Contents

1 Introduction

NHGRI maintains and routinely updates a database of selected genome-wide association studies. This document describes R/Bioconductor facilities for working with contents of this database.

1.1 Installation

The package can be installed using Bioconductor’s package, with the sequence

1.2 Attachment and access to documentation

Once the package has been installed, use to obtain interactive access to all the facilities. After executing this command, use to obtain an overview. The current version of this vignette can always be accessed at www.bioconductor.org, or by suitably navigating the web pages generated with .

1.3 Using tidy methods – added August 2022

## # A tibble: 402,121 × 38
##    DATE ADDED T…¹ PUBME…² FIRST…³ DATE       JOURNAL LINK  STUDY DISEA…⁴ INITI…⁵
##    <date>           <dbl> <chr>   <date>     <chr>   <chr> <chr> <chr>   <chr>  
##  1 2008-06-16      1.58e7 Klein … 2005-03-10 Science www.… Comp… Age-re… 96 Eur…
##  2 2008-06-16      1.63e7 Maraga… 2005-09-09 Am J H… www.… High… Parkin… 381 Eu…
##  3 2008-06-16      1.66e7 Arking… 2006-04-30 Nat Ge… www.… A co… QT int… 100 Eu…
##  4 2008-06-16      1.71e7 Fung HC 2006-09-28 Lancet… www.… Geno… Parkin… 267 Eu…
##  5 2008-06-16      1.71e7 Fung HC 2006-09-28 Lancet… www.… Geno… Parkin… 267 Eu…
##  6 2008-06-16      1.71e7 Fung HC 2006-09-28 Lancet… www.… Geno… Parkin… 267 Eu…
##  7 2008-06-16      1.71e7 Dewan A 2006-10-19 Science www.… HTRA… Age-re… 96 Sou…
##  8 2008-06-16      1.71e7 Duerr … 2006-10-26 Science www.… A ge… Inflam… 547 Eu…
##  9 2008-06-16      1.72e7 Bierut… 2006-12-07 Hum Mo… www.… Nove… Nicoti… 482 Eu…
## 10 2008-06-16      1.72e7 Bierut… 2006-12-07 Hum Mo… www.… Nove… Nicoti… 482 Eu…
## # … with 402,111 more rows, 29 more variables: `REPLICATION SAMPLE SIZE` <chr>,
## #   REGION <chr>, CHR_ID <chr>, CHR_POS <chr>, `REPORTED GENE(S)` <chr>,
## #   MAPPED_GENE <chr>, UPSTREAM_GENE_ID <chr>, DOWNSTREAM_GENE_ID <chr>,
## #   SNP_GENE_IDS <chr>, UPSTREAM_GENE_DISTANCE <dbl>,
## #   DOWNSTREAM_GENE_DISTANCE <dbl>, `STRONGEST SNP-RISK ALLELE` <chr>,
## #   SNPS <chr>, MERGED <dbl>, SNP_ID_CURRENT <dbl>, CONTEXT <chr>,
## #   INTERGENIC <dbl>, `RISK ALLELE FREQUENCY` <chr>, `P-VALUE` <dbl>, …
## # ℹ Use `print(n = ...)` to see more rows, and `colnames()` to see all variable names

We can produce a GRanges in two forms. By default we get an mcols that has a small set of columns. Note that records that lack a CHR_POS value are omitted.
Records that have complicated CHR_POS values, including semicolons or " x " notation are kept, but only the first position is retained. The CHR_ID field may have complicated character values, these are not normalized, and are simply used as seqnames “as is”.

## dropping 18239 records that have NA for CHR_POS
## 261 records have semicolon in CHR_POS; splitting and using first entry.
## 251 records have ' x ' in CHR_POS indicating multiple SNP effects, using first.
## GRanges object with 383882 ranges and 4 metadata columns:
##            seqnames    ranges strand |  PUBMEDID       DATE
##               <Rle> <IRanges>  <Rle> | <numeric>     <Date>
##        [1]        1 161509955      * |  19915573 2009-11-15
##        [2]        6  31143579      * |  19915573 2009-11-15
##        [3]       13  26957130      * |  19915573 2009-11-15
##        [4]        9   5213687      * |  19915573 2009-11-15
##        [5]        6  32465390      * |  19915573 2009-11-15
##        ...      ...       ...    ... .       ...        ...
##   [383878]       10  68192278      * |  34077760 2021-06-01
##   [383879]       13 110066208      * |  34077760 2021-06-01
##   [383880]       21  28133942      * |  34077760 2021-06-01
##   [383881]        1  91730044      * |  34077760 2021-06-01
##   [383882]       11  58646437      * |  34077760 2021-06-01
##                     DISEASE/TRAIT        SNPS
##                       <character> <character>
##        [1]     Ulcerative colitis   rs1801274
##        [2]     Ulcerative colitis   rs9263739
##        [3]     Ulcerative colitis  rs17085007
##        [4]     Ulcerative colitis  rs10975003
##        [5]     Ulcerative colitis   rs2395185
##        ...                    ...         ...
##   [383878] Vertical cup-disc ra..  rs10998007
##   [383879] Vertical cup-disc ra..  rs12875868
##   [383880] Vertical cup-disc ra..   rs6516818
##   [383881] Vertical cup-disc ra..  rs10783002
##   [383882] Vertical cup-disc ra..   rs1938598
##   -------
##   seqinfo: 209 sequences from GRCh38 genome; no seqlengths

We can set the seqinfo as follows, retaining only records that employ standard chromosomes.

