xGR2nGenes: Function to define nearby genes given a list of genomic...

In Pi: Leveraging Genetic Evidence to Prioritise Drug Targets at the Gene and Pathway Level

Description

xGR2nGenes is supposed to define nearby genes given a list of genomic regions (GR) within certain distance window. The distance weight is calcualted as a decaying function of the gene-to-GR distance.

Usage

xGR2nGenes(
data,
format = c("chr:start-end", "data.frame", "bed", "GRanges"),
build.conversion = c(NA, "hg38.to.hg19", "hg18.to.hg19"),
distance.max = 50000,
decay.kernel = c("rapid", "slow", "linear", "constant"),
decay.exponent = 2,
GR.Gene = c("UCSC_knownGene", "UCSC_knownCanonical"),
scoring = FALSE,
scoring.scheme = c("max", "sum", "sequential"),
scoring.rescale = FALSE,
verbose = TRUE,
RData.location = "http://galahad.well.ox.ac.uk/bigdata",
guid = NULL
)

Arguments

data	input genomic regions (GR). If formatted as "chr:start-end" (see the next parameter 'format' below), GR should be provided as a vector in the format of 'chrN:start-end', where N is either 1-22 or X, start (or end) is genomic positional number; for example, 'chr1:13-20'. If formatted as a 'data.frame', the first three columns correspond to the chromosome (1st column), the starting chromosome position (2nd column), and the ending chromosome position (3rd column). If the format is indicated as 'bed' (browser extensible data), the same as 'data.frame' format but the position is 0-based offset from chromomose position. If the genomic regions provided are not ranged but only the single position, the ending chromosome position (3rd column) is allowed not to be provided. The data could also be an object of 'GRanges' (in this case, formatted as 'GRanges')
format	the format of the input data. It can be one of "data.frame", "chr:start-end", "bed" or "GRanges"
build.conversion	the conversion from one genome build to another. The conversions supported are "hg38.to.hg19" and "hg18.to.hg19". By default it is NA (no need to do so)
distance.max	the maximum distance between genes and GR. Only those genes no far way from this distance will be considered as seed genes. This parameter will influence the distance-component weights calculated for nearby GR per gene
decay.kernel	a character specifying a decay kernel function. It can be one of 'slow' for slow decay, 'linear' for linear decay, and 'rapid' for rapid decay. If no distance weight is used, please select 'constant'
decay.exponent	a numeric specifying a decay exponent. By default, it sets to 2
GR.Gene	the genomic regions of genes. By default, it is 'UCSC_knownGene', that is, UCSC known genes (together with genomic locations) based on human genome assembly hg19. It can be 'UCSC_knownCanonical', 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". Note: you can also load your customised GR object directly
scoring	logical to indicate whether gene-level scoring will be further calculated. By default, it sets to false
scoring.scheme	the method used to calculate seed gene scores under a set of GR. It can be one of "sum" for adding up, "max" for the maximum, and "sequential" for the sequential weighting. The sequential weighting is done via: ∑_{i=1}{\frac{R_{i}}{i}}, where R_{i} is the i^{th} rank (in a descreasing order)
scoring.rescale	logical to indicate whether gene scores will be further rescaled into the [0,1] range. By default, it sets to false
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

If scoring sets to false, a data frame with following columns:

• Gene: nearby genes

• GR: genomic regions

• Dist: the genomic distance between the gene and the GR

• Weight: the distance weight based on the genomic distance

If scoring sets to true, a data frame with following columns:

• Gene: nearby genes

• Score: gene score taking into account the distance weight based on the genomic distance

Note

For details on the decay kernels, please refer to xVisKernels

See Also

xGR, xRDataLoader, xSparseMatrix

Examples

RData.location <- "http://galahad.well.ox.ac.uk/bigdata"
## Not run: 

# a) provide the genomic regions
## load ImmunoBase
ImmunoBase <- xRDataLoader(RData.customised='ImmunoBase',
RData.location=RData.location)
## get lead SNPs reported in AS GWAS and their significance info (p-values)
gr <- ImmunoBase$AS$variant
df <- as.data.frame(gr, row.names=NULL)
chr <- df$seqnames
start <- df$start
end <- df$end
data <- paste(chr,':',start,'-',end, sep='')

# b) define nearby genes taking into acount distance weight
# without gene scoring
df_nGenes <- xGR2nGenes(data=data, format="chr:start-end",
distance.max=10000, decay.kernel="slow", decay.exponent=2,
RData.location=RData.location)
# with their scores
df_nGenes <- xGR2nGenes(data=data, format="chr:start-end",
distance.max=10000, decay.kernel="slow", decay.exponent=2,
scoring=TRUE, scoring.scheme="max", RData.location=RData.location)

# c) define nearby genes without taking into acount distance weight
# without gene scoring
df_nGenes <- xGR2nGenes(data=data, format="chr:start-end",
distance.max=10000, decay.kernel="constant",
RData.location=RData.location)
# with their scores
df_nGenes <- xGR2nGenes(data=data, format="chr:start-end",
distance.max=10000, decay.kernel="constant", scoring=TRUE,
scoring.scheme="max", RData.location=RData.location)

## End(Not run)

Pi documentation built on Nov. 29, 2021, 3 p.m.