Names of group members are in bold.

2022

S. Mangiola, A. Schulze*, M. Trussart*, E. Zozaya*, M. Ma, Z. Gao, A. F. Rubin, T. P. Speed#, H. Shim#, A. T. Papenfuss#, Robust differential composition and variability analysis for multisample cell omics (*: These authors contributed equally; #: These authors contributed equally)[link][R package sccomp]

R. Lyu, V. Tsui, W. Crismani, R. Liu, H. Shim, D.J. McCarthy, sgcocaller and comapr: personalised haplotype assembly and comparative crossover map analysis using single gametes [link][software sgcocaller][software comapr in github][software comapr in Bioconductor][code for analysis 1][code for analysis 2]

Q. Feng, K. Tiedje, S. Ruybal-Pesántez, G. Tonkin-Hill, M. Duffy, K. Day, H. Shim, Y. Chan, An accurate method for identifying recent recombinants from unaligned sequences. Bioinformatics. 2022 Jan 13, doi:10.1093/bioinformatics/btac012 [link][software]

2021

Y. S. Foo and H. Shim, A Comparison of Bayesian Inference Techniques for Sparse Factor Analysis.[link][Implementation of proposed algorithms]

Y. You, M. B. Clark, H. Shim, NanoSplicer: Accurate identification of splice junctions using Oxford Nanopore sequencing.[link][supplementary material] [software NanoSplicer]

H. Shim, Z. Xing, E. Pantaleo, F. Luca, R. Pique-Regi, M. Stephens, Multi-scale Poisson process approaches for differential expression analysis of high-throughput sequencing data.[link][supplementary material] [software multiseq][code for analysis]

I. Alqassem, Y. Sonthalia, E. Klitzke, H. Shim*, S. Canzar*, McSplicer: a probabilistic model for estimating splice site usage from RNA-seq data. Bioinformatics. 2021 Jan 30, doi: 10.1093/bioinformatics/btab050 (*: joint corresponding authors) [link][software McSplicer]

2018

A. G. Shanku, A. Findley, C. A. Kalita, H. Shim, F. Luca, R. Pique-Regi, circuitSNPs: Predicting genetic effects using a Neural Network to model regulatory modules of DNase-seq footprints [link]

2017

I. E. Schor, J. F. Degner, D. Harnett, E. Cannavo, F. P. Casale, H. Shim, D. Garfield, E. Birney, M. Stephens, O. Stegle, E. E. Furlong, Promoter shape varies across populations and affects promoter evolution and expression noise, Nature Genetics, 2017, February 13, doi:10.1038/ng.3791 [link]

H. Shim and B. Larget, BayesCAT: Bayesian Co-estimation of Alignment and Tree, Biometrics. 2017 Jan 18. doi: 10.1111/biom.12640 [link][supplementary materials][software BayesCAT]

2016

A. Raj*, S. Wang*, H. Shim*, A. Harpak, Y. I. Li, B. Englemann, M. Stephens, Y. Gilad, J. K. Pritchard, Thousands of novel translated open reading frames in humans inferred by ribosome footprint profiling, eLife 2016;10.7554/eLife.13328. (*: co-first authors) [link][software riboHMM]

2015

A. Raj*, H. Shim*, Y. Gilad, J. K. Pritchard and M. Stephens, msCentipede: Modeling heterogeneity across genomic sites improves accuracy in the inference of transcription factor binding, PLoS ONE 10(9): e0138030, 2015. (*: co-first authors)[link][software msCentipede]

H. Shim and M. Stephens, Wavelet-based genetic association analysis of functional phenotypes arising from high-throughput sequencing assays, Ann. Appl. Stat. 9 (2015), no. 2, 665–686.[pdf][link][software WaveQTL][supplementary materials][supplementary figures]

H. Shim, D. I. Chasman, J. D. Smith, S. Mora, P. M. Ridker, D. A. Nickerson, R. M. Krauss, M. Stephens,  A multivariate genome-wide association analysis of 10 LDLsubfractions, and their response to statin treatment, in 1868 Caucasians, PLoS ONE 10(4): e0120758, 2015. [link][software mvBIMBAM]

Previous

L. M. Mangravite, B. E. Engelhardt, M. W. Medina, J. D. Smith, C. D. Brown, D. I. Chasman, B. H. Mecham, B. Howie, H. Shim, D. Naidoo, Q. Feng, M. J. Rieder, Y. D. Chen, J. I. Rotter, P. M. Ridker, J. C. Hopewell, S. Parish, J. Armitage, R. Collins, R. A. Wilke, D. A. Nickerson, M. Stephens, R. M. Krauss.  A statin-dependent QTL for GATM expression is associated with statin-induced myopathy, Nature, 502:377–380, 2013. [link]

H. Shim*, H. Chun*, C. D. Engelman, and B. A. Payseur. Genome-wide association studies using SNPs vs. haplotypes:  An empirical comparison with data from the North American Rheumatoid Arthritis Consortium, BMC Proceedings, 3 (Suppl 7):S35, 2009 (*: co-first authors) [link]

H. Shim and S. Keles. Integrating quantitative information from ChIP-chip experiments into motif finding, Biostatistics, 9(1):51-65, 2007. [link][software SUCcESS]