Filter samples based on experiment variables

cyto_filter(x, ...)

Arguments

x	object of class `flowSet` or `GatingSet`.
...	tidyverse-style subsetting using comma separated logical predicates based on experimental variables stored in `cyto_details(x)`. See examples below for demonstration.

Value

flowSet or GatingSet restricted to samples which meet the filtering criteria.

Author

Dillon Hammill, Dillon.Hammill@anu.edu.au

Examples


# Load in CytoExploreRData to access data
library(CytoExploreRData)

# Look at experiment details
cyto_details(Activation)
#>                                name OVAConc Treatment
#> Activation_1.fcs   Activation_1.fcs       0    Stim-A
#> Activation_2.fcs   Activation_2.fcs       0    Stim-A
#> Activation_3.fcs   Activation_3.fcs       5    Stim-A
#> Activation_4.fcs   Activation_4.fcs       5    Stim-A
#> Activation_5.fcs   Activation_5.fcs      50    Stim-A
#> Activation_6.fcs   Activation_6.fcs      50    Stim-A
#> Activation_7.fcs   Activation_7.fcs     500    Stim-A
#> Activation_8.fcs   Activation_8.fcs     500    Stim-A
#> Activation_9.fcs   Activation_9.fcs       0    Stim-B
#> Activation_10.fcs Activation_10.fcs       0    Stim-B
#> Activation_11.fcs Activation_11.fcs       5    Stim-B
#> Activation_12.fcs Activation_12.fcs       5    Stim-B
#> Activation_13.fcs Activation_13.fcs      50    Stim-B
#> Activation_14.fcs Activation_14.fcs      50    Stim-B
#> Activation_15.fcs Activation_15.fcs     500    Stim-B
#> Activation_16.fcs Activation_16.fcs     500    Stim-B
#> Activation_17.fcs Activation_17.fcs       0    Stim-C
#> Activation_18.fcs Activation_18.fcs       0    Stim-C
#> Activation_19.fcs Activation_19.fcs       5    Stim-C
#> Activation_20.fcs Activation_20.fcs       5    Stim-C
#> Activation_21.fcs Activation_21.fcs      50    Stim-C
#> Activation_22.fcs Activation_22.fcs      50    Stim-C
#> Activation_23.fcs Activation_23.fcs     500    Stim-C
#> Activation_24.fcs Activation_24.fcs     500    Stim-C
#> Activation_25.fcs Activation_25.fcs       0    Stim-D
#> Activation_26.fcs Activation_26.fcs       0    Stim-D
#> Activation_27.fcs Activation_27.fcs       5    Stim-D
#> Activation_28.fcs Activation_28.fcs       5    Stim-D
#> Activation_29.fcs Activation_29.fcs      50    Stim-D
#> Activation_30.fcs Activation_30.fcs      50    Stim-D
#> Activation_31.fcs Activation_31.fcs     500    Stim-D
#> Activation_32.fcs Activation_32.fcs     500    Stim-D
#> Activation_33.fcs Activation_33.fcs       0        NA

# Select Stim-C samples with 0 and 500 nM OVA concentrations
fs <- cyto_filter(
  Activation,
  Treatment == "Stim-C",
  OVAConc %in% c(0, 500)
)

# Select Stim-A and Stim-C treatment groups
fs <- cyto_filter(
  Activation,
  Treatment %in% c("Stim-A", "Stim-C")
)