PeakSegJoint (version 2022.4.6)

binSum: binSum

Description

Compute sum of compressed coverage profile in bins, using fast C code.

Usage

binSum(compressed, bin.chromStart = 0L, 
    bin.size = 1L, n.bins = 2000L, 
    empty.as.zero = FALSE)

Arguments

compressed

data.frame with integer columns chromStart, chromEnd, count.

bin.chromStart

Base before first bin.

bin.size

Bin size.

n.bins

Number of bins.

empty.as.zero

Sometimes the last few bins do not have any overlapping data in compressed. If TRUE, set these counts to 0. If FALSE, ignore these bins (returning a data.frame with fewer than n.bins rows).

Value

data.frame with n.bins rows and columns chromStart, chromEnd, count, mean.

Examples

# NOT RUN {
## bins of size 3bp.
## -1-   -3-   -5-
##    -2-   -4-
## 123456789012345 base index.
## --2---
##       --1-
##           --0-------
## Coverage profile.
profile <- data.frame(chromStart=as.integer(c(0, 6, 10)),
                      chromEnd=as.integer(c(6, 10, 10000)),
                      count=as.integer(c(2, 1, 0)))
library(PeakSegJoint)
bins <- binSum(profile,
               bin.chromStart=0L,
               bin.size=3L,
               n.bins=2000L)
library(ggplot2)
bases <- data.frame(position=1:15, base="N")
ggplot()+
  ylab("")+
  geom_text(aes(position, 0, label=base),
            data=bases)+
  geom_step(aes(chromStart+0.5, count, color=what),
            data=data.frame(profile, what="profile"),
            size=2)+
  geom_step(aes(chromStart+0.5, count, color=what),
            data=data.frame(bins, what="bin total"))+
  geom_step(aes(chromStart+0.5, mean, color=what),
            data=data.frame(bins, what="bin mean"))+
  coord_cartesian(xlim=c(0, max(bases$position)))
# }