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What is a “unimodal” cell population? Using statistical tests as criteria for unimodality in automated gating and quality control

Johnsson, Kerstin LU ; Linderoth, Magnus LU and Fontes, Magnus LU (2017) In Cytometry Part A 91(9). p.908-916
Abstract

Many automated gating algorithms for flow cytometry data are based on the concept of unimodal cell populations. However, in this article, we show that criteria previously used to make decisions on unimodality cannot adequately distinguish unimodal from bimodal densities. We show that dip and bandwidth tests for unimodality, taken from the statistics literature, can do this with consistent and low error rates. These tests also have the possibility to adjust the significance level to handle the trade-off between failing to detect a second mode and seeing a second mode when there is none. The differences between the dip and bandwidth tests are elucidated using real data from the FlowCAP I challenge, also guidelines for flow cytometry data... (More)

Many automated gating algorithms for flow cytometry data are based on the concept of unimodal cell populations. However, in this article, we show that criteria previously used to make decisions on unimodality cannot adequately distinguish unimodal from bimodal densities. We show that dip and bandwidth tests for unimodality, taken from the statistics literature, can do this with consistent and low error rates. These tests also have the possibility to adjust the significance level to handle the trade-off between failing to detect a second mode and seeing a second mode when there is none. The differences between the dip and bandwidth tests are elucidated using real data from the FlowCAP I challenge, also guidelines for flow cytometry data preprocessing are given.

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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
automated gating, bandwidth test, calibration, data analysis, dip test, flow cytometry, quality control, unimodality
in
Cytometry Part A
volume
91
issue
9
pages
9 pages
publisher
John Wiley & Sons
external identifiers
  • scopus:85026477395
ISSN
1552-4922
DOI
10.1002/cyto.a.23173
language
English
LU publication?
yes
id
9f0c3646-9c96-4e7f-97cc-e4090526f34e
date added to LUP
2018-01-18 09:03:08
date last changed
2018-01-19 03:00:02
@article{9f0c3646-9c96-4e7f-97cc-e4090526f34e,
  abstract     = {<p>Many automated gating algorithms for flow cytometry data are based on the concept of unimodal cell populations. However, in this article, we show that criteria previously used to make decisions on unimodality cannot adequately distinguish unimodal from bimodal densities. We show that dip and bandwidth tests for unimodality, taken from the statistics literature, can do this with consistent and low error rates. These tests also have the possibility to adjust the significance level to handle the trade-off between failing to detect a second mode and seeing a second mode when there is none. The differences between the dip and bandwidth tests are elucidated using real data from the FlowCAP I challenge, also guidelines for flow cytometry data preprocessing are given.</p>},
  author       = {Johnsson, Kerstin and Linderoth, Magnus and Fontes, Magnus},
  issn         = {1552-4922},
  keyword      = {automated gating,bandwidth test,calibration,data analysis,dip test,flow cytometry,quality control,unimodality},
  language     = {eng},
  month        = {09},
  number       = {9},
  pages        = {908--916},
  publisher    = {John Wiley & Sons},
  series       = {Cytometry Part A},
  title        = {What is a “unimodal” cell population? Using statistical tests as criteria for unimodality in automated gating and quality control},
  url          = {http://dx.doi.org/10.1002/cyto.a.23173},
  volume       = {91},
  year         = {2017},
}