Package 'drawProteins' reference manual

Title:	Package to Draw Protein Schematics from Uniprot API output
Description:	This package draws protein schematics from Uniprot API output. From the JSON returned by the GET command, it creates a dataframe from the Uniprot Features API. This dataframe can then be used by geoms based on ggplot2 and base R to draw protein schematics.
Authors:	Paul Brennan [aut, cre]
Maintainer:	Paul Brennan <[email protected]>
License:	MIT + file LICENSE
Version:	1.25.0
Built:	2024-09-22 04:17:26 UTC
Source:	https://github.com/bioc/drawProteins

Create ggplot2 object with protein chains from feature database

Description

draw_canvas uses the dataframe containing the protein features to creates the basic plot element by determining the length of the longest protein and the number of proteins to plot.

Usage

draw_canvas(data)
draw_canvas(data)

Arguments

data

Dataframe of one or more rows with the following column names: 'type', 'description', 'begin', 'end', 'length', 'accession', 'entryName', 'taxid', 'order'. Must contain a minimum of one "CHAIN" as data$type.

Value

A ggplot2 object either in the plot window or as an object.

Examples

# draws a blank canvas of the correct size
data("five_rel_data")
draw_canvas(five_rel_data)

# draws a blank canvas of the correct size
data("five_rel_data")
draw_canvas(five_rel_data)

Create ggplot2 object with protein chains from feature database

Description

draw_chains uses the dataframe containing the protein features to plot the chains, the full length proteins. It creates the basic plot element by determining the length of the longest protein. The ggplot2 function geom_rect is then used to draw each of the protein chains proportional to their number of amino acids (length).

Usage

draw_chains(p, data = data,
    outline = "black", fill = "grey",
    label_chains = TRUE, labels = data[data$type == "CHAIN",]$entryName,
    size = 0.5, label_size = 4)
draw_chains(p, data = data,
    outline = "black", fill = "grey",
    label_chains = TRUE, labels = data[data$type == "CHAIN",]$entryName,
    size = 0.5, label_size = 4)

Arguments

`p`	ggplot2 object ideally created with `draw_canvas`.
`data`	Dataframe of one or more rows with the following column names: 'type', 'description', 'begin', 'end', 'length', 'accession', 'entryName', 'taxid', 'order'. Must contain a minimum of one "CHAIN" as data$type.
`outline`	Colour of the outline of each chain.
`fill`	Colour of the fill of each chain.
`label_chains`	Option to label chains or not.
`labels`	Vector with source of names for the chains. EntryName used as default but can be changed.
`size`	Size of the outline of the chains.
`label_size`	Size of the text used for labels.

Value

A ggplot2 object either in the plot window or as an object.

Examples

# combines with draw_canvas to plot and label chains.
data("five_rel_data")
p <- draw_canvas(five_rel_data)
draw_chains(p, five_rel_data)

# draws five chains with different colours to default
data("five_rel_data")
p <- draw_canvas(five_rel_data)
draw_chains(p, five_rel_data,
    label_chains = FALSE,
    fill = "red",
    outline = "grey")

# combines with draw_canvas to plot and label chains.
data("five_rel_data")
p <- draw_canvas(five_rel_data)
draw_chains(p, five_rel_data)

# draws five chains with different colours to default
data("five_rel_data")
p <- draw_canvas(five_rel_data)
draw_chains(p, five_rel_data,
    label_chains = FALSE,
    fill = "red",
    outline = "grey")

Add protein domains to ggplot2 object.

Description

draw_domains adds domains to the ggplot2 object created by draw_chains. It uses the data object. The ggplot2 function geom_rect is used to draw each of the domain chains proportional to their number of amino acids (length).

Usage

draw_domains(p,
         data = data,
         label_domains = TRUE,
         label_size = 4,
         show.legend = TRUE,
         type = "DOMAIN")
draw_domains(p,
         data = data,
         label_domains = TRUE,
         label_size = 4,
         show.legend = TRUE,
         type = "DOMAIN")

Arguments

`p`	ggplot2 object ideally created with `draw_canvas`.
`data`	Dataframe of one or more rows with the following column names: 'type', 'description', 'begin', 'end', 'length', 'accession', 'entryName', 'taxid', 'order'. Must contain a minimum of one "CHAIN" as data$type.
`label_domains`	Option to label domains or not.
`label_size`	Size of the text used for labels.
`show.legend`	Option to include legend in this layer
`type`	Can change to show other protein features

Value

A ggplot2 object either in the plot window or as an object with an additional geom_rect layer.

