Package 'MetAlyzer' reference manual

Title:	Read and Analyze 'MetIDQ™' Software Output Files
Description:	The 'MetAlyzer' S4 object provides methods to read and reformat metabolomics data for convenient data handling, statistics and downstream analysis. The resulting format corresponds to input data of the Shiny app 'MetaboExtract' (<https://www.metaboextract.shiny.dkfz.de/MetaboExtract/>).
Authors:	Qian-Wu Liao [aut], Luis Herfurth [aut] (ORCID: <https://orcid.org/0009-0000-9933-3056>), Christina Schmidt [aut] (ORCID: <https://orcid.org/0000-0002-3867-0881>), Nils Mechtel [aut] (ORCID: <https://orcid.org/0000-0002-1278-7125>), Hagen Gegner [aut], Alice Limonciel [aut], Julio Saez-Rodriguez [aut] (ORCID: <https://orcid.org/0000-0002-8552-8976>), Rüdiger Hell [aut], Junyan Lu [aut, cre], Gernot Poschet [aut]
Maintainer:	Junyan Lu <[email protected]>
License:	GPL-3
Version:	1.2.0
Built:	2026-05-27 06:34:49 UTC
Source:	https://github.com/lu-group-ukhd/metalyzer

Get Aggregated Data

Description

This function returns the tibble "aggregated_data".

Usage

aggregated_data(metalyzer_se)
aggregated_data(metalyzer_se)

Arguments

metalyzer_se

SummarizedExperiment

Examples

metalyzer_se <- MetAlyzer::read_webidq(file_path = MetAlyzer::load_demodata_biocrates())

MetAlyzer::aggregated_data(metalyzer_se)
metalyzer_se <- MetAlyzer::read_webidq(file_path = MetAlyzer::load_demodata_biocrates())

MetAlyzer::aggregated_data(metalyzer_se)

Helper function to calculate conditional mean based on significance

Description

Calculates mean of a metric vector based on q-values. Prioritizes values where qval <= q_thresh. If none exist, uses all non-NA values.

Usage

calculate_conditional_mean(metric_vec, qval_vec, q_thresh)
calculate_conditional_mean(metric_vec, qval_vec, q_thresh)

Arguments

metric_vec

Numeric vector of the metric to average (e.g., log2FC).

qval_vec

Numeric vector of corresponding q-values.

q_thresh

Significance threshold for q-values.

Value

The calculated conditional mean, or NA.

Calculate Node-Level Aggregate Statistics (Conditional on Significance)

Description

Calculates mean log2FC, p-value, and q-value for each node (Label), prioritizing significant metabolites (qval <= q_value). If none are significant, uses all measured metabolites for the node. Adds results to both dataframes.

Usage

calculate_node_aggregates_conditional(
  nodes_sep_df,
  nodes_orig_df,
  q_value,
  stat_col_name,
  ...
)
calculate_node_aggregates_conditional(
  nodes_sep_df,
  nodes_orig_df,
  q_value,
  stat_col_name,
  ...
)

Arguments

nodes_sep_df

Dataframe with metabolites separated (e.g., 'nodes_final'). Must contain Label, log2FC, qval.

nodes_orig_df

Original dataframe with potentially semi-colon separated metabolites. Must contain Label.

q_value

Significance threshold for q-values (e.g., 0.05).

stat_col_name

p value column name

...

Column names of numeric values to be processed (e.g., log2FC, pval, qval).

Value

A list containing two dataframes: $nodes_separated: Input nodes_sep_df with 2 new columns: node_values, node_stat $nodes: Input nodes_orig_df with 2 new columns: node_values, node_stat

Creates a viridis color style for Plotly plots.

Description

This function can generate either a Plotly-compatible colorscale for a color bar or a vector of hex color codes for manual coloring.

Usage

create_viridis_style(
  color_scale,
  type = "scale",
  data = NULL,
  values_col_name = NULL
)
create_viridis_style(
  color_scale,
  type = "scale",
  data = NULL,
  values_col_name = NULL
)

Arguments

color_scale

The name of the palette (e.g., "Magma", "Viridis").

type

The desired output type: "scale" (for a color bar), "hex" or "inital" (for a color scalde, a vector of hex codes, or the correct scale for viridis package). Defaults to "scale".

data

The data frame containing the values. Only required if type = "hex".

values_col_name

The name of the column with numeric values. Only required if type = "hex".

