## ----load_packages, include=FALSE----------------------------------------
knitr::opts_knit$set(progress = TRUE, verbose = TRUE)
library(hicrep)
data("HiCR1")
data("HiCR2")
## ------------------------------------------------------------------------
dim(HiCR1)
HiCR1[1:10,1:10]
## ---- eval=TRUE----------------------------------------------------------
scc.out = get.scc(HiCR1, HiCR2, 1000000, 2, 0, 5000000)
#SCC score
scc.out$scc
#Standard deviation of SCC
scc.out$std
## ---- eval = TRUE--------------------------------------------------------
smd_mat = fast.mean.filter(HiCR1, 2)
## ---- eval=TRUE----------------------------------------------------------
h_hat <- htrain(HiCR1, HiCR2, 1000000, lbr = 0, ubr = 5000000, range = 0:2)
h_hat
## ------------------------------------------------------------------------
#check total number of reads before adjustment
sum(HiCR1)
# sub-sample 200000 total reads
DS_HiCR1 <- depth.adj(HiCR1, 200000)
#check total number of reads after adjustment
sum(DS_HiCR1)
## ------------------------------------------------------------------------
sessionInfo()
## ------------------------------------------------------------------------
#check total number of reads before adjustment
sum(HiCR1)
# sub-sample 200000 total reads
DS_HiCR1 <- depth.adj(HiCR1, 200000)
#check total number of reads after adjustment
sum(DS_HiCR1)
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