Package 'CompoundDb'

Description

CompDb objects provide access to general (metabolite) compound annotations along with metadata information such as the annotation's source, date and release version. The data is stored internally in a database (usually an SQLite database).

hasMsMsSpectra returns TRUE if MS/MS spectrum data is available in the database and FALSE otherwise.

Usage

CompDb(x, flags = SQLITE_RO)

hasMsMsSpectra(x)

src_compdb(x)

tables(x)

copyCompDb(x, y)

## S4 method for signature 'CompDb'
dbconn(x)

## S4 method for signature 'CompDb'
Spectra(object, filter, ...)

## S4 method for signature 'CompDb'
supportedFilters(object)

## S4 method for signature 'CompDb'
metadata(x, ...)

## S4 method for signature 'CompDb'
spectraVariables(object, ...)

## S4 method for signature 'CompDb'
compoundVariables(object, includeId = FALSE, ...)

## S4 method for signature 'CompDb'
compounds(
  object,
  columns = compoundVariables(object),
  filter,
  return.type = c("data.frame", "tibble"),
  ...
)

## S4 method for signature 'CompDb,Spectra'
insertSpectra(object, spectra, columns = spectraVariables(spectra), ...)

## S4 method for signature 'CompDb'
deleteSpectra(object, ids = integer(0), ...)

## S4 method for signature 'CompDb'
mass2mz(x, adduct = c("[M+H]+"), name = "formula")

## S4 method for signature 'CompDb'
insertCompound(object, compounds = data.frame(), addColumns = FALSE)

## S4 method for signature 'CompDb'
deleteCompound(object, ids = character(), recursive = FALSE, ...)

Arguments

For all other methods: a `CompDb` object.

Details

CompDb objects should be created using the constructor function CompDb() providing the name of the (SQLite) database file providing the compound annotation data.

Value

See description of the respective function.

Retrieve annotations from the database

Annotations/compound informations can be retrieved from a CompDb database with the compounds() and Spectra() functions:

• compounds() extracts compound data from the CompDb object. In contrast to src_compdb it returns the actual data as a data.frame (if return.type = "data.frame") or a tibble::tibble() (if return.type = "tibble"). A compounds() call will always return all elements from the ms_compound table (unless a filter is used).

• Spectra() extract spectra from the database and returns them as a Spectra() object from the Spectra package. Additional annotations requested with the columns parameter are added as additional spectra variables.

General functions

• CompDb(): connect to a compound database.

• compoundVariables(): returns all available columns/database fields for compounds.

• copyCompDb(): allows to copy the content from a CompDb to another database. Parameter x is supposed to be either a CompDb or a database connection from which the data should be copied and y a connection to a database to which it should be copied.

• dbconn(): returns the connection (of type DBIConnection) to the database.

• metadata(): returns general meta data of the compound database.

• spectraVariables(): returns all spectra variables (i.e. columns) available in the CompDb.

• src_compdb() provides access to the CompDb's database via the functionality from the dplyr/dbplyr package.

• supportedFilters(): provides an overview of the filters that can be applied on a CompDb object to extract only specific data from the database.

• tables(): returns a named list (names being table names) with the fields/columns from each table in the database.

• mass2mz(): calculates a table of the m/z values for each compound based on the provided set of adduct(s). Adduct definitions can be provided with parameter adduct. See MetaboCoreUtils::mass2mz() for more details. Parameter name defines the database table column that should be used as rownames of the returned matrix. By default name = "formula", m/z values are calculated for each unique formula in the CompDb x.

Adding and removing data from a database

Note that inserting and deleting data requires read-write access to the database. Databases returned by CompDb are by default read-only. To get write access CompDb should be called with parameter flags = RSQLite::SQLITE_RW.

• insertCompound(): adds additional compound(s) to a CompDb. The compound(s) to be added can be specified with parameter compounds that is expected to be a data.frame with columns "compound_id", "name", "inchi", "inchikey", "formula", "exactmass". Column "exactmass" is expected to contain numeric values, all other columns character. Missing values are allowed for all columns except "compound_id". An optional column "synonyms" can be used to provide alternative names for the compound. This column can contain a single character by row, or a list with multiple character (names) per row/compound (see examples below for details). By setting parameter addColumns = TRUE any additional columns in compound will be added to the database table. The default is addColumns = FALSE. The function returns the CompDb with the compounds added. See also createCompDb() for more information and details on expected compound data and the examples below for general usage.

• deleteCompound(): removes specified compounds from the CompDb database. The IDs of the compounds that should be deleted need to be provided with parameter ids. To include compound IDs in the output of a compounds() call "compound_id" should be added to the columns parameter. By default an error is thrown if for some of the specified compounds also MS2 spectra are present in the database. To force deletion of the compounds along with all associated MS2 spectra use recursive = TRUE. See examples below for details. The function returns the updated CompDb database.

• insertSpectra(): adds further spectra to the database. The method always adds all the spectra specified through the spectra parameter and does not check if they are already in the database. Note that the input spectra must have the variable compound_id and only Spectra whose compound_id values are also in compounds(object, "compound_id") can be added. Parameter columns defines which spectra variables from the spectra should be inserted into the database. By default, all spectra variables are added but it is strongly suggested to specifically select (meaningful) spectra variables that should be stored in the database. Note that a spectra variable "compound_id" is mandatory. If needed, the function adds additional columns to the msms_spectrum database table. The function returns the updated CompDb object.

