Description Usage Arguments Value Author(s) Examples
Use of a fully Bayesian hierarchical model for chromosomewide profiling of nucleosome positions based on highthroughput shortread data (MNaseSeq data). Beware that for a genomewide profiling, each chromosome must be treated separatly.
1 2 3 
startPosForwardReads 
a 
startPosReverseReads 
a 
nbrIterations 
a positive 
kMax 
a positive 
lambda 
a positive 
minInterval 
a 
maxInterval 
a 
minReads 
a positive 
adaptIterationsToReads 
a 
a list
of class
"rjmcmcNucleosomes" containing:
call
the matched call.
K
a vector
of integer
, the estimation of the
number of the nucleosomes for each iteration.
k
a integer
, the final estimation of the number
of nucleosomes.
mu
a vector
of numeric
of length
k
, the positions of the nucleosomes.
sigmaf
a vector
of numeric
of length
k
, the variance of the forward reads for each nucleosome.
sigmar
a vector
of numeric
of length
k
, the variance of the reverse reads for each nucleosome.
delta
a vector
of numeric
of length
k
, the distance between the maxima of the forward and reverse reads
position densities for each nucleosome.
df
a vector
of numeric
of length
k
, the degrees of freedom for each nucleosome.
w
a vector
of positive numerical
of length
k
, the weight for each nucleosome. The sum of all w
values
must be equal to 1
.
qmu
a matrix
of numerical
with a number of rows
of k
, the 2.5% and 97.5% quantiles of each mu
.
qsigmaf
a matrix
of numerical
with a number of
rows of k
, the 2.5% and 97.5% quantiles of the variance of the
forward reads for each nucleosome.
qsigmar
a matrix
of numerical
with a number of
rows of k
, the 2.5% and 97.5% quantiles of the variance the
reverse reads for each nucleosome.
qdelta
a matrix
of numerical
with a number of
rows of k
, the 2.5% and 97.5% quantiles of the distance between
the maxima of the forward and reverse reads
position densities for each nucleosome.
qdf
a matrix
of numerical
with a number of
rows of k
, the 2.5% and 97.5% quantiles of the degrees of freedom
for each nucleosome.
qw
a matrix
of numerical
with a number of rows
of k
, the 2.5% and 97.5% quantiles of the weight for each
nucleosome.
Rawane Samb, Pascal Belleau, Astrid Desch<c3><aa>nes
1 2 3 4 5 6 7 8 9 10 11 12 13 14  ## Loading dataset
data(reads_demo)
## Nucleosome positioning, running both merge and split functions
result < rjmcmc(startPosForwardReads = reads_demo$readsForward,
startPosReverseReads = reads_demo$readsReverse,
nbrIterations = 1000, lambda = 2, kMax = 30,
minInterval = 146, maxInterval = 292, minReads = 5)
## Print the final estimation of the number of nucleosomes
result$k
## Print the position of nucleosomes
result$mu

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