Package 'KEGGlincs' reference manual

Title:	Visualize all edges within a KEGG pathway and overlay LINCS data
Description:	See what is going on 'under the hood' of KEGG pathways by explicitly re-creating the pathway maps from information obtained from KGML files.
Authors:	Shana White
Maintainer:	Shana White <[email protected]>, Mario Medvedovic <[email protected]>
License:	GPL-3
Version:	1.33.0
Built:	2024-10-31 06:24:37 UTC
Source:	https://github.com/bioc/KEGGlincs

Annotate KEGG edge mappings with user data

Description

Add data column[s] to object created from function expand_KEGG_edges

Usage

add_edge_data(expanded_edges, KEGG_mappings, user_data,
  data_column_no = 3, map_type = "SYMBOL", only_mapped = TRUE)
add_edge_data(expanded_edges, KEGG_mappings, user_data,
  data_column_no = 3, map_type = "SYMBOL", only_mapped = TRUE)

Arguments

`expanded_edges`	The data frame object generated via the function expand_KEGG_edges
`KEGG_mappings`	KEGG_mappings The data.frame object generated by the function expand_KEGG_mappings
`user_data`	A data frame where in which the first two columns contain gene symbols representing an edge and any/all other column[s] contain corresponding edge data.
`data_column_no`	The column index for desired user data to be added
`map_type`	If the genes in your data set are left untranslated set to "NUMBER" (assuming numbers are gene accession numbers)
`only_mapped`	A logical indicator; if set to FALSE will return 'de-novo' edges that 'exist' in data but are not documented in KEGG

Value

A data frame object with detailed KEGG edge mappings annotated with user data

Examples

p53_KGML <- get_KGML('hsa04115')
p53_KEGG_mappings <- expand_KEGG_mappings(p53_KGML)
p53_edges <- expand_KEGG_edges(p53_KGML, p53_KEGG_mappings)
p53_HA1E_data <- overlap_info(p53_KGML, p53_KEGG_mappings, 'HA1E', 
                               data_type = '100_bing', only_mapped = FALSE)
                               
p53_edges_HA1E <- add_edge_data(p53_edges, p53_KEGG_mappings, 
                                        p53_HA1E_data, c(3, 10,12))
p53_KGML <- get_KGML('hsa04115')
p53_KEGG_mappings <- expand_KEGG_mappings(p53_KGML)
p53_edges <- expand_KEGG_edges(p53_KGML, p53_KEGG_mappings)
p53_HA1E_data <- overlap_info(p53_KGML, p53_KEGG_mappings, 'HA1E', 
                               data_type = '100_bing', only_mapped = FALSE)
                               
p53_edges_HA1E <- add_edge_data(p53_edges, p53_KEGG_mappings, 
                                        p53_HA1E_data, c(3, 10,12))

Send graph to Cytoscape via CyREST

Description

View the KEGG pathway in Cytoscape. With either the 'expanded edges' or 'stacked nodes' layout, users can visualize and interact with the graphs [strictly] as they are documented in the most recent KGML available from KEGG. This function is a modified version of the function send2cy(), which is part of the cyREST utility functions.

Usage

cyto_vis(graph_object, title = "Cytoscape Graph Window",
  edge_width_attribute = "summary_score", port.number = 1234)
cyto_vis(graph_object, title = "Cytoscape Graph Window",
  edge_width_attribute = "summary_score", port.number = 1234)

Arguments

`graph_object`	An igraph object such as the one generated by the function `get_graph_object`
`title`	An optional title for the graph when it is in Cytoscape
`edge_width_attribute`	The attribute that will be used for edge width; if data is not added or the attribute is not part of the graphing information, the edge width will default to 1.
`port.number`	The port address for Cytoscape

Value

A dynamic map in Cytoscape automatically formatted for convenient viewing.