• deleteSpectra(): deletes specified spectra from the database. The IDs of the spectra to be deleted need to be provided with parameter ids.

Filtering the database

Data access methods such as compounds() and Spectra allow to filter the results using specific filter classes and expressions. Filtering uses the concepts from Bioconductor's AnnotationFilter package. All information for a certain compound with the ID "HMDB0000001" can for example be retrieved by passing the filter expression filter = ~ compound_id == "HMDB0000001" to the compounds function.

Use the supportedFilters() function on the CompDb object to get a list of all supported filters. See also examples below or the usage vignette for details.

Author(s)

Johannes Rainer

See Also

createCompDb() for the function to create a SQLite compound database.

CompoundIdFilter() for filters that can be used on the CompDb database.

Examples

## We load a small compound test database based on MassBank which is
## distributed with this package.
cdb <- CompDb(system.file("sql/CompDb.MassBank.sql", package = "CompoundDb"))
cdb

## Get general metadata information from the database, such as originating
## source and version:
metadata(cdb)

## List all available compound annotations/fields
compoundVariables(cdb)

## Extract a data.frame with these annotations for all compounds
compounds(cdb)

## Note that the `compounds` function will by default always return a
## data frame of **unique** entries for the specified columns. Including
## also the `"compound_id"` to the requested columns will ensure that all
## data is returned from the tables.
compounds(cdb, columns = c("compound_id", compoundVariables(cdb)))

## Add also the synonyms (aliases) for the compounds. This will cause the
## tables compound and synonym to be joined. The elements of the compound_id
## and name are now no longer unique
res <- compounds(cdb, columns = c("name", "synonym"))
head(res)

## List all database tables and their columns
tables(cdb)

## Any of these columns can be used in the `compounds` call to retrieve
## the specific annotations. The corresponding database tables will then be
## joined together
compounds(cdb, columns = c("formula", "publication"))

## Calculating m/z values for the exact masses of unique chemical formulas
## in the database:
mass2mz(cdb, adduct = c("[M+H]+", "[M+Na]+"))

## By using `name = "compound_id"` the calculation will be performed for
## each unique compound ID instead (resulting in potentially redundant
## results)
mass2mz(cdb, adduct = c("[M+H]+", "[M+Na]+"), name = "compound_id")

## Create a Spectra object with all MS/MS spectra from the database.
library(Spectra)
sps <- Spectra(cdb)
sps

## Extract spectra for a specific compound.
sps <- Spectra(cdb, filter = ~ name == "Mellein")
sps

## List all available annotations for MS/MS spectra
spectraVariables(sps)

## Get access to the m/z values of these
mz(sps)

library(Spectra)
## Plot the first spectrum
plotSpectra(sps[1])


#########
## Filtering the database
##
## Get all compounds with an exact mass between 310 and 320
res <- compounds(cdb, filter = ~ exactmass > 310 & exactmass < 320)
res

## Get all compounds that have an H14 in their formula.
res <- compounds(cdb, filter = FormulaFilter("H14", "contains"))
res

#########
## Using CompDb with the *tidyverse*
##
## Using return.type = "tibble" the result will be returned as a "tibble"
compounds(cdb, return.type = "tibble")

## Use the CompDb in a dplyr setup
library(dplyr)
src_cmp <- src_compdb(cdb)
src_cmp

## Get a tbl for the ms_compound table
cmp_tbl <- tbl(src_cmp, "ms_compound")

## Extract the id, name and inchi
cmp_tbl %>% select(compound_id, name, inchi) %>% collect()

########
## Creating an empty CompDb and sequentially adding content
##
## Create an empty CompDb and store the database in a temporary file
cdb <- emptyCompDb(tempfile())
cdb

## Define a data.frame with some compounds to add
cmp <- data.frame(
    compound_id = c(1, 2),
    name = c("Caffeine", "Glucose"),
    formula = c("C8H10N4O2", "C6H12O6"),
    exactmass = c(194.080375584, 180.063388116))

## We can also add multiple synonyms for each compound
cmp$synonyms <- list(c("Cafeina", "Koffein"), "D Glucose")
cmp

## These compounds can be added to the empty database with insertCompound
cdb <- insertCompound(cdb, compounds = cmp)
compounds(cdb)

## insertCompound would also allow to add additional columns/annotations to
## the database. Below we define a new compound adding an additional column
## hmdb_id
cmp <- data.frame(
    compound_id = 3,
    name = "Alpha-Lactose",
    formula = "C12H22O11",
    exactmass = 342.116211546,
    hmdb_id = "HMDB0000186")

## To add additional columns we need to set addColumns = TRUE
cdb <- insertCompound(cdb, compounds = cmp, addColumns = TRUE)
cdb
compounds(cdb)

######
## Deleting selected compounds from a database
##
## Compounds can be deleted with the deleteCompound function providing the
## IDs of the compounds that should be deleted. IDs of compounds in the
## database can be retrieved by adding "compound_id" to the columns parameter
## of the compounds function:
compounds(cdb, columns = c("compound_id", "name"))

## Compounds can be deleted with the deleteCompound function. Below we delete
## the compounds with the IDs "1" and "3" from the database
cdb <- deleteCompound(cdb, ids = c("1", "3"))
compounds(cdb)

## If also MS2 spectra associated with any of these two compounds an error
## would be thrown. Setting the parameter `recursive = TRUE` in the
## `deleteCompound` call would delete the compounds along with their MS2
## spectra.