Value

A data frame if type is "scale", or a character vector if type is "hex".

Get example mutation data

Description

This function returns the mutation_data_MxP_Quant_500_XL.xlsx file path.

Usage

example_mutation_data_xl()
example_mutation_data_xl()

Value

mutation_data_MxP_Quant_500_XL.xlsx file path

Examples

fpath <- MetAlyzer::example_mutation_data_xl()
fpath <- MetAlyzer::example_mutation_data_xl()

Export filtered raw data as csv

Description

This function exports the filtered raw data in the CSV format.

Usage

export_conc_values(metalyzer_se, ..., file_path = "metabolomics_data.csv")
export_conc_values(metalyzer_se, ..., file_path = "metabolomics_data.csv")

Arguments

metalyzer_se

SummarizedExperiment

...

Additional columns from meta_data

file_path

file path

Examples

metalyzer_se <- MetAlyzer::read_webidq(file_path = MetAlyzer::load_demodata_biocrates())

output_file <- file.path(tempdir(), "metabolomics_data.csv")
MetAlyzer::export_conc_values(metalyzer_se,
                              `Sample Description`,
                              file_path = output_file
                              )
unlink(output_file)
metalyzer_se <- MetAlyzer::read_webidq(file_path = MetAlyzer::load_demodata_biocrates())

output_file <- file.path(tempdir(), "metabolomics_data.csv")
MetAlyzer::export_conc_values(metalyzer_se,
                              `Sample Description`,
                              file_path = output_file
                              )
unlink(output_file)

Filter meta data

Description

This function updates the "Filter" column in meta_data to filter out samples.

Usage

filter_meta_data(metalyzer_se, ..., inplace = FALSE)
filter_meta_data(metalyzer_se, ..., inplace = FALSE)

Arguments

metalyzer_se

SummarizedExperiment

...

Use ´col_name´ and condition to filter selected variables.

inplace

If FALSE, return a copy. Otherwise, do operation inplace and return None.

Value

An updated SummarizedExperiment

Examples

metalyzer_se <- MetAlyzer::read_webidq(file_path = MetAlyzer::load_demodata_biocrates())

metalyzer_se <- MetAlyzer::filter_meta_data(metalyzer_se, `Sample Description` %in% 1:6)
metalyzer_se <- MetAlyzer::read_webidq(file_path = MetAlyzer::load_demodata_biocrates())

metalyzer_se <- MetAlyzer::filter_meta_data(metalyzer_se, `Sample Description` %in% 1:6)

Filter metabolites

Description

This function filters out certain classes or metabolites of the metabolites vector. If aggregated_data is not empty, metabolites and class will also be filtered here.

Usage

filter_metabolites(
  metalyzer_se,
  drop_metabolites = c("Metabolism Indicators"),
  drop_NA_concentration = FALSE,
  drop_quant_status = NULL,
  min_percent_valid = NULL,
  valid_status = c("Valid", "LOQ"),
  per_group = NULL,
  inplace = FALSE
)
filter_metabolites(
  metalyzer_se,
  drop_metabolites = c("Metabolism Indicators"),
  drop_NA_concentration = FALSE,
  drop_quant_status = NULL,
  min_percent_valid = NULL,
  valid_status = c("Valid", "LOQ"),
  per_group = NULL,
  inplace = FALSE
)

Arguments

metalyzer_se

SummarizedExperiment

drop_metabolites

A character vector defining metabolite classes or individual metabolites to be removed

drop_NA_concentration

A boolean whether to drop metabolites which have any NAs in their concentration value

drop_quant_status

A character, vector of characters or list of characters specifying which quantification status to remove. Metabolites with at least one quantification status of this vector will be removed.

min_percent_valid

A numeric lower threshold between 0 and 1 (t less than or equal to x) to remove invalid metabolites that do not meet a given percentage of valid measurements per group (default per Metabolite).

valid_status

A character vector that defines which quantification status is considered valid.

per_group

A character vector of column names from meta_data that will be used to split each metabolite into groups. The threshold 'min_percent_valid' will be applied for each group. The selected columns from meta_data will be added to aggregated_data.

inplace

If FALSE, return a copy. Otherwise, do operation inplace and return None.

