get.scc: calculate the stratum-adjusted correlation coefficient

Description Usage Arguments Details Value References Examples

Description

calculate the stratum-adjusted correlation coefficient

Usage

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get.scc(mat1, mat2, resol, h, lbr = 0, ubr = 5e+06)

Arguments

mat1

Replicate 1 : a n*n intrachromosome Hi-C contact map.

mat2

Replicate 2 : a n*n intrachromosome Hi-C contact map.

resol

An integer indicating the resolution of the Hi-C matrix.

h

An integer indicating the size of the smoothing neighborhood.

lbr

An integer indicating the minumum distance of interaction that is considered. Default is 0.

ubr

An integer indicating the maximum distance of interaction that is considered. Defalt is 5000000.

Details

The function stratifies the Hi-C reads count according to their interacting distance, calculates the Pearson correlation coefficient for each stratum, then aggregrates them using a weighted average.

Value

A list of results including stratum-specific correlation coefficients, weights, stratum-adjusted correlation coefficient (scc), and the asymptotic standard deviation of scc.

References

HiCRep: assessing the reproducibility of Hi-C data using a stratum-adjusted correlation coefficient. Tao Yang, Feipeng Zhang, Galip Gurkan Yardimci, Fan Song, Ross C Hardison, William Stafford Noble, Feng Yue, Qunhua Li. Genome Research 2017. doi: 10.1101/gr.220640.117

Examples

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data(HiCR1)
data(HiCR2)
scc.out = get.scc(HiCR1, HiCR2, 100000, 0, 0, 5000000)
scc.out$scc
scc.out$std

MonkeyLB/hicrep documentation built on Dec. 15, 2020, 12:47 a.m.