Transformation methods and flow data
Dear all,
We have been comparing BM samples that we classify as control BM based on genetics (PCR-negative for mutations), morphology (absence of abnormal cells) and flow cytometry, using manual FlowJo gating strategies. We have been using Cytofkit clustering tools to assess the flow data. In the GUI we have selected the default autological transformation and generated clustering data. While playing around we also ran clustering with the Arcsinh transformation selected and unsurprisingly get different clustering results. In a nutshell, the Arcsinh gave clustering data that fit better with what we know about the samples, which was unexpected as it isnt the recommended method for flow data.
In trying to understand how the different methods transform the data we ran some flow data files in the Hao Chen transformation comparation SHINY app )https://chenhao.shinyapps.io/TransformationComparation_shinyAPP/). This showed us that Arcsinh generates a peak of negative values at the x axis while autological generates a spread out continuum/tail of negative values (see attached image).
We would appreciate some feedback on whether using Arcsinh in flow data is acceptable, and whether the generated clustering data would be considered reliable?
We have been comparing BM samples that we classify as control BM based on genetics (PCR-negative for mutations), morphology (absence of abnormal cells) and flow cytometry, using manual FlowJo gating strategies. We have been using Cytofkit clustering tools to assess the flow data. In the GUI we have selected the default autological transformation and generated clustering data. While playing around we also ran clustering with the Arcsinh transformation selected and unsurprisingly get different clustering results. In a nutshell, the Arcsinh gave clustering data that fit better with what we know about the samples, which was unexpected as it isnt the recommended method for flow data.
In trying to understand how the different methods transform the data we ran some flow data files in the Hao Chen transformation comparation SHINY app )https://chenhao.shinyapps.io/TransformationComparation_shinyAPP/). This showed us that Arcsinh generates a peak of negative values at the x axis while autological generates a spread out continuum/tail of negative values (see attached image).
We would appreciate some feedback on whether using Arcsinh in flow data is acceptable, and whether the generated clustering data would be considered reliable?