Description

compound_tbl_lipidblast() extracts basic compound annotations from a LipidBlast file in (json format) downloaded from http://mona.fiehnlab.ucdavis.edu/downloads . Note that no mass spectra data is extracted from the json file.

Usage

compound_tbl_lipidblast(
  file,
  collapse = character(),
  n = -1L,
  verbose = FALSE,
  BPPARAM = bpparam()
)

Arguments

Value

A tibble::tibble with general compound information (one row per compound):

• compound_id: the ID of the compound.

• name: the compound's name.

• inchi: the InChI of the compound.

• inchikey: the InChI key.

• smiles: the SMILES representation of the compound.

• formula: the chemical formula.

• exactmass: the compound's mass.

• compound_class: the class of the compound.

• ionization_mode: the ionization mode.

• precursor_mz: the precursor m/z value.

• precursor_type: the precursor type.

• retention_time: the retention time.

• ccs: the collision cross-section.

• spectrum: the spectrum data (i.e. the mass peaks, as a concatenated character string).

• synonyms: the compound's synonyms (aliases). This type of this column is by default a list to support multiple aliases per compound, unless argument collapse is provided, in which case multiple synonyms are pasted into a single element separated by the value of collapse.

Author(s)

Johannes Rainer, Jan Stanstrup and Prateek Arora

See Also

Other compound table creation functions: compound_tbl_sdf()

Examples

## Read compound information from a subset of HMDB
fl <- system.file("json/MoNa-LipidBlast_sub.json", package = "CompoundDb")
cmps <- compound_tbl_lipidblast(fl, n = 50000, verbose = TRUE)
cmps

Description

compound_tbl_sdf() extracts basic compound annotations from a file in SDF format (structure-data file). The function currently supports SDF files from:

• HMDB (Human Metabolome Database): http://www.hmdb.ca

• ChEBI (Chemical Entities of Biological Interest): http://ebi.ac.uk/chebi

• LMSD (LIPID MAPS Structure Database): http://www.lipidmaps.org

• PubChem: https://pubchem.ncbi.nlm.nih.gov/

• MoNa: http://mona.fiehnlab.ucdavis.edu/ (see notes below!)

Usage

compound_tbl_sdf(file, collapse, onlyValid = TRUE, nonStop = TRUE)

Arguments

Details

Column "name" reports for HMDB files the "GENERIC_NAME", for ChEBI the "ChEBI Name", for PubChem the "PUBCHEM_IUPAC_TRADITIONAL_NAME", and for Lipid Maps the "COMMON_NAME", if that is not available, the first of the compounds synonyms and, if that is also not provided, the "SYSTEMATIC_NAME".

Value

A tibble::tibble with general compound information (one row per compound):

• compound_id: the ID of the compound.

• name: the compound's name.

• inchi: the InChI of the compound.

• inchikey: the InChI key.

• formula: the chemical formula.

• exactmass: the compound's (monoisotopic exact) mass.

• synonyms: the compound's synonyms (aliases). This type of this column is by default a list to support multiple aliases per compound, unless argument collapse is provided, in which case multiple synonyms are pasted into a single element separated by the value of collapse.

• smiles: the compound's SMILES (if provided).

Note

compound_tbl_sdf() supports also to read/process gzipped files.

MoNa SDF files organize the data by individual spectra (i.e. each element is one spectrum) and individual compounds can not easily and consistently defined (i.e. not all entries have an InChI ID or other means to uniquely identify compounds). Thus, the function returns a highly redundant compound table. Feedback on how to reduce this redundancy would be highly welcome!

LIPID MAPS was tested August 2020. Older SDF files might not work as the field names were changed.

Author(s)

Johannes Rainer and Jan Stanstrup

See Also

createCompDb() for a function to create a SQLite-based compound database.

Other compound table creation functions: compound_tbl_lipidblast()

Examples

## Read compound information from a subset of HMDB
fl <- system.file("sdf/HMDB_sub.sdf.gz", package = "CompoundDb")
cmps <- compound_tbl_sdf(fl)
cmps

## Column synonyms contains a list
cmps$synonyms

## If we provide the optional argument collapse, multiple entries will be
## collapsed.
cmps <- compound_tbl_sdf(fl, collapse = "|")
cmps
cmps$synonyms

Description

CompDb databases can be created with the createCompDb() or the emptyCompDb() functions, the former creating and initializing (filling) the database with existing data, the latter creating an empty database that can be subsequently filled with insertCompound() or insertSpectra() calls.

emptyCompDb() requires only the file name of the database that should be created as input and returns a CompDb representing the empty database.

createCompDb() creates a SQLite-based CompDb object/database from a compound resource provided as a data.frame or tbl. Alternatively, the name(s) of the file(s) from which the annotation should be extracted can be provided. Supported are SDF files (such as those from the Human Metabolome Database HMDB) that can be read using the compound_tbl_sdf() or LipidBlast files (see compound_tbl_lipidblast().

An additional data.frame providing metadata information including the data source, date, version and organism is mandatory. By default, the function will define the name of the database based on the provided metadata, but it is also possible to define this manually with the dbFile parameter.

Optionally MS/MS (MS2) spectra for compounds can be also stored in the database. Currently only MS/MS spectra from HMDB are supported. These can be downloaded in XML format from HMDB (http://www.hmdb.ca), loaded with the msms_spectra_hmdb() or msms_spectra_mona() function and passed to the function with the msms_spectra argument. See msms_spectra_hmdb() or msms_spectra_mona() for information on the expected columns and format.

