runMatrixAnalysis(
data, # data to use for analysis
analysis = c(
"pca", "pca_ord", "pca_dim", # PCA
"mca", "mca_ord", "mca_dim", # MCA (PCA on categorical data)
"mds", "mds_ord", "mds_dim", # MDS
"tsne", "dbscan", "kmeans", # Clustering
"hclust", "hclust_phylo" # Hierarchical clustering
),
parameters = NULL,
column_w_names_of_multiple_analytes = NULL,
column_w_values_for_multiple_analytes = NULL,
columns_w_values_for_single_analyte = NULL,
columns_w_additional_analyte_info = NULL,
columns_w_sample_ID_info = NULL,
transpose = FALSE, # default = FALSE, this chooses whether to transpose the data
distance_method = c( # the distance metric to use in computing a distance matrix
"euclidean", "maximum",
"manhattan", "canberra",
"binary", "minkowski",
"coeff_unlike"
),
agglomeration_method = c( # the clustering method to use in heirarchical clustering
"ward.D2", "ward.D", "single", "complete",
"average", # (= UPGMA)
"mcquitty", # (= WPGMA)
"median", # (= WPGMC)
"centroid" # (= UPGMC)
),
unknown_sample_ID_info = NULL,
components_to_return = 2, # how many principal components to return
scale_variance = NULL, ## default = TRUE, except for hclust, then default = FALSE
na_replacement = c("mean", "none", "zero", "drop"), # default = "mean", this chooses what to do with missing values
output_format = c("wide", "long"), # default = "wide", this chooses whether to output a wide or long format
)