XGR (version 1.1.7)

xSNP2eGenes: Function to define eQTL genes given a list of SNPs or a customised eQTL mapping data

Description

xSNP2eGenes is supposed to define eQTL genes given a list of SNPs or a customised eQTL mapping data. The eQTL weight is calcualted as Cumulative Distribution Function of negative log-transformed eQTL-reported signficance level.

Usage

xSNP2eGenes(
data,
include.eQTL = NA,
eQTL.customised = NULL,
cdf.function = c("empirical", "exponential"),
plot = FALSE,
verbose = TRUE,
RData.location = "http://galahad.well.ox.ac.uk/bigdata",
guid = NULL
)

Arguments

data

an input vector containing SNPs. SNPs should be provided as dbSNP ID (ie starting with rs). Alternatively, they can be in the format of 'chrN:xxx', where N is either 1-22 or X, xxx is number; for example, 'chr16:28525386'

include.eQTL

the eQTL supported currently. By default, it is 'NA' to disable this option. Pre-built eQTL datasets are detailed in xDefineEQTL

eQTL.customised

a user-input matrix or data frame with 4 columns: 1st column for SNPs/eQTLs, 2nd column for Genes, 3rd for eQTL mapping significance level (p-values or FDR), and 4th for contexts (required even though only one context is input). Alternatively, it can be a file containing these 4 columns. It is designed to allow the user analysing their eQTL data. This customisation (if provided) will populate built-in eQTL data

cdf.function

a character specifying a Cumulative Distribution Function (cdf). It can be one of 'exponential' based on exponential cdf, 'empirical' for empirical cdf

plot

logical to indicate whether the histogram plot (plus density or CDF plot) should be drawn. By default, it sets to false for no plotting

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

guid

a valid (5-character) Global Unique IDentifier for an OSF project. See xRDataLoader for details

Value

a data frame with following columns:

• Gene: eQTL-containing genes

• SNP: eQTLs

• Sig: the eQTL mapping significant level (the best/minimum)

• Weight: the eQTL weight

See Also

xRDataLoader

Examples

# NOT RUN {
# Load the library
library(XGR)
# }
# NOT RUN {
RData.location <- "http://galahad.well.ox.ac.uk/bigdata"
# }
# NOT RUN {
# a) provide the SNPs with the significance info
data(ImmunoBase)
gr <- ImmunoBase$AS$variants
AS <- as.data.frame(GenomicRanges::mcols(gr)[, c('Variant','Pvalue')])

# b) define eQTL genes
df_eGenes <- xSNP2eGenes(data=AS[,1], include.eQTL="JKscience_TS2A",
RData.location=RData.location)
# }