Reconstructing DNA copy number by penalized estimation and imputation

DOI10.1214/10-AOAS357zbMath1220.62146arXiv0906.2234OpenAlexW2020386917WikidataQ34973122 ScholiaQ34973122MaRDI QIDQ542936

Zhongyang Zhang, Roel Ophoff, Chiara Sabatti, Kenneth L. Lange

Publication date: 20 June 2011

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0906.2234

zbMATH Keywords

dynamic programmingMM algorithm\(\ell 1\) penaltyfused lasso

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Applications of mathematical programming (90C90) Biochemistry, molecular biology (92C40) Cell biology (92C37) Genetics and epigenetics (92D10)

Related Items

A decision-theoretic approach for segmental classification ⋮ Smoothing proximal gradient method for general structured sparse regression ⋮ The screening and ranking algorithm to detect DNA copy number variations ⋮ Multiple change-point detection: a selective overview

Uses Software

• VanillaICE
• PennCNV

Cites Work

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• Nonlinear total variation based noise removal algorithms
• Near-ideal model selection by \(\ell _{1}\) minimization
• Hidden Markov models for the assessment of chromosomal alterations using high-throughput SNP arrays
• Pathwise coordinate optimization
• Coordinate descent algorithms for lasso penalized regression
• Mathematical Models for Local Nontexture Inpaintings
• $\ell_1$ Trend Filtering
• Spatial smoothing and hot spot detection for CGH data using the fused lasso
• Ideal spatial adaptation by wavelet shrinkage
• Sparsity and Smoothness Via the Fused Lasso

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