add_R2_to_dataset_list: Harmonize R2 and MAF inputs
In AbbVie-ComputationalGenomics/POEMColoc: Implement POEM colocalization method
Description
Usage
Arguments
Examples
View source: R/add_R2_to_dataset_list.R
Description
Harmonize R2 and MAF inputs
Usage
1
2
add_R2_to_dataset_list(dataset_list, gds_file, R2, MAF, subset,
window_size, get_dosage_fn = get_dosage_alt)
Arguments
dataset_list
list of datasets formatted according to the requirements of coloc.abf with the following differences
pos, and chr are additionally required.
snp is ignored as it is determined by pos.
For top SNP datasets, R2 and MAF and gds_file and subset are optional, if supplied as arguments to the function.
For full summary statistic datasets, MAF is required.
imputation class either all or top
top_pos giving the position of the top p-value
gds_file
path to a gds file for the reference panel. Can be NULL if specifying R2 and MAF, or if supplying within dataset.
R2
A matrix of R2 LD between SNP positions. This should contain LD information for top SNPs in rows and LD for positions to be imputed in columns. Can be NULL if specifying gds_file or if included in individual datasets.
Column and row names should be position.
MAF
optional input of minor allele frequencies.
only used for top SNP datasets
names should be position
subset
optional parameter that is the path to a file giving the names of samples to include as formatted in the gds file. each line should be the name of a sample.
window_size
if NULL, window size is determined to cover all positions in dataset_list
if specified, covers all positions in dataset list plus window_size around top SNP dataset
get_dosage_fn
a function taking gds file connection and returning
a matrix with the genotype or imputed dosage at each position. The function
should not perform any filtering or reordering of variants. rows must correspond
to individuals and columns to positions.
Examples
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# R2 and MAF from function
dataset_top_SNP <- list(pos = 2, N= 10000, s =0.5, type="cc", pvalues = 10^-9, chr = "Z", imputation_class = "top", top_pos=2, snp="2")
dataset_full <- list(pos = c(1, 2, 4), N=1000, type ="quant", pvalues = c(2 * 10^-8, 4 * 10^-8, 0.01), chr= "Z", snp = c("1","2","4"), imputation_class = "all", MAF = c(0.2,0.4, 0.3))
R2 <- matrix(data = c(0.94, 1, 0.65, 0, 0.51, 0.32, 0.64, 0.65, 1, 0, 0.21, 0.12), nrow=2, byrow=TRUE)
colnames(R2) <- 1:6
rownames(R2) <- 2:3
MAF = c(0.14, 0.15, 0.25, 0.2, 0.4, 0.25)
names(MAF) <- 1:6
add_R2_to_dataset_list(list(dataset_full, dataset_top_SNP), R2 = R2, MAF = MAF, subset = NULL, window_size= 2, gds_file=NULL)
# R2 and MAF from function some positions missing from to impute
add_R2_to_dataset_list(list(dataset_full, dataset_top_SNP), R2 = R2[,c("1","2")], MAF = MAF[c("1","2")], subset = NULL, window_size= 2, gds_file=NULL)
add_R2_to_dataset_list(list(dataset_full, dataset_top_SNP), R2 = R2[,c("1","2")], MAF = MAF[c("2")], subset = NULL, window_size= 2, gds_file=NULL)
# R2 and MAF from function top position missing
add_R2_to_dataset_list(list(dataset_full, dataset_top_SNP), R2 = R2[c("3"),,drop=FALSE], MAF = MAF, subset = NULL, window_size= 2, gds_file=NULL)
# R2 and MAF from input
dataset_top_SNP2 <- list(pos = 2, N= 10000, s =0.5, type="cc", pvalues = 10^-9, chr = "Z", imputation_class = "top", top_pos=2, snp="2", R2=R2, MAF=MAF)
add_R2_to_dataset_list(list(dataset_full, dataset_top_SNP2), gds_file = NULL, subset = NULL, R2 = NULL, MAF = NULL, window_size= 2)
