AStrap: Identification AS events and classification AS types.

In BMILAB/AStrap: Identificantion of alternative splicing events and classificaiton of alternative splicing types

Description

This function can identify AS events and classify AS events from transcripts without a reference.Two classification models trained on collected AS data from rice (MSU7) and human (GRCH38) were integrated in AStrap, which could be directly applied for distinguishing AS types for other species. Certainly, users can also train a specific model on their own data sets using several functions provided in AStrap, see the function of buildTrainModel.

Usage

AStrap(cluster.alignment, transcriptSeq, trainModel, identity = 0.7,
  coverage = 0.7, bias = 0, ASlength = 0)

Arguments

cluster.alignment	A data frame holds pairwise alignment of isoforms in a cluster.
transcriptSeq	An XStringSet object holds the transcript sequence.
trainModel	A model object for which prediction is desired.
identity	AS detection is performed if identity above a given threshold (default: 0.7).
coverage	AS detection is performed if coverage above a given threshold (default: 0.7).
bias	Maximum number of mismatches in pairwise sequence alignment (default: 0).
ASlength	AS detection is performed if AS length above a given threshold (default: 0).

Value

A list of AS events and AS types. This object contains three elements: ASevent, feature, predict. ASevent is a data frame stroage the identified AS events; feature is a feature data frame for AS events based on transcript, including 511 features; predict is the calssification of AS events. and the form of the value returned by predict depends on the class of its argument.

Examples

##Loading transcript sequence
trSequence.path <- system.file("extdata","example_TRsequence.fasta",
                              package = "AStrap")
trSequence <-  readDNAStringSet(trSequence.path,format = "fasta")

##Loadinding example data output by CD-HIT-EST
cdhit.path <- system.file("extdata","example_cdhitest.clstr",
                         package = "AStrap")
raw.cluster <- readCDHIT(cdhit.path)

##Loading example data output by GMAP
gmap.path <- system.file("extdata","example_gmap.gff3",package = "AStrap")

##getting pairwise alignment of isoforms of the same cluster
cluster.align <- readGMAP(gmap.path,raw.cluster, recluster = TRUE,
                          recluster.identity = 0.7,
                          recluster.coverage = 0.7)
alignment <- cluster.align$alignment
rew.cluster <- cluster.align$cluster

##Loading rice model
load(system.file("data","rice_model.Rdata",package = "AStrap"))

##Identification and prediction based on rice RF-based model
result <- AStrap(alignment,trSequence,rice_RFmodel)

BMILAB/AStrap documentation built on Nov. 20, 2020, 4:03 p.m.