Package 'regutools' reference manual

Title:	regutools: an R package for data extraction from RegulonDB
Description:	RegulonDB has collected, harmonized and centralized data from hundreds of experiments for nearly two decades and is considered a point of reference for transcriptional regulation in Escherichia coli K12. Here, we present the regutools R package to facilitate programmatic access to RegulonDB data in computational biology. regutools provides researchers with the possibility of writing reproducible workflows with automated queries to RegulonDB. The regutools package serves as a bridge between RegulonDB data and the Bioconductor ecosystem by reusing the data structures and statistical methods powered by other Bioconductor packages. We demonstrate the integration of regutools with Bioconductor by analyzing transcription factor DNA binding sites and transcriptional regulatory networks from RegulonDB. We anticipate that regutools will serve as a useful building block in our progress to further our understanding of gene regulatory networks.
Authors:	Joselyn Chavez [aut, cre] , Carmina Barberena-Jonas [aut] , Jesus E. Sotelo-Fonseca [aut] , Jose Alquicira-Hernandez [ctb] , Heladia Salgado [ctb] , Leonardo Collado-Torres [aut] , Alejandro Reyes [aut]
Maintainer:	Joselyn Chavez <[email protected]>
License:	Artistic-2.0
Version:	1.19.0
Built:	2024-12-11 03:52:02 UTC
Source:	https://github.com/bioc/regutools

Construct logical condition to query database

Description

Given a list of filters, this function builds a logical condition to query database. The output is used in get_dataset().

Usage

build_condition(regulondb, dataset, filters, operator, interval, partialmatch)
build_condition(regulondb, dataset, filters, operator, interval, partialmatch)

Arguments

`regulondb`	A `regulondb()` object.
`dataset`	dataset of interest
`filters`	List of filters to be used. The names should correspond to the attribute and the values correspond to the condition for selection.
`operator`	A string indicating if all the filters (AND) or some of them (OR) should be met
`interval`	the filters with values considered as interval
`partialmatch`	name of the condition(s) with a string pattern for full or partial match in the query

Value

A character(1) with the sql logical condition to query the dataset .

Author(s)

Carmina Barberena Jonás, Jesús Emiliano Sotelo Fonseca, José Alquicira Hernández, Joselyn Chávez

Examples


## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Build the regulon db object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "E.coli",
        database_version = "1",
        genome_version = "1"
    )

## Build the condition for ara
build_condition(
    e_coli_regulondb,
    dataset = "GENE",
    filters = list(
        name = c("ara"),
        strand = c("forward"),
        posright = c("2000", "40000")
    ),
    operator = "AND",
    interval = "posright",
    partialmatch = "name"
)
## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Build the regulon db object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "E.coli",
        database_version = "1",
        genome_version = "1"
    )

## Build the condition for ara
build_condition(
    e_coli_regulondb,
    dataset = "GENE",
    filters = list(
        name = c("ara"),
        strand = c("forward"),
        posright = c("2000", "40000")
    ),
    operator = "AND",
    interval = "posright",
    partialmatch = "name"
)

Connect to the regulondb database

Description

This function downloads the RegulonDB SQLite database file prior to making a connection to it. It will cache the database file such that subsequent calls will run faster. This function requires an active internet connection.

Usage

connect_database(
  ah = AnnotationHub::AnnotationHub(),
  bfc = BiocFileCache::BiocFileCache()
)
connect_database(
  ah = AnnotationHub::AnnotationHub(),
  bfc = BiocFileCache::BiocFileCache()
)

Arguments

`ah`	An `AnnotationHub` object AnnotationHub-class. Can be `NULL` if you want to force to use the backup download mechanism.
`bfc`	A `BiocFileCache` object BiocFileCache-class. Used when `ah` is not available.

Value

An SQLiteConnection-class connection to the RegulonDB database.

Examples


## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Connect to the database without using AnnotationHub
regulondb_conn_noAH <- connect_database(ah = NULL)
## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Connect to the database without using AnnotationHub
regulondb_conn_noAH <- connect_database(ah = NULL)

Function to convert output of regulondb queries to Biostrings objects

Description

This function converts, when possible, a regulon_result object into a Biostrings object.