Required columns for the data.frame providing the compound information ( parameter x) are:

• "compound_id": the ID of the compound. Can be an integer or character. Duplicated IDs are supported (for compatibility reasons), but not suggested. No missing values allowed.

• "name": the compound's name.

• "inchi": the InChI of the compound.

• "inchikey": the InChI key.

• "formula": the chemical formula.

• "exactmass": the compound's (exact) mass.

• "synonyms": additional synonyms/aliases for the compound. Should be either a single character or a list of values for each compound.

Any additional columns in the provided data.frame (such as e.g. "smiles" providing the compound's SMILES) are also supported and will be inserted into the database table.

See e.g. compound_tbl_sdf() or compound_tbl_lipidblast() for functions creating such compound tables.

The table containing the MS2 spectra data should have the following format and columns:

• "spectrum_id": an arbitrary ID for the spectrum. Has to be an integer.

• "compound_id": the ID of the compound to which the spectrum can be associated with. This has to be present in the data.frame defining the compounds.

• "polarity": the polarity (as an integer, 0 for negative, 1 for positive, NA for not set).

• "collision_energy": the collision energy.

• "predicted": whether the spectrum was predicted or measured.

• "splash": the SPLASH of the spectrum.

• "instrument_type": the instrument type.

• "instrument": the name of the instrument.

• "precursor_mz": the precursor m/z (as a numeric).

• "mz": the m/z values.

• "intensity": the intensity values.

Only for columns "spectrum_id", "compound_id", "mz" and "intensity" a value has to be provided in each row of the data.frame. The others are optional. Note that the data.frame can be either in the format as in the example below (i.e. each row being one spectrum and columns "mz" and "intensity" being of type list each element being the m/z or intensity values of one spectrum) or in a full form, in which each row represents one peak and all columns except "mz" and "intensity" containing redundant information of each spectrum (hence columns "mz" and "intensity" being of type numeric).

The metadata data.frame is supposed to have two columns named "name" and "value" providing the following minimal information as key-value pairs (see make_metadata for a utility function to create such a data.frame):

• "source": the source from which the data was retrieved (e.g. "HMDB").

• "url": the url from which the original data was retrieved.

• "source_version": the version from the original data source (e.g. "v4").

• "source_date": the date when the original data source was generated.

• "organism": the organism. Should be in the form "Hsapiens" or "Mmusculus".

createCompDbPackage creates an R data package with the data from a CompDb object.

make_metadata() helps generating a metadata data.frame in the correct format expected by the createCompDb function. The function returns a data.frame.

Usage

createCompDb(x, metadata, msms_spectra, path = ".", dbFile = character())

createCompDbPackage(
  x,
  version,
  maintainer,
  author,
  path = ".",
  license = "Artistic-2.0"
)

make_metadata(
  source = character(),
  url = character(),
  source_version = character(),
  source_date = character(),
  organism = NA_character_
)

emptyCompDb(dbFile = character())

Arguments

For `createCompDbPackage()`: `character(1)` with the file name of the
`CompDb` SQLite file (created by `createCompDb`).

Details

Metadata information is also used to create the file name for the database file. The name starts with "CompDb", followed by the organism, the data source and its version. A compound database file for HMDB version 4 with human metabolites will thus be named: "CompDb.Hsapiens.HMDB.v4".

A single CompDb database is created from multiple SDF files (e.g. for PubChem) if all the file names are provided with parameter x. Parallel processing is currently not enabled because SQLite does not support it yet natively.

Value

For createCompDb(): a character(1) with the database name (invisibly).

Author(s)

Johannes Rainer

See Also

compound_tbl_sdf() and compound_tbl_lipidblast() for functions to extract compound annotations from files in SDF format, or files from LipidBlast.

import_mona_sdf() to import both the compound and spectrum data from a SDF file from MoNa (Massbank of North America) in one call.

msms_spectra_hmdb() and msms_spectra_mona() for functions to import MS/MS spectrum data from xml files from HMDB or an SDF file from MoNa.

CompDb() for how to use a compound database.

Examples

## Read compounds for a HMDB subset
fl <- system.file("sdf/HMDB_sub.sdf.gz", package = "CompoundDb")
cmps <- compound_tbl_sdf(fl)

## Create a metadata data.frame for the compounds.
metad <- data.frame(name = c("source", "url", "source_version",
    "source_date", "organism"), value = c("HMDB", "http://www.hmdb.ca",
    "v4", "2017-08-27", "Hsapiens"))

## Alternatively use the make_metadata helper function
metad <- make_metadata(source = "HMDB", source_version = "v4",
    source_date = "2017-08", organism = "Hsapiens",
    url = "http://www.hmdb.ca")
## Create a SQLite database in the temporary folder
db_f <- createCompDb(cmps, metadata = metad, path = tempdir())

## The database can be loaded and accessed with a CompDb object
db <- CompDb(db_f)
db

## Create a database for HMDB that includes also MS/MS spectrum data
metad2 <- make_metadata(source = "HMDB_with_spectra", source_version = "v4",
    source_date = "2017-08", organism = "Hsapiens",
    url = "http://www.hmdb.ca")

## Import spectrum information from selected MS/MS xml files from HMDB
## that are provided in the package
xml_path <- system.file("xml", package = "CompoundDb")
spctra <- msms_spectra_hmdb(xml_path)

