calEnrichment: Compute bias towards SNPs with allelic DNA imbalance
In redaq/atMPRA: Analysis Toolset for MPRA data

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/calEnrichment.R

This function uses hypergeometric tests to compute enrichment in SNPs with significant allelic DNA imbalance among the SNPs with significant allele-specific effect defined by each method.

1	calEnrichment(resultAll, threshold = 0.05)

`resultAll`	A data frame containing the p-values for all SNPs using a number of analyses methods. This can be generated using /codeanalyzeMPRA. The first column is named 'simN' which is the SNP name, the second column is the p-value indicating whether there is allelic DNA-imbalance for the SNP. The other columns are the p-values for testing allele-specific effects using different methods.
`threshold`	The significance level used. 0.05 is the default.

This method to used to check for bias in the specified tests caused by allelic DNA imbalance, i.e. difference in the DNA count distributions between the two alleles.

enrichmen

A data frame containing the enrichment p-values for each method. Column 'q' refers to the number of significant SNPs with allelic DNA imbalance. Column 'm' refers to the number of significant tests with allele-specific effect defined by each method in each row. 'enrichP' is the p-value from the hypergeometric test. Only SNPs with valid test p-values were considered here.

Dandi Qiao

Qiao, D., Zigler, C., Cho, M.H., Silverman, E.K., Zhou, X., et al. (2018). Statistical considerations for the analysis of massively parallel reporter assays data.

atMPRA atMPRA atMPRA atMPRA

nsim = 10
ntag = 10
slope=c(rep(1, ntag*nsim), rep(1.5, ntag*nsim)) 
nrep=5
data(datMean)
simData = sim_fixTotalD(datMean=datMean, totalDepth=200000, sigma2_DNA_a0=0.001, sigma2_DNA_a1=0.23, sigma2_RNA_a0=0.18, sigma2_RNA_a1=35, ntag=ntag, nsim=nsim, nrep=nrep, slope=slope)
results = analyzeMPRA(simData, nrep, rnaCol=2+nrep+1, nrep, nsim, ntag, method=c("MW","mpralm", "edgeR", "DESeq2"), cutoff=0, cutoffo=0)
calEnrichment(results)