Examples

# combines with draw_chains to plot chains and domains.
data("five_rel_data")
p <- draw_canvas(five_rel_data)
p <- draw_chains(p, five_rel_data, label_size = 1.25)
draw_domains(p, five_rel_data)

# combines with draw_chains to plot chains and domains.
data("five_rel_data")
p <- draw_canvas(five_rel_data)
p <- draw_chains(p, five_rel_data, label_size = 1.25)
draw_domains(p, five_rel_data)

Add regions to ggplot object: alpha-helixes, beta-strands and turns.

Description

draw_folding adds alpha-helixes, beta-strands and turns to the ggplot2 object created by draw_chains. It uses the data object. The ggplot2 function geom_rect is used to draw parts of the protein chain which has alpha-helixes, beta-strands and turns proportional to the number of amino acids (length).

Usage

draw_folding(p, data = data,
show.legend = TRUE,show_strand = TRUE,show_helix = TRUE, show_turn = TRUE)
draw_folding(p, data = data,
show.legend = TRUE,show_strand = TRUE,show_helix = TRUE, show_turn = TRUE)

Arguments

`p`	ggplot2 object ideally created with `draw_canvas`.
`data`	Dataframe of one or more rows with the following column names: 'type', 'description', 'begin', 'end', 'length', 'accession', 'entryName', 'taxid', 'order'. Uses STRAND, HELIX and TURN type to indicate these parts of the proteins.
`show.legend`	Option to include legend in this layer
`show_strand`	Option to show STRAND in this layer
`show_helix`	Option to show HELIX in this layer
`show_turn`	Option to show TURN in this layer

Value

A ggplot2 object either in the plot window or as an object with an additional geom_rect layer.

Examples

# combines with draw_chains to colour chain with helicies, strands and turns.
data("five_rel_data")
p <- draw_canvas(five_rel_data)
p <- draw_chains(p, five_rel_data, label_size = 1.25)
draw_folding(p, five_rel_data)



# combines with draw_chains to colour chain with helicies, strands and turns.
data("five_rel_data")
p <- draw_canvas(five_rel_data)
p <- draw_chains(p, five_rel_data, label_size = 1.25)
draw_folding(p, five_rel_data)

Add protein motifs sites to ggplot2 object.

Description

draw_motif adds protein motifs from Uniprot to ggplot2 object created by draw_canvas and draw_chains. It uses the data object. The ggplot2 function geom_rect is used to draw each of the motifs proportional to their number of amino acids (length).

Usage

draw_motif(p, data = data, show.legend = TRUE)
draw_motif(p, data = data, show.legend = TRUE)

Arguments

`p`	ggplot2 object ideally created with `draw_canvas`.
`data`	Dataframe of one or more rows with the following column names: 'type', 'description', 'begin', 'end', 'length', 'accession', 'entryName', 'taxid', 'order'. Must contain a minimum of one "CHAIN" as data$type.
`show.legend`	Option to include legend in this layer

Value

A ggplot2 object either in the plot window or as an object with an additional geom_rect layer.

Examples

# combines with draw_chains to plot chains and motifs
data("five_rel_data")
p <- draw_canvas(five_rel_data)
p <- draw_chains(p, five_rel_data, label_size = 1.25)
draw_motif(p, five_rel_data)

# combines with draw_chains to plot chains and motifs
data("five_rel_data")
p <- draw_canvas(five_rel_data)
p <- draw_chains(p, five_rel_data, label_size = 1.25)
draw_motif(p, five_rel_data)

Add protein phosphorylation sites to ggplot2 object.

Description

draw_phospho adds phosphorylation sites to ggplot2 object created by draw_canvas and draw_chains. It uses the data object. The ggplot2 function geom_point is used to draw each of the phosphorylation sites at their location as determined by data object.

