Bioconductor Single Package Builder - Build History

Snapshot Date: 
Last Changed Rev:  / Revision: 
Last Changed Date: 

nebbiolo2 Linux (Ubuntu 22.04.3 LTS)/x86_64   ERROR     skipped     skipped     skipped  

nebbiolo2 Summary


Package: funOmics
Version: 0.99.7
RVersion: 4.4
BiocVersion: 3.20
BuildCommand: /home/biocbuild/bbs-3.20-bioc/R/bin/R CMD build --keep-empty-dirs --no-resave-data funOmics
BuildTime: 0 minutes 51.59 seconds
PackageFileSize: -1.00 KiB
BuildID:: funOmics_20240514174431
PreProcessing: Starting Git clone. Installing dependencies. Checking Git Clone. Installing package: funOmics. Starting Build package.
PostProcessing: Finished Git clone. Package type: Software. Installing dependency status: 0. Checking git clone status: 0. Installing package status: 0. Build Package status: 1.

nebbiolo2 BUILD SRC output





* checking for file ‘funOmics/DESCRIPTION’ ... OK
* preparing ‘funOmics’:
* checking DESCRIPTION meta-information ... OK
* installing the package to build vignettes
* creating vignettes ... ERROR
--- re-building ‘funomics_vignette.Rmd’ using rmarkdown
get_kegg_sets             package:funOmics             R Documentation

_R_e_t_r_i_e_v_e_s _K_E_G_G _p_a_t_h_w_a_y _g_e_n_e _s_e_t_s _f_o_r _a _s_p_e_c_i_f_i_e_d _o_r_g_a_n_i_s_m _a_n_d _g_e_n_e _I_D


     This function retrieves KEGG pathway gene sets for a specified
     organism.  It fetches all pathways available for the specified
     organism from the KEGG database and maps the genes involved in
     each pathway.  Currently, the function only supports choice of
     gene identifiers (entrez IDs, gene symbols or Ensembl IDs) for
     Homo sapiens (organism = "hsa") using the package.


     get_kegg_sets(organism = "hsa", geneid_type = "entrez")

organism: The organism abbreviation for which KEGG pathway gene sets
          are to be retrieved (e.g., "ecj" for E. coli). Default is
          "hsa" (Homo sapiens).

geneid_type: The type of gene IDs to provide. Default is "entrez";
          options are "entrez", "symbol", or "ensembl".  This parameter
          is only used when the organism is "hsa" (Homo sapiens).


     A list where each element represents a KEGG pathway gene set. The
     names of the list correspond to the pathway names.

_S_e_e _A_l_s_o:


     'keggLink', 'keggList'



     # Retrieve KEGG pathway gene sets for Homo sapiens with entrez IDs (default)
     hsa_kegg_sets_entrez <- get_kegg_sets()
     # Retrieve KEGG molecular sets using gene symbols
     hsa_kegg_sets_symbol <- get_kegg_sets(geneid_type = "symbol")
     # Retrieve KEGG molecular sets using Ensembl IDs
     hsa_kegg_sets_ensembl <- get_kegg_sets(geneid_type = "ensembl")
     # Retrieve KEGG pathway gene sets for another organism (e.g., Escherichia coli)
     ecoli_kegg_sets <- get_kegg_sets(organism = "ecj")

short_sets_detail           package:funOmics           R Documentation

_R_e_t_r_i_e_v_e _d_e_t_a_i_l_s _a_n_d _i_n_f_o_r_m_a_t_i_o_n _a_b_o_u_t _s_h_o_r_t _m_o_l_e_c_u_l_a_r _s_e_t_s


     This function identifies molecular sets with sizes less than a
     specified threshold and returns information about these sets.


     short_sets_detail(sets, minsize)

    sets: A list of molecular sets.

 minsize: The minimum size threshold for sets.


     This function identifies molecular sets in the input list that
     have sizes less than the specified minimum size ('minsize'). It
     returns a list containing the names, lengths, and molecules of
     these short molecular sets.