Usage

convert_to_biostrings(regulondb_result, seq_type = "DNA")
convert_to_biostrings(regulondb_result, seq_type = "DNA")

Arguments

`regulondb_result`	A regulon_result object.
`seq_type`	A character string with either DNA or protein, specyfing what

Value

A XStringSet object.

Author(s)

Alejandro Reyes

Examples

## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Build the regulon db object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "E.coli",
        database_version = "1",
        genome_version = "1"
    )

## Obtain all the information from the "GENE" dataset
convert_to_biostrings(get_dataset(e_coli_regulondb, dataset = "GENE"))
## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Build the regulon db object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "E.coli",
        database_version = "1",
        genome_version = "1"
    )

## Obtain all the information from the "GENE" dataset
convert_to_biostrings(get_dataset(e_coli_regulondb, dataset = "GENE"))

Function to convert output of regulondb queries to GenomicRanges objects

Description

This function converts, when possible, a regulon_result object into a GRanges object.

Usage

convert_to_granges(regulondb_result)
convert_to_granges(regulondb_result)

Arguments

regulondb_result

A regulon_result object.

Value

A GRanges object.

Author(s)

Alejandro Reyes

Examples

## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Build the regulon db object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "E.coli",
        database_version = "1",
        genome_version = "1"
    )

## Obtain all the information from the "GENE" dataset
convert_to_granges(get_dataset(e_coli_regulondb, dataset = "GENE"))
## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Build the regulon db object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "E.coli",
        database_version = "1",
        genome_version = "1"
    )

## Obtain all the information from the "GENE" dataset
convert_to_granges(get_dataset(e_coli_regulondb, dataset = "GENE"))

Constructs a particular logical condition to query database

Description

Given a list of filters, this function builds a logical condition to query database using intervals. The output is used in build_condition().

Usage

existing_intervals(filters, interval, operator, partialmatch)
existing_intervals(filters, interval, operator, partialmatch)

Arguments

`filters`	List of filters to be used. The names should correspond to the attribute and the values correspond to the condition for selection.
`interval`	the filters with values considered as interval.
`operator`	A string indicading if all the filters (AND) or some of them (OR) should be met.
`partialmatch`	name of the condition(s) with a string pattern for full or partial match in the query.

Value

A character(1) with the sql logical condition to query the dataset.

Author(s)

Carmina Barberena Jonás, Jesús Emiliano Sotelo Fonseca, José Alquicira Hernández, Joselyn Chávez

Examples


## Build the SQL query for existing interval partial matches for ara
existing_intervals(
    filters = list(
        name = "ara",
        strand = "for",
        posright = c("2000", "40000")
    ),
    interval = c("posright"),
    operator = "AND",
    partialmatch = c("name", "strand")
)
## Build the SQL query for existing interval partial matches for ara
existing_intervals(
    filters = list(
        name = "ara",
        strand = "for",
        posright = c("2000", "40000")
    ),
    interval = c("posright"),
    operator = "AND",
    partialmatch = c("name", "strand")
)

Constructs a logical condition to query database

Description

Given a list of filters, this function builds a logical condition to query database using intervals. The output is used in existing_intervals() and non_existing_intervals().

Usage

existing_partial_match(filters, partialmatch, operator)
existing_partial_match(filters, partialmatch, operator)

Arguments

`filters`	List of filters to be used. The names should correspond to the attribute and the values correspond to the condition for selection.
`partialmatch`	name of the condition(s) with a string pattern for full or partial match in the query.
`operator`	A string indicating if all the filters (AND) or some of them (OR) should be met.

Value

A character(1) with the sql logical condition to query the dataset.

