Package 'gwasglue'

Perform LD clumping

Description

<full description>

Usage

clump_gwasvcf(
  vcf,
  clump_kb = 1000,
  clump_r2 = 0.001,
  clump_p = 5e-08,
  pop = NULL,
  bfile = NULL,
  plink_bin = NULL,
  access_token = NULL
)

Arguments

vcf	VCF file or VCF object
clump_kb	Clumping kb window. Default is very strict, 10000
clump_r2	Clumping r2 threshold. Default is very strict, 0.001
clump_p	Clumping sig level for index variants. Default = 1 (i.e. no threshold)
pop	Super-population to use as reference panel. Default = "EUR". Options are EUR, SAS, EAS, AFR, AMR. 'legacy' also available - which is a previously used verison of the EUR panel with a slightly different set of markers
bfile	If this is provided then will use the API. Default = NULL
plink_bin	If null and bfile is not null then will detect packaged plink binary for specific OS. Otherwise specify path to plink binary. Default = NULL
access_token	Google OAuth2 access token. Used to authenticate level of access to data

Value

data frame of clumped results

---

Perform conditional analysis using GCTA COJO

Description

For a list of fine-mapped rsids, will assign to regions and generate conditionally independent summary stats for each rsid

Usage

cojo_cond(
  vcffile,
  bfile,
  snplist,
  pop,
  gcta = genetics.binaRies::get_gcta_binary(),
  workdir = tempdir(),
  threads = 1
)

Arguments

vcffile	Path to vcffile
bfile	LD reference panel
snplist	List of rsids
pop	EUR, ASN or AFR
gcta	Path to gcta binary. For convenience can use default=genetics.binaRies::get_gcta_binary()
workdir	Location to store temporary files. Default=tempdir()
threads	Number of parallel threads. Default=1

Value

List of independent summary stats

---

Write vcf file to cojo sumstat file

Description

Write vcf file to cojo sumstat file

Usage

cojo_sumstat_file(vcffile, outfile)

Arguments

vcffile	Path to vcf file
outfile	Path to output file

Value

vcf object

---

Convert coloc dataset to gassocplot dataset

Description

Convert coloc dataset to gassocplot dataset

Usage

coloc_to_gassocplot(coloclist, bfile = NULL, plink_bin = NULL)

Arguments

coloclist	Output from *_to_coloc
bfile	If number of SNPs > 500 then need to provide your own LD reference panel. Provide plink dataset here.
plink_bin	If number of SNPs > 500 then need to provide your own LD reference panel. Provide plink executable here

Value

List to feed into gassocplot

---

Generate coloc dataset from vcf files

Description

Generate coloc dataset from vcf files

Usage

gwasvcf_to_coloc(vcf1, vcf2, chrompos)

Arguments

vcf1	VCF object or path to vcf file
vcf2	VCF object or path to vcf file
chrompos	Character of chr:pos1-pos2

Value

List of datasets to feed into coloc

---

Generate data for fine mapping analysis

Description

For a given region and VCF file, extracts the variants in the region along with LD matrix from a reference panel

Usage

gwasvcf_to_finemapr(
  region,
  vcf,
  bfile,
  plink_bin = genetics.binaRies::get_plink_binary(),
  threads = 1
)

Arguments

region	Region of the genome to extract eg 1:109317192-110317192". Can be array
vcf	Path to VCF file or VCF object
bfile	LD reference panel
plink_bin	Path to plink. Default = genetics.binaRies::get_plink_binary()
threads	Number of threads to run in parallel. Default=1

Value

List of datasets for finemapping

---

Create exposure or outcome data format for TwoSampleMR from vcf

Description

Create exposure or outcome data format for TwoSampleMR from vcf

Usage

gwasvcf_to_TwoSampleMR(vcf, type = "exposure")

Arguments

vcf	VCF object
type	="exposure" or "outcome"

Value

data frame

---

Generic harmonisation function

Description

Assumes ref and alt alleles available for target and reference datasets, and uses chr:pos for alignment

Usage

harmonise(
  chr1,
  pos1,
  ref1,
  alt1,
  chr2,
  pos2,
  ref2,
  alt2,
  rsid2 = NULL,
  indel_recode = FALSE,
  strand_flip = FALSE
)

