Collect signal from telomeres for all chromosome arms

Pulls out the ChIP signal starting at chromosome ends inward up to a specified distance.

signal_from_telomeres2(signal_data, length_to_collect = 1e+05,
  averaging_window = 1, genome)

Arguments

signal_data

Input signal track data as a GRanges object (see ?"GRanges-class" for more details). To load wiggle and bedGraph data run import_wiggle and import_bedGraph, respectively. No default.
length_to_collect

Integer specifying the length (in bp) of the region to collect signal for, starting form the telomeres. Defaults to 100000 (i.e. 100 kb).
averaging_window

Integer specifying the length (in bp) of the window to average the signal in. Defaults to 1 (i.e. 1 bp: no window averaging).
genome

Character object specifying the genome version; accepts one of the following options:

  1. "SK1Yue"

  2. "S288CYue"

  3. "sacCer3"

  4. "SK1"

  5. "SK1_S288CYue"

No default.

Value

An R data frame containing 32 rows (one for each chromosome arm) and a number of columns dependent on the specified length_to_collect. The following columns are included:

  1. chr The chromosome number

  2. arm The chromosome arm; one of "L" and "R"

  3. size-cat The chromosome size category; one of "small" and "large"

  4. t1:tn Signal columns for each position; number depends on the the specified collection length (n = length_to_collect)

Warning

The fact that some sub-telomeric sequences may be incomplete in the genome means that in some cases we have ChIP-seq data mapping all the way to the very end of the available sequence. This, together with the read extension performed by MACS, leads to some cases where the last positions in the signal data for the right chromosome arms are higher than the annotated length of the respective chromosome. As a result, some negative position values may appear in the output of this function (typically not off by more than 150 bp).

Examples

# NOT RUN {
signal_from_telomeres2(WT, genome = "SK1Yue")

signal_from_telomeres2(WT, length_to_collect = 50000, averaging_window = 100,
                       genome = "sacCer3")
# }