Author(s)

Carmina Barberena Jonás, Jesús Emiliano Sotelo Fonseca, José Alquicira Hernández

Examples


## Build the SQL query for existing partial matches for ara
existing_partial_match(
    filters = list(
        name = c("ara"),
        strand = c("forward"),
        posright = c("2000", "40000")
    ),
    partialmatch = "name",
    operator = "AND"
)
## Build the SQL query for existing partial matches for ara
existing_partial_match(
    filters = list(
        name = c("ara"),
        strand = c("forward"),
        posright = c("2000", "40000")
    ),
    partialmatch = "name",
    operator = "AND"
)

Get the binding sites for a Transcription Factor (TF)

Description

Retrieve the binding sites and genome location for a given transcription factor.

Usage

get_binding_sites(regulondb, transcription_factor, output_format = "GRanges")
get_binding_sites(regulondb, transcription_factor, output_format = "GRanges")

Arguments

`regulondb`	A `regulondb()` object.
`transcription_factor`	name of the transcription factor.
`output_format`	The output object. Can be either a `GRanges` (default) or `Biostrings`.

Value

Either a GRanges object or a Biostrings object summarizing information about the binding sites of the transcription factors.

Author(s)

José Alquicira Hernández, Jacques van Helden, Joselyn Chávez

Examples

## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Build the regulon db object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "E.coli",
        database_version = "1",
        genome_version = "1"
    )

## Get the binding sites for AraC
get_binding_sites(e_coli_regulondb, transcription_factor = "AraC")
## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Build the regulon db object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "E.coli",
        database_version = "1",
        genome_version = "1"
    )

## Get the binding sites for AraC
get_binding_sites(e_coli_regulondb, transcription_factor = "AraC")

Extract data from RegulonDB

Description

This function retrieves data from RegulonDB. Attributes from datasets can be selected and filtered.

Usage

get_dataset(
  regulondb,
  dataset = NULL,
  attributes = NULL,
  filters = NULL,
  and = TRUE,
  interval = NULL,
  partialmatch = NULL,
  output_format = "regulondb_result"
)
get_dataset(
  regulondb,
  dataset = NULL,
  attributes = NULL,
  filters = NULL,
  and = TRUE,
  interval = NULL,
  partialmatch = NULL,
  output_format = "regulondb_result"
)

Arguments

`regulondb`	A `regulondb()` object.
`dataset`	Dataset of interest. Use the function list_datasets for an overview of valid datasets.
`attributes`	Vector of attributes to be retrieved.
`filters`	List of filters to be used. The names should correspond to the attribute and the values correspond to the condition for selection.
`and`	Logical argument. If FALSE, filters will be considered under the "OR" operator
`interval`	the filters whose values will be considered as interval
`partialmatch`	name of the condition(s) with a string pattern for full or partial match in the query
`output_format`	A string specifying the output format. Possible options are "regulondb_result", "GRanges", "DNAStringSet" or "BStringSet".

Value

By default, a regulon_results object. If specified in the parameter output_format, it can also return either a GRanges object or a Biostrings object.

Author(s)

Carmina Barberena Jonas, Jesús Emiliano Sotelo Fonseca, José Alquicira Hernández, Joselyn Chávez

Examples

## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Build the regulon db object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "E.coli",
        database_version = "1",
        genome_version = "1"
    )

## Obtain all the information from the "GENE" dataset
get_dataset(e_coli_regulondb, dataset = "GENE")

## Get the attributes posright and name from the "GENE" dataset
get_dataset(e_coli_regulondb,
    dataset = "GENE",
    attributes = c("posright", "name")
)

## From "GENE" dataset, get the gene name, strand, posright, product name
## and id of all genes regulated with name like "ara", strand as "forward"
## with a position right between 2000 and 40000
get_dataset(
    e_coli_regulondb,
    dataset = "GENE",
    attributes = c("name", "strand", "posright", "product_name", "id"),
    filters = list(
        name = c("ara"),
        strand = c("forward"),
        posright = c("2000", "40000")
    ),
    and = TRUE,
    partialmatch = "name",
    interval = "posright"
)
## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Build the regulon db object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "E.coli",
        database_version = "1",
        genome_version = "1"
    )

## Obtain all the information from the "GENE" dataset
get_dataset(e_coli_regulondb, dataset = "GENE")

## Get the attributes posright and name from the "GENE" dataset
get_dataset(e_coli_regulondb,
    dataset = "GENE",
    attributes = c("posright", "name")
)

