| Title: | representing and modeling data in the EMBL-EBI GWAS catalog |
|---|---|
| Description: | Represent and model data in the EMBL-EBI GWAS catalog. |
| Authors: | VJ Carey <[email protected]> |
| Maintainer: | VJ Carey <[email protected]> |
| License: | Artistic-2.0 |
| Version: | 2.39.0 |
| Built: | 2024-12-06 06:16:11 UTC |
| Source: | https://github.com/bioc/gwascat |
extractor for gwaswloc
## S4 method for signature 'gwaswloc,ANY,ANY,ANY' x[i, j, ..., drop = FALSE]## S4 method for signature 'gwaswloc,ANY,ANY,ANY' x[i, j, ..., drop = FALSE]
x |
gwaswloc |
i |
index |
j |
index |
... |
addtl indices |
drop |
logical(1) |
produce a GRanges from gwascat tibble
as_GRanges( x, short = TRUE, for_short = c("PUBMEDID", "DATE", "DISEASE/TRAIT", "SNPS"), genome_tag = "GRCh38" )as_GRanges( x, short = TRUE, for_short = c("PUBMEDID", "DATE", "DISEASE/TRAIT", "SNPS"), genome_tag = "GRCh38" )
x |
a tibble from 'get_cached_gwascat()' |
short |
logical(1) if TRUE only keep selected columns in mcols |
for_short |
character() column names to keep in mcols |
genome_tag |
character(1) defaults to "GRCh38" |
bind CADD scores of Kircher et al. 2014 to a GRanges instance; by default will use HTTP access at UW
bindcadd_snv( gr, fn = "http://krishna.gs.washington.edu/download/CADD/v1.0/1000G.tsv.gz" )bindcadd_snv( gr, fn = "http://krishna.gs.washington.edu/download/CADD/v1.0/1000G.tsv.gz" )
gr |
query ranges to which CADD scores should be bound |
fn |
path to Tabix-indexed bgzipped TSV of CADD as distributed at krishna.gs.washington.edu on 1 April 2014 |
joins CADD fields at addresses that match query; the CADD fields for query ranges that are not matched are set to NA
GRanges instance with additional fields as obtained in the CADD resource
This software developed in part with support from Genentech, Inc.
VJ Carey <[email protected]>
M Kircher, DM Witten, P Jain, BJ O'Roak, GM Cooper, J Shendure, A general framework for estimating the relative pathogenicity of human genetic variants, Nature Genetics Feb 2014, PMID 24487276
## Not run: data(ebicat_2020_04_30) g2 = as(ebicat_2020_04_30, "GRanges") # would need to lift over here bindcadd_snv( g2[which(seqnames(g2)=="chr2")][1:20] ) ## End(Not run)## Not run: data(ebicat_2020_04_30) g2 = as(ebicat_2020_04_30, "GRanges") # would need to lift over here bindcadd_snv( g2[which(seqnames(g2)=="chr2")][1:20] ) ## End(Not run)
return TRUE if all named SNPs with locations in both the SNPlocs package and the gwascat agree
chklocs(chrtag = "20", gwwl = gwrngs19)chklocs(chrtag = "20", gwwl = gwrngs19)
chrtag |
character, chromosome identifier |
gwwl |
instance of |
serialized gwaswloc instance from april 30 2020, sample of 50000 records
ebicat_2020_04_30ebicat_2020_04_30
gwaswloc instance
SnpMatrix instance from chr17
g17SMg17SM
snpStats SnpMatrix instance
use BiocFileCache to retrieve and keep an image of the tsv file distributed by EBI
get_cached_gwascat( url = "http://www.ebi.ac.uk/gwas/api/search/downloads/alternative", cache = BiocFileCache::BiocFileCache(), refresh = FALSE, ... )get_cached_gwascat( url = "http://www.ebi.ac.uk/gwas/api/search/downloads/alternative", cache = BiocFileCache::BiocFileCache(), refresh = FALSE, ... )
url |
character(1) url to use |
cache |
BiocFileCache::BiocFileCache instance |
refresh |
logical(1) force download and recaching |
... |
passed to bfcadd |
a tibble as produced by readr::read_tsv, with attributes extractDate (as recorded in cache as 'access_time', and problems (a tibble returned by read_tsv).
