TEtranscriptsParam-class: TEtranscripts parameter class
In functionalgenomics/atena: Analysis of Transposable Elements

TEtranscriptsParam-class

R Documentation

TEtranscripts parameter class

Description

This is a class for storing parameters provided to the TEtranscripts algorithm. It is a subclass of the 'QuantifyParam-class'.

Build an object of the class TEtranscriptsParam

Usage

TEtranscriptsParam(
  bfl,
  teFeatures,
  aggregateby = character(0),
  ovMode = "ovUnion",
  geneFeatures = NULL,
  singleEnd = TRUE,
  ignoreStrand = FALSE,
  strandMode = 1L,
  fragments = TRUE,
  tolerance = 1e-04,
  maxIter = 100L,
  verbose = TRUE
)

## S4 method for signature 'TEtranscriptsParam'
show(object)

Arguments

`bfl`	a character string vector of BAM file names.
`teFeatures`	A `GRanges` or `GRangesList` object with the TE annotated features to be quantified. Elements in this object should have names, which are used as a grouping factor for genomic ranges forming a common locus, unless other metadata column names are specified in the `aggregateby` parameter.
`aggregateby`	Character vector with column names from the annotation to be used to aggregate quantifications. By default, this is an empty vector, which means that the names of the input `GRanges` or `GRangesList` object given in the `teFeatures` parameter are used to aggregate quantifications.
`ovMode`	Character vector indicating the overlapping mode. Available options are: "ovUnion" (default) and "ovIntersectionStrict", which implement the corresponding methods from HTSeq (https://htseq.readthedocs.io/en/release_0.11.1/count.html). Ambiguous alignments (alignments overlapping > 1 feature) are addressed as in the original TEtranscripts method.
`geneFeatures`	(Default NULL) A `GRanges` or `GRangesList` object with the gene annotated features to be quantified. Following the TEtranscripts algorithm, overlaps with unique reads are first tallied with respect to these gene features. Elements should have names indicating the gene name/id. In case that `geneFeatures` is a `GRanges` and contains a metadata column named `type`, only the elements with `type` = `exon` are considered for the analysis. Then, exon counts are summarized to the gene level. If NULL, gene expression is not quantified.
`singleEnd`	(Default TRUE) Logical value indicating if reads are single (`TRUE`) or paired-end (`FALSE`).
`ignoreStrand`	(Default FALSE) Logical value that defines if the strand should be taken into consideration when computing the overlap between reads and annotated features. When `ignoreStrand = FALSE`, an aligned read is considered to be overlapping an annotated feature as long as they have a non-empty intersecting genomic range on the same strand, while when `ignoreStrand = TRUE` the strand is not considered.
`strandMode`	(Default 1) Numeric vector which can take values 0, 1 or 2. The strand mode is a per-object switch on `GAlignmentPairs` objects that controls the behavior of the strand getter. See `GAlignmentPairs` class for further detail. If `singleEnd = TRUE`, then `strandMode` is ignored.
`fragments`	(Default TRUE) Logical value applied to paired-end data only. In both cases (`fragments=FALSE` and `fragments=TRUE`), the read-counting method discards not properly paired reads. Moreover, when `fragments=FALSE`, only non-ambiguous properly paired reads are counted. When `fragments=TRUE`, ambiguous reads are also counted (see "Pairing criteria" in `readGAlignments()`). `fragments=TRUE` is equivalent to the behavior of the TEtranscripts algorithm. For further details see `summarizeOverlaps()`.
`tolerance`	A positive numeric scalar storing the minimum tolerance above which the SQUAREM algorithm (Du and Varadhan, 2020) keeps iterating. Default is `1e-4` and this value is passed to the `tol` parameter of the `squarem()` function.
`maxIter`	A positive integer scalar storing the maximum number of iterations of the SQUAREM algorithm (Du and Varadhan, 2020). Default is 100 and this value is passed to the `maxiter` parameter of the `squarem()` function.
`verbose`	(Default `TRUE`) Logical value indicating whether to report progress.
`object`	A TEtranscriptsParam object.