## Create a SQLite database in the temporary folder
db_f2 <- createCompDb(cmps, metadata = metad2, msms_spectra = spctra,
    path = tempdir())

## The database can be loaded and accessed with a CompDb object
db2 <- CompDb(db_f2)
db2

## Does the database contain MS/MS spectrum data?
hasMsMsSpectra(db2)

## Create a database for a ChEBI subset providing the file name of the
## corresponding SDF file
metad <- make_metadata(source = "ChEBI_sub", source_version = "2",
    source_date = NA, organism = "Hsapiens", url = "www.ebi.ac.uk/chebi")
db_f <- createCompDb(system.file("sdf/ChEBI_sub.sdf.gz",
    package = "CompoundDb"), metadata = metad, path = tempdir())
db <- CompDb(db_f)
db

compounds(db)

## connect to the database and query it's tables using RSQlite
library(RSQLite)
con <- dbConnect(dbDriver("SQLite"), db_f)

dbGetQuery(con, "select * from metadata")
dbGetQuery(con, "select * from ms_compound")

## To create a CompDb R-package we could simply use the
## createCompDbPackage function on the SQLite database file name.

Description

expandMzIntensity() expands a data.frame with m/z and/or intensity values stored as a list in columns "mz" and "intensity". The resulting data.frame has the m/z and intensity values stored as numeric in columns "mz" and "intensity", one value per row, with the content of other columns repeated as many times as there are m/z and intensity values.

Usage

expandMzIntensity(x)

Arguments

Value

data.frame with "mz" and "intensity" columns expanded. See description for details.

Author(s)

Johannes Rainer

Examples

## Read a data.frame with collapsed columns mz and intensity columns
dr <- system.file("xml/", package = "CompoundDb")
msms_spctra <- msms_spectra_hmdb(dr)

msms_spctra

## Columns mz and intensity are "collased"
msms_spctra$mz

## Expand the data.frame to get one row per m/z and intensity value
spctra_exp <- expandMzIntensity(msms_spctra)
spctra_exp

Description

A variety of different filters can be applied to the CompDb object to retrieve only subsets of the data. These filters extend the AnnotationFilter::AnnotationFilter class and support the filtering concepts introduced by Bioconductor's AnnotationFilter package.

The supported filters are:

• CompoundIdFilter: filter based on the compound ID.

• FormulaFilter: filter based on the compound's formula.

• InchiFilter: filter based on the compound's InChI.

• InchikeyFilter: filter based on the compound's InChI key.

• ExactmassFilter: filter based on the compound's (exact) mass.

• NameFilter: filter based on the compound name.

• MsmsMzRangeMinFilter: retrieve entries based on the smallest m/z of all peaks of their MS/MS spectra. Requires that MS/MS spectra data are present (i.e. hasMsMsSpectra(cmp_db) returns TRUE).

• MsmsMzRangeMaxFilter: retrieve entries based on the largest m/z of all peaks of their MS/MS spectra. Requires that MS/MS spectra data are present (i.e. hasMsMsSpectra(cmp_db) returns TRUE).

• SpectrumIdFilter: retrieve entries associated with the provided IDs of MS/MS spectra.

In addition to the filters listed above, the following ones are supported by a IonDb (but not by a CompDb):

• IonIdFilter: filter based on the ion ID.

• IonAdductFilter: filter based on the adduct.

• IonMzFilter: filter based on the mz of the ion.

• IonRtFilter: filter based on the rt of the ion.

Usage

CompoundIdFilter(value, condition = "==")

SpectrumIdFilter(value, condition = "==")

NameFilter(value, condition = "==")

MsmsMzRangeMinFilter(value, condition = ">=")

MsmsMzRangeMaxFilter(value, condition = "<=")

ExactmassFilter(value, condition = "==")

FormulaFilter(value, condition = "==")

InchiFilter(value, condition = "==")

InchikeyFilter(value, condition = "==")

IonIdFilter(value, condition = "==")

IonAdductFilter(value, condition = "==")

IonMzFilter(value, condition = "==")

IonRtFilter(value, condition = "==")

Arguments

Value

Constructor functions return an instance of the respective class.

Author(s)

Johannes Rainer

See Also

supportedFilters() for the method to list all supported filters for a CompDb (or a IonDb) object.

Examples

## Create a filter for the compound id
cf <- CompoundIdFilter("comp_a")
cf

## Create a filter using a formula expression
AnnotationFilter(~ compound_id == "comp_b")

## Combine filters
AnnotationFilterList(CompoundIdFilter("a"), NameFilter("b"))

## Using a formula expression
AnnotationFilter(~ compound_id == "a" | name != "b")

Description

import_mona_sdf() allows to import compound and spectrum information from an SDF file from MoNa (Massbank of North America http://mona.fiehnlab.ucdavis.edu/). This function is a convenience function using the compound_tbl_sdf() and msms_spectra_mona() functions for data import but avoiding to read the SDF files twice.

Usage

import_mona_sdf(x, nonStop = TRUE)

Arguments

Value

A list with elements "compound" and "msms_spectrum" containing data.frames with compound and MS/MS spectrum data, respectively.

Note

MoNa SDF files organize the data by individual spectra (i.e. each element is one spectrum) and individual compounds can not easily and consistently defined (i.e. not all entries have an InChI ID or other means to uniquely identify compounds). Thus, the function returns a highly redundant compound table. Feedback on how to reduce this redundancy would be highly welcome!

Author(s)

Johannes Rainer

See Also

compound_tbl_sdf() to read only the compound information.

msms_spectra_mona() to read only the spectrum data.