## From "GENE" dataset, get the gene name, strand, posright, product name
## and id of all genes regulated with name like "ara", strand as "forward"
## with a position right between 2000 and 40000
get_dataset(
    e_coli_regulondb,
    dataset = "GENE",
    attributes = c("name", "strand", "posright", "product_name", "id"),
    filters = list(
        name = c("ara"),
        strand = c("forward"),
        posright = c("2000", "40000")
    ),
    and = TRUE,
    partialmatch = "name",
    interval = "posright"
)

Retrieve genomic elements from regulonDB

Description

Retrieve genomic elements from regulonDB

Usage

get_dna_objects(
  regulondb,
  genome = "eschColi_K12",
  grange = GRanges("chr", IRanges(1, 5000)),
  elements = "gene"
)
get_dna_objects(
  regulondb,
  genome = "eschColi_K12",
  grange = GRanges("chr", IRanges(1, 5000)),
  elements = "gene"
)

Arguments

`regulondb`	A `regulondb()` object.
`genome`	A valid UCSC genome name.
`grange`	A `GenomicRanges::GRanges-class()` object indicating position left and right.
`elements`	A character vector specifying which annotation elements to plot. It can be any from: `"-10 promoter box"`, `"-35 promoter box"`, `"gene"`, `"promoter"`, `"Regulatory Interaction"`, `"sRNA interaction"`, or `"terminator"`.

Value

GenomicRanges::GRanges-class() object with the elements found.

Author(s)

Joselyn Chavez

Examples

## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) {
      regulondb_conn <- connect_database()
  }

## Build the regulondb object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "chr",
        database_version = "1",
        genome_version = "1"
    )

## Get all genes from E. coli
get_dna_objects(e_coli_regulondb)

## Get genes providing Genomic Ranges
grange <- GenomicRanges::GRanges(
    "chr",
    IRanges::IRanges(5000, 10000)
)
get_dna_objects(e_coli_regulondb, grange)

## Get aditional elements within genomic positions
get_dna_objects(e_coli_regulondb,
    grange,
    elements = c("gene", "promoter")
)
## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) {
      regulondb_conn <- connect_database()
  }

## Build the regulondb object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "chr",
        database_version = "1",
        genome_version = "1"
    )

## Get all genes from E. coli
get_dna_objects(e_coli_regulondb)

## Get genes providing Genomic Ranges
grange <- GenomicRanges::GRanges(
    "chr",
    IRanges::IRanges(5000, 10000)
)
get_dna_objects(e_coli_regulondb, grange)

## Get aditional elements within genomic positions
get_dna_objects(e_coli_regulondb,
    grange,
    elements = c("gene", "promoter")
)

Get TFs or genes that regulate the genes of interest

Description

Given a list of genes (name, bnumber or GI), get all transcription factors or genes that regulate them. The effect of regulators over the gene of interest can be positive (+), negative (-) or dual (+/-)

Usage

get_gene_regulators(regulondb, genes, format = "multirow", output.type = "TF")
get_gene_regulators(regulondb, genes, format = "multirow", output.type = "TF")

Arguments

`regulondb`	A regulondb class.
`genes`	Vector of genes (name, bnumber or GI).
`format`	Output format: multirow, onerow, table
`output.type`	How regulators will be represented: "TF"/"GENE"

Value

A regulondb_result object.

Author(s)

Carmina Barberena Jonas, Jesús Emiliano Sotelo Fonseca, José Alquicira Hernández, Joselyn Chávez

Examples

## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Build the regulon db object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "E.coli",
        database_version = "1",
        genome_version = "1"
    )

## Get Transcription factors that regulate araC in one row
get_gene_regulators(
    e_coli_regulondb,
    genes = c("araC"),
    output.type = "TF",
    format = "onerow"
)

## Get genes that regulate araC in table format
get_gene_regulators(
    e_coli_regulondb,
    genes = c("araC"),
    output.type = "GENE",
    format = "table"
)
## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Build the regulon db object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "E.coli",
        database_version = "1",
        genome_version = "1"
    )

## Get Transcription factors that regulate araC in one row
get_gene_regulators(
    e_coli_regulondb,
    genes = c("araC"),
    output.type = "TF",
    format = "onerow"
)

## Get genes that regulate araC in table format
get_gene_regulators(
    e_coli_regulondb,
    genes = c("araC"),
    output.type = "GENE",
    format = "table"
)

Retrieve gene synonyms

Description

Given a list of genes (id, name, bnumber or gi), get the gene synonyms (name, bnumber of gi).