Examples

p53_KGML <- get_KGML("hsa04115")
p53_KEGG_mappings <- expand_KEGG_mappings(p53_KGML, FALSE)
nodes <- node_mapping_info(p53_KEGG_mappings)

p53_edges <- expand_KEGG_edges(p53_KGML, p53_KEGG_mappings)
edges <- edge_mapping_info(p53_edges) 

p53_graph_object <- get_graph_object(nodes, edges)
                                      
## Not run: 
cyto_vis(p53_graph_object, "Default p53 Graph [no data added]")

#Workflow to visualize graph with data-dependent attributes:

p53_KGML <- get_KGML("hsa04115")
p53_KEGG_mappings <- expand_KEGG_mappings(p53_KGML)
nodes <- node_mapping_info(p53_KEGG_mappings)

p53_edges <- expand_KEGG_edges(p53_KGML, p53_KEGG_mappings)

p53_HA1E_data <- overlap_info(p53_KGML, p53_KEGG_mappings, "HA1E", 
                               data_type = "100_bing")
p53_edges_plus_data <- add_edge_data(p53_edges, p53_KEGG_mappings, 
                                      p53_HA1E_data, c(3, 10,12),
                                      only_mapped = TRUE)

edges <- edge_mapping_info(p53_edges_plus_data, data_added = TRUE)
                                            
p53_plus_data_graph_object <- get_graph_object(nodes, edges)
                                                
cyto_vis(p53_plus_data_graph_object, "p53 Graph: Mapped Edges + HA1E Data",
         edge_width_attribute = "UP")
         
## End(Not run)
p53_KGML <- get_KGML("hsa04115")
p53_KEGG_mappings <- expand_KEGG_mappings(p53_KGML, FALSE)
nodes <- node_mapping_info(p53_KEGG_mappings)

p53_edges <- expand_KEGG_edges(p53_KGML, p53_KEGG_mappings)
edges <- edge_mapping_info(p53_edges) 

p53_graph_object <- get_graph_object(nodes, edges)
                                      
## Not run: 
cyto_vis(p53_graph_object, "Default p53 Graph [no data added]")

#Workflow to visualize graph with data-dependent attributes:

p53_KGML <- get_KGML("hsa04115")
p53_KEGG_mappings <- expand_KEGG_mappings(p53_KGML)
nodes <- node_mapping_info(p53_KEGG_mappings)

p53_edges <- expand_KEGG_edges(p53_KGML, p53_KEGG_mappings)

p53_HA1E_data <- overlap_info(p53_KGML, p53_KEGG_mappings, "HA1E", 
                               data_type = "100_bing")
p53_edges_plus_data <- add_edge_data(p53_edges, p53_KEGG_mappings, 
                                      p53_HA1E_data, c(3, 10,12),
                                      only_mapped = TRUE)

edges <- edge_mapping_info(p53_edges_plus_data, data_added = TRUE)
                                            
p53_plus_data_graph_object <- get_graph_object(nodes, edges)
                                                
cyto_vis(p53_plus_data_graph_object, "p53 Graph: Mapped Edges + HA1E Data",
         edge_width_attribute = "UP")
         
## End(Not run)

Prepare edges for mapping

Description

Modify the mapping information for desired look when graphed in Cytoscape

Usage

edge_mapping_info(expanded_edges, data_added = FALSE,
  significance_markup = FALSE, tidy_edge = TRUE)
edge_mapping_info(expanded_edges, data_added = FALSE,
  significance_markup = FALSE, tidy_edge = TRUE)

Arguments

`expanded_edges`	The data frame object generated via the function expand_KEGG_edges() OR has been modified by the function add_edge_data()
`data_added`	A logical indicator; must be set to TRUE if user data has been added (i.e. edges modified by function add_edge_data())
`significance_markup`	A logical indicator; if set to TRUE will color edges based on direction and significance of correlation (as determined by user-data-analysis)
`tidy_edge`	A logical indicator; must be set to FALSE for expanded edges

Value

A data.frame object for edges that will be passed on to the function get_graph_object

Examples

p53_KGML <- get_KGML("hsa04115")
p53_KEGG_mappings <- expand_KEGG_mappings(p53_KGML)

#Default; no data added to edges:

p53_edges <- expand_KEGG_edges(p53_KGML, p53_KEGG_mappings)
p53_edge_mapping_info <- edge_mapping_info(p53_edges) 

#If data is added to edges as additional attribute[s]:

p53_HA1E_data <- overlap_info(p53_KGML, p53_KEGG_mappings, 
                               "HA1E", data_type = "100_bing")

p53_edges_HA1E_data_MAPPED <- add_edge_data(p53_edges, p53_KEGG_mappings, 
                                            p53_HA1E_data, 
                                            data_column_no = c(3, 10,12),
                                            only_mapped = TRUE)
                                               
p53_edge_mapping_HA1E <- edge_mapping_info(p53_edges_HA1E_data_MAPPED, 
                                                      data_added = TRUE)
                                                      
p53_KGML <- get_KGML("hsa04115")
p53_KEGG_mappings <- expand_KEGG_mappings(p53_KGML)

