15 citations · 21 across the 4 of their papers we have counts for
4 papers
Generalized Functional Pruning Optimal Partitioning (GFPOP) for Constrained Changepoint Detection in Genomic Data
Toby Dylan Hocking, Guillem Rigaill, Paul Fearnhead +1
We describe a new algorithm and R package for peak detection in genomic data sets using constrained changepoint algorithms. These detect changes from background to peak regions by…
A log-linear time algorithm for constrained changepoint detection
Toby Dylan Hocking, Guillem Rigaill, Paul Fearnhead +1
Changepoint detection is a central problem in time series and genomic data. For some applications, it is natural to impose constraints on the directions of changes. One example is…
PeakSegJoint: fast supervised peak detection via joint segmentation of multiple count data samples
Toby Dylan Hocking, Guillaume Bourque
Joint peak detection is a central problem when comparing samples in genomic data analysis, but current algorithms for this task are unsupervised and limited to at most 2 sample typ…
Visual annotations and a supervised learning approach for evaluating and calibrating ChIP-seq peak detectors
Toby Dylan Hocking, Patricia Goerner-Potvin, Andreanne Morin +2
Many peak detection algorithms have been proposed for ChIP-seq data analysis, but it is not obvious which method and what parameters are optimal for any given data set. In contrast…