R: Nucleosome positioning mapping on a large segment, up to a...

rjmcmcCHR {RJMCMCNucleosomes}

R Documentation

Nucleosome positioning mapping on a large segment, up to a chromosome

Description

Use of a fully Bayesian hierarchical model for chromosome-wide profiling of nucleosome positions based on high-throughput short-read data (MNase-Seq data). Beware that for a genome-wide profiling, each chromosome must be treated separatly. This function is optimized to run on an entire chromosome.

The function will process by splittingg the GRanges of reads (as example, the reads from a chromosome) in a list of smaller GRanges segments that can be run by the rjmcmc function. All those steps are done automatically.

Usage

rjmcmcCHR(reads, seqName = NULL, zeta = 147, delta, maxLength,
  nbrIterations, kMax, lambda = 3, minInterval, maxInterval, minReads = 5,
  adaptIterationsToReads = TRUE, vSeed = -1, nbCores = 1,
  dirOut = "out", saveAsRDS = FALSE, saveSEG = TRUE)

Arguments

`reads`	a `GRanges`, the forward and reverse reads that need to be segmented.
`seqName`	a `character` string containing the label of the chromosome, present in the `GRanges` object, that will be used. The `NULL` value is accepted when only one seqname is present in the `GRanges`; the only seqname present will be used. Default: `NULL`.
`zeta`	a positive `integer` or `numeric`, the length of the nucleosomes. Default: 147.
`delta`	a positive `integer` or `numeric`, the accepted range of overlapping section between segments. The overlapping section being `zeta` + `delta`.
`maxLength`	a positive `integer` or `numeric`, the length of each segment.
`nbrIterations`	a positive `integer` or `numeric`, the number of iterations. Non-integer values of `nbrIterations` will be casted to `integer` and truncated towards zero.
`kMax`	a positive `integer` or `numeric`, the maximum number of degrees of freedom per region. Non-integer values of `kMax` will be casted to `integer` and truncated towards zero.
`lambda`	a positive `numeric`, the theorical mean of the Poisson distribution. Default: 3.
`minInterval`	a `numeric`, the minimum distance between two nucleosomes.
`maxInterval`	a `numeric`, the maximum distance between two nucleosomes.
`minReads`	a positive `integer` or `numeric`, the minimum number of reads in a potential canditate region. Non-integer values of `minReads` will be casted to `integer` and truncated towards zero. Default: 5.
`adaptIterationsToReads`	a `logical` indicating if the number of iterations must be modified in function of the number of reads. Default: `TRUE`.
`vSeed`	a `integer`. A seed used when reproducible results are needed. When a value inferior or equal to zero is given, a random integer is used. Default: -1.
`nbCores`	a positive `integer`, the number of cores used to run in parallel. Default: 1.
`dirOut`	a `character` string. The name of the directory where 2 directories are created (if they don't already exists). The directory "dirOut/results" contents the rjmcmc results for each segment. The directory "dirOut/done" contents file a log file for each segment in RData format. If the log file for a segment is in the directory, the program considers that it is has been processed and run the next segment. Default: "out".
`saveAsRDS`	a `logical`. When `TRUE`, a RDS file containing the complete output of the `rjmcmc` function is created. Default: `FALSE`.
`saveSEG`	a `logical`. When `TRUE`, a RDS file containing the segments generated by `segmentation` function is saved in directory named from paramter `dirOut`. Default: `FALSE`.

Value

a list of class "rjmcmcNucleosomesBeforeAndAfterPostTreatment" containing:

k a integer, the number of nucleosomes.
mu a GRanges containing the positions of the nucleosomes.
kPost a integer, the number of nucleosomes after post-treatment and '*' as strand. The seqnames of the GRanges correspond to the seqName input value. NA when no nucleosome is detected.
muPost a GRanges containing the positions of the nucleosomes after post-treament and '*' as strand. The seqnames of the GRanges correspond to the seqName input value. NA when no nucleosome is detected.

Author(s)

Pascal Belleau, Astrid Deschenes

Examples


## Load synthetic dataset of reads
data(syntheticNucleosomeReads)

## Use dataset of reads to create GRanges object
sampleGRanges <- GRanges(syntheticNucleosomeReads$dataIP)

## Run nucleosome detection on the entire sample
## Not run: result <- rjmcmcCHR(reads = sampleGRanges, zeta = 147, delta=50,
maxLength=1200, nbrIterations = 1000, lambda = 3, kMax = 30,
minInterval = 146, maxInterval = 292, minReads = 5, vSeed = 10113,
nbCores = 2, saveAsRDS = FALSE)
## End(Not run)

[Package RJMCMCNucleosomes version 1.4.0 Index]