#Default; no data added to edges:

p53_edges <- expand_KEGG_edges(p53_KGML, p53_KEGG_mappings)
p53_edge_mapping_info <- edge_mapping_info(p53_edges) 

#If data is added to edges as additional attribute[s]:

p53_HA1E_data <- overlap_info(p53_KGML, p53_KEGG_mappings, 
                               "HA1E", data_type = "100_bing")

p53_edges_HA1E_data_MAPPED <- add_edge_data(p53_edges, p53_KEGG_mappings, 
                                            p53_HA1E_data, 
                                            data_column_no = c(3, 10,12),
                                            only_mapped = TRUE)
                                               
p53_edge_mapping_HA1E <- edge_mapping_info(p53_edges_HA1E_data_MAPPED, 
                                                      data_added = TRUE)

Get detailed KEGG mapping information for each relation [edge] documented in KEGG

Description

Extract relationship information from KGML object and re-map based on normalized node information

Usage

expand_KEGG_edges(KGML_file, KEGG_mappings)
expand_KEGG_edges(KGML_file, KEGG_mappings)

Arguments

`KGML_file`	An object of formal class KEGGPathway
`KEGG_mappings`	The data.frame object generated by the function expand_KEGG_mappings

Value

A dataframe object with unique entry information for all edges documented in the KEGG pathway. Note that each row has a unique combination of values for (entry1, entry2, entry1symbol, entry2symbol).

Examples

p53_KGML <- get_KGML("hsa04115")
p53_KEGG_mappings <- expand_KEGG_mappings(p53_KGML, FALSE)
p53_edges <- expand_KEGG_edges(p53_KGML, p53_KEGG_mappings)
p53_KGML <- get_KGML("hsa04115")
p53_KEGG_mappings <- expand_KEGG_mappings(p53_KGML, FALSE)
p53_edges <- expand_KEGG_edges(p53_KGML, p53_KEGG_mappings)

Get detailed KEGG mapping information for each map entity

Description

Extract mapping information from KGML object and normalize mappings based on multi-valued name attribute

Usage

expand_KEGG_mappings(KGML_file, convert_KEGG_IDs = TRUE)
expand_KEGG_mappings(KGML_file, convert_KEGG_IDs = TRUE)

Arguments

KGML_file

An object of formal class KEGGPathway

convert_KEGG_IDs

A logical indicator; if set to FALSE will run faster however genes and compounds will remain labeled via KEGG codes (compounds) or accession numbers (genes). This option must be taken into account if data is being added. For example, the genes in 'KO_data' are identified by symbols, thus it is neccessary to retain the default option to convert IDs to symbols when planning to add edge data of this type.

Value

A dataframe object with unique entry information for all [node] objects documented in the KEGG pathway. Note that if mutiple objects (i.e. genes or compounds) have the same entryID, this indicates that they share the same node [location] in the pathway.

Examples

p53_KGML <- get_KGML("hsa04115")
p53_KEGG_mappings <-  expand_KEGG_mappings(p53_KGML, FALSE)
p53_KGML <- get_KGML("hsa04115")
p53_KEGG_mappings <-  expand_KEGG_mappings(p53_KGML, FALSE)

The 'boilerplate' for this package's desired graph style

Description

Generates an object that can be converted to a JSON file and subsequently applied to the graph for the markup specified by this package and the layout mirroring KEGG. Intended for use within cyto_vis

Usage

generate_mappings(style_name, map_edge_width, edge_width_attribute,
  min_score, max_score)
generate_mappings(style_name, map_edge_width, edge_width_attribute,
  min_score, max_score)

Arguments

`style_name`	An argument to name style; when used inside of `cyto_vis` no name is needed
`map_edge_width`	A logical indicator; if FALSE no continuous mapping of edge width will be applied
`edge_width_attribute`	The attribute that will be used for edge width; if data is not added or the attribute is not part of the graphing information, the edge width will default to 1.
`min_score`	The minimum attribute value for the column used to map edge width
`max_score`	The maximum attribute value for the column used to map edge width

Value

A list that can be converted to a JSON file to apply desired style/layout in Cytoscape

Examples

style.name = "myKEGGstyle"
mappings <- generate_mappings(style.name, FALSE)
style.name = "myKEGGstyle"
mappings <- generate_mappings(style.name, FALSE)

Perform Fisher's Exact test for edges in pathway

Description

Obtain a measure for strength and significance for the relationship (i.e. an edge) based on the concordance/discordance of UP-and-DOWN regulated genes shared by two different experimental gene-knockouts Intended for use within overlap_info

Usage

get_fisher_info(edges, method)
get_fisher_info(edges, method)

Arguments

`edges`	The set of eges to be analyzed; Although the intended use is for LINCS data overlaps, the function should work with any typical data object as long as it has columns labeled ("UP", "DOWN", "UK1_DK2", "DK1_UK2") that contain integer values.
`method`	The method to correct/adjust p-values for multiple testing. For available methods, type 'p.adjust.methods' into command promt and press enter.

