initiation_sites: Cryptic transcription start sites (cTSS)
In yCrypticRNAs: Cryptic Transcription Analysis in Yeast

Description Usage Arguments Details Value Examples

View source: R/initiation_points_methods.R

For genes expresing a cryptic transcript, the method allows the identification of cTSS. Five differents methods are available.

initiation_sites(name, bamfiles, types, annotations, introns = NULL,
  sf = replicate(length(bamfiles), 1), replicates = 200, percentage = 0.1,
  method = c("methodC_gaussian", "methodA", "methodB", "methodC", "methodD"),
  paired_end = TRUE, as_fragments = TRUE)

`name`	The name of the gene for which to calculate the cryptic initiation site(s).
`bamfiles`	a vector of characters indicating the BAM file paths.
`types`	a vector of the same length as bamfiles indicating the type of data in each file. Example: WT vs MUT or untreated vs treated".
`annotations`	An object of type `annotationsSet` containing information on genes.
`introns`	an objet of type `annotationsSet` containing the annotations of the intronic regions. Note: The introns must have same name as the gene they are associated with.
`sf`	A vector of the scaling factors to apply to each sample. Must be the same length as the `fragments_file`
`replicates`	The number of time to sample the data. Default = 200.
`percentage`	Th fraction of data to be removed at each simulation. Default = 0.1.
`method`	A character string or a vector specifying the method to use to calculate the cryptic initiations sites. Must be one of "methodC_gaussian" (default), "methodA", "methodB", "methodC" or "methodD".
`paired_end`	logical indicating whether the `bamfile` contains paired_end data.
`as_fragments`	logical indicating if paired_end data must paired and merged to form fragments.

By definition, the observed f value for a gene is the perpendicular distance between the differential cumulative RNA-seq values (type1 - type2) and a diagonal linking the first and last data points. The simulated f max is the maximum f value for a gene after re-sampling the data.

Method A identify a cryptic zone by calculating positions for which the observed f value is in the distribution of simulated f max.

Method B identify a cryptic zone by calculating positions for which the mean simulated f value is in the distribution of simulated f max.

Method C identify a cryptic zone by calculating positions for which the simulated f value is in the distribution of simulated f max.

Method D identify a cryptic zone by calculating the positions for each simulated f max.

Method C gaussian determine the mean and standard deviation of all the positions for which the simulated f value is in the distribution of simulated f max.

A list with the following components:

`methodC_gaussian`	cTSS mean and sd values using the method C (gaussian)
`methodA`	cryptic zones start and end position using the method A
`methodB`	cryptic zones start and end position using the method B
`methodC`	cryptic zones start and end position using the method C
`methodD`	cryptic zones start and end position using the method D
`gene_information`	An object of class `annotationsSet` containing the information on the gene.

data("annotations")
samples <- c("wt_rep1", "wt_rep2", "mut_rep1", "mut_rep2")
bamfiles <- system.file("extdata", paste0(samples, ".bam"),
                        package = "yCrypticRNAs")
sf <- c(0.069872847, 0.081113079, 0.088520251, 0.069911116)
data(introns)
types = c("wt", "wt", "mut", "mut")


initiation_sites("YER109C", bamfiles, types, annotations,
                 introns, sf = sf, replicates = 5)
#initiation_sites("YER109C", bamfiles, types, annotations,
                # introns, sf = sf, percentage = 0.2, method = "methodA")