Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures | Paper Citation Record

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Rank Discrim- inants for Predicting Phenotypes from RNA Expression.The Annals of Applied Statistics, 8(3):1469–1491, 2014

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Deciphering signatures of mutational processes operative in human cancer.Cell reports, 3(1):246–259, 2013

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures A tutorial on adaptive mcmc

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures MOFA+: a statistical framework for comprehensive integration of multi-modal single-cell data

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Integrative clustering reveals a novel split in the lumi- nal A subtype of breast cancer with impact on outcome.Breast Cancer Research, 19(1):44, 2017

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This paper cites Badgeley, Stuart C.

Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Badgeley, Stuart C

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This paper cites Understanding uncertainty in bayesian cluster analysis.arXiv preprint arXiv:2506.16295.

Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Understanding uncertainty in bayesian cluster analysis.arXiv preprint arXiv:2506.16295

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures PAM50 breast cancer subtyping 34 by RT-qPCR and concordance with standard clinical molecular markers

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Adaptive Stereographic MCMC

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This paper cites Chen and Daniela M.

Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Chen and Daniela M

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Stability post-processing for items im- portance in preference learning via the bayesian mallows model

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures The genomic and transcriptomic ar- chitecture of 2,000 breast tumours reveals novel subgroups.Nature, 486(7403):346–352, 2012

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Bayesian aggregation of order-based rank data.Journal of the American Statistical Association, 109(507):1023–1039, 2014

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Vol- ume 11 of Lecture Notes - Monograph Series

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Rank-based bayesian variable selection for genome-wide transcriptomic analyses.Statis- tics in Medicine, 41(23):4532–4553, 2022

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Systematic bias in genomic classifi- cation due to contaminating non-neoplastic tissue in breast tumor samples

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Dna methylation at enhancers identifies distinct breast cancer lineages.Nature Communications, 8(1):1379, 2017

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Unresolved cited work

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Variable selection methods for model-based clustering.Statistics Surveys, 12:18–65, 2018

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Selective inference for hierarchical clustering.Journal of the American Statistical Association, 119(545):332–342, 2024

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Uncovering clinically relevant breast cancer subtypes biomarkers using integrative bioinformatics and machine learning approaches.Biomarkers, pages 1–12, 2026

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome.BMC Bioinformatics, 12(1):323, 2011

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures A sparse negative binomial mixture model for clustering RNA-seq count data.Biostatistics, 24(1):68–84, 2023

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Model-based learning from preference data.Annual Review of Statistics and Its Application, 6(1):329–354, 2019

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Effective Sampling and Learning for Mal- lows Models with Pairwise-Preference Data.Journal of Machine Learning Research, 15(117):3963–4009, 2014

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Luce.Individual choice behavior: A theoretical analysis

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Non-null ranking models

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures An Exponential Model for Infinite Rankings

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Dirichlet Process Mixtures of Generalized Mallows Models

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures A fully bayesian latent variable model for integrative clustering analysis of multi-type omics data.Biostatistics, 19(1):71–86, 05 2017

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures PGC-1 alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human di- abetes.Nature Genetics, 34:267–73, 2003

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Spike-and-slab lasso biclustering.The Annals of Applied Statistics, 15(1):148–173, 2021

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Comparison of sparse biclustering algorithms for gene expression datasets.Briefings in bioinformatics, 22(6):bbab140, 2021

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Parker, Michael Mullins, Maggie Chon U Cheang, Samuel C Y Le- ung, David Voduc, Tammi L

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Molecular portraits of human breast tumours.Nature, 406(6797):747–752, 2000

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Clinical implications of the intrinsic molecular subtypes of breast cancer.The Breast, 24:S26–S35, 2015

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures BayesMallows: An R Package for the Bayesian Mallows Model.The R Journal, 12(1):324–342, 2020

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Mootha, Sayan Mukher- jee, Benjamin L

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Bayesian variable selection in clustering high-dimensional data.Journal of the American Statistical Association, 100(470):602–617, 2005

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Probabilistic preference learning with the mallows rank model

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Bayesian Cluster Analysis: Point Esti- mation and Credible Balls (with Discussion).Bayesian Analysis, 13(2):559– 626, 2018

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures MapSplice: Accurate mapping of RNA-seq reads for splice junction discovery.Nucleic Acids Research, 38(18):e178, 2010

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Breast cancer molecular profiling with single sample predictors: a retrospective analysis

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Bayesian genome-wide clustering and variable selection of transcriptomic data via rank-based mixtures Witten and Robert Tibshirani

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