Arguments

chr1	Vector
pos1	Vector
ref1	Vector
alt1	Vector
chr2	Vector
pos2	Vector
ref2	Vector
alt2	Vector
rsid2	Optional vector
indel_recode	=FALSE. If TRUE then attempts to recode D/I
strand_flip	=FALSE. If TRUE then attempts to flip strand when alignment is not otherwise possible

Details

0: stick 1: swap 2: rename indel 3: rename indel and swap 4: flip 5: flip and swap 6: drop (no match) 7: drop (no reference)

Value

Dataframe of outcomes

---

Harmonise gwas alleles to be same as reference

Description

Harmonise gwas alleles to be same as reference

Usage

harmonise_against_ref(gwas, reference)

Arguments

gwas	<what param does>
reference	<what param does>

Value

data frame with attributes

---

Generate coloc dataset from the IEU GWAS database

Description

Generate coloc dataset from the IEU GWAS database

Usage

ieugwasr_to_coloc(id1, id2, chrompos, type1 = NULL, type2 = NULL)

Arguments

id1	ID for trait 1
id2	ID for trait 2
chrompos	Character of chr:pos1-pos2
type1	Provide "cc" or "quant" to override automatic lookup of trait type for trait 1
type2	Provide "cc" or "quant" to override automatic lookup of trait type for trait 2

Value

List of datasets to feed into coloc

---

Generate data for analysis in various finemapping methods

Description

Uses the finemapr package https://github.com/variani/finemapr

Usage

ieugwasr_to_finemapr(region, id, bfile = NULL, plink_bin = NULL)

Arguments

region	Region of the genome to extract eg 1:109317192-110317192"
id	Array of GWAS studies to query. See gwasinfo for available studies
bfile	If this is provided then will use the API. Default = NULL
plink_bin	If null and bfile is not null then will detect packaged plink binary for specific OS. Otherwise specify path to plink binary. Default = NULL

Value

Each id will be a list of z score data, ld matrix, and sample size

---

Generate regional plot for ieugwasr

Description

Uses James Staley's gassocplot package https://github.com/jrs95/gassocplot

Usage

ieugwasr_to_gassocplot(chrpos, id, bfile = NULL, plink_bin = NULL)

Arguments

chrpos	A window range to plot e.g. 16:3349655-3849655
id	Vector of one or more IEU GWAS db study IDs
bfile	If number of SNPs > 500 then need to provide your own LD reference panel. Provide plink dataset here.
plink_bin	If number of SNPs > 500 then need to provide your own LD reference panel. Provide plink executable here

Value

assoc_plot or stack_assoc_plot if multiple markers given

---

Convert output from query to TwoSampleMR format

Description

Convert output from query to TwoSampleMR format

Usage

ieugwasr_to_TwoSampleMR(x, type = "exposure")

Arguments

x	Output from ieugwasr query e.g. associations, tophits, phewas
type	"exposure" (default) or "outcome"

Value

data frame

---

Check a GWAS dataset against a reference known to be on the forward strand

Description

Assuming reference data is all on forward strand, check if the GWAS is also. Use some threshold e.g. if more than 90 need to be flipped then it's likely that the dataset is on the forward strand

Usage

is_forward_strand(
  gwas_snp,
  gwas_a1,
  gwas_a2,
  ref_snp,
  ref_a1,
  ref_a2,
  threshold = 0.9
)

Arguments

gwas_snp	Vector of SNP names for the dataset being checked
gwas_a1	Vector of alleles
gwas_a2	Vector of alleles
ref_snp	Vector of SNP names for the reference dataset
ref_a1	Vector of alleles
ref_a2	Vector of alleles
threshold	=0.9 If the proportion of allele strands match is above this threshold, then declare the dataset to be on the forward strand

Details

This function can be used to evaluate how strict harmonisation should be The trade off if you assume we are not on the forward strand then palindromic SNPs are dropped within a particular frequency range But you could instead have some small probability of error for whether palindromic SNPs are on the forward strand, and avoid dropping too many variants.

