CMMR provides a programmatic interface in R to interact with the CEU Mass Mediator RESTful API, facilitating automated metabolomics data analysis from mass spectrometry experiments.
The package integrates batch searches, advanced searches, and MS/MS spectral searches, allowing seamless incorporation into R-based metabolomics workflows. Users can leverage this package to process mass spectrometry data efficiently, without manual intervention through the web interface.
For further details on the CEU Mass Mediator platform, visit the CEU Mass Mediator website.
This package was built on top of the CEU Mass Mediator API by Albert Gil. Special thanks to @albertogilf for his contributions!
The package interacts with the following API endpoints:
To install the stable version from CRAN, run:
install.packages("cmmr")
To install the development version, which may include bug fixes or experimental features, use:
# install.packages("devtools")
::install_github("YaoxiangLi/cmmr") devtools
Perform a batch search in positive ion mode:
library(cmmr)
<- batch_search(
batch_df_pos cmm_url = 'https://ceumass.eps.uspceu.es/api/v3/batch',
metabolites_type = 'all-except-peptides',
databases = '["all-except-mine"]',
masses_mode = 'mz',
ion_mode = 'positive',
adducts = '["M+H","M+Na"]',
tolerance = 10,
tolerance_mode = 'ppm',
unique_mz = c(178.1219, 243.9134, 977.6763)
)
head(batch_df_pos)
str(batch_df_pos)
Perform a batch search in negative ion mode:
library(cmmr)
<- batch_search(
batch_df_neg cmm_url = 'https://ceumass.eps.uspceu.es/api/v3/batch',
metabolites_type = 'all-except-peptides',
databases = '["all-except-mine"]',
masses_mode = 'mz',
ion_mode = 'negative',
adducts = '["M-H","M+Cl"]',
tolerance = 100,
tolerance_mode = 'ppm',
unique_mz = c(670.4623, 1125.2555, 602.6180)
)
head(batch_df_neg)
str(batch_df_neg)
Load a list of m/z values from a CSV file and use it in the batch search:
# Load unique m/z values from CSV
<- system.file("extdata", "unique_mz.csv", package = "cmmr")
unique_mz_file <- read.table(unique_mz_file, sep = ",", stringsAsFactors = FALSE, header = FALSE)
unique_mz <- as.array(unique_mz[, 1])
unique_mz
# Perform batch search using the loaded m/z values
<- batch_search(
batch_df_neg cmm_url = 'https://ceumass.eps.uspceu.es/api/v3/batch',
metabolites_type = 'all-except-peptides',
databases = '["all-except-mine"]',
masses_mode = 'mz',
ion_mode = 'negative',
adducts = '["M-H","M+Cl"]',
tolerance = 10,
tolerance_mode = 'ppm',
unique_mz = unique_mz
)
Save the results:
# Save the results in the same folder as the original CSV
write.table(batch_df_neg, sub(".csv", "_db_search.csv", unique_mz_file), sep = ",", row.names = FALSE)
# Save to the current working directory
write.table(batch_df_neg, "batch_df_neg.csv", sep = ",", row.names = FALSE)
library(cmmr)
<- advanced_batch_search(
advanced_batch_df cmm_url = 'https://ceumass.eps.uspceu.es/api/v3/advancedbatch',
chemical_alphabet = 'ALL',
modifiers_type = 'none',
metabolites_type = 'all-except-peptides',
databases = '["hmdb"]',
masses_mode = 'mz',
ion_mode = 'positive',
adducts = '["all"]',
deuterium = FALSE,
tolerance = 7.5,
tolerance_mode = 'ppm',
masses = c(400.3432, 288.2174),
all_masses = '[]',
retention_times = c(18.842525, 4.021555),
all_retention_times = '[]',
composite_spectra = paste0(
'[ [ { "mz": 400.3432, "intensity": 307034.88 },',
' { "mz": 311.20145, "intensity": 400.03336 } ] ]'
)
)
head(advanced_batch_df)
str(advanced_batch_df)
library(cmmr)
# Define MS/MS peaks (m/z and intensity)
<- matrix(
ms_ms_peaks c(40.948, 0.174,
56.022, 0.424,
84.370, 53.488,
101.500, 8.285,
102.401, 0.775,
129.670, 100.000,
146.966, 20.070),
ncol = 2,
byrow = TRUE
)
# Perform MS/MS search
<- msms_search(
ms2_df ion_mass = 147,
ms_ms_peaks = ms_ms_peaks,
ion_mode = 'positive'
)
head(ms2_df)
str(ms2_df)
If you’d like to contribute to the development of CMMR, please follow the tidyverse style guide. Below are a few key conventions to adhere to: