[BioC] flowcore/flowviz filter

[Mike]

You might be thinking of |cur2Filter|. Here is an example

|library(flowViz)
data(GvHD)
fr <- GvHD[[2]]

#transform the data
trs <- logTransform()
fr_trans <- transform(fr,`FL1-H` = trs(`FL1-H`),`FL2-H` = trs(`FL2-H`))

#use flowCore::curv2Filter
  cf <- curv2Filter(x="FL1-H", y ="FL2-H", filterId ="s5a02", bwFac =4.5)
  #fres <- filter()
  xyplot(`FL1-H`~`FL2-H`, fr_trans, smooth =F, xbin =64, filter = cf)
|


Alternatively, you can use |flowClust.2d| from |openCyto| package to 
gate out the target population more precisely.

|library(openCyto)
# use openCyto::flowclust
fres <- flowClust.2d(fr = fr_trans, xChannel ="FL1-H", yChannel ="FL2-H", K=2, target = c(3,2))
xyplot(`FL1-H`~`FL2-H`, fr_trans, smooth =F, xbin =64, filter = fres)
|

Also, you want to check out http://opencyto.org/ for a more *robust 
framework of automated flow data analysis* .

Mike Jiang

On 02/19/2014 08:32 AM, Nacho [guest] wrote:

> Hi!
>
> I am using flowCore and flowViz for interpreting flow cytometry data. I need a filter for the graphics in which I only choose the regions that have high density points in a plot, for example, of the columns FL1.log vs FS.Log, and I know there is one, but I don't find it.
>
> I will thank your help.
>
>
>   -- output of sessionInfo():
>
> R version 2.14.1 (2011-12-22)
> Platform: x86_64-pc-linux-gnu (64-bit)
>
> locale:
>   [1] LC_CTYPE=es_ES.UTF-8       LC_NUMERIC=C
>   [3] LC_TIME=es_ES.UTF-8        LC_COLLATE=es_ES.UTF-8
>   [5] LC_MONETARY=es_ES.UTF-8    LC_MESSAGES=es_ES.UTF-8
>   [7] LC_PAPER=C                 LC_NAME=C
>   [9] LC_ADDRESS=C               LC_TELEPHONE=C
> [11] LC_MEASUREMENT=es_ES.UTF-8 LC_IDENTIFICATION=C
>
> attached base packages:
> [1] stats     graphics  grDevices utils     datasets  methods   base
>
> --
> Sent via the guest posting facility at bioconductor.org.