node.map: Map molecular data onto KEGG pathway nodes

In datapplab/pathview: a tool set for pathway based data integration and visualization

Map molecular data onto KEGG pathway nodes

Description

The mapper function, mapping molecular data(gene expression, metabolite abundance etc)to nodes in KEGG pathway.

Usage

node.map(mol.data = NULL, node.data, node.types = c("gene", "ortholog",
"compound")[1], node.sum = c("sum", "mean", "median", "max", "max.abs",
"random")[1], entrez.gnodes=TRUE)

Arguments

mol.data	Either vector (single sample) or a matrix-like data (multiple sample). Vector should be numeric with molecule IDs as names or it may also be character of molecule IDs. Character vector is treated as discrete or count data. Matrix-like data structure has molecules as rows and samples as columns. Row names should be molecule IDs. Default mol.data=NULL. This argument is equivalent to gene.data or cpd.data in the pathview function. Check pahtview function for more information.
node.data	a named list of 10 elements, the results returned by node.info, check the function for details.
node.types	character, sepcify the node type to map the mol.data to, either "gene", "compound", or "compound". Default node.types="gene".
node.sum	character, the method name to calculate node summary given that multiple genes or compounds are mapped to it. Poential options include "sum","mean", "median", "max", "max.abs" and "random". Default node.sum="sum".
entrez.gnodes	logical, whether EntrezGene (NCBI GeneID) is used as the default gene ID in the KEGG data files. This is needed because KEGG uses different types default gene ID for different species. Some most common model species use EntrezGene, but majority of others use Locus tag. Default entrez.gnodes=TRUE.

Details

Mapper function node.map maps user supplied molecular data to KEGG pathways. This function takes standard KEGG molecular IDs (Entrez Gene ID or KEGG Compound Accession) and map them to pathway nodes. None KEGG molecular gene IDs or Compound IDs are pre-mapped to standard KEGG IDs by calling another function mol.sum. When multiple molecules map to one node, the corresponding molecular data are summarized into a single node summary by calling function specified by node.sum. This mapped node summary data together with the parsed KGML data are then returned for further processing. Proper input data include: gene expression, protein expression, genetic association, metabolite abundance, genomic data, literature, and other data types mappable to pathways. The input mol.data may be NULL, then no molecular data are actually mapped, but all nodes of the specified node.type are considered "mappable" and their parsed KGML data returned.

Value

A data.frame composed of parsed KGML data and summary molecular data for each mapped node. Each row is a mapped node, and columns are:

kegg.names	standard KEGG IDs/Names for mapped nodes. It's Entrez Gene ID or KEGG Compound Accessions.
labels	Node labels to be used when needed
type	node type, currently 4 types are supported: "gene","enzyme", "compound" and "ortholog".
x	x coordinate in the original KEGG pathway graph.
y	y coordinate in the original KEGG pathway graph.
width	node width in the original KEGG pathway graph.
height	node height in the original KEGG pathway graph.
other columns	columns of the mapped gene/compound data

Author(s)

Weijun Luo <[e-mail]>

References

Luo, W. and Brouwer, C., Pathview: an R/Bioconductor package for pathway based data integration and visualization. Bioinformatics, 2013, 29(14): 1830-1831, doi: 10.1093/bioinformatics/btt285

See Also

mol.sum the auxillary molecular data mapper, id2eg, cpd2kegg etc the auxillary molecular ID mappers, node.color the node color coder, pathview the main function, node.info the parser.

Examples

xml.file=system.file("extdata", "hsa04110.xml", package = "pathview")
node.data=node.info(xml.file)
names(node.data)
data(gse16873.d)
plot.data.gene=node.map(mol.data=gse16873.d[,1], node.data,
  node.types="gene")
head(plot.data.gene)

datapplab/pathview documentation built on March 30, 2024, 9:06 a.m.