View source: R/vis_identifier.R
vis_identifier_grp_comparison | R Documentation |
NOTE: the dataset must be dense matrix in UCSC Xena data hubs.
vis_identifier_grp_comparison( dataset = NULL, id = NULL, grp_df, samples = NULL, fun_type = c("betweenstats", "withinstats"), type = c("parametric", "nonparametric", "robust", "bayes"), pairwise.comparisons = TRUE, p.adjust.method = c("holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none"), ggtheme = cowplot::theme_cowplot(), ... )
dataset |
the dataset to obtain identifiers. |
id |
the molecule identifier. |
grp_df |
When
|
samples |
default is |
fun_type |
select the function to compare groups. |
type |
A character specifying the type of statistical approach:
You can specify just the initial letter. |
pairwise.comparisons |
Logical that decides whether pairwise comparisons
are to be displayed (default: |
p.adjust.method |
Adjustment method for p-values for multiple
comparisons. Possible methods are: |
ggtheme |
A |
... |
other parameters passing to ggstatsplot::ggbetweenstats or ggstatsplot::ggwithinstats. |
a (gg)plot object.
## Not run: library(UCSCXenaTools) expr_dataset <- "TCGA.LUAD.sampleMap/HiSeqV2_percentile" cli_dataset <- "TCGA.LUAD.sampleMap/LUAD_clinicalMatrix" id <- "TP53" cli_df <- XenaGenerate( subset = XenaDatasets == "TCGA.LUAD.sampleMap/LUAD_clinicalMatrix" ) %>% XenaQuery() %>% XenaDownload() %>% XenaPrepare() # group data.frame with 2 columns vis_identifier_grp_comparison(expr_dataset, id, cli_df[, c("sampleID", "gender")]) # group data.frame with 3 columns vis_identifier_grp_comparison( expr_dataset, id, cli_df[, c("sampleID", "pathologic_M", "gender")] %>% dplyr::filter(pathologic_M %in% c("M0", "MX")) ) # When not use the value of `identifier` from `dataset` vis_identifier_grp_comparison(grp_df = cli_df[, c(1, 2, 71)]) vis_identifier_grp_comparison(grp_df = cli_df[, c(1, 2, 71, 111)]) ## End(Not run)
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