Dissecting Gene Expression Heterogeneity: Generalized Pearson Correlation Squares and the <i>K</i> -Lines Clustering Algorithm-Reference-Cited by-同舟云学术

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Dissecting Gene Expression Heterogeneity: Generalized Pearson Correlation Squares and the K -Lines Clustering Algorithm

Published:2024-05-24 Issue: Volume: Page:1-14
ISSN:0162-1459
Container-title:Journal of the American Statistical Association
language:en
Short-container-title:Journal of the American Statistical Association

Author:

Li Jingyi Jessica¹^ORCID,Zhou Heather J.¹,Bickel Peter J.²,Tong Xin³^ORCID

Affiliation:

1. Department of Statistics and Data Science, University of California, Los Angeles, Los Angeles, CA

2. Department of Statistics, University of California, Berkeley, Berkeley, CA

3. Department of Data Sciences and Operations, University of Southern California, Los Angeles, CA

Funder

NIH/NIGMS

Johnson and Johnson

Sloan Research Fellowship

UCLA David Geffen School of Medicine W.M. Keck Foundation

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/01621459.2024.2342639

Reference37 articles.

1. A Single-Cell Transcriptomic Map of the Human and Mouse Pancreas Reveals Inter- and Intra-cell Population Structure

2. mixtools: AnRPackage for Analyzing Finite Mixture Models

3. Correlation Curves: Measures of Association as Functions of Covariate Values

4. Estimating Optimal Transformations for Multiple Regression and Correlation

5. A New Coefficient of Correlation

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