Parametric analysis of histograms measured in flow cytometry
Flow cytometric histograms frequently consist of several components that show various degrees of overlap. For many types of analysis it is of great importance to decompose the original histogram into its components. To that purpose, we investigated the maximum likelihood approach in detail. It is sh...
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          | Published in | Cytometry (New York, N.Y.) Vol. 4; no. 1; pp. 75 - 82 | 
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| Main Authors | , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
        Hoboken
          Wiley Subscription Services, Inc., A Wiley Company
    
        01.07.1983
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| Subjects | |
| Online Access | Get full text | 
| ISSN | 0196-4763 1097-0320 1097-0320  | 
| DOI | 10.1002/cyto.990040111 | 
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| Abstract | Flow cytometric histograms frequently consist of several components that show various degrees of overlap. For many types of analysis it is of great importance to decompose the original histogram into its components. To that purpose, we investigated the maximum likelihood approach in detail. It is shown that the iterative method to solve the maximum likelihood equations is well behaved for a variety of initial values. Algorithms to obtain initial values are presented, and the performance of the method is tested when applied to the analysis of DNA measurements from heterogeneous cell populations that differ with respect to DNA content. | 
    
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| AbstractList | Flow cytometric histograms frequently consist of several components that show various degrees of overlap. For many types of analysis it is of great importance to decompose the original histogram into its components. To that purpose, we investigated the maximum likelihood approach in detail. It is shown that the iterative method to solve the maximum likelihood equations is well behaved for a variety of initial values. Algorithms to obtain initial values are presented, and the performance of the method is tested when applied to the analysis of DNA measurements from heterogeneous cell populations that differ with respect to DNA content.Flow cytometric histograms frequently consist of several components that show various degrees of overlap. For many types of analysis it is of great importance to decompose the original histogram into its components. To that purpose, we investigated the maximum likelihood approach in detail. It is shown that the iterative method to solve the maximum likelihood equations is well behaved for a variety of initial values. Algorithms to obtain initial values are presented, and the performance of the method is tested when applied to the analysis of DNA measurements from heterogeneous cell populations that differ with respect to DNA content. Flow cytometric histograms frequently consist of several components that show various degrees of overlap. For many types of analysis it is of great importance to decompose the original histogram into its components. To that purpose, we investigated the maximum likelihood approach in detail. It is shown that the iterative method to solve the maximum likelihood equations is well behaved for a variety of initial values. Algorithms to obtain initial values are presented, and the performance of the method is tested when applied to the analysis of DNA measurements from heterogeneous cell populations that differ with respect to DNA content.  | 
    
| Author | Hand, R. E. Mann, R. C. Braslawsky, G. R.  | 
    
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/6617397$$D View this record in MEDLINE/PubMed | 
    
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| Cites_doi | 10.1002/cyto.990020305 10.1093/carcin/3.8.847 10.1093/biomet/56.3.463 10.1002/cyto.990030204 10.1109/TPAMI.1981.4767074 10.1111/j.1749-6632.1976.tb41607.x 10.1016/0010-4809(76)90006-9  | 
    
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| Copyright | Copyright © 1983 Wiley‐Liss, Inc. | 
    
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| Notes | This research was sponsored jointly by the Office of Health and Environmental Research, U.S. Department of Energy, under contract W‐7405‐eng‐26 with the Union Carbide Corporation, and the National Institute of Environmental Health Sciences under Interagency Agreement 40–689–78 (222‐YO1‐ES‐20041). This paper was originally presented at the Combined International Conference on Analytical Cytology and Cytometry IX and the 6th International Symposium on Flow Cytometry, Schloss Elmau, October 18–23, 1982. R.C. Mann is a recipient of a Feodor–Lynen Fellowship from the Alexander von Humboldt–Foundation, Bonn, Federal Republic of Germany. ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23  | 
    