Value

The input edge data.frame object with additional columns containing the results of the applied statistical test

Examples

ex.data <- data.frame("UP" = c(70,6), "DOWN" = c(8,20),
                    "UK1_DK2" = c(4,47), "DK1_UK2" = c(3, 28))

overlaps <- get_fisher_info(ex.data, method = "BH")
ex.data <- data.frame("UP" = c(70,6), "DOWN" = c(8,20),
                    "UK1_DK2" = c(4,47), "DK1_UK2" = c(3, 28))

overlaps <- get_fisher_info(ex.data, method = "BH")

Generate graph object from nodes and edges

Description

Obtain a graph object in the form of an igraph with KEGG-specific graphical information

Usage

get_graph_object(node_mapping_info, expanded_edges,
  layered_nodes = FALSE)
get_graph_object(node_mapping_info, expanded_edges,
  layered_nodes = FALSE)

Arguments

`node_mapping_info`	The data.frame object generated by the function node_mapping_info()
`expanded_edges`	The data.frame object generated by the function edge_mapping_info()
`layered_nodes`	A logical indicator; if set to TRUE will create a graph with 'stacked' nodes that the user can manipulate when multiple nodes are mapped to one location

Value

A list object with the node and edge information from the graph required for mapping.

Examples


p53_KGML <- get_KGML("hsa04115")
p53_KEGG_mappings <-  expand_KEGG_mappings(p53_KGML)

p53_node_mapping_info <- node_mapping_info(p53_KEGG_mappings)
p53_edge_mapping_info <- expand_KEGG_edges(p53_KGML, p53_KEGG_mappings)

#Default graph object will have 'expanded edges':
expanded_edges_graph_object <- get_graph_object(p53_node_mapping_info, 
                                                p53_edge_mapping_info)

#Graph with layered nodes:
layered_nodes_graph_object <- get_graph_object(p53_node_mapping_info,
                                               p53_edge_mapping_info, 
                                               layered_nodes = TRUE)
p53_KGML <- get_KGML("hsa04115")
p53_KEGG_mappings <-  expand_KEGG_mappings(p53_KGML)

p53_node_mapping_info <- node_mapping_info(p53_KEGG_mappings)
p53_edge_mapping_info <- expand_KEGG_edges(p53_KGML, p53_KEGG_mappings)

#Default graph object will have 'expanded edges':
expanded_edges_graph_object <- get_graph_object(p53_node_mapping_info, 
                                                p53_edge_mapping_info)

#Graph with layered nodes:
layered_nodes_graph_object <- get_graph_object(p53_node_mapping_info,
                                               p53_edge_mapping_info, 
                                               layered_nodes = TRUE)

Download and parse KGML file

Description

Download and parse KGML file

Usage

get_KGML(pathwayid, get_if_no_edges = FALSE)
get_KGML(pathwayid, get_if_no_edges = FALSE)

Arguments

`pathwayid`	A KEGG pathway ID of the form "hsa12345" (only human pathways currently)
`get_if_no_edges`	A logical indicator; if pathway has no edges returns null value if set to TRUE

Value

an object of Formal class KEGGPathway

Examples

mtor_KGML <- get_KGML("hsa04150")

# Some pathways contain only node information; since the purpose of this
# package is to explore pathways in an edge-focused manner, the default
# options return a warning message instead of a parsed KGML file if the 
# input pathway has no edges.
ribosome_KGML <- get_KGML("hsa03020") 
ribosome_KGML <- get_KGML("hsa03020", get_if_no_edges = TRUE) 

mtor_KGML <- get_KGML("hsa04150")

# Some pathways contain only node information; since the purpose of this
# package is to explore pathways in an edge-focused manner, the default
# options return a warning message instead of a parsed KGML file if the 
# input pathway has no edges.
ribosome_KGML <- get_KGML("hsa03020") 
ribosome_KGML <- get_KGML("hsa03020", get_if_no_edges = TRUE)