Usage

get_gene_synonyms(
  regulondb,
  genes,
  from = "name",
  to = c("id", "name", "bnumber", "gi")
)
get_gene_synonyms(
  regulondb,
  genes,
  from = "name",
  to = c("id", "name", "bnumber", "gi")
)

Arguments

`regulondb`	A `regulondb()` object.
`genes`	Character vector of gene identifiers (id, name, bnumber or gi).
`from`	A `character()` specifying one of: id, name, bnumber of gi
`to`	A `character()` specifying one or more of: id, name, bnumber of gi

Value

A regulondb_result object.

Author(s)

Jesús Emiliano Sotelo Fonseca

Examples

## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Build the regulon db object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "E.coli",
        database_version = "1",
        genome_version = "1"
    )

## Lists all available identifiers for "araC"
get_gene_synonyms(e_coli_regulondb, "araC", from = "name")

## Retrieve only the ID
get_gene_synonyms(e_coli_regulondb, "araC", from = "name", to = "id")

## Use an ID to retrieve the synonyms
get_gene_synonyms(e_coli_regulondb, "ECK120000998", from = "id")
## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Build the regulon db object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "E.coli",
        database_version = "1",
        genome_version = "1"
    )

## Lists all available identifiers for "araC"
get_gene_synonyms(e_coli_regulondb, "araC", from = "name")

## Retrieve only the ID
get_gene_synonyms(e_coli_regulondb, "araC", from = "name", to = "id")

## Use an ID to retrieve the synonyms
get_gene_synonyms(e_coli_regulondb, "ECK120000998", from = "id")

Return complete regulatory network.

Description

This function retrieves all the regulation networks in regulonDB between TF-TF, GENE-GENE or TF-GENE depending on the parameter 'type'.

Usage

get_regulatory_network(
  regulondb,
  regulator = NULL,
  type = "TF-GENE",
  cytograph = FALSE
)
get_regulatory_network(
  regulondb,
  regulator = NULL,
  type = "TF-GENE",
  cytograph = FALSE
)

Arguments

`regulondb`	A `regulondb()` object.
`regulator`	Name of TF or gene that acts as regulator. If `NULL`, the function retrieves all existent networks in the regulonDB.
`type`	"TF-GENE", "TF-TF", "GENE-GENE"
`cytograph`	If TRUE, displays network in Cytoscape. This option requires previous instalation and launch of Cytoscape.

Value

A regulondb_result object.

Author(s)

Carmina Barberena Jonas, Jesús Emiliano Sotelo Fonseca, José Alquicira Hernández, Joselyn Chávez

Examples


## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Build the regulon db object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "E.coli",
        database_version = "1",
        genome_version = "1"
    )

## Retrieve regulation of 'araC'
get_regulatory_network(e_coli_regulondb,
    regulator = "AraC",
    type = "TF-GENE"
)

## Retrieve all GENE-GENE networks
get_regulatory_network(e_coli_regulondb, type = "GENE-GENE")

## Retrieve TF-GENE network of AraC and display in Cytoscape
## Note that Cytospace needs to be open for this to work
cytoscape_present <- try(RCy3::cytoscapePing(), silent = TRUE)
if (!is(cytoscape_present, "try-error")) {
    get_regulatory_network(
        e_coli_regulondb,
        regulator = "AraC",
        type = "TF-GENE",
        cytograph = TRUE
    )
}
## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Build the regulon db object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "E.coli",
        database_version = "1",
        genome_version = "1"
    )