Examples

## Define the test file containing a small subset from MoNa
fl <- system.file("sdf/MoNa_export-All_Spectra_sub.sdf.gz",
    package = "CompoundDb")

## Import the data
res <- import_mona_sdf(fl)

Description

IonDb objects extends CompDb by allowing to store also information about measured ions to a CompDb() database. This information includes the type (adduct) of the ion, it's measured (or expected) retention time for a certain LC-MS setup and its mass-to-charge ratio.

As suggested use case, users might create (or download) a CompDb (SQLite) database e.g. containing compound (and eventually MS/MS spectra) annotations from public databases such as the Human Metabolome Database (HMDB) or MassBank. To store now measured ions (e.g. of lab-internal standards) for a certain LC-MS setup, such a CompDb can then be converted to an IonDb using the IonDb() constructor function. Ions can be subsequently added using the insertIon() function. In general, it is suggested to create one IonDb database for one specific LC-MS setup. Such an IonDb database can then be used to match experimental m/z and retention times against ions defined in the database (using the functionality of the MetaboAnnotation package).

Usage

## S4 method for signature 'IonDb'
ionVariables(object, includeId = FALSE, ...)

## S4 method for signature 'IonDb'
ions(
  object,
  columns = ionVariables(object),
  filter,
  return.type = c("data.frame", "tibble"),
  ...
)

## S4 method for signature 'IonDb'
insertIon(object, ions, addColumns = FALSE)

## S4 method for signature 'IonDb'
deleteIon(object, ids = integer(0), ...)

## S4 method for signature 'missing,missing'
IonDb(x, cdb, flags = SQLITE_RWC, ...)

## S4 method for signature 'CompDb,missing'
IonDb(x, cdb, ions = data.frame(), ...)

## S4 method for signature 'character,missing'
IonDb(x, cdb, flags = SQLITE_RW, ...)

## S4 method for signature 'DBIConnection,missing'
IonDb(
  x,
  cdb,
  ions = data.frame(),
  flags = SQLITE_RW,
  ...,
  .DBNAME = character()
)

## S4 method for signature 'character,CompDb'
IonDb(x, cdb, ions = data.frame(), flags = SQLITE_RW, ...)

## S4 method for signature 'DBIConnection,CompDb'
IonDb(
  x,
  cdb,
  ions = data.frame(),
  flags = SQLITE_RW,
  ...,
  .DBNAME = character()
)

Arguments

For all other methods: an `IonDb` object.

Value

See description of the respective function.

Creation of IonDb objects/databases

• A new IonDb database can be created and initialized with data from an existing CompDb database by passing either the database connection (e.g. an SQLiteConnection) or the file path of a (to be created) SQLite database with parameter x to the IonDb() function and the CompDb object with parameter cdb. Optional parameter ions allows insert in addition ion definitions (which can also be added later using insertIon() function calls).

• An existing CompDb can be converted to an IonDb by passing the CompDb() object with parameter x to the IonDb function. Optional parameter ions allows to provide a data.frame with ion definitions to be inserted in to the database (which can also be added later using insertIon() function calls). Note that this fails if the database connection for the CompDb is read-only.

• Previously created IonDb databases can be loaded by passing either the database connection (e.g. an SQLiteConnection) or the file path of the (SQLite) database with parameter x to the IonDb() function.

Retrieve annotations and ion information from the database

Annotations/compound informations can be retrieved from a IonDb in the same way as thay are extracted from a CompDb. In addition, the function ions() allows to retrieve the specific ion information from the database. It returns the actual data as a data.frame (if return.type = "data.frame") or a tibble::tibble() (if return.type = "tibble"). An ions() call will always return all elements from the ms_ion table (unless a filter is used).

General functions (beside those inherited from CompDb)

• IonDb(): connect to or create a compound/ion database.

• ionVariables(): returns all available columns/database fields for ions.

Adding and removing data from a database

IonDb inherits the insertCompound(), insertSpectra(), deleteCompound() and deleteSpectra() functions from CompDb(). In addition, IonDb defines the functions:

• insertIon(): adds ions to the IonDb object. Note that insertIon() always adds all the ions specified through the ions parameter and does not check if they are already in the database. To add columns present in the submitted data.frame to the database table set addColumns = TRUE (default is addColumns = FALSE).

• deleteIon(): deletes ions from the IonDb object by specifying their IDs.

Filtering the database

Like compounds() and Spectra() also ions() allows to filter the results using specific filter classes and expressions. Filtering uses the concepts from Bioconductor's AnnotationFilter package. All information for a certain compound with the ID "1" can for example be retrieved by passing the filter expression filter = ~ ion_id == 1 to the ions() function.

Use the supportedFilters() function on the IonDb object to get a list of all supported filters. See also examples below or the usage vignette for details.