Combines all other package functions for one-step pathway visualization

Description

Combines all other package functions for one-step pathway visualization

Usage

KEGG_lincs(pathwayid, cell_line = NA, refine_by_cell_line = NA,
  add_L1000_edge_data = TRUE, significance_markup = TRUE,
  data_type = "100_full", pert_time = 96, only_mapped = TRUE,
  layered_nodes = FALSE, graph_title = "default", get_data = FALSE,
  convert_KEGG_IDs = TRUE, tidy_edge = FALSE)
KEGG_lincs(pathwayid, cell_line = NA, refine_by_cell_line = NA,
  add_L1000_edge_data = TRUE, significance_markup = TRUE,
  data_type = "100_full", pert_time = 96, only_mapped = TRUE,
  layered_nodes = FALSE, graph_title = "default", get_data = FALSE,
  convert_KEGG_IDs = TRUE, tidy_edge = FALSE)

Arguments

`pathwayid`	A KEGG pathway ID of the form "hsa12345" (only human pathways currently)
`cell_line`	If left as NA will generate a pathway map without data-dependent attributes (such as edge width). To use in combination with LINCS data, choose from the set of cell lines: (A375,A549,ASC,HA1E,HCC515,HEK293T,HEKTE,HEPG2,HT29,MCF7,NCIH716,NPC,PC3, SHSY5Y,SKL,SW480,VCAP)
`refine_by_cell_line`	A logical indicator
`add_L1000_edge_data`	A logical indicator
`significance_markup`	A logical indicator; if set to TRUE will color edges based on direction and significance of correlation (as determined by user-data-analysis)
`data_type`	Choose from data types: (100_full, 100_bing, 50_lm)
`pert_time`	Choose from (6,24,48,96,120,144,168)
`only_mapped`	A logical indicator; if set to FALSE will return 'de-novo' edges that 'exist' in data but are not documented in KEGG
`layered_nodes`	A logical indicator; if set to TRUE will create a graph with 'stacked' nodes that the user can manipulate when multiple nodes are mapped to one location
`graph_title`	An optional user-specified graph title
`get_data`	A logical indicator; if set to true, will return the 'expanded' edge information for the specified pathway
`convert_KEGG_IDs`	A logical indicator; if set to TRUE KEGG compounds will remain labeled via KEGG codes (do not need KEGGREST)
`tidy_edge`	A logical indicator; must be set to FALSE for expanded edges

Value

A dynamic map in Cytoscape automatically formatted for convenient viewing and, if idicated by user, a data.frame object with detailed information for 'expanded' KEGG edges

Examples

## Not run:  

#Default KEGG pathway with colored edges representing type of relationship:
KEGG_lincs("hsa04115", convert_KEGG_IDs = FALSE)

#KEGG pathway with edge width and color based on observed experimental data:
KEGG_lincs("hsa04115", "HA1E")

#Have edge information data.frame to be output to the global environment:
p53_edge_info <- KEGG_lincs("hsa04115", graph_title = "p53"
                             convert_KEGG_IDs = FALSE, get_data = TRUE)
                             
## End(Not run)
## Not run:  

#Default KEGG pathway with colored edges representing type of relationship:
KEGG_lincs("hsa04115", convert_KEGG_IDs = FALSE)

#KEGG pathway with edge width and color based on observed experimental data:
KEGG_lincs("hsa04115", "HA1E")

#Have edge information data.frame to be output to the global environment:
p53_edge_info <- KEGG_lincs("hsa04115", graph_title = "p53"
                             convert_KEGG_IDs = FALSE, get_data = TRUE)
                             
## End(Not run)

Add in edges to map documented in other pathways

Description

For a specific pathway entity(gene), search KEGG databases to see if it has any other documented relationships in KEGG. expand_KEGG_edges

Usage

keggerize_edges(entry_accession, KGML, KEGG_mappings, edges)
keggerize_edges(entry_accession, KGML, KEGG_mappings, edges)

Arguments

`entry_accession`	The Accession # of the pathway entity to 'keggerize'
`KGML`	The KGML file of the current pathway
`KEGG_mappings`	KEGG mappings for the current pathway
`edges`	The expanded edges for the current pathway

