Description Usage Arguments Details Value Author(s) Examples
Find hotspots (groups of single-read changes) from a NucDyn
object.
This function helps in the analysis of the nucleosome dynamics by
finding the regions with relevant changes in the individual position
of the nucleosomes.
There are 4 types of basic hotspots:
1 2 3 4 5 6 7 8 | findHotspots(dyn, nuc, wins = 10000, indel.threshold = NULL,
shift.threshold = NULL, indel.nreads = NULL, shift.nreads = NULL,
mc.cores = 1)
## S4 method for signature 'NucDyn'
findHotspots(dyn, nuc, wins = 10000,
indel.threshold = NULL, shift.threshold = NULL,
indel.nreads = NULL, shift.nreads = NULL, mc.cores = 1)
|
dyn |
NucDyn object with the dynamic to analyze. |
nuc |
list of two |
wins |
Size of the window in base-pairs where the relative scores are computed |
indel.threshold |
Maximum p-value for an |
shift.threshold |
Maximum p-value for a |
indel.nreads |
Minimum number of reads in an |
shift.nreads |
Minimum number of reads in a |
mc.cores |
If |
SHIFT +: Translational movement of nucleosomes, downstream (+).
SHIFT -: Translational movement of nucleosomes, upstream (-).
EVICTION: Nucleosome reads removed from that locus.
INCLUSION: Nucleosome reads added to that locus.
As translational and coverage changes can happen anywhere, only those
involving a certain number of reads are reported. This number can by
adjusted by the threshold
parameter. If threshold
is a character
vector representing a percentage value (i.e., 60%), this will be
automatically converted to the absolute value given by the corresponding
percentile of the coverage in the window. If, instead, threshold
is a
numeric
value, this value will be used as absolute threhold.
It two adjacent hotspots with shifts in opposite directions are detected but
one of them is relatively small in comparison with the other, but will be
reported as shifts, disregarding the value of combined
. We consider two
hotspots of the same magnitude if the ratio between the number of reads in
one and the other is smaller than same.magnitude
. This ratio is always
performed by using the larger number as numerator and the smaller as
denominator; therefore, same.magnitude
must always be greater of equal
than 1.
For example, with same.magnitude=2
, we consider that 25 reads shifting
downstream followed bby 17 reads shifting upstream will be of the same
magnitude (25/17 == 1.47 < 2) and we will annotate it as a "DISPERSION". In
another example, if we have 25 shifts downstream followed by only 5 shifts
upstream (25/5 == 5 > 2), both hotspot will be annotated as "SHIFT".
A data.frame
with the following columns:
start: initial position of the detected hotspot
end: final position of the detected hotspot
peak: point of largest change (shortest p-value)
nreads: Number of reads involved at peak position
score: average p-value in the hotspot weighted by the coverage of reads involved in the hotspot
type: The type of the hotspot (as listed above).
chr: Chromosome name.
Ricard Illa, Diana Buitrago diana.buitrago@irbbarcelona.org
1 2 3 4 5 | data(readsG2_chrII)
data(readsM_chrII)
data(nuc_chrII)
dyn <- nucleosomeDynamics(setA=readsG2_chrII, setB=readsM_chrII)
hs <- findHotspots(dyn, nuc_chrII)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.