Author(s)

Andrea Vicini, Johannes Rainer

Examples

# We load a small compound test database based on MassBank which is
# distributed with this package.
cdb <- CompDb(system.file("sql/CompDb.MassBank.sql", package = "CompoundDb"))
cdb

# We next want to convert this CompDb into an IonDb, but the original CompDb
# database is read only, thus we have to provide the name (or connection) of
# an other database to transfer all the data from the CompDb to that.
idb <- IonDb(paste0(tempdir(), "/idb_ex.db"), cdb)
idb

# It is also possible to load a previously created IonDb passing only the
# connection to the database.
idb2 <- IonDb(paste0(tempdir(), "/idb_ex.db"))

# Ion definitions can be added to the database with the `insertIon` function
# providing a `data.frame` with ion definition. This `data.frame` is expected
# to provide the IDs of the compounds, an adduct name/definition and the
# (experimentally determined) m/z and retention time of the ion. To list
# compound IDs from the CompDb database:
head(compounds(cdb, c("compound_id", "name")))

ions = data.frame(compound_id = c("1", "1", "2", "3", "6", "35"),
                  ion_adduct = c("[M+H]+", "[M+Na]+", "[M+Na]+",
                                 "[M+Na]+", "[M+2H]2+", "[M+H-NH3]+"),
                  ion_mz = c(179.0703, 201.0522, 201.0522,
                             201.0522, 253.66982, 312.0390),
                  ion_rt = 1:6)

# Inserting ion definitions.
idb <- insertIon(idb, ions)
idb

ions(idb, columns = c("name", "formula", "ion_adduct", "ion_mz", "ion_rt"))

## List all available ion variables
ionVariables(idb)

## Extract a data.frame with ion variables for all ions
ions(idb)

## List all database tables and their columns
tables(idb)

## Filtering the database
##
## Get all ions with an m/z between 200 and 300
res <- ions(idb, filter = ~ ion_mz > 200 & ion_mz < 300)
res

## Get all ions that have a H in their adduct definition.
res <- ions(idb, filter = IonAdductFilter("H", "contains"))
res

Description

The MsBackendCompDb represents MS2 spectra data from a CompDb() object/database. The object keeps only the primary keys of the spectra, the associated compound IDs and the precursor m/z values in memory and has thus only a very low memory footprint. All spectra variables, including m/z and intensity values are retrieved from the database on-demand. By extending the MsBackendCached() class directly, MsBackendCompDb supports adding/replacing spectra variables. These values are however only cached within the object and not propagated (written) to the database.

It is not intended that users create or use instances of this class directly, the Spectra() call on CompDb() will return a Spectra object that uses this backend.

The MsBackendCompDb does not support parallel processing because the database connection stored within the object can not be used across multiple parallel processes. The backendBpparam() method for MsBackendCompDb thus returns always SerialParam and hence any function that uses this method to check for parallel processing capability of a MsBackend will by default disable parallel processing.

Usage

MsBackendCompDb()

## S4 method for signature 'MsBackendCompDb'
backendInitialize(object, x, filter, ...)

## S4 method for signature 'MsBackendCompDb'
show(object)

## S4 method for signature 'MsBackendCompDb'
peaksData(object, columns = c("mz", "intensity"))

## S4 method for signature 'MsBackendCompDb'
peaksVariables(object)

## S4 method for signature 'MsBackendCompDb'
dataStorage(object)

## S4 replacement method for signature 'MsBackendCompDb'
intensity(object) <- value

## S4 replacement method for signature 'MsBackendCompDb'
mz(object) <- value

## S4 method for signature 'MsBackendCompDb'
spectraData(object, columns = spectraVariables(object))

## S4 method for signature 'MsBackendCompDb'
spectraNames(object)

## S4 replacement method for signature 'MsBackendCompDb'
spectraNames(object) <- value

## S4 method for signature 'MsBackendCompDb,ANY'
x[i, j, ..., drop = FALSE]

## S4 replacement method for signature 'MsBackendCompDb'
x$name <- value

## S4 method for signature 'MsBackendCompDb'
precScanNum(object)

## S4 method for signature 'MsBackendCompDb'
tic(object, initial = TRUE)

## S4 method for signature 'MsBackendCompDb'
backendBpparam(object, BPPARAM = bpparam())

Arguments

Value

See the description of the respective function.

Methods implemented for MsBackendCompDb

The methods listed here are implemented for the MsBackendCompDb. All other methods are inherited directly from the parent MsBackendCached() class. See the help of MsBackend() in the Spectra package for a complete listing of methods.

• peaksData(): gets the full list of peak matrices. Returns a list(), length equal to the number of spectra and each element being a matrix with columns "mz" and "intensity" with the spectra's m/z and intensity values.

• peaksVariables(): lists the available peaks variables in the backend (database). These can be used for parameter columns of peaksData().

• ⁠intensity<-⁠: not supported.

• ⁠mz<-⁠: not supported.

• spectraData(): returns the complete spectrum data including m/z and intensity values as a DataFrame().

• ⁠$<-⁠: replace or add a spectrum variable. Note that mz, intensity and spectrum_id variables can not be replaced.

Note

For higher performance it is suggested to change the backend of the Spectra() object to an MsBackendMemory() backend with the setBackend() method of Spectra objects.

Author(s)

Johannes Rainer

Examples

## MsBackendCompDb are not expected to be created/instanciated by users
## directly. Users also almost never directly interact with this type of
## object, as it is intented as a pure data backend for the `Spectra` object.
## Users will thus access MS data through such `Spectra` object, which can
## be created for `CompDb` objects using the `Spectra` method (see help
## of the `CompDb` object for more information. This examples shows how
## a `MsBackendCompDb` could be created purely from an SQLite database
## with data from a CompoundDb database.

## Connect to the SQLite database of a `CompDb` distributed via this package
library(RSQLite)
library(Spectra)
cdb <- CompDb(system.file("sql/CompDb.MassBank.sql", package = "CompoundDb"))

be <- backendInitialize(MsBackendCompDb(), cdb)
be

## Accessing m/z values
mz(be)

Description

msms_spectra_hmdb() imports MS/MS spectra from corresponding xml files from HMDB (http://www.hmdb.ca) and returns the data as a data.frame. HMDB stores MS/MS spectrum data in xml files, one file per spectrum.