Usage

draw_phospho(p, data = data, size = 2,
         fill = "yellow", show.legend = FALSE)
draw_phospho(p, data = data, size = 2,
         fill = "yellow", show.legend = FALSE)

Arguments

`p`	ggplot2 object ideally created with `draw_canvas`.
`data`	Dataframe of one or more rows with the following column names: 'type', 'description', 'begin', 'end', 'length', 'accession', 'entryName', 'taxid', 'order'. Must contain a minimum of one "CHAIN" as data$type.
`size`	Size of the circle
`fill`	Colour of the circle.
`show.legend`	Option to include legend in this layer

Value

A ggplot2 object either in the plot window or as an object with an additional geom_point layer.

Examples

# combines will with draw_domains to plot chains and phosphorylation sites.
data("five_rel_data")
p <- draw_canvas(five_rel_data)
p <- draw_chains(p, five_rel_data, label_size = 1.25)
draw_phospho(p, five_rel_data)

# combines will with draw_domains to plot chains and phosphorylation sites.
data("five_rel_data")
p <- draw_canvas(five_rel_data)
p <- draw_chains(p, five_rel_data, label_size = 1.25)
draw_phospho(p, five_rel_data)

Add receptor domains to ggplot2 object.

Description

draw_recept_dom adds receptor domains to the ggplot2 object created by draw_chains. It uses the data object. The ggplot2 function geom_rect is used to draw each of the domain chains proportional to their number of amino acids (length).

Usage

draw_recept_dom(p, data = data, label_domains = FALSE, label_size = 4,
         show.legend = TRUE)
draw_recept_dom(p, data = data, label_domains = FALSE, label_size = 4,
         show.legend = TRUE)

Arguments

`p`	ggplot2 object ideally created with `draw_canvas`.
`data`	Dataframe of one or more rows with the following column names: 'type', 'description', 'begin', 'end', 'length', 'accession', 'entryName', 'taxid', 'order'. Uses TOPO_DOM and TRANSMEM type to plot these parts of receptors
`label_domains`	Option to label receptor domains or not.
`label_size`	Size of the text used for labels.
`show.legend`	Option to include legend in this layer

Value

A ggplot2 object either in the plot window or as an object with an additional geom_rect layer.

Examples

# combines with draw_chains to plot chains and domains.
# we like to draw receptors vertically so flip using ggplot2 functions
# scale_x_reverse and coord_flip
data("tnfs_data")
p <- draw_canvas(tnfs_data)
p <- draw_chains(p, tnfs_data, label_size = 1.25)
draw_recept_dom(p, tnfs_data) + ggplot2::scale_x_reverse() +
ggplot2::coord_flip()

# combines with draw_chains to plot chains and domains.
# we like to draw receptors vertically so flip using ggplot2 functions
# scale_x_reverse and coord_flip
data("tnfs_data")
p <- draw_canvas(tnfs_data)
p <- draw_chains(p, tnfs_data, label_size = 1.25)
draw_recept_dom(p, tnfs_data) + ggplot2::scale_x_reverse() +
ggplot2::coord_flip()

Add protein region sites to ggplot2 object.

Description

draw_regions adds protein regions from Uniprot to ggplot2 object created by draw_canvas draw_chains. It uses the data object. The ggplot2 function geom_rect is used to draw each of the regions proportional to their number of amino acids (length).

Usage

draw_regions(p, data = data, show.legend=TRUE)
draw_regions(p, data = data, show.legend=TRUE)

Arguments

`p`	ggplot2 object ideally created with `draw_canvas`.
`data`	Dataframe of one or more rows with the following column names: 'type', 'description', 'begin', 'end', 'length', 'accession', 'entryName', 'taxid', 'order'. Must contain a minimum of one "CHAIN" as data$type.
`show.legend`	Option to include legend in this layer

Value

A ggplot2 object either in the plot window or as an object with an additional geom_rect layer.

Examples

# combines with draw_chains to plot chains and regions.
data("five_rel_data")
p <- draw_canvas(five_rel_data)
p <- draw_chains(p, five_rel_data, label_size = 1.25)
draw_regions(p, five_rel_data)

# combines with draw_chains to plot chains and regions.
data("five_rel_data")
p <- draw_canvas(five_rel_data)
p <- draw_chains(p, five_rel_data, label_size = 1.25)
draw_regions(p, five_rel_data)

Add protein repeats sites to ggplot2 object.

Description

draw_repeat adds protein repeats from Uniprot to ggplot2 object created by draw_canvas and draw_chains. It uses the data object. The ggplot2 function geom_rect is used to draw each of the motifs proportional to their number of amino acids (length).

