RoarDataset-class: Class '"RoarDataset"'

In vodkatad/roar: Identify differential APA usage from RNA-seq alignments

Description

RoarDataset - a class to perform 3'UTR shortening analyses

Objects from the Class

Objects of thiss class should be created using the functions RoarDataset or RoarDatasetFromFiles, ideally the raw new method should never be invoked by end users. Then to perform the analysis the user should call, in order: countPrePost, computeRoars, computePvals and one of the methods to format results.

Slots

treatmentBams:

Object of class "list" - a list of GappedAlignment objects for the first condition (by convention it is considered the “treated” condition) in analysis.

controlBams:

Object of class "list" - a list of GappedAlignment objects for the second condition (by convention it is considered the “control” condition) in analysis.

prePostCoords:

Object of class "GRanges" - represents the APA sites coords, defining "PRE" (last exon coords up until the alternative APA, defining the shorter isoform) and "POST" (from the alternative APA to the “standard” one) regions of the genes.

postCoords:

Object of class "GRanges" - private object.

countsTreatment:

Object of class "RangedSummarizedExperiment" - private object.

countsControl:

Object of class "RangedSummarizedExperiment" - private object.

pVals:

Object of class "RangedSummarizedExperiment" - private object.

paired:

"logical" slot - private.

step:

"numeric" slot - private.

cores:

"numeric" slot - private.

metadata:

"list" slot - private.

rowRanges:

Object of class "GRangesORGRangesList" - private object.

colData:

Object of class "DataFrame" - private object.

assays:

Object of class "Assays" - private object.

Extends

Class "RangedSummarizedExperiment", directly.

Methods

countPrePost

signature(rds = "RoarDataset", stranded = "logical"): Counts reads falling over PRE/POST portions of the given transcripts.

computeRoars

signature(rds = "RoarDataset"): Computes m/M and roar values for this RoarDataset object.

computePvals

signature(rds = "RoarDataset"): Computes pvalues (Fisher test) for this RoarDataset object.

totalResults

signature(rds = "RoarDataset"): Returns a dataframe with results of the analysis for a RoarDataset object.

fpkmResults

signature(rds = "RoarDataset"): The last step of a classical Roar analyses: it returns a dataframe containing m/M values, roar values, pvalues and estimates of expression (a measure recalling FPKM).

countResults

signature(rds = "RoarDataset"): The last step of a classical Roar analyses: it returns a dataframe containing m/M values, roar values, pvalues and estimates of expression (counts over PRE portions).

standardFilter

signature(rds = "RoarDataset", fpkmCutoff = "double"): Returns a dataframe with results of the analysis for a RoarDataset object.

pvalueFilter

signature(rds = "RoarDataset", fpkmCutoff = "double", pvalCutoff = "double"): ...

cores

signature(rds = "RoarDataset"): returns the number of cores used for computation, right now always 1.

Author(s)

Elena Grassi, PhD student in Biomedical Sciences and Oncology - Dept. of Molecular Biotechnologies and Health Sciences, Molecular Biotechnology Center, Torino

Examples

showClass("RoarDataset")

vodkatad/roar documentation built on March 30, 2020, 2:56 p.m.