Value

An updated SummarizedExperiment

Examples

metalyzer_se <- MetAlyzer::read_webidq(file_path = MetAlyzer::load_demodata_biocrates())

drop_metabolites <- c("C0", "C2", "C3", "Metabolism Indicators",
  inplace = TRUE
)
metalyzer_se <- MetAlyzer::filter_metabolites(metalyzer_se, drop_metabolites)
metalyzer_se <- MetAlyzer::read_webidq(file_path = MetAlyzer::load_demodata_biocrates())

drop_metabolites <- c("C0", "C2", "C3", "Metabolism Indicators",
  inplace = TRUE
)
metalyzer_se <- MetAlyzer::filter_metabolites(metalyzer_se, drop_metabolites)

Get demodata from biocrates

Description

This function returns the Metalyzer_demo dataset_biocrates MxP Quant 500 XL_2025-04.xlsx file path.

Usage

load_demodata_biocrates()
load_demodata_biocrates()

Value

Metalyzer_demo dataset_biocrates MxP Quant 500 XL_2025-04 file path

Examples

fpath <- MetAlyzer::load_demodata_biocrates()
fpath <- MetAlyzer::load_demodata_biocrates()

Get example extraction data

Description

This function returns the extraction_data_MxP_Quant_500.xlsx file path.

Usage

load_rawdata_extraction()
load_rawdata_extraction()

Value

extraction_data_MxP_Quant_500.xlsx file path

Examples

fpath <- MetAlyzer::load_rawdata_extraction()
fpath <- MetAlyzer::load_rawdata_extraction()

Get log2FC Data

Description

This function returns the tibble "log2FC".

Usage

log2FC(metalyzer_se)
log2FC(metalyzer_se)

Arguments

metalyzer_se

SummarizedExperiment

Examples

metalyzer_se <- MetAlyzer::read_webidq(file_path = MetAlyzer::load_demodata_biocrates())
metalyzer_se@metadata$log2FC <- readRDS(MetAlyzer::toy_diffres())
MetAlyzer::log2FC(metalyzer_se)
metalyzer_se <- MetAlyzer::read_webidq(file_path = MetAlyzer::load_demodata_biocrates())
metalyzer_se@metadata$log2FC <- readRDS(MetAlyzer::toy_diffres())
MetAlyzer::log2FC(metalyzer_se)

Get MetAlyzer colors

Description

This function returns the vector loaded from metalyzer_colors.RDS.

Usage

metalyzer_colors()
metalyzer_colors()

Value

data frame loaded from metalyzer_colors.RDS

Examples

fpath <- MetAlyzer::metalyzer_colors()
fpath <- MetAlyzer::metalyzer_colors()

Open file and read data

Description

This function was deprecated in version v2.0.0

Usage

MetAlyzer_dataset(...)
MetAlyzer_dataset(...)

Arguments

...

Declare this function as out of date

Get pathway file path

Description

This function returns the latest pathway.xlsx file path.

Usage

pathway()
pathway()

Value

pathway.xlsx file path

Examples

fpath <- MetAlyzer::pathway()
fpath <- MetAlyzer::pathway()

Plot Pathway Network

Description

This function plots the log2 fold change for each metabolite and visualizes it, in a pathway network.