Value

1 = Forward strand; 2 = Not on forward strand

---

Create a harmonised dataset from lists of vcf files

Description

This mimics the TwoSampleMR::make_dat function, which automatically looks up exposure and outcome datasets and harmonises them, except this function uses GWAS-VCF datasets instead. The supporting reference datasets can be accessed by UoB users on BC4 using set_bc4_files()

Usage

make_TwoSampleMR_dat(
  id1,
  id2,
  proxies = TRUE,
  nthreads = 1,
  vcfdir = options()$gwasglue.vcfdir,
  proxydb = options()$gwasglue.proxydb,
  rsidx = options()$gwasglue.rsidx,
  bfile = options()$gwasglue.bfile,
  action = 1,
  plink_bin = genetics.binaRies::get_plink_binary()
)

Arguments

id1	Exposure datasets. Either an array of vcf files, or array of IDs if vcfdir is set
id2	Outcome datasets. Either an array of vcf files, or array of IDs if vcfdir is set
proxies	Lookup proxies? default=TRUE but requires either bfile or proxydb to be set
nthreads	Parellelise default=1
vcfdir	Location of vcf files if id1 and id2 are just IDs. Defaults to options()$gwasglue.vcfdir
proxydb	Location of LD proxy database Default=options()$gwasglue.proxydb
rsidx	Location of rsidx index database Default=options()$gwasglue.rsidx
bfile	Location of LD reference panel Default=options()$gwasglue.bfile

Value

harmonised dataset

---

For a set of variants map to LD regions

Description

LD regions defined here https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4731402/

Usage

map_variants_to_regions(chrpos, pop)

Arguments

chrpos	Array of chr:pos
pop	EUR, AFR or ASN

---

Figure out specific files and IDs depending on what files exist and whethet vcfdir is set

Description

Figure out specific files and IDs depending on what files exist and whethet vcfdir is set

Usage

organise_ids(id, vcfdir)

Arguments

id	List of IDs within the vcfdir structure, or a list of GWAS VCF files, or a mixture
vcfdir	Location of GWAS VCF files, or NULL if id is a list of actual files

Value

File paths to all datasets

---

Read in GWAS dataset

Description

Read in GWAS dataset

Usage

read_gwas(
  filename,
  skip,
  delimiter,
  gzipped,
  snp,
  nea,
  ea,
  ea_af,
  effect,
  se,
  pval,
  n,
  info,
  z
)

Arguments

filename	<what param does>
skip	<what param does>
delimiter	<what param does>
gzipped	<what param does>
snp	<what param does>
nea	<what param does>
ea	<what param does>
ea_af	<what param does>
effect	<what param does>
se	<what param does>
pval	<what param does>
n	<what param does>
info	<what param does>
z	<what param does>

Value

data frame with log attributes

---

Read in reference dataset

Description

Read in reference dataset

Usage

read_reference(
  reference_file,
  rsid = NULL,
  chrompos = NULL,
  remove_dup_rsids = TRUE
)

Arguments

reference_file	Reference vcf
rsid	List of variants to read
chrompos	List of chrompos to read
remove_dup_rsids	=TRUE Remove duplicates from output

Value

data frame

---

Determine locations of useful reference datasets on bluecrystal4

Description

This is a convenience function for members at the University of Bristol to automatically set file locations for various reference datasets. It relates only to paths on bc4

Usage

set_bc4_files()

---

Perform fine mapping pipeline using susieR

Description

Clumps data, then maps those to LD representative regions. Within each detected LD representative region, fine mapping is performed

Usage

susieR_pipeline(
  vcffile,
  bfile,
  plink_bin,
  pop,
  threads = 1,
  clump_kb = 1000,
  clump_r2 = 0.001,
  clump_p = 5e-08,
  ...
)

Arguments

vcffile	Path to vcf file
bfile	Path to ld reference panel
plink_bin	Path to plink
pop	EUR, ASN or AFR
clump_kb	<what param does>
clump_r2	<what param does>
clump_p	<what param does>
...	Optional arguments to be passed to susie_rss

Value

List

---

Create format for HPC pipeline

Description

Takes raw files and aligns them to reference. Important if files don't have chr:pos already

Usage

write_out(harmonised, path)

Arguments

harmonised	Output from /codeharmonise_against_ref
path	Path to write out json file and txt file

---