AsDiscover-methods: Report PSI and PIR using experimental junctions

In estepi/ASpliD: Analysis of alternative splicing using RNA-Seq

Description

Given a bin, it is possible to calculate PSI/PIR metric using junctions to estimate changes in the use of it along different conditions.

Usage

AsDiscover(counts, 
          targets, 
          features, 
          bam, 
          l,
          pair,
          threshold, 
          cores)

Arguments

counts	An object of class ASpliCounts.
targets	A dataframe containing sample, bam and condition columns
features	An object of class ASpliFeatures.
bam	A list with BAM files
l	Read length of sequenced read. Default 100L
pair	Vector of length two, either numeric or character, providing the pair of groups to be compared
threshold	Minimun number of reads supporting junctions. Default=5
cores	Number of proccesors to use

Value

An object of class ASpliAS

irPIR	reports: event, e1i counts (J1), ie1 counts (J2), j_within (J3), PIR by condition. J1, J2, J3 sum of junctions (J1, J2, J3) by condition.
altPSI	reports: event, J1 (start), J2 (end), J3 (exclusion), PSI. J1, J2, J3 sum of junctions (J1, J2, J3) by condition.
esPSI	reports: event, J1 (start), J2 (end), J3 (exclusion), PSI. J1, J2, J3 sum of junctions (J1, J2, J3) by condition.
junctionsPIR	PIR metric for each experimental junction using e1i and ie2 counts. Exclusion junction is the junction itself. This output helps to discover new introns as well as new retention events
junctionsPSI	Given a junction, it is possible to analyze if it shares start, end or both with another junction. If so, is because there is more than one way for/of splicing. Using strand information it is possible to classify those pair of junctions into Alt5'ss, Alt3'ss or ES. Ratio between them along samples is reported.

Author(s)

Estefania Mancini, Marcelo Yanovsky and Ariel Chernomoretz

See Also

Accesors: irPIR, altPSI, esPSI, junctionsPIR,junctionsPSI Export: writeAS

Examples

library(RNAseqData.HNRNPC.bam.chr14)
chr14 <- system.file("extdata","chr14.sqlite", package="ASpli")
genome <- loadDb(chr14)
features <- binGenome(genome)
targets <- data.frame(bam=RNAseqData.HNRNPC.bam.chr14_BAMFILES,
                       condition=c(rep("CT",4),rep("KD",4)))
bam <- loadBAM(targets)
counts <- readCounts(features, bam, l=100L, maxISize=50000)
group <- factor(c(rep("CT",4),rep("KD",4)))
pair <- c("CT","KD")  
as <- AsDiscover(counts, targets, features, bam, l=100L, pair=pair)
writeAS(as=as, output.dir="only_as")

estepi/ASpliD documentation built on May 16, 2019, 8:53 a.m.