Description Usage Arguments Examples
This is a wrapper function that performs SHLR or SHLR-fam statistic to a genomic region one marker at a time. The scan results will be outputted to a file.
1 2 3 4 5 6 | run.SHLR.scan(haps, phen, marker.map, outfile, outcome,
out.dist = "Gaussian", cov = "", missing.id.code = "0",
method, nSplits = 1, pca.thres = NULL, hap.freq.thres = 0.005,
window.size = 100, threads = NULL, corstr = "kinship",
std.err = "naive", gender = "", fid = "", iid = "", pid = "",
mid = "")
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haps |
Haplotypes array stored as a string of character per row. Every two rows contains the haplotypes for each individual. (Required) |
phen |
Phenotype table. The phenotype table contains information about trait of interest and other covariates. (Required) |
marker.map |
The marker map contains information about marker name (1st column) and marker position (2nd column). (Required) |
outfile |
The desired name of the output file. (Required) |
outcome |
The column name for the phenotype of interest in the phenotype table. (Required) |
out.dist |
The assumed outcome distribution of the model. e.g. : gaussian, binomial, etc. (Required) |
cov |
The column names for the covariates in the phenotype table. |
missing.id.code |
The code for missing id in the pedigree structure. Usually, it is coded as '0'. (Required only if method is 'SHLR-fam' and corstr is 'kinship') |
method |
The choice for the SHLR method (i.e. : SHLR or SHLR-fam). (Required) |
nSplits |
The number of splits. This option will determine how often the program prints out results to the output file. |
pca.thres |
The proportion of variation retained in the design matrix of the model based on PCA. |
hap.freq.thres |
The minimum haplotype frequency proportion threshold. Haplotypes that meet this threshold will be considered in the model. |
window.size |
The number of markers that form the haplotype. |
threads |
The number of CPUs for parallel computation. |
corstr |
The type of correlation structure. The options are: 'kinship', 'exchangeable', or 'independence'. (SHLR-fam parameter) |
std.err |
The method for estimating variance for SHLR-fam. The options are: 'naive' or 'sandwich'. (SHLR-fam parameter) |
gender |
The column name that indicates gender in the phenotype table. (Required if method is SHLR-fam and cor.str is 'kinship') |
fid |
The column name that indicates family id in the phenotype table. (Required if method is SHLR-fam and cor.str is 'kinship') |
iid |
The column name that indicates individual id in the phenotype table. (Required if method is SHLR-fam and cor.str is 'kinship') |
pid |
The column name that indicates father id in the phenotype table. (Required if method is SHLR-fam and cor.str is 'kinship') |
mid |
The column name that indicates mother id in the phenotype table. (Required if method is SHLR-fam and cor.str is 'kinship') |
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 | library(SHLR)
####reading in pedigree data
fam <- read.table(system.file("extdata","plink.fam",package="SHLR"),
header=FALSE, stringsAsFactors=FALSE)
colnames(fam) <- c("fam_id","id","dad_id","mom_id","sex","qtrait")
####add simulated covariates to create phenotype table
N <- dim(fam)[1]
cov1 <- rnorm(N, 0, 2)
cov2 <- rbinom(N, 1, 0.7)
phen <- data.frame(fam, cov1=cov1, cov2=cov2)
##Read phased haplotype
shapeit <- read.shapeit.haps(system.file("extdata","phased.haps",package="SHLR"))
haps <- shapeit$haps
marker.map <- shapeit$marker.map
##Initialize parameters for SHLR.scan
outfile <- "out.txt"
outcome <- "qtrait"
cov <- c("sex","cov1","cov2")
famid <- "fam_id"
iid <- "id"
pid <- "dad_id"
mid <- "mom_id"
gender <- "sex"
missid <- "0"
corstr <- "kinship"
out_dist <- "gaussian"
std.err <- "naive"
method <- "SHLR-fam"
window.size <- 35
pca.thres <- 0.8
nSplits <- 1
run.SHLR.scan(haps, phen, marker.map, outfile,
outcome, out.dist=out_dist, cov=cov, missing.id.code=missid,
method=method, nSplits=nSplits, pca.thres=pca.thres, hap.freq.thres=0.001,
window.size=window.size, threads=2, corstr=corstr,
std.err=std.err, gender=gender, fid=famid, iid=iid, pid=pid, mid=mid)
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