will If query of cache with 'ebi.ac.uk/gwas' returns 0-row tibble, will populate cache with bfcadd. Uses readr::read_tsv on cache content to return tibble. The etag field does not seem to be used at EBI, thus user must check for updates.
generic snp name retrieval
getRsids(x)getRsids(x)
x |
gwaswloc |
specific snp name retrieval
## S4 method for signature 'gwaswloc' getRsids(x)## S4 method for signature 'gwaswloc' getRsids(x)
x |
gwaswloc |
generic trait retrieval
getTraits(x)getTraits(x)
x |
gwaswloc |
specific trait retrieval
## S4 method for signature 'gwaswloc' getTraits(x)## S4 method for signature 'gwaswloc' getTraits(x)
x |
gwaswloc |
genotype matrix from chr17 1000 genomes
gg17Ngg17N
matrix
data(gg17N) gg17N[1:4,1:4]data(gg17N) gg17N[1:4,1:4]
image of locon6 in GRanges, lifted over to hg38
gr6.0_hg38gr6.0_hg38
GRanges instance
character vector of rs numbers for SNP on chr17
gw6.rs_17gw6.rs_17
character vector
grab an image of EBI GWAS catalog from AnnotationHub
gwascat_from_AHub(tag = "AH91571", simple = FALSE, fixNonASCII = TRUE)gwascat_from_AHub(tag = "AH91571", simple = FALSE, fixNonASCII = TRUE)
tag |
character(1) defaults to "AH91571" which is the 3.30.2021 image |
simple |
logical(1) if TRUE, just returns data.frame as retrieved from EBI; defaults to FALSE |
fixNonASCII |
logical(1) if TRUE, use iconv to identify and eliminate non-ASCII content |
If 'simple', a data.frame is returned based on TSV data produced by EBI. Otherwise, non-ASCII content is processed according to the value of 'fixNonASCII' and a 'gwaswloc' instance is returned, which has a concise show method. This can be coerced to a simple GRanges instance with as(..., "GRanges"). The reference build is GRCh38.
gwcat = gwascat_from_AHub() gwcatgwcat = gwascat_from_AHub() gwcat
GRanges with LD information on 9998 SNP
gwastaggergwastagger
GRanges
container for gwas hit data and GRanges for addresses
use AnnotationHub snapshot as basis for gwaswloc structure creation
gwcat_snapshot(x, fixNonASCII = TRUE)gwcat_snapshot(x, fixNonASCII = TRUE)
x |
inherits from data.frame, with columns consistent with EBI table |
fixNonASCII |
logical(1) if TRUE, use iconv to replace non-ASCII character, important for CMD check but perhaps not important for applied use |
ah = AnnotationHub::AnnotationHub() entitytab = AnnotationHub::query(ah, "gwascatData") cand = names(entitytab)[1] stopifnot(nchar(cand)>0) tab = ah[[cand]] gww = gwcat_snapshot(tab) gww length(gww)ah = AnnotationHub::AnnotationHub() entitytab = AnnotationHub::query(ah, "gwascatData") cand = names(entitytab)[1] stopifnot(nchar(cand)>0) tab = ah[[cand]] gww = gwcat_snapshot(tab) gww length(gww)
Prepare salient components of GWAS catalog for rendering with Gviz
gwcex2gviz( basegr, contextGR = GRanges(seqnames = "chr17", IRanges::IRanges(start = 37500000, width = 1e+06)), txrefobj = TxDb.Hsapiens.UCSC.hg19.knownGene::TxDb.Hsapiens.UCSC.hg19.knownGene, genome = "hg19", genesymobj = org.Hs.eg.db::org.Hs.eg.db, plot.it = TRUE, maxmlp = 25 )gwcex2gviz( basegr, contextGR = GRanges(seqnames = "chr17", IRanges::IRanges(start = 37500000, width = 1e+06)), txrefobj = TxDb.Hsapiens.UCSC.hg19.knownGene::TxDb.Hsapiens.UCSC.hg19.knownGene, genome = "hg19", genesymobj = org.Hs.eg.db::org.Hs.eg.db, plot.it = TRUE, maxmlp = 25 )
basegr |