dataset_top_SNP3 <- list(pos = 2, N= 10000, s =0.5, type="cc", pvalues = 10^-9, chr = "Z", imputation_class = "top", top_pos=2, snp="2", R2=R2["2",], MAF=MAF)
add_R2_to_dataset_list(list(dataset_full, dataset_top_SNP3), gds_file = NULL, subset = NULL, R2 = NULL, MAF = NULL, window_size= 2)
# R2 and MAF from input some positions missing
dataset_top_SNP4 <- list(pos = 2, N= 10000, s =0.5, type="cc", pvalues = 10^-9, chr = "Z", imputation_class = "top", top_pos=2, snp="2", R2=R2["2",c("1","2")], MAF=MAF[c("1","2")])
add_R2_to_dataset_list(list(dataset_full, dataset_top_SNP4), gds_file = NULL, subset = NULL, R2 = NULL, MAF = NULL, window_size= 2)
gds_file <- system.file("extdata", "example.gds", package = "POEMColoc")
gds_file2 <- system.file("extdata", "example2.gds", package = "POEMColoc")
subset <- system.file("extdata", "subset.ped", package = "POEMColoc")
subset2 <- system.file("extdata", "subset2.ped", package = "POEMColoc")
# R2 and MAF from gds function
dataset_top_SNP5 <- list(pos = 2, N= 10000, s =0.5, type="cc", pvalues = 10^-9, chr = "Z", imputation_class = "top", top_pos=2, snp="2")
add_R2_to_dataset_list(list(dataset_full, dataset_top_SNP5), gds_file = gds_file, subset = subset2, R2 = NULL, MAF = NULL, window_size= 2)
add_R2_to_dataset_list(list(dataset_full, dataset_top_SNP5), gds_file = gds_file, subset = subset2, R2 = NULL, MAF = NULL, window_size= 3)
# R2 and MAF from gds function some positions missing
dataset_full2 <- list(pos = c(1, 2, 7), N=1000, type ="quant", pvalues = c(2 * 10^-8, 4 * 10^-8, 0.01), chr= "Z", snp = c("1","2","7"), imputation_class = "all", MAF = c(0.2,0.4, 0.3))
add_R2_to_dataset_list(list(dataset_full2, dataset_top_SNP5), gds_file = gds_file, subset = subset2, R2 = NULL, MAF = NULL, window_size= 1)
# R2 and MAF from gds dataset
dataset_top_SNP6 <- list(pos = 2, N= 10000, s =0.5, type="cc", pvalues = 10^-9, chr = "Z", imputation_class = "top", top_pos=2, snp="2", gds_file = gds_file)
add_R2_to_dataset_list(list(dataset_full2, dataset_top_SNP6), gds_file = gds_file, subset = subset2, R2 = NULL, MAF = NULL, window_size= 1)
# MAF from function should fail for full summary statistics - not supported
dataset_full3 <- list(pos = c(1, 2, 4), N=1000, type ="quant", pvalues = c(2 * 10^-8, 4 * 10^-8, 0.01), chr= "Z", snp = c("1","2","4"), imputation_class = "all")
try(add_R2_to_dataset_list(list(dataset_full3, dataset_top_SNP6), gds_file = gds_file, subset = subset2, R2 = NULL, MAF = MAF, window_size= 1))
# Should fail due to missing MAF
dataset_full4 <- list(pos = c(1, 2, 7), N=1000, type ="quant", pvalues = c(2 * 10^-8, 4 * 10^-8, 0.01), chr= "Z", snp = c("1","2","7"), imputation_class = "all")
try(add_R2_to_dataset_list(list(dataset_full4, dataset_top_SNP6), gds_file = gds_file, subset = subset2, R2 = NULL, MAF = NULL, window_size= 1))
# Same datasets in a list
add_R2_to_dataset_list(list(dataset_full, dataset_full2, dataset_top_SNP, dataset_top_SNP2, dataset_top_SNP3, dataset_top_SNP4, dataset_top_SNP5, dataset_top_SNP6), gds_file = gds_file, subset = subset2, R2 = R2, MAF = MAF, window_size= 3)
# complex input with different gds
add_R2_to_dataset_list(list(c(dataset_top_SNP, list(gds_file = gds_file, subset = subset)),
c(dataset_top_SNP, list(gds_file = gds_file, subset = subset2)),
c(dataset_top_SNP, list(gds_file = gds_file2, subset = subset)), dataset_full, dataset_full2), R2 = NULL, MAF = NULL, gds_file = NULL, subset=NULL, window_size =1)
AbbVie-ComputationalGenomics/POEMColoc documentation built on May 20, 2020, 12:32 a.m.
