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Anticlustering for sample allocation to minimize batch effects

delete2025-08-18
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OA
AI
M
Martin Papenberg *
王成 cover
王成 (Cheng Wang)
M
Maïgane Diop
S
Syed Bukhari
B
Boris Oskotsky
B
Brittany Davidson
K
Kim Chi Vo
B
Binya Liu
J
Juan C. Irwin
A
Alexis J. Combes
B
Brice Gaudillière
J
Jingjing Li
D
David K. Stevenson
G
Gunnar W. Klau
L
Linda C. Giudice
M
Marina Sirota
T
Tomiko Oskotsky *
DOI:10.1016/j.crmeth.2025.101137delete
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Abstract

Abstract

En 中文
• Anticlustering balances sample covariates across batches • Supports both categorical and numeric variables for flexible batch design • Must-link feature keeps related samples grouped in the same batch • Outperforms existing tools in simulations from a real-world example
Keywords:
batch effects
sample allocation
high-throughput sequencing
anticlustering
must-link constraints
sample assignment
experimental design
CP: Computational biology
CP: Systems biology
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Cell Reports Methods cover
Cell Reports Methods
IF:
4.5
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921
Citations:
2.0K

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U
university of california
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Stanford University
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Heinrich Heine University Düsseldorf cover
Heinrich Heine University Düsseldorf
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