Usage

draw_repeat(p, data = data, label_size = 2, outline = "dimgrey",
            fill = "dimgrey", label_repeats = TRUE, show.legend = TRUE)
draw_repeat(p, data = data, label_size = 2, outline = "dimgrey",
            fill = "dimgrey", label_repeats = TRUE, show.legend = TRUE)

Arguments

`p`	ggplot2 object ideally created with `draw_canvas`.
`data`	Dataframe of one or more rows with the following column names: 'type', 'description', 'begin', 'end', 'length', 'accession', 'entryName', 'taxid', 'order'. Must contain a minimum of one "CHAIN" as data$type.
`label_size`	Size of text used for labels of protein repeats.
`outline`	Colour of the outline of each repeat.
`fill`	Colour of the fill of each repeat.
`label_repeats`	Option to label repeats or not.
`show.legend`	Option to include legend in this layer

Value

A ggplot2 object either in the plot window or as an object with an additional geom_rect layer.

Examples

# combines with draw_chains to plot chains and repeats.
data("five_rel_data")
p <- draw_canvas(five_rel_data)
p <- draw_chains(p, five_rel_data, label_size = 1.25)
draw_repeat(p, five_rel_data)


# combines with draw_chains to plot chains and repeats.
data("five_rel_data")
p <- draw_canvas(five_rel_data)
p <- draw_chains(p, five_rel_data, label_size = 1.25)
draw_repeat(p, five_rel_data)

drawProteins.

Description

This package has been created to allow the visualisation of protein schematics based on the data obtained from the [Uniprot Protein Database](http://www.uniprot.org/).

Create a dataframe of protein features from JSON object (List of 6)

Description

Converts the list of 6 JSON object created by getting the features from UniProt. Used in the feature_to_dataframe(). Does not give order. Does not operate on List of lists - just the list of 6.

Usage

extract_feat_acc(features_list)
extract_feat_acc(features_list)

Arguments

features_list

A JSON object - list of 6 with features inside. Created as one of the lists in the list of lists by the get_features() function.

Value

A dataframe with features: "type", "description", "begin", "end" and adds accession, entryName and taxid for each row.

Examples

data("five_rel_list")
one_protein_features <- extract_feat_acc(five_rel_list[[1]])
head(one_protein_features)

data("five_rel_list")
one_protein_features <- extract_feat_acc(five_rel_list[[1]])
head(one_protein_features)

Extract protein names into a list

Description

Extracts protein names from JSON object produced by a search of Uniprot with a single protein asking for all the information. The search produces a Large list that contains all the Uniprot information about a protein.

Usage

extract_names(protein_json)
extract_names(protein_json)

Arguments

protein_json

A JSON object from a search with 14 primary parts

Value

A List of 6 with "accession", "name", "protein.recommendedName.fullName", gene.name.primary, gene.name.synonym and organism.name.scientific

Examples

# using internal data
data("protein_json")
prot_names <- extract_names(protein_json)
# generates a list of 6

## Not run: 
# access the Uniprot Protein API
uniprot_acc <- c("Q04206")  # change this for your fav protein
# Get UniProt entry by accession
acc_uniprot_url <-
    c("https://www.ebi.ac.uk/proteins/api/proteins?accession=")
comb_acc_api <- paste0(acc_uniprot_url, uniprot_acc)
# basic function is GET() which accesses the API
# requires internet access
protein <- httr::GET(comb_acc_api, accept_json())
status_code(protein)  # returns a 200 means it worked
# use content() function from httr to give us a list
protein_json <- httr::content(protein) # gives a Large list
# with 14 primary parts and lots of bits inside
# function from my package to extract names of protein
names <- extract_names(protein_json)

## End(Not run)

# using internal data
data("protein_json")
prot_names <- extract_names(protein_json)
# generates a list of 6

## Not run: 
# access the Uniprot Protein API
uniprot_acc <- c("Q04206")  # change this for your fav protein
# Get UniProt entry by accession
acc_uniprot_url <-
    c("https://www.ebi.ac.uk/proteins/api/proteins?accession=")
comb_acc_api <- paste0(acc_uniprot_url, uniprot_acc)
# basic function is GET() which accesses the API
# requires internet access
protein <- httr::GET(comb_acc_api, accept_json())
status_code(protein)  # returns a 200 means it worked
# use content() function from httr to give us a list
protein_json <- httr::content(protein) # gives a Large list
# with 14 primary parts and lots of bits inside
# function from my package to extract names of protein
names <- extract_names(protein_json)

## End(Not run)

Create a new dataframe of protein features from dataframe with multiple transcripts separated so that each transcript is drawn separtely with only the appropriate features.