## Retrieve regulation of 'araC'
get_regulatory_network(e_coli_regulondb,
    regulator = "AraC",
    type = "TF-GENE"
)

## Retrieve all GENE-GENE networks
get_regulatory_network(e_coli_regulondb, type = "GENE-GENE")

## Retrieve TF-GENE network of AraC and display in Cytoscape
## Note that Cytospace needs to be open for this to work
cytoscape_present <- try(RCy3::cytoscapePing(), silent = TRUE)
if (!is(cytoscape_present, "try-error")) {
    get_regulatory_network(
        e_coli_regulondb,
        regulator = "AraC",
        type = "TF-GENE",
        cytograph = TRUE
    )
}

Return summary of gene regulation.

Description

This function takes the output of get_gene_regulators() with format multirow, onerow or table, or a vector with genes and retrieves information about the TFs and their regulated genes

Usage

get_regulatory_summary(regulondb, gene_regulators)
get_regulatory_summary(regulondb, gene_regulators)

Arguments

`regulondb`	A `regulondb()` object.
`gene_regulators`	Result from `get_gene_regulators()` or vector of genes

Value

A data frame with the following columns:

The name or gene of TF
Regulated Genes per TF
Percent of regulated genes per TF
positive, negative or dual regulation
Name(s) of regulated genes

Author(s)

Carmina Barberena Jonas, Jesús Emiliano Sotelo Fonseca, José Alquicira Hernández, Joselyn Chávez

Examples

## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Build the regulon db object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "E.coli",
        database_version = "1",
        genome_version = "1"
    )

## Get the araC regulators
araC_regulation <-
    get_gene_regulators(
        e_coli_regulondb,
        genes = c("araC"),
        format = "multirow",
        output.type = "TF"
    )

## Summarize the araC regulation
get_regulatory_summary(e_coli_regulondb, araC_regulation)

## Retrieve summary of genes 'araC' and 'modB'
get_regulatory_summary(e_coli_regulondb,
    gene_regulators = c("araC", "modB")
)

## Obtain the summary for 'ECK120000050' and 'modB'
get_regulatory_summary(e_coli_regulondb,
    gene_regulators = c("ECK120000050", "modB")
)
## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Build the regulon db object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "E.coli",
        database_version = "1",
        genome_version = "1"
    )

## Get the araC regulators
araC_regulation <-
    get_gene_regulators(
        e_coli_regulondb,
        genes = c("araC"),
        format = "multirow",
        output.type = "TF"
    )

## Summarize the araC regulation
get_regulatory_summary(e_coli_regulondb, araC_regulation)

## Retrieve summary of genes 'araC' and 'modB'
get_regulatory_summary(e_coli_regulondb,
    gene_regulators = c("araC", "modB")
)

## Obtain the summary for 'ECK120000050' and 'modB'
get_regulatory_summary(e_coli_regulondb,
    gene_regulators = c("ECK120000050", "modB")
)

Guess gene id type

Description

Given a gene identifier, return the most likely gene_id type.

Usage

guess_id(gene, regulondb)
guess_id(gene, regulondb)

Arguments

`gene`	Character vector of gene identifiers (id, name, bnumber or gi).
`regulondb`	A `regulondb()` object.

Value

A character(1) vector with the name column guessed value.

Author(s)

Jesús Emiliano Sotelo Fonseca

Examples

## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Build the regulon db object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "E.coli",
        database_version = "1",
        genome_version = "1"
    )

## Lists all available identifiers for "araC"
## Guess name
guess_id("araC", e_coli_regulondb)

## Guess id
guess_id("ECK120000050", e_coli_regulondb)

## Guess bnumber
guess_id("b0064", e_coli_regulondb)
## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Build the regulon db object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "E.coli",
        database_version = "1",
        genome_version = "1"
    )

## Lists all available identifiers for "araC"
## Guess name
guess_id("araC", e_coli_regulondb)

## Guess id
guess_id("ECK120000050", e_coli_regulondb)

## Guess bnumber
guess_id("b0064", e_coli_regulondb)

List attributes/fields from a dataset/table

Description

List all attributes and their description of a dataset from RegulonDB. The result of this function may be used as parameter 'values' in list_attributes() function.

