Plot differential analysis results for a feature — plot_feature

Plot timewise differential analysis results for a single feature. Points are log fold-changes, and error bars indicate standard errors.

Usage

plot_feature_logfc(
  assay = NULL,
  tissue = NULL,
  feature_ID = NULL,
  feature = NULL,
  title = NULL,
  add_gene_symbol = FALSE,
  facet_by_sex = FALSE,
  scale_x_by_time = TRUE,
  add_adj_p = TRUE,
  metareg = TRUE,
  return_data = FALSE,
  ...
)

Arguments

assay: NULL or character, assay abbreviation, one of MotrpacRatTraining6moData::ASSAY_ABBREV
tissue: NULL or character, tissue abbreviation, one of MotrpacRatTraining6moData::TISSUE_ABBREV
feature_ID: NULL or character, MoTrPAC feature identifier or metabolite RefMet ID
feature: NULL or character, unique feature identifier in the format 'MotrpacRatTraining6moData::ASSAY_ABBREV;MotrpacRatTraining6moData::TISSUE_ABBREV;feature_ID' only for training-regulated features at 5% IHW FDR. For redundant differential features, 'feature_ID' is prepended with the specific platform to make unique identifiers. See MotrpacRatTraining6moData::REPEATED_FEATURES for details.. If NULL, assay, tissue, and feature_ID must all be specified.
title: character, plot title. By default, the plot ID is feature. If add_gene_symbol = TRUE, the gene symbol is also added to the plot title.
add_gene_symbol: bool, whether to add corresponding gene symbol to plot title. Default: FALSE
facet_by_sex: bool, whether to facet the plot by sex. If TRUE, lines are colored by tissue. If FALSE, lines are colored by sex. Default: FALSE
scale_x_by_time: bool, whether to scale the x-axis by time. If FALSE, space the time points (0w, 1w, 2w, 4w, 8w) evenly. Default: TRUE
add_adj_p: bool, whether to include the training adjusted p-value (AKA selection FDR) in the plot subtitle. Default: TRUE
metareg: bool, whether to use the meta-regression version of differential analysis results for metabolomics data. If FALSE, use the redundant, non-meta-analyzed results. Default: TRUE
return_data: bool, whether to return data instead of plot. Default: FALSE
...: additional arguments passed to get_file_from_url()

Value

a ggplot2::ggplot() object or a data frame if return_data = TRUE

or NULL if the data cannot be found

Examples

# Plot a differential feature and add gene symbol
plot_feature_logfc(feature = "ACETYL;HEART;NP_001003673.1_K477k",
                   add_gene_symbol = TRUE)

                             
# Plot a differential epigenetic feature and facet by sex
plot_feature_logfc(feature = "METHYL;HEART;chr20-38798_cluster11",
                   add_gene_symbol = TRUE,
                   facet_by_sex = TRUE)


# Plot a redundant differential feature
plot_feature_logfc(assay = "IMMUNO",
                   tissue = "PLASMA",
                   feature_ID = "BDNF",
                   facet_by_sex = TRUE)
#> IMMUNO_PLASMA_DA
#> Multiple measurements for feature 'IMMUNO;PLASMA;BDNF'. Taking the smallest training-dea FDR for the plot label.

                             
# Plot one measurement of a redundant feature
plot_feature_logfc(assay = "IMMUNO",
                   tissue = "PLASMA",
                   feature_ID = "rat-myokine:BDNF",
                   facet_by_sex = TRUE)

                             
# Plot a non-differential feature
plot_feature_logfc(assay = "PROT",
                   tissue = "SKM-GN",
                   feature_ID = "YP_665629.1")
#> PROT_SKMGN_DA

                             
# Plot a merged feature from meta-regression, facet by sex, 
# don't scale the x-axis, and exclude the training p-value
plot_feature_logfc(assay = "METAB",
                   tissue = "PLASMA",
                   feature_ID = "glucose",
                   scale_x_by_time = FALSE,
                   facet_by_sex = TRUE,
                   add_adj_p = FALSE)
#> METAB_PLASMA_DA_METAREG