7 Cleaning Data

7.1 The Essentials 1. Install flowcut

if(!require(flowCut)) BiocManager::install("flowCut")
#> Loading required package: flowCut
#> Loading required package: flowCore
#> rgeos version: 0.6-4, (SVN revision 699)
#>  GEOS runtime version: 3.11.2-CAPI-1.17.2 
#>  Please note that rgeos will be retired during October 2023,
#> plan transition to sf or terra functions using GEOS at your earliest convenience.
#> See https://r-spatial.org/r/2023/05/15/evolution4.html for details.
#>  GEOS using OverlayNG
#>  Linking to sp version: 2.0-0 
#>  Polygon checking: TRUE
#> Warning: replacing previous import 'flowCore::plot' by
#> 'graphics::plot' when loading 'flowDensity'

2. Load RDS if necessary (if you don’t see FLOWSET in your Environment tab then you will need this step, otherwise, disregard) 3. Clean your data

library(here)
flowCut::flowCut("FLOWSET", Directory= here("Output"))

7.2 A Deeper Dive

Cleaning data is a large part of data analysis. We do this in multiple ways. For instance, we have already cleaned our data in two ways so far - Gating - Removing dead cells and doublets - Removes confounding events - Makes files smaller - premessa - Cleaning channel names and removing extraneous channels - Channel name parity that our code runs smoothly - Removing extraneous channels