Value

A modified expanded edges data frame with additional rows for new entries

Examples

## Not run: 
KGML <- get_KGML("hsa04150")
KEGG_mappings <- expand_KEGG_mappings(KGML)
edges <- expand_KEGG_edges(KGML, KEGG_mappings)
entry_accession <- "2475"
mtor_plus_mtor <- keggerize_edges(entry_accession = entry_accession, 
                                  KGML = KGML,KEGG_mappings = KEGG_mappings,
                                  edges = edges) 
## End(Not run)

## Not run: 
KGML <- get_KGML("hsa04150")
KEGG_mappings <- expand_KEGG_mappings(KGML)
edges <- expand_KEGG_edges(KGML, KEGG_mappings)
entry_accession <- "2475"
mtor_plus_mtor <- keggerize_edges(entry_accession = entry_accession, 
                                  KGML = KGML,KEGG_mappings = KEGG_mappings,
                                  edges = edges) 
## End(Not run)

KEGGlincs: an R package designed to explore the edges in KEGG pathways

Description

KEGGlincs: an R package designed to explore the edges in KEGG pathways

Combines all other package functions for one-step cell line comparison

Description

Combines all other package functions for one-step cell line comparison

Usage

KL_compare(pathwayid, cell_line1 = NA, cell_line2 = NA,
  refine_by_cell_line = TRUE, data_type = "100_full", pert_time = 96,
  only_mapped = TRUE, get_data = FALSE, convert_KEGG_IDs = TRUE,
  graph_title = "default", tidy_edge = TRUE, layered_nodes = FALSE)
KL_compare(pathwayid, cell_line1 = NA, cell_line2 = NA,
  refine_by_cell_line = TRUE, data_type = "100_full", pert_time = 96,
  only_mapped = TRUE, get_data = FALSE, convert_KEGG_IDs = TRUE,
  graph_title = "default", tidy_edge = TRUE, layered_nodes = FALSE)

Arguments

`pathwayid`	A KEGG pathway ID of the form "hsa12345" (only human pathways currently)
`cell_line1`	Choose from the set of cell lines: (A375,A549,ASC,HA1E,HCC515,HEK293T,HEKTE,HEPG2,HT29,MCF7,NCIH716,NPC,PC3, SHSY5Y,SKL,SW480,VCAP)
`cell_line2`	A cell line such that cell_line1 != cell_line2
`refine_by_cell_line`	A logical indicator
`data_type`	Choose from data types: (100_full, 100_bing, 50_lm)
`pert_time`	Choose from (6,24,48,96,120,144,168)
`only_mapped`	A logical indicator; if set to FALSE will return 'de-novo' edges that 'exist' in data but are not documented in KEGG
`get_data`	A logical indicator; if set to true, will return the 'expanded' edge information for the specified pathway
`convert_KEGG_IDs`	A logical indicator; if set to TRUE KEGG compounds will remain labeled via KEGG codes (do not need KEGGREST)
`graph_title`	An optional user-specified graph title
`tidy_edge`	A logical indicator; must be set to FALSE for expanded edges
`layered_nodes`	A logical indicator; if set to TRUE will create a graph with 'stacked' nodes that the user can manipulate when multiple nodes are mapped to one location

Value

A dynamic map in Cytoscape automatically formatted for convenient viewing and, if idicated by user, a data.frame object with detailed information for 'expanded' KEGG edges

Examples

## Not run:  

# Compare p53 pathway between cell lines A375 and A549:
KL_compare("hsa04115", "A375", "A549")

## End(Not run)
## Not run:  

# Compare p53 pathway between cell lines A375 and A549:
KL_compare("hsa04115", "A375", "A549")

## End(Not run)

Prepare nodes for mapping

Description

Modify the mapping information for desired look when graphed in Cytoscape

Usage

node_mapping_info(KEGG_mappings)
node_mapping_info(KEGG_mappings)

Arguments

KEGG_mappings

The data.frame object generated by the function expand_KEGG_mappings()

Value

A data.frame object for nodes that will be passed on to the function get_graph_object

Examples

p53_KGML <- get_KGML("hsa04115")
p53_KEGG_mappings <- expand_KEGG_mappings(p53_KGML, FALSE)

p53_node_mapping_info <- node_mapping_info(p53_KEGG_mappings)
p53_KGML <- get_KGML("hsa04115")
p53_KEGG_mappings <- expand_KEGG_mappings(p53_KGML, FALSE)

p53_node_mapping_info <- node_mapping_info(p53_KEGG_mappings)

