RSA_by_cm function

Reporter score analysis after C-means clustering

Reporter score analysis after C-means clustering

Extract one cluster from rs_by_cm object

Plot c_means result

RSA_by_cm(
  kodf,
  group,
  metadata = NULL,
  k_num = NULL,
  filter_var = 0.7,
  verbose = TRUE,
  method = "pearson",
  ...
)

extract_cluster(rsa_cm_res, cluster = 1)

plot_c_means(
  rsa_cm_res,
  filter_membership,
  mode = 1,
  show.clust.cent = TRUE,
  show_num = TRUE,
  ...
)

Arguments

• kodf: KO_abundance table, rowname is ko id (e.g. K00001),colnames is samples.
• group: The comparison groups (at least two categories) in your data, one column name of metadata when metadata exist or a vector whose length equal to columns number of kodf. And you can use factor levels to change order.
• metadata: sample information data.frame contains group
• k_num: if NULL, perform the cm_test_k, else an integer
• filter_var: see c_means
• verbose: verbose
• method: method from reporter_score
• ...: additional
• rsa_cm_res: a cm_res object
• cluster: integer
• filter_membership: filter membership 0~1.
• mode: 1~2
• show.clust.cent: show cluster center?
• show_num: show number of each cluster?

Returns

rs_by_cm

reporter_score object

ggplot

Examples

message("The following example require some time to run:")

if (requireNamespace("e1071") && requireNamespace("factoextra")) {
  data("KO_abundance_test")
  rsa_cm_res <- RSA_by_cm(KO_abundance, "Group2", metadata,
    k_num = 3,
    filter_var = 0.7, method = "pearson", perm = 199
  )
  extract_cluster(rsa_cm_res, cluster = 1)
}

See Also

Other C_means: cm_test_k()