gcq: gcq

In d0minicO/mhscanR: Analysis of Microhomologies in CRISPR/Cas9 Deletions

Description

This function is for calculating GC content in CRISPR/Cas9 deletions that have already been analysed using the mhq function. It filters the deletions for those with a given amount of microhomology and then performs a chi sqaure test to compare the observed vs the expected GC content of the microhomologies.

Usage

gcq(input, MH, equalTo = F, expected, CRISPResso = T)

Arguments

input	dataframe output after running mhq(yourData)
MH	microhomology amount to filter for
equalTo	if set to TRUE search ONLY for microhomologies equal to MH. If set to FALSE search for microhomologies greater than or equal to MH
expected	background GC content over the region containing deletions (if 50 percent background, expected=0.5.) Determined by the user.
CRISPResso	are you analysing a dataframe containing analysed CRISPResso data?

Details

Output is a dataframe with columns:

• baseType = GC bases or AT bases

• baseNum = number of bases of each type (in alleles with the given amount of microhomology)

• baseProb = observed number of bases of each type in the microhomologies analysed (0 to 1 a.k.a 0 to 100

• expectedProb = expected probability (0 to 1) of bases of each type (known background for the region of the deletions - determined by the user)

• pval = chi sqaure test p value (chance of finding the observed vs expected probability)

Examples

gcq(mhqOutCRISPResso, MH=1, equalTo=F, expected=0.46, CRISPResso=T)
gcq(mhqOutSanger, MH=2, equalTo=T, expected=0.51, CRISPResso=F)

d0minicO/mhscanR documentation built on May 4, 2021, 5:22 p.m.