Usage

list_attributes(regulondb, dataset)
list_attributes(regulondb, dataset)

Arguments

`regulondb`	A `regulondb()` object.
`dataset`	Dataset of interest. The name should correspond to a table of the database.

Value

A character vector with the field names.

Author(s)

Carmina Barberena Jonás, Jesús Emiliano Sotelo Fonseca, José Alquicira Hernández, Joselyn Chavez

Examples

## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Build the regulon db object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "E.coli",
        database_version = "1",
        genome_version = "1"
    )

## List the transcription factor attributes
list_attributes(e_coli_regulondb, "TF")

## List the operon attributes
list_attributes(e_coli_regulondb, "OPERON")
## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Build the regulon db object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "E.coli",
        database_version = "1",
        genome_version = "1"
    )

## List the transcription factor attributes
list_attributes(e_coli_regulondb, "TF")

## List the operon attributes
list_attributes(e_coli_regulondb, "OPERON")

List available datasets in RegulonDB database

Description

This function returns a vector of all available tables from a regulondb class.

Usage

list_datasets(regulondb)
list_datasets(regulondb)

Arguments

regulondb

A regulondb class.

Value

A character() with the names of the available datasets.

Examples


## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Build the regulon db object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "E.coli",
        database_version = "1",
        genome_version = "1"
    )

## List the available datasets
list_datasets(e_coli_regulondb)
## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Build the regulon db object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "E.coli",
        database_version = "1",
        genome_version = "1"
    )

## List the available datasets
list_datasets(e_coli_regulondb)

Constructs a logical condition to query database

Description

Given a list of filters, this function builds a logical condition to query database using intervals. The output is used in build_condition().

Usage

non_existing_intervals(filters, interval, operator, partialmatch)
non_existing_intervals(filters, interval, operator, partialmatch)

Arguments

`filters`	List of filters to be used. The names should correspond to the attribute and the values correspond to the condition for selection.
`interval`	the filters whose values will be considered as interval
`operator`	A string indicating if all the filters (AND) or some of them (OR) should be met.
`partialmatch`	name of the condition(s) with a string pattern for full or partial match in the query.

Value

A character(1) with the sql logical condition to query the dataset.

Author(s)

Carmina Barberena Jonás, Jesús Emiliano Sotelo Fonseca, José Alquicira Hernández

Examples

## Build the SQL query for finidng non-existing intervals for the gene ara
non_existing_intervals(
    filters = list(name = "ara", strand = "for"),
    interval = NULL,
    operator = "AND",
    partialmatch = c("name", "strand")
)
## Build the SQL query for finidng non-existing intervals for the gene ara
non_existing_intervals(
    filters = list(name = "ara", strand = "for"),
    interval = NULL,
    operator = "AND",
    partialmatch = c("name", "strand")
)

Plot annotation elements within genomic region

Description

Plot annotation elements within genomic region

Usage

plot_dna_objects(
  regulondb,
  genome = "eschColi_K12",
  grange = GRanges("chr", IRanges(1, 5000)),
  elements = "gene"
)
plot_dna_objects(
  regulondb,
  genome = "eschColi_K12",
  grange = GRanges("chr", IRanges(1, 5000)),
  elements = "gene"
)

Arguments

`regulondb`	A `regulondb()` object.
`genome`	A valid UCSC genome name.
`grange`	A `GenomicRanges::GRanges-class()` object indicating position left and right.
`elements`	A character vector specifying which annotation elements to plot. It can be any from: `"-10 promoter box"`, `"-35 promoter box"`, `"gene"`, `"promoter"`, `"Regulatory Interaction"`, `"sRNA interaction"`, or `"terminator"`.

Value

A plot with genomic elements found within a genome region, including genes and regulators.

