ct47

Repeat units that encode for a cancer testis antigen. 
Locus (hg18): Xq24 
Unit (kb): 4.8 
Restriction enzyme: EcoRI 
Encoded product : cancer testis antigen 47

datasets

A two-step Bayesian approach for mode inference following
Cross, Hoogerheide, Labonne and van Dijk (2024) <doi:10.1016/j.econlet.2024.111579>).
First, a mixture distribution is fitted on the data using a sparse finite
mixture (SFM) Markov chain Monte Carlo (MCMC) algorithm. The number of
mixture components does not have to be known; the size of the mixture is
estimated endogenously through the SFM approach. Second, the modes of the
estimated mixture at each MCMC draw are retrieved using algorithms
specifically tailored for mode detection. These estimates are then used to
construct posterior probabilities for the number of modes, their locations
and uncertainties, providing a powerful tool for mode inference.

Paul Labonne

BayesMultiMode

Bayesian Mode Inference

Nalan Baştürk

Jamie Cross

Peter de Knijff

Lennart Hoogerheide

Herman van Dijk

ct47 function

A vector of counts with 410 elements.

Format

Repeat units that encode for a cancer testis antigen. 
Locus (hg18): Xq24 
Unit (kb): 4.8 
Restriction enzyme: EcoRI 
Encoded product : cancer testis antigen 47

ct47: X chromosomal macrosatellite repeats ct47

Description

Usage

Arguments

Format

References