     A list containing information about short molecular sets:

short_sets: Names of the short molecular sets.

 lengths: Lengths of the short molecular sets.

   genes: Short molecular sets themselves.


     ex_sets <- list(set1 = c("mol1", "mol2"), set2 = c("mol3", "mol4", "mol5"))
     short_sets_info <- short_sets_detail(ex_sets, minsize = 3)

summarize_pathway_level        package:funOmics        R Documentation

_A_g_g_r_e_g_a_t_e_s _o_r _s_u_m_m_a_r_i_z_e_s _o_m_i_c_s _d_a_t_a _i_n_t_o _h_i_g_h_e_r-_l_e_v_e_l _f_u_n_c_t_i_o_n_a_l
_r_e_p_r_e_s_e_n_t_a_t_i_o_n_s _t_h_a_t _c_a_n _b_e _i_n_t_e_r_p_r_e_t_e_d _a_s _f_u_n_c_t_i_o_n_a_l _a_c_t_i_v_i_t_y _s_c_o_r_e_s
_o_r _m_e_a_s_u_r_e_s.


     Given an omics matrix and a list of functional molecular sets,
     this function aggregates or summarizes the omics data into
     higher-level functional representations such as GO terms gene sets
     or KEGG metabolic pathways, facilitating the analysis of
     functional molecular sets that allow reducing dimensionality and
     providing easier and faster biological interpretations.
     Coordinated functional activity scores can be as informative as
     single molecules.


     summarize_pathway_level(omicsmat, sets = NULL, type = "mean", minsize = 10)

omicsmat: A matrix or data frame representing omics data. Rows
          correspond to molecular identifiers, and columns correspond
          to samples.

    sets: A list of functional sets. Each element in the list should
          represent a molecular set, and the elements of the set should
          match the row names of the omics matrix.

    type: The type of pooling operator to be applied for each set.
          Possible values include "mean" (default), "median", "sd",
          "min", "max", "pca", "mds", "pathifier", "nmf", "ttest",
          "wilcox", "kolmogorov".

 minsize: The minimum size per molecular set (default is 10).



     - Different aggregation operators can be used, including summary
     statistics such as median (default), mean, sd, min, max,
     dimensionality reduction scores such as pca, mds, pathifier, or
     nmf, and statistical tests such as ttest, wilcoxon test,
     kolmogorov test.

     - The minimum size per molecular set is by default 10 molecules
     (e.g. genes or metabolites) and can be changed with the parameter

     - If "pathifier" is chosen as pooling type, the `aggby_pathifier`
     function internally generates a log file named 'pathifierlog.txt'
     during its execution.

     This log file may contain additional information that could be
     useful for troubleshooting or advanced analysis.

     Users typically do not need to interact with this file directly,
     but it is mentioned here for informational purposes. For more
     details, this function utilizes the Pathifier package.


     A matrix-like table with the activity measures for each group or
     set of molecules, i.e., sxn matrix, for s molecular sets and n


     Elisa Gomez de Lope


     # Example usage:
     g <- 10000
     s <- 20
     X <- matrix(abs(rnorm(g * s)), nrow = g, dimnames = list(paste0("g", 1:g), paste0("s", 1:s)))
     pathways <- as.list(sample(10:100, size = 100, replace = TRUE))
     pathways <- lapply(pathways, function(s, g) paste0("g", sample(1:g, size = s, replace = FALSE)), g)
     names(pathways) <- paste0("pathway", seq_along(pathways))
     pathway_activity <- summarize_pathway_level(X, pathways, type = "mean", minsize = 12)

Quitting from lines  at lines 182-184 [unnamed-chunk-18] (funomics_vignette.Rmd)
Error: processing vignette 'funomics_vignette.Rmd' failed with diagnostics:
'what' must be a function or character string
--- failed re-building ‘funomics_vignette.Rmd’

SUMMARY: processing the following file failed:

Error: Vignette re-building failed.
Execution halted

nebbiolo2 CHECK output



nebbiolo2 BUILD BIN output