Joint modeling and registration of cell populations in cohorts of high-dimensional flow cytometric data.
Joint modeling and registration of cell populations in cohorts of high-dimensional flow cytometric data.
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DOI:
10.1371/journal.pone.0100334
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发表时间:
2014
期刊:
影响因子:
3.7
通讯作者:
McLachlan GJ
中科院分区:
文献类型:
--
作者:
Pyne S;Lee SX;Wang K;Irish J;Tamayo P;Nazaire MD;Duong T;Ng SK;Hafler D;Levy R;Nolan GP;Mesirov J;McLachlan GJ
In biomedical applications, an experimenter encounters different potential sources of variation in data such as individual samples, multiple experimental conditions, and multivariate responses of a panel of markers such as from a signaling network. In multiparametric cytometry, which is often used for analyzing patient samples, such issues are critical. While computational methods can identify cell populations in individual samples, without the ability to automatically match them across samples, it is difficult to compare and characterize the populations in typical experiments, such as those responding to various stimulations or distinctive of particular patients or time-points, especially when there are many samples. Joint Clustering and Matching (JCM) is a multi-level framework for simultaneous modeling and registration of populations across a cohort. JCM models every population with a robust multivariate probability distribution. Simultaneously, JCM fits a random-effects model to construct an overall batch template – used for registering populations across samples, and classifying new samples. By tackling systems-level variation, JCM supports practical biomedical applications involving large cohorts. Software for fitting the JCM models have been implemented in an R package EMMIX-JCM, available from http://www.maths.uq.edu.au/~gjm/mix_soft/EMMIX-JCM/.
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DOI:
10.1126/science.1198704
发表时间:
2011-05-06
期刊:
Science (New York, N.Y.)
影响因子:
--
作者:
Bendall SC;Simonds EF;Qiu P;Amir el-AD;Krutzik PO;Finck R;Bruggner RV;Melamed R;Trejo A;Ornatsky OI;Balderas RS;Plevritis SK;Sachs K;Pe'er D;Tanner SD;Nolan GP
通讯作者:
Nolan GP
影响因子:
48
作者:
Aghaeepour N;Finak G;FlowCAP Consortium;DREAM Consortium;Hoos H;Mosmann TR;Brinkman R;Gottardo R;Scheuermann RH
通讯作者:
Scheuermann RH
DOI:
10.1002/cyto.990130311
发表时间:
1992-01-01
期刊:
CYTOMETRY
影响因子:
--
作者:
DEMERS, S;KIM, J;LEGENDRE, L
通讯作者:
LEGENDRE, L
DOI:
10.1073/pnas.0706409104
发表时间:
2007-11-20
影响因子:
11.1
作者:
Maier, Lisa M.;Anderson, David E.;Hafler, David A.
通讯作者:
Hafler, David A.
影响因子:
50.3
作者:
Kotecha N;Flores NJ;Irish JM;Simonds EF;Sakai DS;Archambeault S;Diaz-Flores E;Coram M;Shannon KM;Nolan GP;Loh ML
通讯作者:
Loh ML