2016
DOI: 10.1002/cyto.a.22837
|View full text |Cite
|
Sign up to set email alerts
|

flowClean: Automated identification and removal of fluorescence anomalies in flow cytometry data

Abstract: Modern flow cytometry systems can be coupled to plate readers for high-throughput acquisition. These systems allow hundreds of samples to be analyzed in a single day. Quality control of the data remains challenging, however, and is further complicated when a large number of parameters is measured in an experiment. Our examination of 29.228 publicly available FCS files from laboratories worldwide indicates 13.7% have a fluorescence anomaly. In particular, fluorescence measurements for a sample over the collecti… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
40
0

Year Published

2016
2016
2023
2023

Publication Types

Select...
8

Relationship

3
5

Authors

Journals

citations
Cited by 52 publications
(40 citation statements)
references
References 13 publications
0
40
0
Order By: Relevance
“…A first quality control step is to visualize scatter and marker values over time, and filter out regions that show abnormal behaviour (for example, due to clogging, speed change or air measurements when the tube is empty). Both the flowQ 34 and flowClean 35 packages provide this functionality. A second control step is to check for batch effects, which gives an idea of the between-sample variation.…”
Section: Algorithmic Benchmarking and Software Availabilitymentioning
confidence: 98%
“…A first quality control step is to visualize scatter and marker values over time, and filter out regions that show abnormal behaviour (for example, due to clogging, speed change or air measurements when the tube is empty). Both the flowQ 34 and flowClean 35 packages provide this functionality. A second control step is to check for batch effects, which gives an idea of the between-sample variation.…”
Section: Algorithmic Benchmarking and Software Availabilitymentioning
confidence: 98%
“…FlowClean, flowAI) (42,43) Provide QC results to users as needed to ensure good instrument operation during data acquisition Identify and communicate data sets that are erroneous. For example, using the time parameter in the FCS file or the inclusion of standard particles (e.g.…”
Section: Quality Assurancementioning
confidence: 99%
“…flowAI evaluates three different properties: flow rate, signal acquisition, and dynamic range . flowClean detects anomalies in the data by tracking fluorescent measurement fluctuations within a sample during acquisition time …”
Section: Data Formats and Data Pre‐processingmentioning
confidence: 99%