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| References | 1969; 56 1976; 267 1963 1982; 15 1972 1981; PAMI‐3 1980 1976; 9 1979 1981; 2 1982; 3 Freeman H (e_1_2_1_8_2) 1963 Bryant J (e_1_2_1_4_2) 1980 Christensen IJ (e_1_2_1_5_2) 1980 e_1_2_1_6_2 e_1_2_1_7_2 Fukunaga K (e_1_2_1_10_2) 1972 Melamed MR (e_1_2_1_11_2) 1979 e_1_2_1_3_2 e_1_2_1_12_2 e_1_2_1_13_2 e_1_2_1_14_2 Baisch H (e_1_2_1_2_2) 1982; 15 e_1_2_1_9_2  | 
    
| References_xml | – volume: 15 start-page: 235 year: 1982 end-page: 249 article-title: A comparison of mathematical methods for the analysis of DNA histograms by flow cytometry publication-title: Cell Tissue Kinet – start-page: 147 year: 1980 end-page: 151 – year: 1963 – volume: 3 start-page: 847 year: 1982 end-page: 850 article-title: Changes in DNA content of rat tracheal epithelial cells during neoplastic progression in vitro publication-title: Carcinogenesis – start-page: 138 year: 1980 end-page: 142 – year: 1972 – volume: 267 start-page: 176 year: 1976 end-page: 191 article-title: Laser flow microphotometry for rapid analysis and sorting of mammalian cells publication-title: Ann NY Acad Sci – volume: 9 start-page: 263 year: 1976 end-page: 276 article-title: Method for the quantitative evaluation of data from flow microfluorometry publication-title: Comp Biomed Res – year: 1979 – volume: PAMI‐3 start-page: 163 year: 1981 end-page: 179 article-title: An approximate solution to normal mixture identification with application to unsupervised pattern classification publication-title: IEEE Trans Pattern Anal Machine Intel – volume: 56 start-page: 463 year: 1969 end-page: 474 article-title: Estimating the components of a mixture of normal distributions publication-title: Biometrika – volume: 2 start-page: 159 year: 1981 end-page: 164 article-title: Mathematical evaluation of two‐parameter cytometric histograms publication-title: Cytometry – volume: 3 start-page: 84 year: 1982 end-page: 90 article-title: Rapid, one step staining procedures for analysis of cellular DNA and protein by single and dual laser flow cytometry publication-title: Cytometry – ident: e_1_2_1_14_2 doi: 10.1002/cyto.990020305 – ident: e_1_2_1_3_2 doi: 10.1093/carcin/3.8.847 – ident: e_1_2_1_7_2 doi: 10.1093/biomet/56.3.463 – ident: e_1_2_1_6_2 doi: 10.1002/cyto.990030204 – volume-title: Introduction to Statistical Pattern Recognition year: 1972 ident: e_1_2_1_10_2 – start-page: 147 volume-title: Flow Cytometry IV year: 1980 ident: e_1_2_1_5_2 – volume-title: Introduction to Statistical Inference year: 1963 ident: e_1_2_1_8_2 – volume-title: Flow Cytometry and Sorting year: 1979 ident: e_1_2_1_11_2 – ident: e_1_2_1_13_2 doi: 10.1109/TPAMI.1981.4767074 – ident: e_1_2_1_12_2 doi: 10.1111/j.1749-6632.1976.tb41607.x – volume: 15 start-page: 235 year: 1982 ident: e_1_2_1_2_2 article-title: A comparison of mathematical methods for the analysis of DNA histograms by flow cytometry publication-title: Cell Tissue Kinet – ident: e_1_2_1_9_2 doi: 10.1016/0010-4809(76)90006-9 – start-page: 138 volume-title: Flow Cytometry IV year: 1980 ident: e_1_2_1_4_2  | 
    
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| SubjectTerms | Animals Cell Cycle Cell Line DNA - analysis Flow Cytometry - methods heterogeneous cell populations Interphase Mathematics Maximum likelihood estimation Mitosis mixture identification Neoplasms - pathology Probability Rats Trachea  | 
    
| Title | Parametric analysis of histograms measured in flow cytometry | 
    
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