Hierarchical clustering of monoclonal antibody reactivity patterns in nonhuman species.

Full Abstract

Monoclonal antibodies (Mab) are an important resource for defining molecular expression and probing molecular function. The characterization of Mab reactivity patterns, however, can be costly and inefficient in nonhuman experimental systems. To develop a computational approach to the pattern analysis of Mab reactivity, we analyzed a panel of 128 Mab recognizing sheep antigens. Quantitative single parameter flow cytometry histograms were obtained from five cell types isolated from normal animals. The resulting 640 histograms were smoothed using a Gaussian kernel over a range of bandwidths. Histogram features were selected by SiZer--an analytic tool that identifies statistically significant features. The extracted histogram features were compared and grouped using hierarchical clustering. The validity of the clustering was indicated by the accurate pairing of externally verified molecular reactivity. We conclude that our computational algorithm is a potentially useful tool for both Mab classification and molecular taxonomy in nonhuman experimental systems.

Author information

Author/s: Pratt, Juan Pablo (JP); Zeng, Qing (Q); Ravnic, Dino (D); Huss, Harold (H); Rawn, James (J); Mentzer, Steven J (SJ);

Affiliation: Laboratory of Immunophysiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA.

Grants: HL47078 (Agency:NHLBI NIH HHS) ; HL75426 (Agency:NHLBI NIH HHS)

Journal and publication information

Publication Type: Comparative Study; Journal Article; Research Support, N.I.H., Extramural

Journal: Cytometry. Part A : the journal of the International Society for Analytical Cytology (Cytometry A), published in United States. (Language: eng)

Reference: 2009-Sep; vol 75 (issue 9) : pp 734-42

Dates: Created 2009/08/19; Completed 2009/10/22;

PMID: 19639632, status: MEDLINE (last retrieval date: 10/22/2009, IMS Date: )

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