process.eqtl.locus | R Documentation |
Same as process.locus
, but for use with eQTL data. Processes the summary statistics for the eQTL data and
all phenotypes within the specified genes and computes all parameters necessary for analysis.
process.eqtl.locus(
gene,
eqtl.input,
phenos = NULL,
min.K = 2,
prune.thresh = 99,
max.prop.K = 0.75,
drop.failed = T
)
gene |
Gene to analyse, from the available genes in eqtl.input$current.genes. Can either be a gene name, or a numeric index. |
eqtl.input |
Input object created with the |
phenos |
Subset of phenotypes from the input object to process. If NULL (default), all phenotypes will be processed |
min.K |
Minimum number of PCs required to process locus (cannot be less than two). If this criterion is not met, the function will fail and the locus cannot be analysed. |
prune.thresh |
PC pruning threshold governing the maximum number of PCs to retain. |
max.prop.K |
Upper bound on retained number of PCs as proportion of lowest sample size of input data. |
drop.failed |
Determines if failed phenotypes are removed from the output object (default) or retained. PCs are selected as such that the cumulative proportion of variance explained is at least that of the threshold (set to 99 percent by default). |
Returns an environment containing general locus info, the processed locus related sumstats, and parameters required for analysis. If the function fails (e.g. due to too few SNPs), it will return NULL. If processing fails for specific phenotypes, only the successful phenotypes will be returned (unless the drop.failed argument is set to true).
id - locus ID
chr / start / stop - locus coordinates
snps - list of locus SNPs
n.snps - number of SNPs within locus
K - number of PCs retained
delta - PC projected joint SNP effects
sigma - sampling covariance matrix
omega - genetic covariance matrix
omega.cor - genetic correlation matrix
N - vector of average N across locus SNPs for each phenotype
phenos - phenotype IDs
binary - boolean vector indicating whether phenotypes are binary
h2.obs - observed local heritability
h2.latent - estimated local population heritability (only relevant for binary phenotypes; requires population prevalence to be specified in the input info file)
failed - boolean vector indicating whether phenotypes failed during processing (only present if drop.failed=F)
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