Usage

plot_network(
  log2fc_df,
  q_value = 0.05,
  metabolite_col_name = "Metabolite",
  values_col_name = "log2FC",
  stat_col_name = "qval",
  metabolite_text_size = 3,
  connection_width = 0.75,
  pathway_text_size = 6,
  pathway_width = 3,
  exclude_pathways = NULL,
  color_scale = "Viridis",
  gradient_colors = NULL,
  save_as = NULL,
  folder_name = format(Sys.Date(), "%Y-%m-%d"),
  folder_path = NULL,
  file_name = "network",
  format = "pdf",
  width = 29.7,
  height = 21,
  units = "cm",
  overwrite = FALSE
)
plot_network(
  log2fc_df,
  q_value = 0.05,
  metabolite_col_name = "Metabolite",
  values_col_name = "log2FC",
  stat_col_name = "qval",
  metabolite_text_size = 3,
  connection_width = 0.75,
  pathway_text_size = 6,
  pathway_width = 3,
  exclude_pathways = NULL,
  color_scale = "Viridis",
  gradient_colors = NULL,
  save_as = NULL,
  folder_name = format(Sys.Date(), "%Y-%m-%d"),
  folder_path = NULL,
  file_name = "network",
  format = "pdf",
  width = 29.7,
  height = 21,
  units = "cm",
  overwrite = FALSE
)

Arguments

log2fc_df

A dataframe with log2FC, qval, additional columns

q_value

The q-value threshold for significance

metabolite_col_name

Columnname that holds the Metabolites

values_col_name

Column name of a column that holds numeric values, to be plotted Default = "log2FC"

stat_col_name

Columnname that holds numeric stat values that are used for significance Default = "qval"

metabolite_text_size

The text size of metabolite labels

connection_width

The line width of connections between metabolites

pathway_text_size

The text size of pathway annotations

pathway_width

The line width of pathway-specific connection coloring

exclude_pathways

Pathway names that are exluded from plotting

color_scale

A string specifying the color scale to use. Options include '"Viridis"', '"Plasma"', '"Magma"', '"Inferno"', '"Cividis"', '"Rocket"', '"Mako"', and '"Turbo"', which use the 'viridis' color scales. If '"gradient"' is selected, a custom gradient is applied based on 'gradient_colors'.

gradient_colors

A vector of length 2 or 3 specifying the colors for a custom gradient. If two colors are provided ('c(low, high)'), 'scale_fill_gradient()' is used. If three colors are provided ('c(low, mid, high)'), 'scale_fill_gradient2()' is used. If 'NULL' or incorrectly specified, the viridis color scale is applied.

save_as

Optional: Select the file type of output plots. Options are svg, pdf, png or NULL. Default = "NULL"

folder_name

Name of the folder where the plot will be saved. Special characters will be removed automatically. Default = date

folder_path

Optional: User-defined path where the folder should be created. If not provided, results will be saved in 'MetAlyzer_results' within the working directory. Default = NULL

file_name

Name of the output file (without extension). Default = "network"

format

File format for saving the plot (e.g., "png", "pdf", "svg"). Default = "pdf"

width

Width of the saved plot in specified units. Default = 29.7

height

Height of the saved plot in specified units. Default = 21.0

units

Units for width and height (e.g., "in", "cm", "mm"). Default = "cm"

overwrite

Logical: If 'TRUE', overwrite existing files without asking. If 'FALSE', prompt user before overwriting. Default = FALSE

Value

list with ggplot object and table of node summaries

Examples

log2fc_df <- readRDS(MetAlyzer::toy_diffres())
network <- MetAlyzer::plot_network(log2fc_df, q_value = 0.05)
network$Plot
network$Table
log2fc_df <- readRDS(MetAlyzer::toy_diffres())
network <- MetAlyzer::plot_network(log2fc_df, q_value = 0.05)
network$Plot
network$Table

Scatter Plot Visualization

Description

This method creates a scatter plot of the log2 fold change for each metabolite.

Usage

plot_scatter(
  log2fc_df,
  show_labels_for = NULL,
  values_col_name = "log2FC",
  stat_col_name = "qval",
  show_p_value = TRUE,
  signif_colors = c(`#5F5F5F` = 1, `#FEBF6E` = 0.1, `#EE5C42` = 0.05, `#8B1A1A` = 0.01),
  save_as = NULL,
  folder_name = format(Sys.Date(), "%Y-%m-%d"),
  folder_path = NULL,
  file_name = "network",
  format = "pdf",
  width = 29.7,
  height = 21,
  units = "cm",
  overwrite = FALSE
)
plot_scatter(
  log2fc_df,
  show_labels_for = NULL,
  values_col_name = "log2FC",
  stat_col_name = "qval",
  show_p_value = TRUE,
  signif_colors = c(`#5F5F5F` = 1, `#FEBF6E` = 0.1, `#EE5C42` = 0.05, `#8B1A1A` = 0.01),
  save_as = NULL,
  folder_name = format(Sys.Date(), "%Y-%m-%d"),
  folder_path = NULL,
  file_name = "network",
  format = "pdf",
  width = 29.7,
  height = 21,
  units = "cm",
  overwrite = FALSE
)

