AsDiscover {ASpli}R Documentation

Report PSI and PIR using experimental junctions

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. PSI or PIR metric is calculated for each bin and experimental condition. The selection of which metric is used is based on the kind of splicing event associated with each bin.

Usage

 
 AsDiscover( counts, targets, features, bam, readLength, threshold , cores )

Arguments

counts

An object of class ASpliCounts.

targets

A dataframe containing sample, bam and experimental factors as columns and samples as rows.

features

An object of class ASpliFeatures.

bam

A list with BAM files contents.

readLength

Read length of sequenced read. Default 100L

threshold

Minimum number of reads supporting junctions. Default=5

cores

Number of processing cores 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. 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


  # Create a transcript DB from gff/gtf annotation file.
  # Warnings in this examples can be ignored. 
  library(GenomicFeatures)
  genomeTxDb <- makeTxDbFromGFF( system.file('extdata','genes.mini.gtf', 
                                 package="ASpli") )
  
  # Create an ASpliFeatures object from TxDb
  features <- binGenome( genomeTxDb )
  
  # Define bam files, sample names and experimental factors for targets.
  bamFileNames <- c( "A_C_0.bam", "A_C_1.bam", "A_C_2.bam", 
                     "A_D_0.bam", "A_D_1.bam", "A_D_2.bam" )
  targets <- data.frame( 
               row.names = paste0('Sample_',c(1:6)),
               bam = system.file( 'extdata', bamFileNames, package="ASpli" ),
               factor1 = c( 'C','C','C','D','D','D') )
  
  # Load reads from bam files
  bams <- loadBAM( targets )
  
  # Read counts from bam files
  counts   <- readCounts( features, bams, targets, cores = 1, readLength = 100, 
                          maxISize = 50000 )
  
  # Calculate differential usage of genes, bins and junctions 
  du       <- DUreport( counts, targets )
  du       <- junctionDUreport( counts, targets, appendTo = du)
  
  # Calculate PSI / PIR for bins and junction.
  as       <- AsDiscover( counts, targets, features, bams, readLength = 100, 
                          threshold = 5, cores = 1 )
  
  writeAS( as = as, output.dir = "only_as" )


[Package ASpli version 1.8.1 Index]