hicrep-package: HiCRep pipeline calculates reproducibility of Hi-C...

In MonkeyLB/hicrep: Measuring the reproducibility of Hi-C data

Description

The pipelne is a two-step method. The first step is to smooth the Hi-C matrix, and the #' second step is to calculate the stratum-adjusted correlation coefficient (scc). The method also provides the estimation of asymptotic standard deviation of scc.

Details

• Package: hicrep

• Type: Package

• Version: 0.99.6

• Date: 2017-2-5

• License: GPL-2

• LazyLoad: Yes

The main functions are get.scc and htrain. The function get.scc computes scc and its asymptotic standard deviation, and the function htrain estimates optimal smoothing neighborhood size from the input matrices.

Author(s)

Tao Yang Maintainer: Tao Yang <[e-mail]>

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

data(HiCR1)
data(HiCR2)

#Estimate the optimial smoothing neighborhood size parameter
h_hat <- htrain(HiCR1, HiCR2, 1000000, 0, 5000000, 0:2)

scc.out <- get.scc(HiCR1, HiCR2, 1000000, 0)
scc.out$scc
scc.out$std

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