publications

2025

1. A paradoxical population structure of var DBL types in Africa

   M.H. Tan, K.E. Tiedje, Q. Feng, and 5 more authors

   PLOS Pathogens, 2025

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2. Spatial transcriptomics identifies molecular niche dysregulation associated with distal lung remodeling in pulmonary fibrosis

   A. Vannan, R. Lyu, A.L. Williams, and 21 more authors

   Nature Genetics, 2025

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   We apply spatial transcriptomics to identify molecular niche dysregulation in pulmonary fibrosis, revealing key changes associated with distal lung remodeling.

2024

1. Going beyond cell clustering and feature aggregation: Is there single cell level information in single-cell ATAC-seq data?

   A.W.C. Kwok, H. Shim, and D.J. McCarthy

   bioRxiv, 2024

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2. Multi-scale Poisson process approaches for differential expression analysis of high-throughput sequencing data

   H. Shim, Z. Xing, E. Pantaleo, and 3 more authors

   Annals of Applied Statistics. Software: multiseq , 2024

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   We develop multiseq, a multi-scale Bayesian method for differential expression analysis of high-throughput sequencing data that models count data directly and substantially outperforms existing approaches.

3. Semi-Supervised Learning Under General Causal Models

   A. Moore, H. Shim, J. Zhu, and 1 more author

   IEEE Transactions on Neural Networks and Learning Systems, 2024

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2023

1. Robust differential composition and variability analysis for multisample cell omics

   S. Mangiola, A. Schulze, M. Trussart, and 7 more authors

   PNAS. Software: sccomp , 2023

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   We develop sccomp, a method for differential composition and variability analysis for multisample cell omics data that is robust to outliers and handles multiple covariates.

2. Identification of cell barcodes from long-read single-cell RNA-seq with BLAZE

   Y. You, Y.D.J. Prawer, R. De Paoli-Iseppi, and 4 more authors

   Genome Biology. Software: BLAZE , 2023

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   We develop BLAZE, a tool for identifying cell barcodes from long-read single-cell RNA-seq data without reference to short-read data.

3. Detecting Jumps on a Tree: a Hierarchical Pitman-Yor Model for Evolution of Phenotypic Distributions

   H. Sun, H. Shim, and V. Rao

   arXiv. Software: treeHPYP , 2023
4. Unravelling var complexity: Relationship between DBL types and var genes in Plasmodium falciparum

   M.H. Tan, H. Shim, Y. Chan, and 1 more author

   Frontiers in Parasitology, 2023

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2022

1. sgcocaller and comapr: personalised haplotype assembly and comparative crossover map analysis using single-gamete sequencing data

   R. Lyu, V. Tsui, W. Crismani, and 3 more authors

   Nucleic Acids Research. Software: comapr , 2022

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   We develop sgcocaller and comapr, tools for personalised haplotype assembly and comparative crossover map analysis using single-gamete sequencing data.

2. Trade-off between conservation of biological variation and batch effect removal in deep generative modeling for single-cell transcriptomics

   L. Hui, D.J. McCarthy, H. Shim, and 1 more author

   BMC Bioinformatics, 2022

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3. NanoSplicer: Accurate identification of splice junctions using Oxford Nanopore sequencing

   Y. You, M. B. Clark, and H. Shim

   Bioinformatics. Software: NanoSplicer , 2022

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   We develop NanoSplicer, a tool for accurate identification of splice junctions using Oxford Nanopore sequencing data.

4. An accurate method for identifying recent recombinants from unaligned sequences

   Q. Feng, K. Tiedje, S. Ruybal-Pesántez, and 5 more authors

   Bioinformatics. Software: detREC , 2022

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2021

1. A Comparison of Bayesian Inference Techniques for Sparse Factor Analysis

   Y. S. Foo, and H. Shim

   arXiv. Software: sparsefactor , 2021
2. McSplicer: a probabilistic model for estimating splice site usage from RNA-seq data

   I. Alqassem, Y. Sonthalia, E. Klitzke, and 2 more authors

   Bioinformatics. Software: McSplicer , 2021

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   McSplicer is a probabilistic model for estimating splice site usages using short-read RNA-seq data.

2018

1. circuitSNPs: Predicting genetic effects using a Neural Network to model regulatory modules of DNase-seq footprints

   A. G. Shanku, A. Findley, C. A. Kalita, and 3 more authors

   bioRxiv, 2018

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2017

1. Promoter shape varies across populations and affects promoter evolution and expression noise

   I. E. Schor, J. F. Degner, D. Harnett, and 8 more authors

   Nature Genetics, 2017

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   We find that promoter shape — the distribution of transcription start sites — varies across populations and affects both promoter evolution and expression noise.

2. BayesCAT: Bayesian Co-estimation of Alignment and Tree

   H. Shim, and B. Larget

   Biometrics. Software: BayesCAT , 2017

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   BayesCAT jointly estimates sequence alignment and phylogeny while modeling arbitrary-length overlapping indel events.

2016

1. Thousands of novel translated open reading frames in humans inferred by ribosome footprint profiling

   A. Raj, S. Wang, H. Shim, and 6 more authors

   eLife. Software: riboHMM , 2016

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   Using riboHMM, a hidden Markov model leveraging ribosome profiling data, we identify thousands of novel translated open reading frames in the human genome.

2015

1. msCentipede: Modeling heterogeneity across genomic sites improves accuracy in the inference of transcription factor binding

   A. Raj, H. Shim, Y. Gilad, and 2 more authors

   PLoS ONE. Software: msCentipede , 2015

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   msCentipede uses hierarchical multi-scale models for Poisson processes to improve transcription factor binding site inference from DNase-seq data.

2. Wavelet-based genetic association analysis of functional phenotypes arising from high-throughput sequencing assays

   H. Shim, and M. Stephens

   Annals of Applied Statistics. Software: WaveQTL , 2015

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   We develop WaveQTL, a wavelet-based method for genetic association analysis of functional phenotypes from high-throughput sequencing assays. WaveQTL identified 50% more dsQTLs than typical window-based analyses.

3. A multivariate genome-wide association analysis of 10 LDL subfractions, and their response to statin treatment, in 1868 Caucasians

   H. Shim, D. I. Chasman, J. D. Smith, and 5 more authors

   PLoS ONE. Software: mvBIMBAM , 2015

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   We develop mvBIMBAM for joint analysis of multiple related phenotypes, demonstrating that joint analyses can considerably increase power to detect associations compared with conventional univariate analyses.

2013

1. A statin-dependent QTL for GATM expression is associated with statin-induced myopathy

   L. M. Mangravite, B. E. Engelhardt, M. W. Medina, and 7 more authors

   Nature, 2013

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2009

1. Genome-wide association studies using SNPs vs. haplotypes: An empirical comparison with data from the North American Rheumatoid Arthritis Consortium

   H. Shim, H. Chun, C. D. Engelman, and 1 more author

   BMC Proceedings, 2009

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2007

1. Integrating quantitative information from ChIP-chip experiments into motif finding

   H. Shim, and S. Keles

   Biostatistics, 2007

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   We develop methods for motif discovery integrating ChIP-seq quantitative information, showing superior sensitivity and specificity especially when the motif of interest has low abundance.