Find enrichment colnames
Usage
find_enrich_colnames(
x,
keyColname = c("ID", "Name", "pathway", "itemsetID", "Description"),
nameColname = c("Name", "pathway", "Description", "itemsetID", "ID"),
descriptionColname = c("Description", "Name", "Pathway", "ID"),
geneColname = c("geneID", "geneNames", "Genes"),
countColname = c("gene_count", "count", "geneHits"),
geneRatioColname = c("GeneRatio", "^Ratio"),
pvalueColname = c("padjust", "p.adjust", "adjp", "padj", "qvalue", "qval", "q.value",
"pvalue", "p.value", "pval", "FDR"),
directionColname = c("activation.z.{0,1}score", "z.{0,1}score"),
pathGenes = c("setSize", "pathGenes", "Count"),
geneHits = c("Count", "geneHits", "gene_count"),
verbose = FALSE,
...
)Arguments
- x
data.frame,enrichList,Mem, orlistofdata.frameobjects.- keyColname
characterdefault 'ID' indicating the primary identifier for each set. This column may be a numeric identifier.- nameColname
characterdefault 'Name', with the set name, typically a short name for each set.- descriptionColname
characterdefault 'Description' with the longer set description. It will usenameColnameorkeyColnameas needed.- geneColname
characterdefault 'geneID' containing delimited genes associated with each enrichment result.- countColname
characterdefault 'Count' with the number of genes in thegeneColnamecolumn. It will be calculated as needed.- geneRatioColname
characterdefault 'GeneRatio' with the numeric (decimal) ratio of test genes to pathway genes, or a character indication in the form '6/24' with 'tested/pathway' gene counts.- pvalueColname
characterdefault 'padjust' with the best available column to use for statistical significance of enrichment.- directionColname
characterdefault 'zscore' with a directional score, typically a z-score or some other reasonably scaled numeric value where the sign indicates directionality, with '+' meaning activated and '-' meaning suppressed.- pathGenes
characterdefault 'setSize' indicating the number of genes in each set as tested for enrichment. This number is not always reported, however it is not used by 'multienrichjam', but is required by someclusterProfilerfunctions.- geneHits
characterdefault 'Count' indicating the number of genes in thegeneColnamecolumn. It will be calculated as needed.- verbose
logicaldefault FALSE, whether to print verbose output.- ...
additional arguments are ignored.
Value
character of recognized colnames named by the type
of column, using NA for any column types not found.
list named by each column name argument, with one character
value or NULL in each entry.
See also
Other jam utility functions:
ashape(),
avg_angles(),
avg_colors_by_list(),
cell_fun_bivariate(),
collapse_mem_clusters(),
colorRamp2D(),
curateIPAcolnames(),
deconcat_df2(),
display_colorRamp2D(),
enrichList2geneHitList(),
find_colname(),
get_hull_data(),
get_igraph_layout(),
gsubs_remove(),
handle_igraph_param_list(),
isColorBlank(),
make_legend_bivariate(),
make_point_hull(),
mem_find_overlap(),
order_colors(),
rank_mem_clusters(),
rotate_coordinates(),
summarize_node_spacing(),
with_ht_opts(),
xyAngle()
Examples
newborn_txt <- system.file("extdata",
"Newborns-IPA.txt",
package="multienrichjam");
ipa_dfs <- importIPAenrichment(newborn_txt);
find_enrich_colnames(ipa_dfs[[1]])
#> $keyColname
#> [1] "Name"
#>
#> $nameColname
#> [1] "Name"
#>
#> $descriptionColname
#> [1] "Name"
#>
#> $geneColname
#> [1] "geneNames"
#>
#> $countColname
#> NULL
#>
#> $geneRatioColname
#> [1] "Ratio"
#>
#> $pvalueColname
#> [1] "P-value"
#>
#> $directionColname
#> NULL
#>
#> $pathGenes
#> NULL
#>
#> $geneHits
#> NULL
#>
er <- enrichDF2enrichResult(ipa_dfs[[1]])
find_enrich_colnames(er)
#> $keyColname
#> [1] "ID"
#>
#> $nameColname
#> [1] "Description"
#>
#> $descriptionColname
#> [1] "Description"
#>
#> $geneColname
#> [1] "geneID"
#>
#> $countColname
#> [1] "Count"
#>
#> $geneRatioColname
#> [1] "GeneRatio"
#>
#> $pvalueColname
#> [1] "p.adjust"
#>
#> $directionColname
#> NULL
#>
#> $pathGenes
#> [1] "setSize"
#>
#> $geneHits
#> [1] "Count"
#>