This behaviour is correct - BayesPeak divides the chromosome into
100bp bins (by default). Because we perform an additional offset
analysis, this is refined to 50bp resolution. This number is usually
much smaller than peak widths and so is sufficient for most purposes.
Are you using the tutorial "ChIP-seq practical: peak detection and
peak annotation"? This document was written a year ago, and BayesPeak
has evolved quite a bit since then. I would strongly recommend using
the current vignette instead (opened with the R command
vignette("BayesPeak")). The function export() in the rtracklayer
library may be of use for the task you are interested in performing.
In particular, sections 7 and 8 in the vignette are worth reading, as
it may be necessary to apply an overfitting correction.
From: email@example.com [bioconductor-
firstname.lastname@example.org] On Behalf Of Binbin Liu
Sent: 11 November 2010 12:17
To: bioconductor at stat.math.ethz.ch
Subject: [BioC] BayesPeak and RangedData obj output
I have two questions here to ask for your suggestions regarding
BayesPeak pkg and RangedData obj output.
I am trying to use BayesPeak for peak identification of my treat with
raw.chr1 = bayespeak(treat, control, chr="chr1", use.multicore=T,
output.chr1 = summarize.peaks(raw.chr1, method="lowerbound")
I had a look at peaks in output.chr1 ----
RangedData with 1376 rows and 1 value column across 1 space
space ranges | PP
<character> <iranges> | <numeric>
1 chr1 [33146139, 33146289] | 0.9333376
2 chr1 [33381689, 33381839] | 0.9753039
3 chr1 [33382089, 33382289] | 0.9999574
4 chr1 [33504139, 33504289] | 0.9997761
5 chr1 [33561739, 33561939] | 0.9999883
6 chr1 [33563589, 33563839] | 1.0000000
7 chr1 [33622739, 33622939] | 0.9999843
8 chr1 [33627989, 33628139] | 0.9997822
9 chr1 [33644589, 33644939] | 0.9999988
10 chr1 [33646539, 33646689] | 0.9771097
and attributes(output.chr1) ----
CompressedIRangesList of length 1
IRanges of length 1376
start end width
 33146139 33146289 151
 33381689 33381839 151
 33382089 33382289 201
 33504139 33504289 151
 33561739 33561939 201
 33563589 33563839 251
 33622739 33622939 201
 33627989 33628139 151
 33644589 33644939 351
... ... ...
Does this look normal to you?, because I am not sure. It seems that
all peaks have very similar width and coordinates. I have tried with
different chip-seq dataset and got similar pattern of output as this.
What have I done wrong here?
The second question is when I try to write output with
write.table(output.chr1, file="blah.txt", sep="\t") as shown on the
BayesPeak tutorial, R complains that
"Error in as.data.frame.default(x[[i]], optional = TRUE) :
cannot coerce class structure("RangedData", package = "IRanges")
into a data.frame"
What is wrong here?
R version 2.10.1 (2009-12-14)
 LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
 LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
 LC_MONETARY=C LC_MESSAGES=en_US.UTF-8
 LC_PAPER=en_US.UTF-8 LC_NAME=C
 LC_ADDRESS=C LC_TELEPHONE=C
 LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
 stats graphics grDevices utils datasets methods base
other attached packages:
 multicore_0.1-4 BayesPeak_1.2.0 IRanges_1.4.16
loaded via a namespace (and not attached):
Many thanks for any help.
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