NetFCM: A semi‐automated web‐based method for flow cytometry data analysis. Issue 11 (18th July 2014)
- Record Type:
- Journal Article
- Title:
- NetFCM: A semi‐automated web‐based method for flow cytometry data analysis. Issue 11 (18th July 2014)
- Main Title:
- NetFCM: A semi‐automated web‐based method for flow cytometry data analysis
- Authors:
- Frederiksen, Juliet
Buggert, Marcus
Karlsson, Annika C.
Lund, Ole - Abstract:
- <abstract abstract-type="main"> <title>Abstract</title> <p>Multi‐parametric flow cytometry (FCM) represents an invaluable instrument to conduct single cell analysis and has significantly increased our understanding of the immune system. However, due to new techniques allowing us to measure an increased number of phenotypes within the immune system, FCM data analysis has become more complex and labor‐intensive than previously. We have therefore developed a semi‐automatic gating strategy (NetFCM) that uses clustering and principal component analysis (PCA) together with other statistical methods to mimic manual gating approaches. NetFCM is an online tool both for subset identification as well as for quantification of differences between samples. Additionally, NetFCM can classify and cluster samples based on multidimensional data. We tested the method using a data set of peripheral blood mononuclear cells collected from 23 HIV‐infected individuals, which were stimulated with overlapping HIV Gag‐p55 and CMV‐pp65 peptides or medium alone (negative control). NetFCM clustered the virus‐specific CD8+ T cells based on IFNγ and TNF responses into distinct compartments. Additionally, NetFCM was capable of identifying HIV‐ and CMV‐specific responses corresponding to those obtained by manual gating strategies. These data demonstrate that NetFCM has the potential to identify relevant T cell populations by mimicking classical FCM data analysis and reduce the subjectivity and amount of time<abstract abstract-type="main"> <title>Abstract</title> <p>Multi‐parametric flow cytometry (FCM) represents an invaluable instrument to conduct single cell analysis and has significantly increased our understanding of the immune system. However, due to new techniques allowing us to measure an increased number of phenotypes within the immune system, FCM data analysis has become more complex and labor‐intensive than previously. We have therefore developed a semi‐automatic gating strategy (NetFCM) that uses clustering and principal component analysis (PCA) together with other statistical methods to mimic manual gating approaches. NetFCM is an online tool both for subset identification as well as for quantification of differences between samples. Additionally, NetFCM can classify and cluster samples based on multidimensional data. We tested the method using a data set of peripheral blood mononuclear cells collected from 23 HIV‐infected individuals, which were stimulated with overlapping HIV Gag‐p55 and CMV‐pp65 peptides or medium alone (negative control). NetFCM clustered the virus‐specific CD8+ T cells based on IFNγ and TNF responses into distinct compartments. Additionally, NetFCM was capable of identifying HIV‐ and CMV‐specific responses corresponding to those obtained by manual gating strategies. These data demonstrate that NetFCM has the potential to identify relevant T cell populations by mimicking classical FCM data analysis and reduce the subjectivity and amount of time associated with such analysis. © 2014 International Society for Advancement of Cytometry</p> </abstract> … (more)
- Is Part Of:
- Cytometry. Volume 85:Issue 11(2014:Nov.)
- Journal:
- Cytometry
- Issue:
- Volume 85:Issue 11(2014:Nov.)
- Issue Display:
- Volume 85, Issue 11 (2014)
- Year:
- 2014
- Volume:
- 85
- Issue:
- 11
- Issue Sort Value:
- 2014-0085-0011-0000
- Page Start:
- 969
- Page End:
- 977
- Publication Date:
- 2014-07-18
- Subjects:
- Flow cytometry -- Periodicals
Imaging systems in biology -- Periodicals
Imaging systems in medicine -- Periodicals
Diagnostic imaging -- Periodicals
571.605 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1552-4930 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/cyto.a.22510 ↗
- Languages:
- English
- ISSNs:
- 1552-4922
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3506.855100
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 3872.xml