Summarize information about flags after array normalization

Description

Compute spot-level information (number of flagged spots, normalization parameters), and display it in a convenient way

Usage

## S3 method for class 'arrayCGH'
flag.summary(arrayCGH, flag.list, flag.var="Flag", nflab="not flagged", ...)
## Default S3 method:
flag.summary(spot.flags, flag.list, nflab="not flagged", ...)

Arguments

Details

This function is used by the function html.report for the generation of an HMTL report of the normalization step. It can also be used by itself.

Value

A data.frame data.frame with 4 columns:

Note

People interested in tools for array-CGH analysis can visit our web-page: http://bioinfo.curie.fr.

Author(s)

Pierre Neuvial, manor@curie.fr.

See Also

html.report, flag

Examples

data(spatial)
data(flags)
flag.list <- list(spatial=local.spatial.flag, spot=spot.corr.flag,
ref.snr=ref.snr.flag, dapi.snr=dapi.snr.flag, rep=rep.flag,
unique=unique.flag) 
flag.list$spatial$args <- alist(var="ScaledLogRatio", by.var=NULL,
nk=5, prop=0.25, thr=0.15, beta=1, family="symmetric") 
flag.list$spot$args <- alist(var="SpotFlag")
flag.list$spot$char <- "O"
flag.list$spot$label <- "Image analysis"

## normalize arrayCGH
## Not run: edge.norm <- norm(edge, flag.list=flag.list,
var="LogRatio", FUN=median, na.rm=TRUE)
## End(Not run) 
fs <- flag.summary(edge.norm, flag.list=flag.list, flag.var="Flag")

print("Flag and normalization parameters summary")
print(fs)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(MANOR)
Loading required package: GLAD

######################################################################################

Have fun with GLAD

For smoothing it is possible to use either
the AWS algorithm (Polzehl and Spokoiny, 2002,
or the HaarSeg algorithm (Ben-Yaacov and Eldar, Bioinformatics,  2008,

If you use the package with AWS, please cite:
Hupe et al. (Bioinformatics, 2004, and Polzehl and Spokoiny (2002,

If you use the package with HaarSeg, please cite:
Hupe et al. (Bioinformatics, 2004, and (Ben-Yaacov and Eldar, Bioinformatics, 2008,

For fast computation it is recommanded to use
the daglad function with smoothfunc=haarseg

######################################################################################

New options are available in daglad: see help for details.


Attaching package: 'MANOR'

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

    norm

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/MANOR/flag.summary.Rd_%03d_medium.png", width=480, height=480)
> ### Name: flag.summary
> ### Title: Summarize information about flags after array normalization
> ### Aliases: flag.summary flag.summary.arrayCGH flag.summary.default
> ### Keywords: misc
> 
> ### ** Examples
> 
> data(spatial)
> data(flags)
> flag.list <- list(spatial=local.spatial.flag, spot=spot.corr.flag,
+ ref.snr=ref.snr.flag, dapi.snr=dapi.snr.flag, rep=rep.flag,
+ unique=unique.flag) 
> flag.list$spatial$args <- alist(var="ScaledLogRatio", by.var=NULL,
+ nk=5, prop=0.25, thr=0.15, beta=1, family="symmetric") 
> flag.list$spot$args <- alist(var="SpotFlag")
> flag.list$spot$char <- "O"
> flag.list$spot$label <- "Image analysis"
> 
> ## normalize arrayCGH
> ## Not run: 
> ##D edge.norm <- norm(edge, flag.list=flag.list,
> ##D var="LogRatio", FUN=median, na.rm=TRUE)
> ## End(Not run) 
> fs <- flag.summary(edge.norm, flag.list=flag.list, flag.var="Flag")
> 
> print("Flag and normalization parameters summary")
[1] "Flag and normalization parameters summary"
> print(fs)
  char                            label  arg count
1    S                       Local bias   NA   127
2    O                   Image analysis   NA    37
3    B  Low signal to noise ratio (Ref) 1.25    19
4    D Low signal to noise ratio (Dapi) 1.25    85
5    E       Poor replicate consistency 0.10     0
6    U                      Unique spot   NA     8
7   OK                      not flagged   NA  7116
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>