clValid: AnRPackage for Cluster Validation

Brock, Guy; Pihur, Vasyl; Datta, Susmita; Datta, Somnath

doi:10.18637/jss.v025.i04

Cited by 653 publications

(570 citation statements)

References 31 publications

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“…This study uses four cluster validation measures to estimate the number of clusters in the data. These measures are implemented in the clValid and fpc packages in R software (Brock et al, 2008;Hennig, 2010;R Development Core Team, 2012).…”

Section: Resultsmentioning

confidence: 99%

Who donates their bodies to science? The combined role of gender and migration status among California whole-body donors

Asad¹,

Anteby²,

Garip³

2014

Social Science & Medicine

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The number of human cadavers available for medical research and training, as well as organ transplantation, is limited. Researchers disagree about how to increase the number of whole-body bequeathals, citing a shortage of donations from the one group perceived as most likely to donate from attitudinal survey data -educated white males over 65. This focus on survey data, however, suffers from two main limitations: First, it reveals little about individuals' actual registration or donation behavior. Second, past studies' reliance on average survey measures may have concealed variation within the donor population. To address this limitation, we employ cluster analysis on all whole-body donors' data from the Universities of California at Davis, Irvine, Los Angeles, and San Francisco. Two donor groups emerge from the analyses: One is made of slightly younger, educated, married individuals, an overwhelming portion of whom are U.S.-born and have U.S.-born parents, while the second includes mostly older, separated women with some college education, a relatively higher share of whom are foreign-born and have foreign-born parents. Our results demonstrate the presence of additional donor groups within and beyond the group of educated and elderly white males previously assumed to be most likely to donate. More broadly, our results suggest how the intersectional nature of donors' demographics -in particular, gender and migration status -shapes the configuration of the donor pool, signaling new ways to possibly increase donations.

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Section: Resultsmentioning

confidence: 99%

Who donates their bodies to science? The combined role of gender and migration status among California whole-body donors

Asad¹,

Anteby²,

Garip³

2014

Social Science & Medicine

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“…The Dynamic Tree Cut (dynamicTreeCut R-package) (8) algorithm was used to define clusters. The clusters were validated using the internal and the stability measures designed in clValid R-package (9). The nonrandomness of patient distribution among clusters was tested by Fisher's Exact Test with simulated P-values (10 7 replicates).…”

Section: B-cell Profile Data Analysis and Hierarchical Clusteringmentioning

confidence: 99%

“…We allowed only groups of five or more patients to be considered as a cluster. The hierarchical clustering algorithm on this dataset was validated by clValid R-package (9). This approach uses all information contained in all six parameters from 1,024 bins to create a similarity matrix.…”

Section: Clusters Of Patientsmentioning

confidence: 99%

Profiling of polychromatic flow cytometry data on B‐cells reveals patients' clusters in common variable immunodeficiency

et al. 2009

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The aim of this study was to find an objective computational approach for phenotype analysis of common variable immunodeficiency (CVID) patients that describes all differences in the six-color space and to form groups of patients using computational methods. CVID is a heterogeneous primary immunodeficiency disorder where molecular defect is recognized in \10% of the cases and is unknown in the majority of patients. The current CVID classification, EUROClass, is based on quantification of selected B-cell subsets. Using six-color polychromatic flow cytometry, we analyzed B-cell phenotypes in a cohort of 48 CVID patients and 49 healthy donors. We used a ''probability binning'' algorithm to create 1,024 bins (each bin is a six-color gate) that covered the cells' distribution within the entire B-cell compartment. A matrix file recording cellular content in all the bins was made. The hierarchical clustering of the individual samples was analyzed using a Pearson correlation of the bins' values. The Cut tree algorithm found 12 clusters. In six clusters, healthy individuals predominated; in one cluster, smB1CD21low (CVID patients by EUROClass) cells prevailed; in one cluster, smB2CD21norm cells prevailed; in one cluster, smB1CD21low cells prevailed; the remaining cluster was mixed. The overall reproducibility of probability binning clustering was confirmed by matching of replicates to the original cohort using the similarity matrix of the Pearson correlation, 15 replicates matched the same individual, three replicates matched a different individual within the same cluster, and three replicates matched to a different cluster. We were able to define B-cell subsets over-or under-represented in a particular cluster and display them back in the flow cytometry software. We describe a new analytical approach that enables a search in an objective computational environment for patient cohorts that are defined by similar B-cell profiles and thus contribute to the description of differences between CVID patient groups. ' 2009 International Society for Advancement of CytometryKey terms B-lymphocyte subsets; common variable immunodeficiency; flow cytometry; probability binning; B-lymphocyte profiling THE peripheral blood B-cell compartment is a dynamic complex of B-cell subsets that undergo maturational steps, antigen exposure, memory cell formation, memory maintenance, and effector functions (antibody secretion). Polychromatic flow cytometry offers an extraordinary tool to investigate such a complex set of cell types. It allows for the definition and proportional assessment of B-cell subsets and also subdivides into less well-characterized intermediates. However, the analysis of complex data obtained from the six-color space is difficult. The standard analysis strategy uses the creation of series of two-dimensional gates, which makes the resulting analysis subjective, and ''a priori'' unknown small subsets are difficult to discover. Analysis of

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“…(Brock et al 2008) was used to select the optimal number of clusters. Almost 60% of variance among cadastres was explained with 5 clusters using PAM method.…”

Section: Methodsmentioning

confidence: 99%

Development of soil consumption driven by urbanization and pattern of built-up areas in Prague periphery since the 19th century

Stachura¹,

Chuman²,

Šefrna³

2015

Soil & Water Res.

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Soil consumption has become a very rapid and intensive process in many European countries, especially around large cities and important highways. The Prague periphery is not an exception. This paper analyses the extent and quality of consumed agricultural land and pattern of built-up areas in selected 22 cadastres in Prague periphery, by using historical maps and orthophotomaps, over four time horizons since the 19 th century till 2010.The results show an extensive soil consumption. The average extent of built-up area increased from less than 1% to more than 13% per cadastre. This extensive development caused consumption of high quality soils and changed the pattern of built-up areas from more compact to less compact built-up areas. The average nearest neighbour distance between built-up patches has increased by more than 38%.

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clValid: AnRPackage for Cluster Validation

Cited by 653 publications

References 31 publications

Who donates their bodies to science? The combined role of gender and migration status among California whole-body donors

Who donates their bodies to science? The combined role of gender and migration status among California whole-body donors

Profiling of polychromatic flow cytometry data on B‐cells reveals patients' clusters in common variable immunodeficiency

Development of soil consumption driven by urbanization and pattern of built-up areas in Prague periphery since the 19<sup>th</sup> century

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