Arguments

log2fc_df

DF with metabolites as row names and columns including log2FC, Class, qval columns.

show_labels_for

Vector with Strings of Metabolite names or classes.

values_col_name

Column name of a column that holds numeric values, to be plotted Default = "log2FC"

stat_col_name

Columnname that holds numeric stat values that are used for significance Default = "qval"

show_p_value

Boolean Value, to color p-values according to their significance level and add a Legend Default = TRUE

signif_colors

Vector assigning significance values different colors

save_as

Optional: Select the file type of output plots. Options are svg, pdf, png or NULL. Default = "NULL"

folder_name

Name of the folder where the plot will be saved. Special characters will be removed automatically. Default = date

folder_path

Optional: User-defined path where the folder should be created. If not provided, results will be saved in 'MetAlyzer_results' within the working directory. Default = NULL

file_name

Name of the output file (without extension). Default = "network"

format

File format for saving the plot (e.g., "png", "pdf", "svg"). Default = "pdf"

width

Width of the saved plot in specified units. Default = 29.7

height

Height of the saved plot in specified units. Default = 21.0

units

Units for width and height (e.g., "in", "cm", "mm"). Default = "cm"

overwrite

Logical: If 'TRUE', overwrite existing files without asking. If 'FALSE', prompt user before overwriting. Default = FALSE

Value

ggplot object

Examples

log2fc_df <- readRDS(MetAlyzer::toy_diffres())
scatter <- MetAlyzer::plot_scatter(log2fc_df)
log2fc_df <- readRDS(MetAlyzer::toy_diffres())
scatter <- MetAlyzer::plot_scatter(log2fc_df)

Get polarity file path

Description

This function returns the polarity.csv file path.

Usage

polarity()
polarity()

Value

polarity.csv file path

Examples

fpath <- MetAlyzer::polarity()
fpath <- MetAlyzer::polarity()

Read and Validate Network Edges (Connections)

Description

Reads edge data from a specified named region, validates that connected nodes exist and are not self-loops, and removes invalid edges.

Usage

read_edges(network_file, nodes, pathways, region_name = "Connections_Header")
read_edges(network_file, nodes, pathways, region_name = "Connections_Header")

Arguments

network_file

Path to the input file containing edge data.

nodes

A data frame of validated nodes (output of read_nodes).

pathways

A data frame of validated pathways (output of read_pathways).

region_name

The named region or sheet containing connections header info.

Value

A data frame of validated edges.

Read Named Regions

Description

This function reads in the named regions of an excel file.

Usage

read_named_region(file_path, named_region)
read_named_region(file_path, named_region)

Arguments

file_path

The file path of the file

named_region

The region name u want to read in

Read and Validate Network Nodes (Metabolites)

Description

Reads node data from a specified named region, validates entries against pathway information, cleans labels, removes invalid nodes, and sets row names.

Usage

read_nodes(network_file, pathways, region_name = "Metabolites_Header")
read_nodes(network_file, pathways, region_name = "Metabolites_Header")

Arguments

network_file

Path to the input file containing node data.

pathways

A data frame of validated pathways (output of read_pathways).

region_name

The named region or sheet containing metabolite header info.

Value

A data frame of validated nodes with labels as row names.

Read and Validate Pathway Annotations

Description

Reads pathway data from a specified named region in the pathway file, validates entries, removes invalid ones, and sets row names.

Usage

read_pathways(network_file, region_name = "Pathways_Header")
read_pathways(network_file, region_name = "Pathways_Header")

Arguments

network_file

Path to the input file containing pathway data.

region_name

The named region or sheet containing pathway header info.

