents a sample. |
rThres |
Numeric, threshold for correlation coefficient, default is 0.2. Only correlations with absolute values above this threshold will be displayed in the plot. |
pThres |
Numeric, threshold for p-value, default is 0.05. Only correlations with p-values below this threshold will be displayed in the plot. |
method |
Character, specifies the correlation method to use: "pearson" (default) or "spearman". |
The function first calculates Pearson correlation coefficients between traits, then adjusts p-values using the FDR method. Finally, it plots the correlation network using the corrplot package. The plot displays only correlations that meet both the correlation coefficient and p-value thresholds.
Returns a correlation network plot object.
He, N., Li, Y., Liu, C., et al. (2020). Plant trait networks: improved resolution of the dimensionality of adaptation. Trends in Ecology & Evolution, 35(10), 908-918. https://doi.org/10.1016/j.tree.2020.06.003
Li, Y., Liu, C., Sack, L., Xu, L., Li, M., Zhang, J., & He, N. (2022). Leaf trait network architecture shifts with speciesārichness and climate across forests at continental scale. Ecology Letters, 25(6), 1442-1457. https://doi.org/10.1111/ele.14009
data(PFF)
PFF_traits <- PFF[, c("Height", "Leaf_area","LDMC","SLA","SRL","SeedMass","FltDate",
"FltDur","Leaf_Cmass","Leaf_Nmass","Leaf_CN","Leaf_Pmass",
"Leaf_NP","Leaf_CP","Root_Cmass","Root_Nmass","Root_CN")]
PFF_traits <- na.omit(PFF_traits)
head(PFF_traits)
TN_corr(traits_matrix = PFF_traits, rThres = 0.3, pThres = 0.01,method = "pearson")
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