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Description Usage Arguments Examples
View source: R/add_R2_to_dataset_list.R
Description
Harmonize R2 and MAF inputs
Usage
1 2 | add_R2_to_dataset_list(dataset_list, gds_file, R2, MAF, subset,
window_size, get_dosage_fn = get_dosage_alt)
|
Arguments
dataset_list |
list of datasets formatted according to the requirements of coloc.abf with the following differences pos, and chr are additionally required. snp is ignored as it is determined by pos. For top SNP datasets, R2 and MAF and gds_file and subset are optional, if supplied as arguments to the function. For full summary statistic datasets, MAF is required. imputation class either all or top top_pos giving the position of the top p-value |
gds_file |
path to a gds file for the reference panel. Can be NULL if specifying R2 and MAF, or if supplying within dataset. |
R2 |
A matrix of R2 LD between SNP positions. This should contain LD information for top SNPs in rows and LD for positions to be imputed in columns. Can be NULL if specifying gds_file or if included in individual datasets. Column and row names should be position. |
MAF |
optional input of minor allele frequencies. only used for top SNP datasets names should be position |
subset |
optional parameter that is the path to a file giving the names of samples to include as formatted in the gds file. each line should be the name of a sample. |
window_size |
if NULL, window size is determined to cover all positions in dataset_list if specified, covers all positions in dataset list plus window_size around top SNP dataset |
get_dosage_fn |
a function taking gds file connection and returning a matrix with the genotype or imputed dosage at each position. The function should not perform any filtering or reordering of variants. rows must correspond to individuals and columns to positions. |
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 | # R2 and MAF from function
dataset_top_SNP <- list(pos = 2, N= 10000, s =0.5, type="cc", pvalues = 10^-9, chr = "Z", imputation_class = "top", top_pos=2, snp="2")
dataset_full <- list(pos = c(1, 2, 4), N=1000, type ="quant", pvalues = c(2 * 10^-8, 4 * 10^-8, 0.01), chr= "Z", snp = c("1","2","4"), imputation_class = "all", MAF = c(0.2,0.4, 0.3))
R2 <- matrix(data = c(0.94, 1, 0.65, 0, 0.51, 0.32, 0.64, 0.65, 1, 0, 0.21, 0.12), nrow=2, byrow=TRUE)
colnames(R2) <- 1:6
rownames(R2) <- 2:3
MAF = c(0.14, 0.15, 0.25, 0.2, 0.4, 0.25)
names(MAF) <- 1:6
add_R2_to_dataset_list(list(dataset_full, dataset_top_SNP), R2 = R2, MAF = MAF, subset = NULL, window_size= 2, gds_file=NULL)
# R2 and MAF from function some positions missing from to impute
add_R2_to_dataset_list(list(dataset_full, dataset_top_SNP), R2 = R2[,c("1","2")], MAF = MAF[c("1","2")], subset = NULL, window_size= 2, gds_file=NULL)
add_R2_to_dataset_list(list(dataset_full, dataset_top_SNP), R2 = R2[,c("1","2")], MAF = MAF[c("2")], subset = NULL, window_size= 2, gds_file=NULL)
# R2 and MAF from function top position missing
add_R2_to_dataset_list(list(dataset_full, dataset_top_SNP), R2 = R2[c("3"),,drop=FALSE], MAF = MAF, subset = NULL, window_size= 2, gds_file=NULL)
# R2 and MAF from input
dataset_top_SNP2 <- list(pos = 2, N= 10000, s =0.5, type="cc", pvalues = 10^-9, chr = "Z", imputation_class = "top", top_pos=2, snp="2", R2=R2, MAF=MAF)
add_R2_to_dataset_list(list(dataset_full, dataset_top_SNP2), gds_file = NULL, subset = NULL, R2 = NULL, MAF = NULL, window_size= 2)