Value

A data frame of validated pathway annotations with labels as row names.

Open file and read data

Description

This function creates a SummarizedExperiment (SE) from the given 'webidq' output Excel sheet: metabolites (rowData), meta data (colData), concentration data (assay), quantification status(assay) The column "Sample Type" and the row "Class" are used as anchor cells in the Excel sheet and are therefore a requirement.

Usage

read_webidq(
  file_path,
  sheet = 1,
  status_list = list(Valid = c("#B9DE83", "#00CD66"), LOQ = c("#B2D1DC", "#7FB2C5",
    "#87CEEB"), LOD = c("#A28BA3", "#6A5ACD", "#BBA7B9"), `ISTD Out of Range` =
    c("#FFF099", "#FFFF33"), Invalid = "#FFFFCC", Incomplete = c("#CBD2D7", "#FFCCCC")),
  silent = FALSE
)
read_webidq(
  file_path,
  sheet = 1,
  status_list = list(Valid = c("#B9DE83", "#00CD66"), LOQ = c("#B2D1DC", "#7FB2C5",
    "#87CEEB"), LOD = c("#A28BA3", "#6A5ACD", "#BBA7B9"), `ISTD Out of Range` =
    c("#FFF099", "#FFFF33"), Invalid = "#FFFFCC", Incomplete = c("#CBD2D7", "#FFCCCC")),
  silent = FALSE
)

Arguments

file_path

A character specifying the file path to the Excel file.

sheet

A numeric index specifying which sheet of the Excel file to use.

status_list

A list of HEX color codes for each quantification status.

silent

If TRUE, mute any print command.

Value

A Summarized Experiment object

Examples

Path <- MetAlyzer::load_demodata_biocrates()
metalyzer_se <- MetAlyzer::read_webidq(file_path = Path)
Path <- MetAlyzer::load_demodata_biocrates()
metalyzer_se <- MetAlyzer::read_webidq(file_path = Path)

Rename meta data

Description

This function renames a column of meta_data.

Usage

rename_meta_data(metalyzer_se, ..., inplace = FALSE)
rename_meta_data(metalyzer_se, ..., inplace = FALSE)

Arguments

metalyzer_se

SummarizedExperiment

...

Use new_name = old_name to rename selected variables

inplace

If FALSE, return a copy. Otherwise, do operation inplace and return None.

Value

An updated SummarizedExperiment

Examples

metalyzer_se <- MetAlyzer::read_webidq(file_path = MetAlyzer::load_demodata_biocrates())

metalyzer_se <- MetAlyzer::rename_meta_data(
  metalyzer_se,
  Method = `Sample Description`
)
metalyzer_se <- MetAlyzer::read_webidq(file_path = MetAlyzer::load_demodata_biocrates())

metalyzer_se <- MetAlyzer::rename_meta_data(
  metalyzer_se,
  Method = `Sample Description`
)

Save plots

Description

This function saves a given ggplot object to a specified folder and file format. It ensures that the folder structure exists and cleans the folder name to remove special characters.

Usage

save_plot(
  plot,
  folder_name = format(Sys.Date(), "%Y-%m-%d"),
  folder_path = NULL,
  file_name = "network",
  format = "pdf",
  units = "cm",
  height = 21,
  width = 29.7,
  overwrite = FALSE
)
save_plot(
  plot,
  folder_name = format(Sys.Date(), "%Y-%m-%d"),
  folder_path = NULL,
  file_name = "network",
  format = "pdf",
  units = "cm",
  height = 21,
  width = 29.7,
  overwrite = FALSE
)

Arguments

plot

A ggplot object to be saved.

folder_name

Name of the folder where the plot will be saved. Special characters will be removed automatically. Default = date

folder_path

Optional: User-defined path where the folder should be created. If not provided, results will be saved in 'MetAlyzer_results' within the working directory. Default = NULL

file_name

Name of the output file (without extension). Default = "network"

format

File format for saving the plot (e.g., "png", "pdf", "svg"). Default = "pdf"

units

Units for width and height (e.g., "in", "cm", "mm"). Default = "cm"

height

Height of the saved plot in specified units. Default = 21.0

width

Width of the saved plot in specified units. Default = 29.7

overwrite

Logical: If 'TRUE', overwrite existing files without asking. If 'FALSE', prompt user before overwriting. Default = FALSE

Value

The function does not return anything but saves the plot to the specified directory.

