WallomicsData (version 1.0)

Metabolomics_Stems: Metabolomics Stems

Description

A dataset containing metabolomics variables measured on floral stems of five A. thaliana genotypes at two growth temperatures. See Ecotype and Temperature for more information.

Usage

data("Metabolomics_Stems")

Format

A data frame with 30 rows and 6 variables:

• Pectin_RGI: Rhamnogalacturonan I (<U+00B5>g/100mg)

• Pectin_HG: Homogalacturonan (<U+00B5>g/100mg)

• XG: Xyloglucan (<U+00B5>g/100mg)

• Pectin_linearity: Linearity of pectin (Ratio)

• Contribution_RG: Contribution of rhamnogalacturonan to pectin population (Ratio)

• RGI_branching: Branching of Rhamnogalacturonan I (Ratio)

Examples

# NOT RUN {
# Load the dataset
data("Metabolomics_Stems")

# Look at simple statistics
summary(Metabolomics_Stems)

# Create a colors' vector
colors <- c(rep("#A6CEE3",3), rep("#1F78B4",3), rep("#B2DF8A",3), rep("#33A02C",3),
            rep("#FB9A99",3), rep("#E31A1C",3), rep("#FDBF6F",3), rep("#FF7F00",3),
            rep("#CAB2D6",3), rep("#6A3D9A",3))

# A graphical representation
plot(x = as.factor(substr(row.names(Metabolomics_Stems), 1, 7)),
     y = Metabolomics_Stems$Pectin_linearity, col = "white", lty = 0,
     xlab = "Genotype x Temperature groups",
     ylab = "Pectin linearity (Ratio)",
     main = "Pectin linearity distribution by genotype and growth temperature")
grid()
abline(h = 1, lty = 2)
points(x = as.factor(substr(row.names(Metabolomics_Stems), 1, 7)),
       y = Metabolomics_Stems$Pectin_linearity, type = "p", pch = 19, lwd = 5,
       col = colors)

# }