Get overlap information for pairs of gene knock-outs from LINCS data

Description

Get overlap information for pairs of gene knock-outs from LINCS data

Usage

overlap_info(KGML_file, KEGG_mappings, cell_type, data_type = "100_full",
  pert_time = 96, only_mapped = TRUE, affy_based = FALSE,
  keep_counts_only = TRUE, add_fisher_information = TRUE,
  p.adjust.method = "BH")
overlap_info(KGML_file, KEGG_mappings, cell_type, data_type = "100_full",
  pert_time = 96, only_mapped = TRUE, affy_based = FALSE,
  keep_counts_only = TRUE, add_fisher_information = TRUE,
  p.adjust.method = "BH")

Arguments

`KGML_file`	An object of formal class KEGGPathway
`KEGG_mappings`	The data.frame object generated by the function expand_KEGG_mappings
`cell_type`	Choose from the set of cell lines: (A375,A549,ASC,HA1E,HCC515,HEK293T,HEKTE,HEPG2,HT29,MCF7,NCIH716,NPC,PC3, SHSY5Y,SKL,SW480,VCAP)
`data_type`	Choose from data types: (100_full, 100_bing, 50_lm)
`pert_time`	Choose from (6,24,48,96,120,144,168)
`only_mapped`	A logical indicator; if set to FALSE will return 'de-novo' edges that 'exist' in data but are not documented in KEGG
`affy_based`	A logical indicator; if set to TRUE will return lists/counts based on probeID instead of gene symbol.
`keep_counts_only`	A logical indicator; if set to FALSE will return data frame with lists [of gene symbols or probe ids] as well as counts
`add_fisher_information`	A logical indicator; by default the relationships are analyzed for strength of correlation via Fisher's Exact Test
`p.adjust.method`	For available methods, type 'p.adjust.methods' into command promt and press enter.

Value

A data frame where each row corresponds to information for pairs of experimental gene knock-outs from LINCS data (found in selected pathway).

Examples

p53_KGML <- get_KGML("hsa04115")
p53_KEGG_mappings <-  expand_KEGG_mappings(p53_KGML)
p53_edges <- expand_KEGG_edges(p53_KGML, p53_KEGG_mappings)

summary <- path_genes_by_cell_type(p53_KEGG_mappings)
p53_HA1E_data <- overlap_info(p53_KGML, p53_KEGG_mappings, 
                               "HA1E", data_type = "100_bing", 
                               only_mapped = FALSE)
p53_KGML <- get_KGML("hsa04115")
p53_KEGG_mappings <-  expand_KEGG_mappings(p53_KGML)
p53_edges <- expand_KEGG_edges(p53_KGML, p53_KEGG_mappings)

summary <- path_genes_by_cell_type(p53_KEGG_mappings)
p53_HA1E_data <- overlap_info(p53_KGML, p53_KEGG_mappings, 
                               "HA1E", data_type = "100_bing", 
                               only_mapped = FALSE)

See how many pathway gene knock-outs are available from data

Description

Check quantity of data across cell lines available from LINCS corresponding to the pathway of interest

Usage

path_genes_by_cell_type(KEGG_mappings, pert_time = 96, get_KOs = FALSE,
  generate_plot = TRUE)
path_genes_by_cell_type(KEGG_mappings, pert_time = 96, get_KOs = FALSE,
  generate_plot = TRUE)

Arguments

`KEGG_mappings`	KEGG_mappings The data.frame object generated by the function expand_KEGG_mappings
`pert_time`	Choose from (6,24,48,96,120,144,168)
`get_KOs`	Logical indicator to have data frame returned
`generate_plot`	Logical indicator to generate histogram

Value

A plot depicting percentage of pathway genes knocked-out by cell line and a data frame object listing the genes [by cell line]

Examples

p53_KGML <- get_KGML("hsa04115")
p53_KEGG_mappings <- expand_KEGG_mappings(p53_KGML)

path_genes_by_cell_type(p53_KEGG_mappings)
p53_KGML <- get_KGML("hsa04115")
p53_KEGG_mappings <- expand_KEGG_mappings(p53_KGML)

path_genes_by_cell_type(p53_KEGG_mappings)

Refine pathway by cell type

Description

Reduce the KEGG pathway by only including genes that are expressed within a given cell type

Usage

refine_mappings(KEGG_mappings, cell_line)
refine_mappings(KEGG_mappings, cell_line)

Arguments

`KEGG_mappings`	The data.frame object generated by the function expand_KEGG_mappings
`cell_line`	Choose from the set of cell lines with baseline data; cell-lines may or may not have corresponding KO data