## GRanges object with 383370 ranges and 4 metadata columns:
##            seqnames    ranges strand |  PUBMEDID       DATE
##               <Rle> <IRanges>  <Rle> | <numeric>     <Date>
##        [1]        1 161509955      * |  19915573 2009-11-15
##        [2]        6  31143579      * |  19915573 2009-11-15
##        [3]       13  26957130      * |  19915573 2009-11-15
##        [4]        9   5213687      * |  19915573 2009-11-15
##        [5]        6  32465390      * |  19915573 2009-11-15
##        ...      ...       ...    ... .       ...        ...
##   [383366]       10  68192278      * |  34077760 2021-06-01
##   [383367]       13 110066208      * |  34077760 2021-06-01
##   [383368]       21  28133942      * |  34077760 2021-06-01
##   [383369]        1  91730044      * |  34077760 2021-06-01
##   [383370]       11  58646437      * |  34077760 2021-06-01
##                     DISEASE/TRAIT        SNPS
##                       <character> <character>
##        [1]     Ulcerative colitis   rs1801274
##        [2]     Ulcerative colitis   rs9263739
##        [3]     Ulcerative colitis  rs17085007
##        [4]     Ulcerative colitis  rs10975003
##        [5]     Ulcerative colitis   rs2395185
##        ...                    ...         ...
##   [383366] Vertical cup-disc ra..  rs10998007
##   [383367] Vertical cup-disc ra..  rs12875868
##   [383368] Vertical cup-disc ra..   rs6516818
##   [383369] Vertical cup-disc ra..  rs10783002
##   [383370] Vertical cup-disc ra..   rs1938598
##   -------
##   seqinfo: 24 sequences from GRCh38 genome

1.4 Getting a recent version of the GWAS catalog

We use BiocFileCache to manage downloaded TSV from EBI’s download site. The file is provided without compression, so prepare for 200+MB download if you are not working from a cache. There is no etag set, so you have to check for updates on your own.

## function (url = "http://www.ebi.ac.uk/gwas/api/search/downloads/alternative", 
##     cache = BiocFileCache::BiocFileCache(), refresh = FALSE, 
##     ...) 
## NULL

This is converted to a manageable extension of GRanges using process_gwas_dataframe.

## function (df) 
## NULL

2 Illustrations: computing

Available functions are:

## gwascat loaded.  Use makeCurrentGwascat() to extract current image.
##  from EBI.  The data folder of this package has some legacy extracts.
##  [1] "as_GRanges"             "bindcadd_snv"           "getRsids"              
##  [4] "getTraits"              "get_cached_gwascat"     "gwascat_from_AHub"     
##  [7] "gwcat_snapshot"         "gwcex2gviz"             "ldtagr"                
## [10] "locs4trait"             "makeCurrentGwascat"     "obo2graphNEL"          
## [13] "process_gwas_dataframe" "riskyAlleleCount"       "subsetByChromosome"    
## [16] "subsetByTraits"         "topTraits"              "traitsManh"

An extended GRanges instance with a sample of 50000 SNP-disease associations reported on 30 April 2020 is obtained as follows, with addresses based on the GRCh38 genome build. We use gwtrunc to refer to it in the sequel.

To determine the most frequently occurring traits in this sample:

## 
##                        Blood protein levels 
##                                        1941 
##                   Heel bone mineral density 
##                                        1309 
##                             Body mass index 
##                                        1283 
##                                      Height 
##                                        1238 
##                           Metabolite levels 
##                                         691 
##                     Systolic blood pressure 
##                                         654 
##                               Schizophrenia 
##                                         643 
## Educational attainment (years of education) 
##                                         642 
##          Post bronchodilator FEV1/FVC ratio 
##                                         479 
##                             Type 2 diabetes 
##                                         466

For a given trait, obtain a GRanges with all recorded associations; here only three associations are shown:

## gwasloc instance with 3 records and 38 attributes per record.
## Extracted:  2020-04-30 23:24:51 
## metadata()$badpos includes records for which no unique locus was given.
## Genome:  GRCh38 
## Excerpt:
## GRanges object with 3 ranges and 3 metadata columns:
##       seqnames    ranges strand |   DISEASE/TRAIT        SNPS   P-VALUE
##          <Rle> <IRanges>  <Rle> |     <character> <character> <numeric>
##   [1]        7  21567734      * | LDL cholesterol  rs12670798     6e-09
##   [2]        5  75355259      * | LDL cholesterol   rs3846662     2e-11
##   [3]        2  43837951      * | LDL cholesterol   rs6756629     3e-10
##   -------
##   seqinfo: 24 sequences from GRCh38 genome

3 Some visualizations

3.2 Annotated Manhattan plot

A simple call permits visualization of GWAS results for a small number of traits. Note the defaults in this call.