Dimensionality reduction through PCA
dimred_pca(
MAE,
tax_level,
color,
shape = NULL,
pcx = 1,
pcy = 2,
pcz = NULL,
datatype = c("logcpm", "relabu", "counts")
)A multi-assay experiment object
The taxon level used for organisms
A condition to color data points by e.g. "AGE"
A condition to shape data points by e.g. "SEX"
Principal component on the x-axis e.g. 1
Principal component on the y-axis e.g. 2
Principal component on the z-axis e.g. 3
Datatype to use e.g. c("logcpm", "relabu", "counts")
A list with a plotly object and summary table
data_dir <- system.file("extdata/MAE.rds", package = "animalcules")
toy_data <- readRDS(data_dir)
result <- dimred_pca(toy_data,
tax_level = "genus",
color = "AGE",
shape = "DISEASE",
pcx = 1,
pcy = 2,
datatype = "logcpm"
)
result$plot
result$table
#> PC Standard Deviation Variance Explained Cumulative Variance
#> PC1 PC1 2.44 9.622% 9.622%
#> PC2 PC2 2.17 7.598% 17.220%
#> PC3 PC3 1.98 6.317% 23.537%
#> PC4 PC4 1.88 5.688% 29.225%
#> PC5 PC5 1.8 5.247% 34.472%
#> PC6 PC6 1.69 4.620% 39.092%
#> PC7 PC7 1.67 4.474% 43.566%
#> PC8 PC8 1.62 4.216% 47.782%
#> PC9 PC9 1.59 4.068% 51.850%
#> PC10 PC10 1.52 3.714% 55.565%
#> PC11 PC11 1.46 3.451% 59.016%
#> PC12 PC12 1.41 3.219% 62.235%
#> PC13 PC13 1.37 3.048% 65.283%
#> PC14 PC14 1.32 2.821% 68.104%
#> PC15 PC15 1.27 2.607% 70.711%
#> PC16 PC16 1.24 2.481% 73.192%
#> PC17 PC17 1.19 2.274% 75.466%
#> PC18 PC18 1.15 2.116% 77.582%
#> PC19 PC19 1.13 2.052% 79.635%
#> PC20 PC20 1.08 1.866% 81.501%
#> PC21 PC21 1.04 1.754% 83.255%
#> PC22 PC22 1.04 1.736% 84.992%
#> PC23 PC23 0.972 1.524% 86.516%
#> PC24 PC24 0.961 1.490% 88.006%
#> PC25 PC25 0.881 1.253% 89.259%
#> PC26 PC26 0.851 1.168% 90.427%
#> PC27 PC27 0.836 1.128% 91.555%
#> PC28 PC28 0.785 0.994% 92.549%
#> PC29 PC29 0.741 0.885% 93.434%
#> PC30 PC30 0.705 0.801% 94.235%
#> PC31 PC31 0.694 0.778% 95.013%
#> PC32 PC32 0.654 0.690% 95.704%
#> PC33 PC33 0.618 0.617% 96.320%
#> PC34 PC34 0.572 0.527% 96.847%
#> PC35 PC35 0.539 0.468% 97.316%
#> PC36 PC36 0.519 0.434% 97.750%
#> PC37 PC37 0.482 0.374% 98.124%
#> PC38 PC38 0.472 0.360% 98.484%
#> PC39 PC39 0.437 0.308% 98.792%
#> PC40 PC40 0.402 0.260% 99.052%
#> PC41 PC41 0.369 0.220% 99.272%
#> PC42 PC42 0.348 0.195% 99.467%
#> PC43 PC43 0.288 0.134% 99.601%
#> PC44 PC44 0.272 0.119% 99.720%
#> PC45 PC45 0.25 0.101% 99.821%
#> PC46 PC46 0.206 0.068% 99.889%
#> PC47 PC47 0.183 0.054% 99.943%
#> PC48 PC48 0.15 0.036% 99.979%
#> PC49 PC49 0.114 0.021% 100.000%
#> PC50 PC50 2.27e-15 0.000% 100.000%