dataset_top_SNP3 <- list(pos = 2, N= 10000, s =0.5, type="cc", pvalues = 10^-9, chr = "Z", imputation_class = "top", top_pos=2, snp="2", R2=R2["2",], MAF=MAF)
add_R2_to_dataset_list(list(dataset_full, dataset_top_SNP3), gds_file = NULL, subset = NULL, R2 = NULL, MAF = NULL, window_size= 2)
# R2 and MAF from input some positions missing
dataset_top_SNP4 <- list(pos = 2, N= 10000, s =0.5, type="cc", pvalues = 10^-9, chr = "Z", imputation_class = "top", top_pos=2, snp="2", R2=R2["2",c("1","2")], MAF=MAF[c("1","2")])
add_R2_to_dataset_list(list(dataset_full, dataset_top_SNP4), gds_file = NULL, subset = NULL, R2 = NULL, MAF = NULL, window_size= 2)
gds_file <- system.file("extdata", "example.gds", package = "POEMColoc")
gds_file2 <- system.file("extdata", "example2.gds", package = "POEMColoc")
subset <- system.file("extdata", "subset.ped", package = "POEMColoc")
subset2 <- system.file("extdata", "subset2.ped", package = "POEMColoc")
# R2 and MAF from gds function
dataset_top_SNP5 <- list(pos = 2, N= 10000, s =0.5, type="cc", pvalues = 10^-9, chr = "Z", imputation_class = "top", top_pos=2, snp="2")
add_R2_to_dataset_list(list(dataset_full, dataset_top_SNP5), gds_file = gds_file, subset = subset2, R2 = NULL, MAF = NULL, window_size= 2)
add_R2_to_dataset_list(list(dataset_full, dataset_top_SNP5), gds_file = gds_file, subset = subset2, R2 = NULL, MAF = NULL, window_size= 3)
# R2 and MAF from gds function some positions missing
dataset_full2 <- list(pos = c(1, 2, 7), N=1000, type ="quant", pvalues = c(2 * 10^-8, 4 * 10^-8, 0.01), chr= "Z", snp = c("1","2","7"), imputation_class = "all", MAF = c(0.2,0.4, 0.3))
add_R2_to_dataset_list(list(dataset_full2, dataset_top_SNP5), gds_file = gds_file, subset = subset2, R2 = NULL, MAF = NULL, window_size= 1)
# R2 and MAF from gds dataset
dataset_top_SNP6 <- list(pos = 2, N= 10000, s =0.5, type="cc", pvalues = 10^-9, chr = "Z", imputation_class = "top", top_pos=2, snp="2", gds_file = gds_file)
add_R2_to_dataset_list(list(dataset_full2, dataset_top_SNP6), gds_file = gds_file, subset = subset2, R2 = NULL, MAF = NULL, window_size= 1)
# MAF from function should fail for full summary statistics - not supported
dataset_full3 <- list(pos = c(1, 2, 4), N=1000, type ="quant", pvalues = c(2 * 10^-8, 4 * 10^-8, 0.01), chr= "Z", snp = c("1","2","4"), imputation_class = "all")
try(add_R2_to_dataset_list(list(dataset_full3, dataset_top_SNP6), gds_file = gds_file, subset = subset2, R2 = NULL, MAF = MAF, window_size= 1))
# Should fail due to missing MAF
dataset_full4 <- list(pos = c(1, 2, 7), N=1000, type ="quant", pvalues = c(2 * 10^-8, 4 * 10^-8, 0.01), chr= "Z", snp = c("1","2","7"), imputation_class = "all")
try(add_R2_to_dataset_list(list(dataset_full4, dataset_top_SNP6), gds_file = gds_file, subset = subset2, R2 = NULL, MAF = NULL, window_size= 1))
# Same datasets in a list
add_R2_to_dataset_list(list(dataset_full, dataset_full2, dataset_top_SNP, dataset_top_SNP2, dataset_top_SNP3, dataset_top_SNP4, dataset_top_SNP5, dataset_top_SNP6), gds_file = gds_file, subset = subset2, R2 = R2, MAF = MAF, window_size= 3)
# complex input with different gds
add_R2_to_dataset_list(list(c(dataset_top_SNP, list(gds_file = gds_file, subset = subset)),
c(dataset_top_SNP, list(gds_file = gds_file, subset = subset2)),
c(dataset_top_SNP, list(gds_file = gds_file2, subset = subset)), dataset_full, dataset_full2), R2 = NULL, MAF = NULL, gds_file = NULL, subset=NULL, window_size =1)
|
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