Description Usage Arguments Details Value Author(s) Examples
Calculations association test statistics for each genetic variant in a block.
1 2 3 4 5 6 7 8 9 10 11 12 | blockassoc(qcall, data, minimac,
usubjid = getOption("gtx.usubjid", "USUBJID"),
threshold.MAF = 0, threshold.Rsq = 0, threshold.pass = NULL,
message.begin = "blockassoc", out.signif = 6, use.compiled = FALSE)
## S3 method for class 'lm'
blockstats(m1, m0, coefname = "GENOTYPE")
## S3 method for class 'glm'
blockstats(m1, m0, coefname = "GENOTYPE")
## S3 method for class 'coxph'
blockstats(m1, m0, coefname = "GENOTYPE")
## S3 method for class 'clm'
blockstats(m1, m0, coefname = "GENOTYPE")
|
qcall |
A quoted call to a model fitting function |
data |
Data frame (phenotype data) in which qcall is to be evaluated |
minimac |
Path to minimac inputed genotype info and dosages |
usubjid |
Name of the unique subject id variable in |
threshold.MAF |
Minimum minor allele frequency (MAF) for inclusion in output |
threshold.Rsq |
Minimum imputation quality (Rsq) for inclusion in output |
threshold.pass |
Character vector of SNP names to include in output independent of MAF or Rsq |
message.begin |
Optional text to begin each progress message with |
out.signif |
Number of significant digits for output |
use.compiled |
Flag whether to use fast C++ code for special cases |
m1 |
Fitted model object with genotype term |
m0 |
Fitted model object without genotype term |
coefname |
Name of the coefficient for genotype in |
TO BE WRITTEN
TO DO - Add arguments for genotypes to be an existing data frame, PLINK binary or –recodeA output, or VCF
Returns a data frame with info and association statistics.
Toby Johnson Toby.x.Johnson@gsk.com
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 | ## Not run:
library(ordinal)
library(survival)
library(MASS)
write.table(blockassoc(quote(lm(simCount ~ sexMale + PC1+PC2+PC3+PC4+PC5+PC6+PC7+PC8+PC9+PC10)),
data = read.table("phenotypes/simCount.pheno", header = TRUE, as.is = TRUE),
minimac = "imputed-20120314/chr22chunk6",
threshold.MAF = 0.01, threshold.Rsq = 0.5),
file = "test-lm.out", row.names = FALSE, quote = FALSE)
write.table(blockassoc(quote(glm(simCount ~ sexMale + PC1+PC2+PC3+PC4+PC5+PC6+PC7+PC8+PC9+PC10,
family = poisson)),
data = read.table("phenotypes/simCount.pheno", header = TRUE, as.is = TRUE),
minimac = "imputed-20120314/chr22chunk6",
threshold.MAF = 0.01, threshold.Rsq = 0.5),
file = "test-glm.out", row.names = FALSE, quote = FALSE)
write.table(blockassoc(quote(clm(factor(simCount) ~ sexMale + PC1+PC2+PC3+PC4+PC5+PC6+PC7+PC8+PC9+PC10)),
data = read.table("phenotypes/simCount.pheno", header = TRUE, as.is = TRUE),
minimac = "imputed-20120314/chr22chunk6",
threshold.MAF = 0.01, threshold.Rsq = 0.5),
file = "test-clm.out", row.names = FALSE, quote = FALSE)
write.table(blockassoc(quote(coxph(Surv(simLife, simSurv) ~ sexMale + PC1+PC2+PC3+PC4+PC5+PC6+PC7+PC8+PC9+PC10)),
data = read.table("phenotypes/simLife.pheno", header = TRUE, as.is = TRUE),
minimac = "imputed-20120314/chr22chunk6",
threshold.MAF = 0.01, threshold.Rsq = 0.5),
file = "test-coxph.out", row.names = FALSE, quote = FALSE)
## End(Not run)
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