XGR (version 1.1.4)

xGRtrack: Function to visualise genes within a genomic region using track plot

Description

xGRtrack is supposed to visualise genes within a genomic region using track plot. Genes in query within a genomic region are displayed on the gene model track along with nearby genes of desired window or number. If scores for genomic region are also provided, the genomic score track will be also displayed at the top.

Usage

xGRtrack(cse.query = NULL, gene.query = NULL, window = 1e+05,
nearby = NULL, name.scoretrack = "Genomic scores",
gene.model = c("UCSC_knownGene_model", "UCSC_knownCanonical_model"),
GR.score = c(NA, "RecombinationRate", "phastCons100way",
"phyloP100way",
"GERP"), GR.score.customised = NULL, name.customised = "Customised",
type.customised = c("point", "line"), label.size = 2,
label.col = "black", label.force = 0.05, verbose = TRUE,
RData.location = "http://galahad.well.ox.ac.uk/bigdata")

Arguments

cse.query

a genomic region in query. By default it is NULL; otherwise provided as 'chrN:start-end', where N is either 1-22 or X, start (or end) is genomic positional number; for example, 'chr1:13-20'. If provided, it will overwrite the parameter 'gene.query' below

gene.query

which gene in query will be visualised. By default it is NULL

window

the maximum distance defining nearby genes around the gene in query. By default it is 1e5

nearby

the maximum number defining nearby genes around the gene in query. By default it is NULL. If not NULL, it will overwrite the parameter 'window' above

name.scoretrack

the name for the score track. By default, it is "Genomic scores"

gene.model

the genomic regions of the gene model. By default, it is 'UCSC_knownGene_model', that is, UCSC known genes (together with genomic locations) based on human genome assembly hg19. It can be 'UCSC_knownCanonical_model', that is, UCSC known canonical genes (together with genomic locations) based on human genome assembly hg19. Alternatively, the user can specify the customised input. To do so, first save your RData file (containing an GR object) into your local computer, and make sure the GR object content names refer to Gene Symbols. Then, tell "GR.Gene" with your RData file name (with or without extension), plus specify your file RData path in "RData.location"

GR.score

the genomic regions together with score data. By default, it is 'NA' to disable this option. Pre-built genomic score data: 'RecombinationRate' (recombintion rate, http://www.ncbi.nlm.nih.gov/pubmed/17943122)), 'phastCons100way', 'phyloP100way', 'GERP'.

GR.score.customised

the customised genomic score data. By default, it is NA to disable this option; otherwise load your customised GR object directly (with the first meta column for scores; if not provided, it will be valued at 1). If provided, it will be appended to 'GR.score' above. Also supported is the labelling by providing a meta-column called 'Label'. It can be also a list of GR objects

name.customised

the name for customised genomic score data. By default, it is "Customised"

type.customised

how to plot customised genomic score data. It can be "point" or "line"

label.size

label size

label.col

label color

label.force

the repelling force between overlapping labels

verbose

logical to indicate whether the messages will be displayed in the screen. By default, it sets to true for display

RData.location

the characters to tell the location of built-in RData files. See xRDataLoader for details

Value

a Tracks object.

See Also

xGRoverlap

Examples

# NOT RUN {
# Load the library
library(XGR)
# }
# NOT RUN {
RData.location <- "http://galahad.well.ox.ac.uk/bigdata"
# }
# NOT RUN {
## given a query gene
tks <- xGRtrack(gene.query='TNF', nearby=10,
gene.model="UCSC_knownGene_model",
GR.score=c("RecombinationRate","phastCons100way"),
RData.location=RData.location)
tks
## given a query genomic region
tks <- xGRtrack(cse.query='chr6:31497996-31584798',
gene.model="UCSC_knownGene_model",
GR.score=c("RecombinationRate","phastCons100way"),
RData.location=RData.location)

### GWAS catalog
GWAScatalog <- xRDataLoader('GWAScatalog',
RData.location=RData.location)
gwas <- xGR(GWAScatalog$cse_hg19, format="chr:start-end")
ind <- match(names(gwas), GWAScatalog$cse_hg19)
gwas$pvalue <- -log10(GWAScatalog$pvalue[ind])
tks <- xGRtrack(gene.query='TNF', nearby=10,
gene.model="UCSC_knownGene_model", GR.score="RecombinationRate",
GR.score.customised=gwas, RData.location=RData.location)
tks

##########################
## Advanced use: customised GR.score
##########################
gene.model <- xRDataLoader("UCSC_knownGene_model",
RData.location=RData.location)

### LDblock_GR
gr <- xRDataLoader("LDblock_GR", RData.location=RData.location)
maf <- gr[,'maf']
distance <- gr[,'distance']
cadd <- gr[,'cadd']
### GR.score.customised as a list of GR objects
GR.score.customised <- list(maf=maf, distance=distance, cadd=cadd)
tks <- xGRtrack(gene.query='TNF', window=1e0, gene.model=gene.model,
GR.score=NA, GR.score.customised=GR.score.customised,
type.customised='point', RData.location=RData.location)
tks

### the built-in provided as the customised
customised <-
c("RecombinationRate","phastCons100way","phyloP100way","GERP","dbSNP_GWAS")
GR.score.customised <- lapply(customised, function(x) xRDataLoader(x,
RData.location=RData.location))
tks <- xGRtrack(gene.query='TNF', nearby=10, gene.model=gene.model,
GR.score=NA, GR.score.customised=GR.score.customised,
type.customised='line', RData.location=RData.location)
tks
# }