User profiles for S. C. Hicks
Stephanie C. HicksAssociate 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
The recent boom in microfluidics and combinatorial indexing strategies, combined with low
sequencing costs, has empowered single-cell sequencing technology. Thousands—or even …
sequencing costs, has empowered single-cell sequencing technology. Thousands—or even …
Orchestrating single-cell analysis with Bioconductor
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 …
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
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 …
which 75% are primary ventral hernias (eg, umbilical or epigastric hernias). Despite the …
Missing data and technical variability in single-cell RNA-sequencing experiments
Until recently, high-throughput gene expression technology, such as RNA-Sequencing (RNA-seq)
required hundreds of thousands of cells to produce reliable measurements. Recent …
required hundreds of thousands of cells to produce reliable measurements. Recent …
Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex
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-…
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
Single-cell RNA-Seq (scRNA-Seq) profiles gene expression of individual cells. Recent
scRNA-Seq datasets have incorporated unique molecular identifiers (UMIs). Using negative …
scRNA-Seq datasets have incorporated unique molecular identifiers (UMIs). Using negative …
[HTML][HTML] A systematic evaluation of single-cell RNA-sequencing imputation methods
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, …
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
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 …
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
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 …
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
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 …
brain, but efforts have largely focused on cortical brain regions. We therefore created a …