Depending on the parameter collapsed, the returned data.frame is either collapsed, meaning that each row represents data from one spectrum xml file, or expanded with one row for each m/z and intensity pair for each spectrum. Columns "mz" and "intensity" are of type list for collapsed = TRUE and numeric for collapsed = FALSE.

Usage

msms_spectra_hmdb(x, collapsed = TRUE)

Arguments

Value

data.frame with as many rows as there are peaks and columns:

• spectrum_id (integer): an arbitrary, unique ID identifying values from one xml file.

• original_spectrum_id (character): the HMDB-internal ID of the spectrum.

• compound_id (character): the HMDB compound ID the spectrum is associated with.

• polarity (integer): 0 for negative, 1 for positive, NA for not set.

• collision_energy (numeric): collision energy voltage.

• predicted (logical): whether the spectrum is predicted or experimentally verified.

• splash (character): the SPLASH (SPectraL hASH) key of the spectrum (Wohlgemuth 2016).

• instrument_type (character): the type of MS instrument on which the spectrum was measured.

• instrument (character): the MS instrument (not available for all spectra in HMDB).

• precursor_mz (numeric): not provided by HMDB and thus NA.

• mz (numeric or list of numeric): m/z values of the spectrum.

• intensity (numeric or list of numeric): intensity of the spectrum.

Note

The HMDB xml files are supposed to be extracted from the downloaded zip file into a folder and should not be renamed. The function identifies xml files containing MS/MS spectra by their file name.

The same spectrum ID can be associated with multiple compounds. Thus, the function assignes an arbitrary ID (column "spectrum_id") to values from each file. The original ID of the spectrum in HMDB is provided in column "original_spectrum_id".

Author(s)

Johannes Rainer

References

Wohlgemuth G, Mehta SS, Mejia RF, Neumann S, Pedrosa D, Pluskal T, Schymanski EL, Willighagen EL, Wilson M, Wishart DS, Arita M, Dorrestein PC, Bandeira N, Wang M, Schulze T, Selak RM, Steinbeck C, Nainala VC, Mistrik R, Nishioka T, Fiehn O. SPLASH, A hashed identifier for mass spectra. Nature Biotechnology 2016 34(11):1099-1101

See Also

createCompDb() for the function to create a CompDb database with compound annotation and spectrum data.

Other spectrum data import functions.: msms_spectra_mona()

Examples

## Locate the folder within the package containing test xml files.
pth <- system.file("xml", package = "CompoundDb")

## List all files in that directory
dir(pth)

## Import spectrum data from HMDB MS/MS spectrum xml files in that directory
msms_spectra_hmdb(pth)

## Import the data as an *expanded* data frame, i.e. with a row for each
## single m/z (intensity) value.
msms_spectra_hmdb(pth, collapsed = FALSE)

Description

msms_spectra_mona() imports MS/MS spectra from a MoNa (Massbank of North America, http://mona.fiehnlab.ucdavis.edu/downloads) SDF file and returns the data as a data.frame.

Depending on the parameter collapsed, the returned data.frame is either collapsed, meaning that each row represents data from one spectrum, or expanded with one row for each m/z and intensity pair for each spectrum. Columns "mz" and "intensity" are of type list for collapsed = TRUE and numeric for collapsed = FALSE.

Usage

msms_spectra_mona(x, collapsed = TRUE)

Arguments

Value

data.frame with as many rows as there are peaks and columns:

• spectrum_id (integer): an arbitrary, unique ID for each spectrum.

• original_spectrum_id (character): The ID from the spectrum as specified in the MoNa SDF.

• compound_id (character): the compound ID the spectrum is associated with.

• polarity (integer): 0 for negative, 1 for positive, NA for not set.

• collision_energy (character): collision energy voltage.

• predicted (logical): whether the spectrum is predicted or experimentally verified.

• splash (character): NA since SPLASH (SPectraL hASH) keys are not provided.

• instrument_type (character): the type of MS instrument on which the spectrum was measured.

• instrument (character): the MS instrument.

• precursor_mz (numeric): precursor m/z.

• adduct (character): ion formed from the precursor ion.

• ms_level (integer): stage of the sequential mass spectrometry (MSn).

• mz (numeric or list of numeric): m/z values of the spectrum.

• intensity (numeric or list of numeric): intensity of the spectrum.

Note

The identifiers provided by MoNa are used as original_spectrum_id. Note also that the MoNa data is not normalized in the sense that each spectrum is associated to one compound and the compound data is partially redundant. Also, MoNa does not provide a splash for a spectrum, hence the corresponding column will only contain NA.

Author(s)

Johannes Rainer

See Also

createCompDb() for the function to create a CompDb database with compound annotation and spectrum data.

Other spectrum data import functions.: msms_spectra_hmdb()

Examples

## Define the test file containing the data
fl <- system.file("sdf/MoNa_export-All_Spectra_sub.sdf.gz",
    package = "CompoundDb")
## Import spectrum data from the SDF file with a subset of the MoNa data
msms_spectra_mona(fl)

## Import the data as an *expanded* data frame, i.e. with a row for each
## single m/z (intensity) value.
msms_spectra_mona(fl, collapsed = FALSE)