Author(s)

Joselyn Chavez

Examples

## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) {
      regulondb_conn <- connect_database()
  }

## Build the regulondb object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "chr",
        database_version = "1",
        genome_version = "1"
    )

## Plot some genes from E. coli using default parameters
plot_dna_objects(e_coli_regulondb)

## Plot genes providing Genomic Ranges
grange <- GenomicRanges::GRanges(
    "chr",
    IRanges::IRanges(5000, 10000)
)
plot_dna_objects(e_coli_regulondb, grange)

## Plot aditional elements within genomic positions
plot_dna_objects(e_coli_regulondb,
    grange,
    elements = c("gene", "promoter")
)
## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) {
      regulondb_conn <- connect_database()
  }

## Build the regulondb object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "chr",
        database_version = "1",
        genome_version = "1"
    )

## Plot some genes from E. coli using default parameters
plot_dna_objects(e_coli_regulondb)

## Plot genes providing Genomic Ranges
grange <- GenomicRanges::GRanges(
    "chr",
    IRanges::IRanges(5000, 10000)
)
plot_dna_objects(e_coli_regulondb, grange)

## Plot aditional elements within genomic positions
plot_dna_objects(e_coli_regulondb,
    grange,
    elements = c("gene", "promoter")
)

Constructor function of a regulondb class

Description

The build_regulondb function is a constructor function of a regulondb class.

Usage

regulondb(database_conn, organism, genome_version, database_version)
regulondb(database_conn, organism, genome_version, database_version)

Arguments

`database_conn`	A SQLiteConnection-class connection to the RegulonDB database made with `connect_database()`.
`organism`	A character vector with the name of the organism of the database.
`genome_version`	A character vector with the version of the genome build.
`database_version`	A character vector with the version of regulondb build.

Value

A regulondb object.

Examples


## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Build a regulondb object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "E.coli",
        database_version = "1",
        genome_version = "1"
    )
## Connect to the RegulonDB database if necessary
if (!exists("regulondb_conn")) regulondb_conn <- connect_database()

## Build a regulondb object
e_coli_regulondb <-
    regulondb(
        database_conn = regulondb_conn,
        organism = "E.coli",
        database_version = "1",
        genome_version = "1"
    )

The regulondb_results class

Description

The regulondb class is an extension of the DataFrame class, with additional slots that host information of the database used to obtain these results.

Slots

organism: A character string with the name of the organism of the database.
genome_version: A character string with the version of the genome build.
database_version: A character string with the version of regulondb build.
dataset: A character string with the name of the table used for the query in get_dataset().

The regulondb class

Description

The regulondb class is an extension of the SQLiteConnection, which as the name suggests, consists of an SQLite connection to a database with the table design of the RegulonDb database. In addition to the slots defined in the SQLiteConnection object, the regulondb class also contains additional slots to store information about database versions, organism information and genome build versions.

Slots

organism: A character vector with the name of the organism of the database.
genome_version: A character vector with the version of the genome build.
database_version: A character vector with the version of regulondb build.

Methods for regulondb objects

Description

Methods for regulondb objects

Usage

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

Arguments

object

A regulondb object

Value

A regulondb object.

Package 'regutools'

Help Index

Construct logical condition to query database

Description

Usage

Arguments

Value

Author(s)

Examples

Connect to the regulondb database

Description

Usage

Arguments

Value

Examples

Function to convert output of regulondb queries to Biostrings objects

Description

Usage

Arguments

Value

Author(s)

Examples

Function to convert output of regulondb queries to GenomicRanges objects

Description

Usage

Arguments

Value

Author(s)

Examples

Constructs a particular logical condition to query database

Description

Usage

Arguments

Value

Author(s)

Examples

Constructs a logical condition to query database

Description

Usage

Arguments

Value

Author(s)

Examples

Get the binding sites for a Transcription Factor (TF)

Description

Usage

Arguments

Value

Author(s)

Examples

Extract data from RegulonDB

Description

Usage

Arguments

Value

Author(s)

Examples

Retrieve genomic elements from regulonDB

Description

Usage

Arguments

Value

Author(s)

Examples

Get TFs or genes that regulate the genes of interest

Description

Usage

Arguments

Value

Author(s)

Examples

Retrieve gene synonyms

Description

Usage

Arguments

Value

Author(s)

Examples

Return complete regulatory network.

Description