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Last data update: 2014.03.03

R: Get a Data Frame of Quality Data from a 'FASTQSummary' object

getQual-methods

R Documentation

Get a Data Frame of Quality Data from a `FASTQSummary` object

Description

An object of class FASTQSummary contains quality data (binned by readSeqFile). getQual is an accessor function that reshapes the data into a data frame.

This accessor function is useful if you want to map variables to custom ggplot2 aesthetics.

Usage

getQual(x)

Arguments

`x`	an S4 object of class `FASTQSummary` from `readSeqFile`.

Value

getQual returns a data.frame with columns:

`position`	the position in the read.
`ymin`	the minimum quality found per a position in the read.
`alt.lower`	the 10% quantile found per a position in the read.
`lower`	the 25% quartile found per a position in the read.
`middle`	the median found per a position in the read.
`upper`	the 75% quartile found per a position in the read.
`alt.upper`	the 90% quantile found per a position in the read.
`ymax`	the maximum quality found per a position in the read.
`mean`	the mean quality (calculated from the binned data by using a weighted mean function) per the position in the read.

Methods

signature(x="FASTQSummary"): getQual is an accessor function that only works if there is quality data, thus it only works with objects of class FASTQSummary.

Author(s)

Vince Buffalo <vsbuffalo@ucdavis.edu>

Examples

  ## Load a FASTQ file, with sequence hashing.
  s.fastq <- readSeqFile(system.file('extdata', 'test.fastq', package='qrqc'))

  ## Mean quality by position
  p <- ggplot(getQual(s.fastq)) + geom_line(aes(x=position, y=mean), color="blue")
  p <- p + scale_y_continuous(limits=c(0, 42))
  p

  ## A different type of quality plot
  p <- ggplot(getQual(s.fastq)) + geom_linerange(aes(x=position,
    ymin=lower, ymax=upper, color=mean))
  p <- p +  scale_color_gradient("mean quality", low="red", high="green")
  p + scale_y_continuous("quality")

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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Platform: x86_64-pc-linux-gnu (64-bit)

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Type 'demo()' for some demos, 'help()' for on-line help, or
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> library(qrqc)
Loading required package: reshape
Loading required package: ggplot2
Loading required package: Biostrings
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Loading required package: S4Vectors
Loading required package: stats4

Attaching package: 'S4Vectors'

The following objects are masked from 'package:reshape':

    expand, rename

The following objects are masked from 'package:base':

    colMeans, colSums, expand.grid, rowMeans, rowSums

Loading required package: IRanges
Loading required package: XVector
Loading required package: biovizBase
Loading required package: brew
Loading required package: xtable
Loading required package: Rsamtools
Loading required package: GenomeInfoDb
Loading required package: GenomicRanges
Loading required package: testthat

Attaching package: 'testthat'

The following object is masked from 'package:S4Vectors':

    compare

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/qrqc/getQual-methods.Rd_%03d_medium.png", width=480, height=480)
> ### Name: getQual-methods
> ### Title: Get a Data Frame of Quality Data from a 'FASTQSummary' object
> ### Aliases: getQual getQual-methods getQual,FASTQSummary-method
> ### Keywords: methods accessor
> 
> ### ** Examples
> 
>   ## Load a FASTQ file, with sequence hashing.
>   s.fastq <- readSeqFile(system.file('extdata', 'test.fastq', package='qrqc'))
> 
>   ## Mean quality by position
>   p <- ggplot(getQual(s.fastq)) + geom_line(aes(x=position, y=mean), color="blue")
>   p <- p + scale_y_continuous(limits=c(0, 42))
>   p
> 
>   ## A different type of quality plot
>   p <- ggplot(getQual(s.fastq)) + geom_linerange(aes(x=position,
+     ymin=lower, ymax=upper, color=mean))
>   p <- p +  scale_color_gradient("mean quality", low="red", high="green")
>   p + scale_y_continuous("quality")
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>

Get a Data Frame of Quality Data from a FASTQSummary object