User profiles for S. C. Hicks

Stephanie C. Hicks

Associate Professor, Johns Hopkins Bloomberg School of Public Health
Verified email at jhu.edu
Cited by 7449

[HTML][HTML] Eleven grand challenges in single-cell data science

…, J Köster, E Szczurek, DJ McCarthy, SC Hicks… - Genome biology, 2020 - Springer
The recent boom in microfluidics and combinatorial indexing strategies, combined with low
sequencing costs, has empowered single-cell sequencing technology. Thousands—or even …

Orchestrating single-cell analysis with Bioconductor

…, W Huber, M Morgan, R Gottardo, SC Hicks - Nature …, 2020 - nature.com
Recent technological advancements have enabled the profiling of a large number of genome-wide
features in individual cells. However, single-cell data present unique challenges that …

Comparison of outcomes of synthetic mesh vs suture repair of elective primary ventral herniorrhaphy: a systematic review and meta-analysis

MT Nguyen, RL Berger, SC Hicks, JA Davila, LT Li… - JAMA …, 2014 - jamanetwork.com
Importance More than 350 000 ventral hernias are repaired in the United States annually, of
which 75% are primary ventral hernias (eg, umbilical or epigastric hernias). Despite the …

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

SC Hicks, FW Townes, M Teng, RA Irizarry - Biostatistics, 2018 - academic.oup.com
Until recently, high-throughput gene expression technology, such as RNA-Sequencing (RNA-seq)
required hundreds of thousands of cells to produce reliable measurements. Recent …

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

…, Y Yin, JE Kleinman, TM Hyde, N Rao, SC Hicks… - Nature …, 2021 - nature.com
We used the 10x Genomics Visium platform to define the spatial topography of gene expression
in the six-layered human dorsolateral prefrontal cortex. We identified extensive layer-…

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

FW Townes, SC Hicks, MJ Aryee, RA Irizarry - Genome biology, 2019 - Springer
Single-cell RNA-Seq (scRNA-Seq) profiles gene expression of individual cells. Recent
scRNA-Seq datasets have incorporated unique molecular identifiers (UMIs). Using negative …

[HTML][HTML] A systematic evaluation of single-cell RNA-sequencing imputation methods

W Hou, Z Ji, H Ji, SC Hicks - Genome biology, 2020 - Springer
Background The rapid development of single-cell RNA-sequencing (scRNA-seq) technologies
has led to the emergence of many methods for removing systematic technical noises, …

[HTML][HTML] A practical guide to methods controlling false discoveries in computational biology

…, A Subramanian, M Teng, C Shukla, EJ Alm, SC Hicks - Genome biology, 2019 - Springer
Background In high-throughput studies, hundreds to millions of hypotheses are typically
tested. Statistical methods that control the false discovery rate (FDR) have emerged as popular …

Development and validation of a risk-stratification score for surgical site occurrence and surgical site infection after open ventral hernia repair

RL Berger, LT Li, SC Hicks, JA Davila, LS Kao… - Journal of the American …, 2013 - Elsevier
Background Current risk-assessment tools for surgical site occurrence (SSO) and surgical
site infection (SSI) are based on expert opinion or are not specific to open ventral hernia …

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

…, M Tippani, BK Barry, DB Hancock, SC Hicks… - Neuron, 2021 - cell.com
Single-cell gene expression technologies are powerful tools to study cell types in the human
brain, but efforts have largely focused on cortical brain regions. We therefore created a …