gwaswloc instance containing information about GWAS in catalog |
contextGR |
A GRanges instance delimiting the visualization in genomic coordinates |
txrefobj |
a TxDb instance |
genome |
character tag like 'hg19' |
genesymobj |
an OrgDb instance |
plot.it |
logical, if FALSE, just return list |
maxmlp |
maximum value of -10 log p – winsorization of all larger values is performed, modifying the contents of Pvalue\_mlogp in the elementMetadata for the call |
data(ebicat_2020_04_30) # GenomeInfoDb::seqlevelsStyle(ebicat_2020_04_30) = "UCSC" # no more GenomeInfoDb::seqlevels(ebicat_2020_04_30) = paste0("chr", GenomeInfoDb::seqlevels(ebicat_2020_04_30)) gwcex2gviz(ebicat_2020_04_30)data(ebicat_2020_04_30) # GenomeInfoDb::seqlevelsStyle(ebicat_2020_04_30) = "UCSC" # no more GenomeInfoDb::seqlevels(ebicat_2020_04_30) = paste0("chr", GenomeInfoDb::seqlevels(ebicat_2020_04_30)) gwcex2gviz(ebicat_2020_04_30)
expand a list of variants by including those in a VCF with LD exceeding some threshold; uses snpStats ld()
ldtagr( snprng, tf, samples, genome = "hg19", lbmaf = 0.05, lbR2 = 0.8, radius = 1e+05 )ldtagr( snprng, tf, samples, genome = "hg19", lbmaf = 0.05, lbR2 = 0.8, radius = 1e+05 )
snprng |
a named GRanges for a single SNP. The name must correspond to the name that will be assigned by genotypeToSnpMatrix (from VariantTools) to the corresponding column of a SnpMatrix. |
tf |
TabixFile instance pointing to a bgzipped tabix-indexed VCF file |
samples |
a vector of sample identifiers, if excluded, all samples used |
genome |
tag like 'hg19' |
lbmaf |
lower bound on variant MAF to allow consideration |
lbR2 |
lower bound on R squared for regarding SNP to be incorporated |
radius |
radius of search in bp around the input range |
a GRanges with names corresponding to 'new' variants and mcols fields 'paramRangeID' (base variant input) and 'R2'
slow but safe approach. probably a matrix method could be substituted using the nice sparse approach already in snpStats
VJ Carey
cand = GenomicRanges::GRanges("1", IRanges::IRanges(113038694, width=1)) names(cand) = "rs883593" requireNamespace("VariantAnnotation") expath = dir(system.file("vcf", package="gwascat"), patt=".*exon.*gz$", full=TRUE) tf = Rsamtools::TabixFile(expath) ldtagr( cand, tf, lbR2 = .8)cand = GenomicRanges::GRanges("1", IRanges::IRanges(113038694, width=1)) names(cand) = "rs883593" requireNamespace("VariantAnnotation") expath = dir(system.file("vcf", package="gwascat"), patt=".*exon.*gz$", full=TRUE) tf = Rsamtools::TabixFile(expath) ldtagr( cand, tf, lbR2 = .8)
location data for 10000 SNP
locon6locon6
data.frame, coordinates are hg19
get locations for SNP affecting a selected trait
locs4trait(gwwl, trait, tag = "DISEASE/TRAIT")locs4trait(gwwl, trait, tag = "DISEASE/TRAIT")
gwwl |
instance of |
trait |
character, name of trait |
tag |
character, name of field to be used for trait enumeration |
SnpMatrix instance from chr17
low17low17
snpStats SnpMatrix instance
read NHGRI GWAS catalog table and construct associated GRanges instance records for which clear genomic position cannot be determined are dropped from the ranges instance an effort is made to use reasonable data types for GRanges metadata, so some qualifying characters such as (EA) in Risk allele frequency field will simply be omitted during coercion of contents of that field to numeric.
