Usage
xEnricherSNPs(data, background = NULL, ontology = c("EF", "EF_disease",
"EF_phenotype", "EF_bp"), include.LD = NA, LD.r2 = 0.8,
size.range = c(10, 2000), min.overlap = 3, which.distance = NULL,
test = c("hypergeo", "fisher", "binomial"), p.adjust.method = c("BH",
"BY", "bonferroni", "holm", "hochberg", "hommel"),
ontology.algorithm = c("none", "pc", "elim", "lea"), elim.pvalue =
0.01,
lea.depth = 2, path.mode = c("all_paths", "shortest_paths",
"all_shortest_paths"), true.path.rule = T, verbose = T,
RData.location = "http://galahad.well.ox.ac.uk/bigdata")
Arguments
data
an input vector. It contains a list of SNPs of interest
background
a background vector. It contains a list of SNPs as
the test background. If NULL, by default all annotatable are used as
background
ontology
the ontology supported currently. Now it is only "EF"
for Experimental Factor Ontology (used to annotate GWAS Catalog SNPs).
However, there are several subparts of this ontology to choose:
'EF_disease' for the subpart under the term 'disease' (EFO:0000408),
'EF_phenotype' for the subpart under the term 'phenotype'
(EFO:0000651), 'EF_bp' for the subpart under the term 'biological
process' (GO:0008150)
include.LD
additional SNPs in LD with Lead SNPs are also
included. By default, it is 'NA' to disable this option. Otherwise, LD
SNPs will be included based on one or more of 26 populations and 5
super populations from 1000 Genomics Project data (phase 3). The
population can be one of 5 super populations ("AFR", "AMR", "EAS",
"EUR", "SAS"), or one of 26 populations ("ACB", "ASW", "BEB", "CDX",
"CEU", "CHB", "CHS", "CLM", "ESN", "FIN", "GBR", "GIH", "GWD", "IBS",
"ITU", "JPT", "KHV", "LWK", "MSL", "MXL", "PEL", "PJL", "PUR", "STU",
"TSI", "YRI"). Explanations for population code can be found at
http://www.1000genomes.org/faq/which-populations-are-part-your-study LD.r2
the LD r2 value. By default, it is 0.8, meaning that SNPs
in LD (r2>=0.8) with input SNPs will be considered as LD SNPs. It can
be any value from 0.8 to 1
size.range
the minimum and maximum size of members of each term
in consideration. By default, it sets to a minimum of 10 but no more
than 2000
min.overlap
the minimum number of overlaps. Only those terms
with members that overlap with input data at least min.overlap (3 by
default) will be processed
which.distance
which terms with the distance away from the
ontology root (if any) is used to restrict terms in consideration. By
default, it sets to 'NULL' to consider all distances
test
the test statistic used. It can be "fisher" for using
fisher's exact test, "hypergeo" for using hypergeometric test, or
"binomial" for using binomial test. Fisher's exact test is to test the
independence between gene group (genes belonging to a group or not) and
gene annotation (genes annotated by a term or not), and thus compare
sampling to the left part of background (after sampling without
replacement). Hypergeometric test is to sample at random (without
replacement) from the background containing annotated and non-annotated
genes, and thus compare sampling to background. Unlike hypergeometric
test, binomial test is to sample at random (with replacement) from the
background with the constant probability. In terms of the ease of
finding the significance, they are in order: hypergeometric test >
fisher's exact test > binomial test. In other words, in terms of the
calculated p-value, hypergeometric test < fisher's exact test <
binomial test
p.adjust.method
the method used to adjust p-values. It can be
one of "BH", "BY", "bonferroni", "holm", "hochberg" and "hommel". The
first two methods "BH" (widely used) and "BY" control the false
discovery rate (FDR: the expected proportion of false discoveries
amongst the rejected hypotheses); the last four methods "bonferroni",
"holm", "hochberg" and "hommel" are designed to give strong control of
the family-wise error rate (FWER). Notes: FDR is a less stringent
condition than FWER
ontology.algorithm
the algorithm used to account for the
hierarchy of the ontology. It can be one of "none", "pc", "elim" and
"lea". For details, please see 'Note' below
elim.pvalue
the parameter only used when "ontology.algorithm" is
"elim". It is used to control how to declare a signficantly enriched
term (and subsequently all genes in this term are eliminated from all
its ancestors)
lea.depth
the parameter only used when "ontology.algorithm" is
"lea". It is used to control how many maximum depth is used to consider
the children of a term (and subsequently all genes in these children
term are eliminated from the use for the recalculation of the
signifance at this term)
path.mode
the mode of paths induced by vertices/nodes with input
annotation data. It can be "all_paths" for all possible paths to the
root, "shortest_paths" for only one path to the root (for each node in
query), "all_shortest_paths" for all shortest paths to the root (i.e.
for each node, find all shortest paths with the equal lengths)
true.path.rule
logical to indicate whether the true-path rule
should be applied to propagate annotations. By default, it sets to
true
verbose
logical to indicate whether the messages will be
displayed in the screen. By default, it sets to false for no display
RData.location
the characters to tell the location of built-in
RData files. See xRDataLoader for details