Publications

  • HL Crowell, SX Morillo Leonardo, C Soneson, MD Robinson. The shaky foundations of simulating single-cell RNA sequencing data. Genome Biology 24, 62 (2023)

  • D Righelli\(^\ast\), HL Crowell\(^\ast\), LM Weber\(^\ast\), B Pardo, L Collado-Torres, S Ghazanfar, ATL Lun, SC Hicks\(^\dagger\), D Risso\(^\dagger\). SpatialExperiment: infrastructure for spatially resolved transcriptomics data in R using Bioconductor. Bioinformatics 38, 3128-3131 (2022)

  • HL Crowell\(^\ast\), S Chevrier\(^\ast\), A Jacobs, S Sivapatham, Tumor Profiler Consortium, B Bodenmiller\(^\dagger\), MD Robinson\(^\dagger\). An R-based reproducible and user-friendly preprocessing pipeline for CyTOF data. F1000Research 9, 1263.v2 (2022)

  • HL Crowell, C Soneson, P-L Germain, D Calini, L Collin, C Raposo, D Malhotra, MD Robinson. muscat detects subpopulation-specific state transitions from multi-sample multi-condition single-cell transcriptomics data. Nature Communications 11, 6077 (2020)

  • S Chevrier\(^\ast\), HL Crowell\(^\ast\), VRT Zanotelli\(^\ast\), S Engler, MD Robinson, B Bodenmiller. Compensation of Signal Spillover in Suspension and Imaging Mass Cytometry. Cell Systems 6, 612–620.e5 (2018)

  • Crowell HL, MacLean AL, Stumpf MPH. Feedback mechanisms control coexistence in a stem cell model of acute myeloid leukaemia. Journal of Theoretical Biology 401, 43-53 (2016)

Collaborations

  • WJ Hutchison, TJ Keyes, The Tidyomics Consortium, HL Crowell, C Soneson, V Yuan, AA Nahid, W Mu, J Park, ES Davis, M Tang, PP Axisa, N Sato, R Gottardo, M Morgan, S Lee, M Lawrence, SC Hicks, GP Nolan, KL Davis, AT Papenfuss, M Love, S Mangiola. The tidyomics ecosystem: Enhancing omic data analyses. bioRxiv, 2023.09.10.557072

  • A Garrido-Trigo, AM Corraliza, M Veny, I Dotti, E Melon-Ardanaz, A Rill, HL Crowell, Á Corbí, V Gudiño, M Esteller, I Álvarez-Teubel, D Aguilar, MC Masamunt, E Killingbeck, Y Kim, M Leon, S Visvanathan, D Marchese, G Caratù, A Martin-Cardona, M Esteve, J Panés, E Ricart, E Mereu\(^\ast\), H Heyn\(^\ast\), A Salas. Macrophage and neutrophil heterogeneity at single-cell spatial resolution in inflammatory bowel disease. Nature Communications 14, 4506 (2023)

  • A Sonrel\(^\ast\), A Luetge\(^\ast\), C Soneson\(^\ast\), IM Gonzalez\(^\ast\), PL Germain, S Knyazev, J Gilis, R Gerber, R Seurinck, D Paul, E Sonder, HL Crowell, I Fanaswala, A Al-Ajami, E Heidari, S Schmeing, S Milosavljevic, Y Saeys, S Mangul, MD Robinson. Meta-analysis of (single-cell method) benchmarks reveals the need for extensibility and interoperability. Genome Biology 24, 119 (2023)

  • S Tiberi, HL Crowell, P Samartsidis, LM Weber, MD Robinson. distinct: a novel approach to differential distribution analyses. Annals of Applied Statistics 17(2):1681-1700 (2023)

  • KD Prummel, HL Crowell, S Nieuwenhuize, EC Brombacher, S Daetwyler, C Soneson, J Kresoja-Rakic, A Kocere, M Ronner, A Ernst, Z Labbaf, DE Clouthier, AB Firulli, H Sánchez-Iranzo, SR Naganathan, R O’Rourke, E Raz, N Mercader, A Burger, E Felley-Bosco, J Huisken, MD Robinson, C Mosimann. Hand2 delineates mesothelium progenitors and is reactivated in mesothelioma. Nature Communications 13, 1677 (2022)

  • RA Heller, J Seelig, HL Crowell, M Pilz, P Haubruck, Q Sun, L Schomburg, V Daniel, A Moghaddam, B Biglari. Predicting neurological recovery after traumatic spinal cord injury by time-resolved analysis of monocyte subsets. Brain 144, 3159 (2021)

  • A Lütge, J Zyprych-Walczak, UB Kunzmann, HL Crowell, D Calini, D Malhotra, C Soneson, MD Robinson. CellMixS: quantifying and visualizing batch effects in single-cell RNA-seq data Life Science Alliance 6, e202001004 (2021)

  • J Seelig\(^\ast\), RA Heller\(^\ast\), P Haubruck, Q Sun, GJ Klingenberg, J Hackler, HL Crowell, V Daniel, A Moghaddam, L Schomburg, B Biglari. Selenium-binding protein 1 (SELENBP1) as biomarker for adverse clinical outcome after traumatic spinal cord injury. Frontiers in Neuroscience 15, 680240 (2021)

  • M Nowicka, C Krieg, HL Crowell, LM Weber, FJ Hartmann, S Guglietta, B Becher, MP Levesque, MD Robinson. CyTOF workflow: differential discovery in high-throughput high-dimensional cytometry datasets. F1000Research 6, 748.v4 (2019)