Description Usage Arguments Value Examples
Like the predNuPoP
function of the parental package
NuPoP does, this function invokes Fortran codes to
compute the Viterbi prediction of nucleosome positioning,
nucleosome occupancy score and histone binding affinity
score. Nucleosomal and linker models
built upon the chemical maps are used for the calculation.
When ActLikePredNuPoP
is TRUE
, this function
acts like the predNuPoP
function of NuPoP:
the function receives the path to a file containing a
DNA sequence (specified by file
) and save a text
file containing the prediction results in the
working directory. Nucleosome positioning throughout a
long chromosome containing ‘N’ can be predicted.
When ActLikePredNuPoP
is FALSE
(dafault),
this function directly receives a DNA sequence as an R
object (inseq
) and returns the prediction results
as a data frame. ‘N’ must not be in the sequence.
1 2 | predNuCpos(file, inseq, species="mm", smoothHBA=FALSE,
std=FALSE, ActLikePredNuPoP = FALSE)
|
file |
The file path to the FASTA file to be tested.
The FASTA must be in a single FASTA format.
This will be ignored when |
inseq |
a character or DNAString object.
The length of the character string must be over 1 kb.
This will be ignored when |
species |
a character = mm, sc or sp; "mm" for mouse, "sc" for S. cerevisiae and "sp" for S. pombe. |
smoothHBA |
a logical value indicating whether
smoothing of histone binding affinity should be
applied as in the |
std |
a logical value indicating whether standardization should be applied to the histone binding affinity score. |
ActLikePredNuPoP |
a logical value indicating whether
the function acts like the |
When the ActLikePredNuPoP
argument is set as TRUE
,
predNuCpos
outputs the prediction
results into the working directory,
in the same format as that generated by the predNuPoP
function of NuPoP. Thus, it can be handled by the
NuPoP functions readNuPoP
and plotNuPoP
.
The output file is named after the input file with
an extension “_Prediction4.txt”.
The output file has five columns:
Position |
position in the input DNA sequence |
P-start |
probability that a nucleosome starts at |
Occup |
nucleosome occupancy score |
N/L |
Viterbi path (1 and 0 for the nucleosome and linker states, repsectively) |
Affinity |
histone binding affinity score |
When the ActLikePredNuPoP
argument is set as FALSE
,
predNuCpos
outputs the prediction
results as a data frame object with five columns,
on which the plotNuPoP
function of NuPoP
can be applied:
pos |
position in the input DNA sequence |
pstart |
probability that a nucleosome starts at |
nucoccup |
nucleosome occupancy score |
viterbi |
Viterbi path (1 and 0 for the nucleosome and linker states, repsectively) |
affinity |
histone binding affinity score |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | predNuCpos(file = system.file("extdata", "TRP1ARS1x1.fasta",
package="nuCpos"), species="sc", smoothHBA=FALSE,
std=FALSE, ActLikePredNuPoP = TRUE)
library(NuPoP)
results.TRP1ARS1.1 <- readNuPoP("TRP1ARS1x1.fasta_Prediction4.txt",
startPos = 1, endPos = 1465)
results.TRP1ARS1.1[72:76,]
plotNuPoP(results.TRP1ARS1.1)
TRP1ARS1 <- paste(scan(file =
system.file("extdata", "TRP1ARS1x1.fasta", package = "nuCpos"),
what = character(), skip = 1), sep = "", collapse = "")
results.TRP1ARS1.2 <-
predNuCpos(inseq = TRP1ARS1, species = "sc", smoothHBA = FALSE,
ActLikePredNuPoP = FALSE)
results.TRP1ARS1.2[72:76,]
plotNuPoP(results.TRP1ARS1.2)
## The DNA sequence TRP1ARS1 is from Fuse et al. (2017).
|
/usr/lib/R/site-library/nuCpos/extdata/TRP1ARS1x1.fasta_Prediction4.txt was created in the working directory.
Position P.start Occup N/L Affinity
72 72 0.001 0.893 1 NA
73 73 0.000 0.893 1 NA
74 74 0.000 0.893 1 0.346
75 75 0.000 0.893 1 -4.435
76 76 0.000 0.893 1 -3.429
Read 1 item
species: sc
pos pstart nucoccup viterbi affinity
72 72 9.802925e-04 0.8926019 1 NA
73 73 3.182192e-04 0.8929201 1 NA
74 74 5.025299e-05 0.8929704 1 0.3456824
75 75 5.160730e-06 0.8929756 1 -4.4353083
76 76 1.397652e-06 0.8929769 1 -3.4287470
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.