makeCurrentGwascat( table.url = "http://www.ebi.ac.uk/gwas/api/search/downloads/alternative", fixNonASCII = TRUE, genome = "GRCh38", withOnt = TRUE )makeCurrentGwascat( table.url = "http://www.ebi.ac.uk/gwas/api/search/downloads/alternative", fixNonASCII = TRUE, genome = "GRCh38", withOnt = TRUE )
table.url |
string identifying the .txt file curated at EBI/EMBL |
fixNonASCII |
logical, if TRUE, non-ASCII characters as identified by iconv will be replaced by asterisk |
genome |
character string: 'GRCh38' is default and yields current image as provided by EMBL/EBI; 'GRCh37' yields a realtime liftOver to hg19 coordinates, via AnnotationHub storage of the chain files. Any other value yields an error. |
withOnt |
logical indicating whether 'alternative' (ontology-present, includes repetition of loci with one:many ontological mapping) or 'full' (ontology-absent, one record per locus report) version of distributed table |
a slightly extended GRanges instance, with class name 'gwaswloc'; the purpose of the introduction of this class is to support a concise show method that does not produce very long lines owing to large numbers of fields in the mcols component.
'readr::read_tsv' records problems when some records have field contents that are inconsistent with the column specification. This information can be retrieved from the metadata slot of the returned object, as noted in a message produced when this function is run.
VJ Carey
# if you have good internet access if (interactive()) { newcatr = makeCurrentGwascat() newcatr }# if you have good internet access if (interactive()) { newcatr = makeCurrentGwascat() newcatr }
convert a typical OBO text file to a graphNEL instance (using Term elements)
obo2graphNEL( obo = "human-phenotype-ontology.obo", kill = "\\[Typedef\\]", killTrailSp = TRUE )obo2graphNEL( obo = "human-phenotype-ontology.obo", kill = "\\[Typedef\\]", killTrailSp = TRUE )
obo |
string naming a file in OBO format |
kill |
entity types to be excluded from processing – probably this should be in a 'keep' form, but for now this works. |
killTrailSp |
In the textual version of EFO ca. Aug 2015, there is a trailing blank in the tag field defining EFO:0000001, which is not present in references to this term. Set this to TRUE to eliminate this, or graphNEL construction will fail to validate. |
Very rudimentary list and grep operations are used to retain sufficient information to map the DAG to a graphNEL, using formal term identifiers as node names and 'is-a' relationships as edges, and term names and other metadata are assigned to nodeData components.
a graphNEL instance
The OBO for Human Disease ontology is serialized as text with this package.
VJ Carey <[email protected]>
For use with human disease ontology, http://www.obofoundry.org/cgi-bin/detail.cgi?id=disease_ontology
data(efo.obo.g) requireNamespace("graph") hn = graph::nodes(efo.obo.g)[1:5] hn graph::nodeData(efo.obo.g, hn[5])data(efo.obo.g) requireNamespace("graph") hn = graph::nodes(efo.obo.g)[1:5] hn graph::nodeData(efo.obo.g, hn[5])
convert GWAS catalog data.frame to gwaswloc, a GRanges extension with simple show method
process_gwas_dataframe(df)process_gwas_dataframe(df)
df |
data.frame |
given a matrix of subjects x SNP calls, count number of risky alleles for various conditions, relative to NHGRI GWAS catalog
riskyAlleleCount( callmat, matIsAB = TRUE, chr, gwwl, snpap = "SNPlocs.Hsapiens.dbSNP144.GRCh37", gencode = c("A/A", "A/B", "B/B") )riskyAlleleCount( callmat, matIsAB = TRUE, chr, gwwl, snpap = "SNPlocs.Hsapiens.dbSNP144.GRCh37", gencode = c("A/A", "A/B", "B/B") )
callmat |
matrix with subjects as rows, SNPs as columns; entries can be generic A/A, A/B, B/B, or specific nucleotide calls |
matIsAB |
logical, FALSE if nucleotide codes are present, TRUE if generic call codes are present; in the latter case, gwascat:::ABmat2nuc will be run |