Launch the Shiny App

Description

This function launches the Shiny application.

Usage

start_app()
start_app()

Summarize concentration values

Description

This function prints quantiles and NAs of raw data.

Usage

summarize_conc_values(metalyzer_se)
summarize_conc_values(metalyzer_se)

Arguments

metalyzer_se

SummarizedExperiment

Examples

metalyzer_se <- MetAlyzer::read_webidq(file_path = MetAlyzer::load_demodata_biocrates())

MetAlyzer::summarize_conc_values(metalyzer_se)
metalyzer_se <- MetAlyzer::read_webidq(file_path = MetAlyzer::load_demodata_biocrates())

MetAlyzer::summarize_conc_values(metalyzer_se)

Summarize quantification status

Description

This function lists the number of each quantification status and its percentage.

Usage

summarize_quant_data(metalyzer_se)
summarize_quant_data(metalyzer_se)

Arguments

metalyzer_se

SummarizedExperiment

Examples

metalyzer_se <- MetAlyzer::read_webidq(file_path = MetAlyzer::load_demodata_biocrates())

MetAlyzer::summarize_quant_data(metalyzer_se)
metalyzer_se <- MetAlyzer::read_webidq(file_path = MetAlyzer::load_demodata_biocrates())

MetAlyzer::summarize_quant_data(metalyzer_se)

Get example log2fc data

Description

This function returns the log2fc dataframe of the Metalyzer_demo dataset_biocrates MxP Quant 500 XL_2025-04 file, created with the MetaVizPro package.

Usage

toy_diffres()
toy_diffres()

Value

toy_diffres.rds file path

Examples

fpath <- MetAlyzer::toy_diffres()
fpath <- MetAlyzer::toy_diffres()

Update meta data

Description

This function adds another column to filtered meta_data.

Usage

update_meta_data(metalyzer_se, ..., inplace = FALSE)
update_meta_data(metalyzer_se, ..., inplace = FALSE)

Arguments

metalyzer_se

SummarizedExperiment

...

Use ´new_col_name = new_column´ to rename selected variables

inplace

If FALSE, return a copy. Otherwise, do operation inplace and return None.

Value

An updated SummarizedExperiment

Examples

metalyzer_se <- MetAlyzer::read_webidq(file_path = MetAlyzer::load_demodata_biocrates())

metalyzer_se <- MetAlyzer::update_meta_data(
  metalyzer_se,
  Date = Sys.Date(), Analyzed = TRUE
)
metalyzer_se <- MetAlyzer::read_webidq(file_path = MetAlyzer::load_demodata_biocrates())

metalyzer_se <- MetAlyzer::update_meta_data(
  metalyzer_se,
  Date = Sys.Date(), Analyzed = TRUE
)

Package 'MetAlyzer'

Help Index

Get Aggregated Data

Description

Usage

Arguments

Examples

Helper function to calculate conditional mean based on significance

Description

Usage

Arguments

Value

Calculate Node-Level Aggregate Statistics (Conditional on Significance)

Description

Usage

Arguments

Value

Creates a viridis color style for Plotly plots.

Description

Usage

Arguments

Value

Get example mutation data

Description

Usage

Value

Examples

Export filtered raw data as csv

Description

Usage

Arguments

Examples

Filter meta data

Description

Usage

Arguments

Value

Examples

Filter metabolites

Description

Usage

Arguments

Value

Examples

Get demodata from biocrates

Description

Usage

Value

Examples

Get example extraction data

Description

Usage

Value

Examples

Get log2FC Data

Description

Usage

Arguments

Examples

Get MetAlyzer colors

Description

Usage

Value

Examples

Open file and read data

Description

Usage

Arguments

Get pathway file path

Description

Usage

Value

Examples

Plot Pathway Network

Description

Usage

Arguments

Value

Examples

Scatter Plot Visualization