Software
This website contains links to codes developed by Dr. Chekouo, together with some of the datasets used in their publications.
BIPnet R package implements an MCMC algorithm for a Bayesian analysis that integrates multi-omics data types, clinical covariates and clinical response variables
Reference paper: Thierry Chekouo and Sandra (2021), Bayesian Integrative Analysis and Prediction with Application to Atherosclerosis Cardiovascular Disease}, Biostatistics, In press.
BayesF2D R package for the implementation of an MCMC algorithm for a Bayesian Analysis for functional 2D data and performs prediction of a scalar response.
Reference paper: Thierry Chekouo, Shariq Mohammed and Arvind Rao (2020), A Bayesian 2D functional linear model for gray-level co-occurrence matrices in texture analysis of lower grade gliomas, NeuroImage: Clinical, Volume 28, Article 102437 [pdf]
BACkPAy R package for identifying patterns with (non) differential expression data using BACkPAy (BAyesian mixture model that efficiently determines Clusters of proteins with similar "pre-defined" expression PAtterns)
Pattern visualization (ShinyApp) for showing patterns for expression data obtained from BACkPAy. Data example, Manual.
Pattern visualization (ShinyApp) obtained from BACkPAy for the observed cell line proteomic data
Reference Paper: Thierry Chekouo et al (2020), Investigating protein patterns in human leukemia cell line experiments: A Bayesian approach for extremely small sample sizes, Statistical methods in medical research, Volume 29, Number 4, pages 1181-1196 [pdf]
Matlab Code for integrative Bayesian models for mRNAs and microRNAs.
Reference paper: Chekouo et al (2015). A Bayesian Integrative Approach to Biomarker Selection with Application to Kidney Cancer, Biometrics, Vol. 71, Issue 2, pages 428-438
Matlab Code for integrative Bayesian models for imaging genetics.
Reference paper: Thierry Chekouo et al (2016), A Bayesian predictive model for imaging genetics with application to schizophrenia, The Annals of Applied Statistics, Volume 10, Number 3 (2016), 1547-1571.
C code for integrative Bayesian approaches with unbalanced sample sizes
Reference paper: Thierry Chekouo et al (2017), A Bayesian integrative approach for multi-platform genomics data: a kidney cancer case study, Biometrics, Vol. 73, Issue 2, pages 615-623
Java code for the Penalized Biclustering model
Reference paper: Thierry Chekouo and Alejandro Murua (2015), The Penalized Biclustering model and Related Algorithms, Journal of Applied Statistics, vol. 42, issue 6, pages 1255-1277