Description

This function works on the object returned by the get_features() function. It creates a data.frame of features and includes the accession number AND an order number. It uses the extract_feat_acc function

Usage

extract_transcripts(data)
extract_transcripts(data)

Arguments

data

Value

A dataframe with extra rows if there were multiple transcripts present. Extra transcripts will have an order at the end of the object Each new row should have 9 variables including type, description, begin, end, length, accession, entryName, taxid and order for plotting.

Examples

data(five_rel_data)
new_data <- extract_transcripts(five_rel_data)
# because there are two entries with two transcripts
max(new_data$order) # should now be 7...

data(five_rel_data)
new_data <- extract_transcripts(five_rel_data)
# because there are two entries with two transcripts
max(new_data$order) # should now be 7...

Create a dataframe of protein features from JSON object

Description

Usage

feature_to_dataframe(features_in_lists_of_six)
feature_to_dataframe(features_in_lists_of_six)

Arguments

features_in_lists_of_six

A list of lists returned by get_features() The number of lists corresponds to the number of accession numbers queried using get_features. The list of 6 contains protein names and features.

Value

A dataframe with 9 variables including type, description, begin, end, length, accession, entryName, taxid and order for plotting.

Examples

data("rel_json")
rel_data <- feature_to_dataframe(rel_json)
head(rel_data)

data("five_rel_list")
prot_data <- feature_to_dataframe(five_rel_list)
head(prot_data)

data("rel_json")
rel_data <- feature_to_dataframe(rel_json)
head(rel_data)

data("five_rel_list")
prot_data <- feature_to_dataframe(five_rel_list)
head(prot_data)

Dataframe features of 5 human NFkappaB proteins Uniprot on 1 Nov 2017

Description

Dataframe features of 5 human NFkappaB proteins Uniprot on 1 Nov 2017

Usage

five_rel_data
five_rel_data

Format

A data frame with 320 rows and 9 variables:

type: type of features - e.g. chain
description: long name for the protein
begin: starting position (amino acid number) of feature
end: ending position (amino acid number) of feature
length: length of feature - number of amino acids
accession: protein Uniprot accession number
entryName: protein Uniprot entry Name
taxid: taxonomic identification - species
order: plotting order from the bottom of the graph

Value

A data frame with 320 rows and 9 variables

Source

Uniprot http://www.uniprot.org Accession numbers Q04206 Q01201 Q04864 P19838 Q00653

Features of five human Rel A proteins

Description

List of features from five human NFkappaB proteins downloaded from Uniprot on 15 August 2017

Usage

five_rel_list
five_rel_list

Format

Large List of 5 elements - one element for each protein

Value

Large List of 5 elements - one element for each protein

Source

Uniprot http://www.uniprot.org Accession numbers Q04206 Q01201 Q04864 P19838 Q00653

GET features of protein(s) from UniProt API

Description

This function creates the URL required to query the UniProt API and returns the features of the protein or proteins in JSON format. It uses the GET() function from the httr package.

Usage

get_features(proteins_acc)
get_features(proteins_acc)

Arguments

proteins_acc

A vector of length 1 with one or more UniProt accession numbers separated by spaces.

Value

If there is internet access and the UniProt accession numbers are good, the function will return a list of lists. The list will be of length equivalent to the number of Uniprot accession numbers supplied. The lists inside will be of length 6 and will contain information about the proteins and the features.

Examples

# Requires internet access
prot_data <- get_features("Q04206 Q01201 Q04864 P19838 Q00653")

# Requires internet access
prot_data <- get_features("Q04206 Q01201 Q04864 P19838 Q00653")

Reformat file or url in gff format to allow to draw

Description

parse_gff loads a file or downloads from an url if provided protein information that is then changed to allow it to work with draw_canvas and other draw functions in drawProteins.

