Identifying the Patterns of Hematopoietic Stem Cells Gene Expressions Using Clustering Methods: Comparison and Summary
Journal of Data SciencePublished 20 July 2021Open access
Jie Chen, Xi He, Linheng Li
Citations3
SJR quartileQ3
SJR score0.39
SNIP0.69
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This paper makes a comparison among popularly used clustering methods with HSC microarray data, and concludes that k- means clustering with hierarchical average or complete linkage initialization performed the best among all the methods the authors compared.
Abstract
Publisher: School of Statistics, Renmin University of China, Journal: Journal of Data Science, Title: Identifying the Patterns of Hematopoietic Stem Cells Gene Expressions Using Clustering Methods - Comparison and Summary, Authors: Jie Chen, Xi He, Linheng Li
Keywords
Biochemistry, Genetics and Molecular Biology
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22,787 Citations1967James B. MacQueen
Proceedings of the National Academy of SciencesCluster analysis and display of genome-wide expression patterns
16,395 Citations1998Michael B. Eisen, Paul T. Spellman +2 more
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BiometricsApplied Multivariate Statistical Analysis.
11,424 Citations1988Andrea Johnson, Dean W. Wichern
Cluster Analysis
9,195 Citations1974Barry J. Everitt, Sabine Landau +1 more
Proceedings of the National Academy of SciencesInterpreting patterns of gene expression with self-organizing maps: Methods and application to hematopoietic differentiation
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PsychometrikaAn Examination of the Effect of Six Types of Error Perturbation on Fifteen Clustering Algorithms
1,170 Citations1980Glenn W. Milligan
An evaluation of several clustering methods indicated that the hierarchical methods were differentially sensitive to the type of error perturbation and two alternative starting procedures for the nonhierarchical methods produced greatly enhanced cluster recovery and were found to be robust to all of the types of error examined.
Systems Research and Behavioral ScienceA clustering technique for summarizing multivariate data
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A practical computing method termed ISODATA, which finds the cluster structure of such data, is described and provides a fit to the data of a set of cluster centers that tends to minimize the sum of the squared distances of each data point from its closest cluster center.
Journal of the American Statistical AssociationOn Some Invariant Criteria for Grouping Data
571 Citations1967Herman Friedman, Jerrold Rubin
This paper attacks the problem of exploring the structure of multivariate data in search of “clusters” by using a computer procedure to obtain the “best” partition of n objects into g groups.
Proceedings of the National Academy of SciencesBootstrapping cluster analysis: Assessing the reliability of conclusions from microarray experiments
474 Citations2001Kathleen F. Kerr, Gary A. Churchill
A general technique for making statistical inference from clustering tools applied to gene expression microarray data by utilizing an analysis of variance model to achieve normalization and estimate differential expression of genes across multiple conditions is introduced.
BloodTranscriptional accessibility for genes of multiple tissues and hematopoietic lineages is hierarchically controlled during early hematopoiesis
366 Citations2002Koichi Akashi, Xi He +7 more
The hypothesis that stem cells possess a wide-open chromatin structure to maintain their multipotentiality, which is progressively quenched as they go down a particular pathway of differentiation, is supported.
BiometricsPractical Problems in a Method of Cluster Analysis
221 Citations1971F. H. C. Marriott
The method of classification based on minimizing the determinant of the within-group dispersion matrix is discussed from the viewpoint of the practical user and it is shown that these can be resolved to give a satisfactory answer to the question of the number of natural clusters and their bounds.
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This study may provide a guideline on how to select suitable clustering algorithms and it may help raise issues in the extraction of meaningful biological information from microarray expression data.
PubMedCluster analysis and data visualization of large-scale gene expression data.
178 Citations1998George S. Michaels, Daniel B. Carr +4 more
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