Details

This is the constructor function for objects of the class TEtranscriptsParam-class. This type of object is the input to the function qtex() for quantifying expression of transposable elements using the TEtranscripts method Jin et al. (2015). The TEtranscripts algorithm quantifies TE expression by using an EM algorithm to optimally distribute ambiguously mapped reads.

Value

A TEtranscriptsParam object.

Slots

singleEnd: (Default FALSE) Logical value indicating if reads are single (TRUE) or paired-end (FALSE).
ignoreStrand: (Default FALSE) A logical which defines if the strand should be taken into consideration when computing the overlap between reads and annotated features. When ignoreStrand = FALSE, an aligned read will be considered to be overlapping an annotated feature as long as they have a non-empty intersecting genomic ranges on the same strand, while when ignoreStrand = TRUE the strand will not be considered.
strandMode: (Default 1) Numeric vector which can take values 0, 1 or 2. The strand mode is a per-object switch on GAlignmentPairs objects that controls the behavior of the strand getter. See GAlignmentPairs class for further detail. If singleEnd = TRUE, then use either strandMode = NULL or do not specify the strandMode parameter.
fragments: (Default TRUE) A logical; applied to paired-end data only. In both cases (fragments=FALSE and fragments=TRUE), the read-counting method discards not properly paired reads. Moreover, when fragments=FALSE, only non-ambiguous properly paired reads are counted. When fragments=TRUE, ambiguous reads are also counted (see "Pairing criteria" in readGAlignments()). fragments=TRUE is equivalent to the behavior of the TEtranscripts algorithm. For further details see summarizeOverlaps().
tolerance: A positive numeric scalar storing the minimum tolerance above which the SQUAREM algorithm (Du and Varadhan, 2020) keeps iterating. Default is 1e-4 and this value is passed to the tol parameter of the squarem() function.
maxIter: A positive integer scalar storing the maximum number of iterations of the SQUAREM algorithm (Du and Varadhan, 2020). Default is 100 and this value is passed to the maxiter parameter of the squarem() function.

References

Jin Y et al. TEtranscripts: a package for including transposable elements in differential expression analysis of RNA-seq datasets. Bioinformatics. 2015;31(22):3593-3599. DOI: https://doi.org/10.1093/bioinformatics/btv422

Examples

bamfiles <- list.files(system.file("extdata", package="atena"),
                       pattern="*.bam", full.names=TRUE)
## Not run: 
## use the following two instructions to fetch annotations, they are here
## commented out to enable running this example quickly when building and
## checking the package
rmskat <- annotaTEs(genome="dm6", parsefun=rmskatenaparser,
                    strict=FALSE, insert=500)
rmskLTR <- getLTRs(rmskat, relLength=0.8,
                   fullLength=TRUE,
                   partial=TRUE,
                   otherLTR=TRUE)

## End(Not run)

## DO NOT TYPE THIS INSTRUCTION, WHICH JUST LOADS A PRE-COMPUTED ANNOTATION
## YOU SHOULD USE THE INSTRUCTIONS ABOVE TO FETCH ANNOTATIONS
rmskLTR <- readRDS(system.file("extdata", "rmskatLTRrlen80flenpartoth.rds",
                               package="atena"))


library(TxDb.Dmelanogaster.UCSC.dm6.ensGene)
txdb <- TxDb.Dmelanogaster.UCSC.dm6.ensGene
txdb_genes <- genes(txdb)

## build a parameter object for TEtranscripts
ttpar <- TEtranscriptsParam(bamfiles,
                            teFeatures=rmskLTR,
                            geneFeatures=txdb_genes,
                            singleEnd=TRUE,
                            ignoreStrand=TRUE,
                            aggregateby="repName")
ttpar

functionalgenomics/atena documentation built on May 7, 2024, 10:33 a.m.