Usage

parse_gff(file_or_link)
parse_gff(file_or_link)

Arguments

file_or_link

link in gff format or a file in gff format that can be read by read_tsv function from the readr package.

Value

Dataframe of one or more rows with the following column names: 'accession', 'source', 'type', 'begin', 'end', 'order', 'entryName', 'description'. Must contain a minimum of one "CHAIN" as data$type to allow plotting.

Examples

data <- parse_gff("https://www.uniprot.org/uniprot/Q04206.gff")

data <- parse_gff("https://www.uniprot.org/uniprot/Q04206.gff")

Create a dataframe of protein features from JSON object

Description

Reduces data.frame of features to just phosphorylation sites. Uses a subsetting step and a grep with the pattern "Phospho".

Usage

phospho_site_info(features)
phospho_site_info(features)

Arguments

features

A dataframe of protein features, for example created by the feature_to_dataframe() function.

Value

A dataframe that only contains protein phosphorylation sites from Uniprot

Examples

data("five_rel_data")
sites <- phospho_site_info(five_rel_data)
head(sites)


data("five_rel_data")
sites <- phospho_site_info(five_rel_data)
head(sites)

Uniprot infor human Rel A protein in JSON format

Description

Large list (968.8 Kb) of information about human Rel A downloaded from Uniprot on 1 November 2017

Usage

protein_json
protein_json

Format

List of 1 with List of 14 inside

Value

List of 6 - information necessary to draw Rel A/p65

Source

http://www.uniprot.org/uniprot/Q04206

Features of human Rel A protein

Description

List of features from human Rel A downloaded from Uniprot on 15 August 2017

Usage

rel_A_features
rel_A_features

Format

List of 6 - information necessary to draw Rel A/p65

Value

List of 6 - information necessary to draw Rel A/p65

Source

http://www.uniprot.org/uniprot/Q04206

Human Rel A protein features in JSON format

Description

List of 1 with List of 6 inside downloaded from Uniprot on 1 November 2017

Usage

rel_json
rel_json

Format

List of 1 with List of 6 - information necessary to draw Rel A/p65

Value

List of 1 with List of 6 - information necessary to draw Rel A/p65

Source

http://www.uniprot.org/uniprot/Q04206

Dataframe features of 2 human TNF receptors from Uniprot on 3 Jan 2018

Description

Dataframe features of 2 human TNF receptors from Uniprot on 3 Jan 2018

Usage

tnfs_data
tnfs_data

Format

A data frame with 127 rows of 9 variables:

type: type of features - e.g. chain
description: long name for the protein
begin: starting position (amino acid number) of feature
end: ending position (amino acid number) of feature
length: length of feature - number of amino acids
accession: protein Uniprot accession number
entryName: protein Uniprot entry Name
taxid: taxonomic identification - species
order: plotting order from the bottom of the graph

Value

A data frame with 127 rows and 9 variables

Source

Uniprot http://www.uniprot.org Accession numbers P19438 P25942

Package 'drawProteins'

Help Index

Create ggplot2 object with protein chains from feature database

Description

Usage

Arguments

Value

Examples

Create ggplot2 object with protein chains from feature database

Description

Usage

Arguments

Value

Examples

Add protein domains to ggplot2 object.

Description

Usage

Arguments

Value

Examples

Add regions to ggplot object: alpha-helixes, beta-strands and turns.

Description

Usage

Arguments

Value

Examples

Add protein motifs sites to ggplot2 object.

Description

Usage

Arguments

Value

Examples

Add protein phosphorylation sites to ggplot2 object.

Description

Usage

Arguments

Value

Examples

Add receptor domains to ggplot2 object.

Description

Usage

Arguments

Value

Examples

Add protein region sites to ggplot2 object.

Description

Usage

Arguments

Value

Examples

Add protein repeats sites to ggplot2 object.

Description

Usage

Arguments

Value

Examples

drawProteins.

Description

Create a dataframe of protein features from JSON object (List of 6)

Description

Usage

Arguments

Value

Examples

Extract protein names into a list

Description

Usage

Arguments

Value

Examples

Create a new dataframe of protein features from dataframe with multiple transcripts separated so that each transcript is drawn separtely with only the appropriate features.

Description

Usage

Arguments

Value

Examples

Create a dataframe of protein features from JSON object

Description

Usage

Arguments