Value

A dataframe object with reduced set of pathway mappings to be passed on to other functions

Examples

p53_KGML <- get_KGML("hsa04115")
p53_KEGG_mappings <-  expand_KEGG_mappings(p53_KGML)
MCF7_p53_mappings <- refine_mappings(p53_KEGG_mappings, "MCF7")
p53_KGML <- get_KGML("hsa04115")
p53_KEGG_mappings <-  expand_KEGG_mappings(p53_KGML)
MCF7_p53_mappings <- refine_mappings(p53_KEGG_mappings, "MCF7")

Tidy up pathway by combining edges inside of edge_mapping_info

Description

Combine edges that share nodes and have other commonalities

Usage

tidy_edge(edges, edge_id, data_added = FALSE, by_significance = FALSE,
  by_number = TRUE)
tidy_edge(edges, edge_id, data_added = FALSE, by_significance = FALSE,
  by_number = TRUE)

Arguments

`edges`	The edge dataframe
`edge_id`	The numeric value for the edge_id
`data_added`	A logical indicator; set to TRUE if data is added
`by_significance`	A logical indicator; option if data is added
`by_number`	A logical indicator; gives rough estimate of edge amount

Value

A data frame that has had the given edge condensed for viewing

Examples

## Not run: 
if (tidy_edge == TRUE) {
   edge_IDs <- seq(min(expanded_edges$edgeID), max(expanded_edges$edgeID))
   for (i in edge_IDs){
     if(data_added == TRUE){
       expanded_edges <- tidy_edge(edges = expanded_edges,
                                   edge_id = edge_IDs[i], 
                                   data_added = TRUE,
                                   by_significance = TRUE)
     }
     if(data_added == FALSE){
       expanded_edges <- tidy_edge(edges = expanded_edges,
                                   edge_id = edge_IDs[i], 
                                   data_added = FALSE)
     }
   }

}

## End(Not run)
## Not run: 
if (tidy_edge == TRUE) {
   edge_IDs <- seq(min(expanded_edges$edgeID), max(expanded_edges$edgeID))
   for (i in edge_IDs){
     if(data_added == TRUE){
       expanded_edges <- tidy_edge(edges = expanded_edges,
                                   edge_id = edge_IDs[i], 
                                   data_added = TRUE,
                                   by_significance = TRUE)
     }
     if(data_added == FALSE){
       expanded_edges <- tidy_edge(edges = expanded_edges,
                                   edge_id = edge_IDs[i], 
                                   data_added = FALSE)
     }
   }

}

## End(Not run)

cyREST utility functions

Description

A subset of the R utility functions available from/defined by cyREST. The function mapAttributes is called from within toCytoscape which, in turn, is called from within cyto_vis.

Usage

toCytoscape(igraphobj)

mapAttributes(attr.names, all.attr, i)
toCytoscape(igraphobj)

mapAttributes(attr.names, all.attr, i)

Arguments

`igraphobj`	A graph object compatible for use with the package igraph
`attr.names`	Attribute names of an igraph object
`all.attr`	The attribute value if an igraph object
`i`	The index for a given igraph object

Value

A JSON object to be sent to Cytoscape

Package 'KEGGlincs'

Help Index

Annotate KEGG edge mappings with user data

Description

Usage

Arguments

Value

Examples

Send graph to Cytoscape via CyREST

Description

Usage

Arguments

Value

Examples

Prepare edges for mapping

Description

Usage

Arguments

Value

Examples

Get detailed KEGG mapping information for each relation [edge] documented in KEGG

Description

Usage

Arguments

Value

Examples

Get detailed KEGG mapping information for each map entity

Description

Usage

Arguments

Value

Examples

The 'boilerplate' for this package's desired graph style

Description

Usage

Arguments

Value

Examples

Perform Fisher's Exact test for edges in pathway

Description

Usage

Arguments

Value

Examples

Generate graph object from nodes and edges

Description

Usage

Arguments

Value

Examples

Download and parse KGML file

Description

Usage

Arguments

Value

Examples

Combines all other package functions for one-step pathway visualization

Description

Usage

Arguments

Value

Examples

Add in edges to map documented in other pathways

Description

Usage

Arguments

Value

Examples

KEGGlincs: an R package designed to explore the edges in KEGG pathways

Description

Combines all other package functions for one-step cell line comparison

Description

Usage

Arguments

Value

Examples

Prepare nodes for mapping

Description

Usage

Arguments