PeakSegDisk

R package PeakSegDisk: Disk-Based Constrained Change-Point Detection. Disk-based implementation of Functional Pruning Optimal Partitioning with up-down constraints <doi:10.18637/jss.v101.i10> for single-sample peak calling (independently for each sample and genomic problem), can handle huge data sets (10^7 or more

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References in zbMATH (referenced in 3 articles , 1 standard article )

Showing results 1 to 3 of 3.
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  1. Toby Dylan Hocking, Guillem Rigaill, Paul Fearnhead, Guillaume Bourque: Generalized Functional Pruning Optimal Partitioning (GFPOP) for Constrained Changepoint Detection in Genomic Data (2022) not zbMATH
  2. Zhao, Zifeng; Yau, Chun Yip: Alternating pruned dynamic programming for multiple epidemic change-point estimation (2021)
  3. Hocking, Toby Dylan; Rigaill, Guillem; Fearnhead, Paul; Bourque, Guillaume: Constrained dynamic programming and supervised penalty learning algorithms for peak detection in genomic data (2020)