chr |
code for chromosome, should work with the SNP annotation getSNPlocs function, so likely "ch[nn]" |
gwwl |
an instance of |
snpap |
name of a Bioconductor SNPlocs.Hsapiens.dbSNP.* package |
gencode |
codes used for generic SNP call |
matrix with rows corresponding to subjects , columns corresponding to SNP
## Not run: data(gg17N) # translated from GGdata chr 17 calls using ABmat2nuc data(ebicat37) library(GenomeInfoDb) seqlevelsStyle(ebicat37) = "UCSC" h17 = riskyAlleleCount(gg17N, matIsAB=FALSE, chr="ch17", gwwl=ebicat37) h17[1:5,1:5] table(as.numeric(h17)) ## End(Not run)## Not run: data(gg17N) # translated from GGdata chr 17 calls using ABmat2nuc data(ebicat37) library(GenomeInfoDb) seqlevelsStyle(ebicat37) = "UCSC" h17 = riskyAlleleCount(gg17N, matIsAB=FALSE, chr="ch17", gwwl=ebicat37) h17[1:5,1:5] table(as.numeric(h17)) ## End(Not run)
Seqinfo for GRCh37
si.hs.37si.hs.37
GenomeInfoDb Seqinfo instance
Seqinfo for GRCh38
si.hs.38si.hs.38
GenomeInfoDb Seqinfo instance
generic trait subsetting
subsetByChromosome(x, ch)subsetByChromosome(x, ch)
x |
gwaswloc |
ch |
character vector of chromosomes |
specific trait subsetting
## S4 method for signature 'gwaswloc' subsetByChromosome(x, ch)## S4 method for signature 'gwaswloc' subsetByChromosome(x, ch)
x |
gwaswloc |
ch |
character vector of chromosomes |
generic trait subsetting
subsetByTraits(x, tr)subsetByTraits(x, tr)
x |
gwaswloc |
tr |
character vector of traits |
specific trait subsetting
## S4 method for signature 'gwaswloc' subsetByTraits(x, tr)## S4 method for signature 'gwaswloc' subsetByTraits(x, tr)
x |
gwaswloc |
tr |
character vector of traits |
operations on GWAS catalog
topTraits(gwwl, n = 10, tag = "DISEASE/TRAIT")topTraits(gwwl, n = 10, tag = "DISEASE/TRAIT")
gwwl |
instance of |
n |
numeric, number of traits to report |
tag |
character, name of field to be used for trait enumeration |
topTraits returns a character vector of most frequently
occurring traits in the database
locs4trait returns a {gwaswloc} object with
records defining associations to the specified trait
chklocs returns a logical that is TRUE when the asserted locations of
SNP in the GWAS catalog agree with the locations given in the dbSNP package
SNPlocs.Hsapiens.dbSNP144.GRCh37
VJ Carey <[email protected]>
data(ebicat_2020_04_30) topTraits(ebicat_2020_04_30)data(ebicat_2020_04_30) topTraits(ebicat_2020_04_30)
use ggbio facilities to display GWAS results for selected traits in genomic coordinates
traitsManh( gwr, selr = GRanges(seqnames = "chr17", IRanges(3e+07, 5e+07)), traits = c("Asthma", "Parkinson's disease", "Height", "Crohn's disease"), truncmlp = 25, ... )traitsManh( gwr, selr = GRanges(seqnames = "chr17", IRanges(3e+07, 5e+07)), traits = c("Asthma", "Parkinson's disease", "Height", "Crohn's disease"), truncmlp = 25, ... )
gwr |
GRanges instance as managed by the gwaswloc container design, with Disease.Trait and Pvalue\_mlog among elementMetadata columns |
selr |
A GRanges instance to restrict the |
traits |
Character vector of traits to be exhibited; GWAS results with traits not among these will be labeled “other”. |
truncmlp |
Maximum value of -log10 p to be displayed; in the raw data this ranges to the hundreds and can cause bad compression. |
... |
not currently used |
uses a ggbio autoplot
autoplot value
An xlab is added, concatenating genome tag with seqnames tag.
VJ Carey <[email protected]>
# do a p-value truncation if you want to reduce compression ## Not run: # ggbio July 2018 data(ebicat_2020_04_30) library(GenomeInfoDb) seqlevelsStyle(ebicat_2020_04_30) = "UCSC" traitsManh(ebicat_2020_04_30) ## End(Not run)# do a p-value truncation if you want to reduce compression ## Not run: # ggbio July 2018 data(ebicat_2020_04_30) library(GenomeInfoDb) seqlevelsStyle(ebicat_2020_04_30) = "UCSC" traitsManh(ebicat_2020_04_30) ## End(Not run)