subset-methods: Subset ASpli objects

Description Usage Arguments Value Author(s) Examples

Description

ASpli provides utility functions to easy subset ASpliCounts objects, ASpliAS objects, targets data frame and lists GAlignments generated with loadBAM function. The subset can be done selecting some of the experimental conditions or samples names ( but not both ).

Usage

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  subset( x, ... )
  subsetBams( x, targets, select )
  subsetTargets( targets, select, removeRedundantExpFactors )

Arguments

x

An ASpliCount or ASpliAS object for subset function, or list of GAlignments for subsetrBams function.

targets

A dataframe containing sample, bam and experimental factor columns.

select

A character vector specifying the conditions or samples to be kept after subset operation. It's assumed that condition names are different from sample names.

removeRedundantExpFactors

When sub-setting the targets data frame, one or more experimental factors can have only one value. If this argument is TRUE those experimental factors are absent in the resulting target data frame.

...

Subsetting ASpliCounts and ASpliAS objects sub subset method requires a targets argument and a select argument with the same specifications that the arguments with the same name in subsetBams and subsetTargets functions

Value

A data frame similar to x ( or targets for subsetTargets) with only the containing only the selected elements.

Author(s)

Estefania Mancini, Andres Rabinovich, Javier Iserte, Marcelo Yanovsky, Ariel Chernomoretz

Examples

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  # 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 )
#  
 # # Create ASpliAS object                        
  #as       <- AsDiscover( counts, targets, features, bams, readLength = 100, 
   #                       threshold = 5, cores = 1 )
    #                      
  # Define selection
  #select <- c('Sample_1', 'Sample_2', 'Sample_4', 'Sample_5')                       
  #
  # Subset target 
  #targets2 <- subsetTargets( targets, select )
  
  # Subset bams 
  #bams2 <- subsetBams( bams, targets, select )
  
  # Subset ASpliCounts object 
  #counts2 <- subset( counts, targets, select )
  
  # Subset ASpliAS object 
  #as2 <- subset( as, targets, select )
  

chernolab/ASpli documentation built on March 11, 2021, 12:24 a.m.