Github

• DIMPLE | Distance based Inference for MultipLex imaging Experiments. (Massoti et al., 2023)

• DreameSpase | R package for Bayesian spatial regression with variable selection that jointly models within- and between-biopsy spatial heterogeneity in non-conformable tumor imaging data. (Osher et al., 2024)

• GraphR | GraphR_supplementary | A probabilistic modeling framework for genomic networks incorporating sample heterogeneity. (Chen et al., 2023)

• iRx | Probabilistic modeling framework to integrate gene expression and drug response data. (Saha et al., 2022)

• QUANTICO | Simulation studies and synthetic real-data analyses of the QUANTICO framework. (Das et al., 2023)

• RADIOHEAD | Radiogenomic Analysis Incorporating Tumor Heterogeneity in Imaging Through Densities. (Mohammed et al., 2021)

• rBGR | R package that implements a flexible Bayesian model to construct heterogeneous graphs under non-normal continuous data. (Yao et al., 2025)

• RxTree | Probabilistic Learning of Treatment Trees in Cancer (Yao et al., 2022), we address this unmet translational research need by proposing a novel Bayesian probabilistic tree-based framework, referred to as treatment trees (Rx-tree), to investigate the hierarchical relationships between treatments. This repository contains the code for the manuscript and we further visualize the result through an R-shiny application.

• SGR | The goal of sGR model is to estimate spatially varying graphs over the spatial domain of the tissue for spatial genomics data. (Acharrya et al., 2025)

• SLAC | The software component of the paper "SLAC: A Data Augmentation Approach to Modeling Multiplex Imaging Data." (manuscript forthcoming)

• SpaceX | Website | Gene Co-expression Network Estimation for Spatial Transcriptomics. (Acharyya et al., 2022)

• SPARTIN | SPARTINsupplement | An implementation of the components of the SPARTIN pipeline in R. (Osher et al., 2023)

• TransPRECISE | Personalized Network Modeling of the Pan-Cancer Patient and Cell Line Interactome. (Bhattacharyya et al., 2020)

• ultrametricMat | A package designed to conduct the Bayesian inference on the ultrametric matrices by the leveraging the bijection map between the ultrametric matrices and the tree space. We refer to more details to "Geometry-driven Bayesian Inference for Ultrametric Covariance Matrices." (Yao et al., 2024)

Shiny Apps

• Bayesian Graphical Regression | (Ni et al., 2018, JASA)

• BaySyn | Bayesian Evidence Synthesis for Multi-system Multiomic Integration. (Bhattacharyya et al., 2022)

• COV-N | Network-based Dynamic Case Prediction and Healthcare Forecasting for COVID-19 in India. (Bhattacharyya et al., 2021)

• DIMPLE | DIstance Matrices for MultiPLEx imaging. (Masotti et al., 2023)

• fiBAG | Functional Integrative Bayesian Analysis of High-dimensional Multiplatform Genomic Data. (Bhattacharyya et al., 2022)

• GPVIBES | Gaussian Process-based Varying Coefficient Model using Bayesian Variable Selection.

• GraphR | A probabilistic modeling framework for genomic networks incorporating sample heterogeneity. (Chen et al., 2023)

• PRECISE | Proteomic based integrated subject-specific networks in cancer. (Ha et al., 2018, Nature Scientific Reports)

• TransPRECISE | Personalized Network Modeling of the Pan-cancer Patient and Cell Line Interactome. (Bhattacharyya et al., 2020)