Hicks, Stephanie C.

Eleven grand challenges in single-cell data science

Lähnemann, D., Köster, J., Szczurek, E., McCarthy, D. J., Hicks, S. C., Robinson, M. D., Vallejos, C. A., Campbell, K. R., Beerenwinkel, N., Mahfouz, A., et al. (2020) · Genome Biology

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 1,327

Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex

Maynard, K. R., Collado-Torres, L., Weber, L. M., Uytingco, C., Barry, B. K., Williams, S. R., Catallini, J. L., Tran, M. N., Besich, Z., Tippani, M., et al. (2021) · Nature Neuroscience

Single-cell and spatial transcriptomicsGenomics and Chromatin Dynamics

Cited by 1,222

Orchestrating single-cell analysis with Bioconductor

Amezquita, R. A., Lun, A. T. L., Becht, E., Carey, V. J., Carpp, L. N., Geistlinger, L., Marini, F., Rue-Albrecht, K., Risso, D., Soneson, C., et al. (2020) · Nature Methods

Single-cell and spatial transcriptomicsGenomics and Phylogenetic Studies

Cited by 945

Missing data and technical variability in single-cell RNA-sequencing experiments

Hicks, S. C., Townes, F. W., Teng, M., & Irizarry, R. A. (2018) · Biostatistics

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 635

Missing Data and Technical Variability in Single-Cell RNA-Sequencing Experiments

Hicks, S. C., Townes, F. W., Teng, M., & Irizarry, R. A. (2015) · Biostatistics

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 625

Feature selection and dimension reduction for single-cell RNA-Seq based on a multinomial model

Townes, F. W., Hicks, S. C., Aryee, M. J., & Irizarry, R. A. (2019) · Genome Biology

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 471

A practical guide to methods controlling false discoveries in computational biology

Korthauer, K., Kimes, P. K., Duvallet, C., Reyes, A., Subramanian, A., Teng, M., Shukla, C., Alm, E. J., & Hicks, S. C. (2019) · Genome Biology

Statistical Methods in Clinical TrialsBioinformatics and Genomic Networks

Cited by 436

Prediction of missense mutation functionality depends on both the algorithm and sequence alignment employed

Hicks, S., Wheeler, D. A., Plon, S. E., & Kimmel, M. (2011) · Human Mutation

Genomics and Rare DiseasesGenomics and Phylogenetic Studies

Cited by 223

Single-nucleus transcriptome analysis reveals cell-type-specific molecular signatures across reward circuitry in the human brain

Tran, M. N., Maynard, K. R., Spangler, A., Huuki, L. A., Montgomery, K. D., Sadashivaiah, V., Tippani, M., Barry, B. K., Hancock, D. B., Hicks, S. C., et al. (2021) · Neuron

Single-cell and spatial transcriptomicsNeurotransmitter Receptor Influence on Behavior

Cited by 219

Genetic demultiplexing of pooled single-cell RNA-sequencing samples in cancer facilitates effective experimental design

Weber, L. M., Hippen, A. A., Hickey, P. F., Berrett, K. C., Gertz, J., Doherty, J. A., Greene, C. S., & Hicks, S. C. (2021) · GigaScience

Single-cell and spatial transcriptomicsGenomics and Phylogenetic Studies

Cited by 37