Stephanie C. Hicks
A5028505800- Single-cell and spatial transcriptomics
- Gene expression and cancer classification
- Cancer Genomics and Diagnostics
- Bioinformatics and Genomic Networks
- Cancer-related Molecular Pathways
- Data Analysis with R
- Head and Neck Cancer Studies
- Hernia repair and management
- Cell Image Analysis Techniques
- Cancer-related molecular mechanisms research
- Statistics Education and Methodologies
- Neuroinflammation and Neurodegeneration Mechanisms
- Molecular Biology Techniques and Applications
- RNA Research and Splicing
- Neural Networks and Applications
- Pelvic and Acetabular Injuries
- Data Mining Algorithms and Applications
- Gene Regulatory Network Analysis
- Lung Cancer Treatments and Mutations
- Congenital Diaphragmatic Hernia Studies
- Extracellular vesicles in disease
- Evolutionary Algorithms and Applications
- Radiomics and Machine Learning in Medical Imaging
- Adipose Tissue and Metabolism
- Statistical Methods and Inference
Johns Hopkins University
2018-2025
Johns Hopkins Medicine
2023
University of Baltimore
2023
Washington University in St. Louis
2018-2022
Massachusetts General Hospital
2022
Centre for Addiction and Mental Health
2022
Lieber Institute for Brain Development
2022
Baylor College of Medicine
2022
University of California, Irvine
2022
Bloomberg (United States)
2021
Until recently, high-throughput gene expression technology, such as RNA-Sequencing (RNA-seq) required hundreds of thousands cells to produce reliable measurements. Recent technical advances permit genome-wide measurement at the single-cell level. Single-cell RNA-Seq (scRNA-seq) is most widely used and numerous publications are based on data produced with this technology. However, RNA-seq scRNA-seq markedly different. In particular, unlike RNA-seq, majority reported levels in zeros, which...
Single-cell RNA-Seq (scRNA-Seq) profiles gene expression of individual cells. Recent scRNA-Seq datasets have incorporated unique molecular identifiers (UMIs). Using negative controls, we show UMI counts follow multinomial sampling with no zero inflation. Current normalization procedures such as log per million and feature selection by highly variable genes produce false variability in dimension reduction. We propose simple methods, including generalized principal component analysis (GLM-PCA)...
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 and powerful tools for error control. While classic FDR use only p values input, more modern been shown increase power by incorporating complementary information informative covariates prioritize, weight, group hypotheses. However, there is currently no consensus on how compare one another. We investigate accuracy,...
The rapid development of single-cell RNA-sequencing (scRNA-seq) technologies has led to the emergence many methods for removing systematic technical noises, including imputation methods, which aim address increased sparsity observed in data. Although have been developed, there is no consensus on how compare each other. Here, we perform a evaluation 18 scRNA-seq assess their accuracy and usability. We benchmark these terms similarity between imputed cell profiles bulk samples whether recover...
Abstract Cardiac radiotherapy (RT) may be effective in treating heart failure (HF) patients with refractory ventricular tachycardia (VT). The previously proposed mechanism of radiation-induced fibrosis does not explain the rapidity and magnitude which VT reduction occurs clinically. Here, we demonstrate hearts from RT that radiation achieve transmural within timeframe reduction. Electrophysiologic assessment irradiated murine reveals a persistent supraphysiologic electrical phenotype,...
Abstract Background Spatially-resolved transcriptomics has now enabled the quantification of high-throughput and transcriptome-wide gene expression in intact tissue while also retaining spatial coordinates. Incorporating precise mapping activity advances our understanding tissue-specific biological processes. In order to interpret these novel data types, interactive visualization tools are necessary. Results We describe spatialLIBD , an R/Bioconductor package interactively explore...
SpatialExperiment is a new data infrastructure for storing and accessing spatially-resolved transcriptomics data, implemented within the R/Bioconductor framework, which provides advantages of modularity, interoperability, standardized operations comprehensive documentation. Here, we demonstrate structure user interface with examples from 10x Genomics Visium seqFISH platforms, provide access to example datasets visualization tools in STexampleData, TENxVisiumData ggspavis packages.
Feature selection to identify spatially variable genes or other biologically informative is a key step during analyses of spatially-resolved transcriptomics data. Here, we propose nnSVG, scalable approach based on nearest-neighbor Gaussian processes. Our method (i) identifies that vary in expression continuously across the entire tissue within priori defined spatial domains, (ii) uses gene-specific estimates length scale parameters process models, and (iii) scales linearly with number...
The complexity and heterogeneity of schizophrenia have hindered mechanistic elucidation the development more effective therapies. Here, we performed single-cell dissection schizophrenia-associated transcriptomic changes in human prefrontal cortex across 140 individuals two independent cohorts. Excitatory neurons were most affected cell group, with transcriptional converging on neurodevelopment synapse-related molecular pathways. Transcriptional alterations included known genetic risk...
Nucleotide changes in gene regulatory elements are important determinants of neuronal development and diseases. Using massively parallel reporter assays primary human cells from mid-gestation cortex cerebral organoids, we interrogated the cis-regulatory activity 102,767 open chromatin regions, including thousands sequences with cell type-specific accessibility variants associated brain regulation. In cells, identified 46,802 active enhancer 164 that alter activity. Activity was comparable...
The molecular organization of the human neocortex historically has been studied in context its histological layers. However, emerging spatial transcriptomic technologies have enabled unbiased identification transcriptionally defined domains that move beyond classic cytoarchitecture. We used Visium gene expression platform to generate a data-driven neuroanatomical atlas across anterior-posterior axis dorsolateral prefrontal cortex. Integration with paired single-nucleus RNA-sequencing data...
Neuropsychiatric genome-wide association studies (GWASs), including those for autism spectrum disorder and schizophrenia, show strong enrichment regulatory elements in the developing brain. However, prioritizing risk genes mechanisms is challenging without a unified atlas. Across 672 diverse human brains, we identified 15,752 harboring gene, isoform, and/or splicing quantitative trait loci, mapping 3739 to cellular contexts. Gene expression heritability drops during development, likely...
The lateral septum (LS) is a midline, subcortical structure that critical regulator of social behaviors. Mouse studies have identified molecularly distinct neuronal populations within the LS, which control specific facets behavior. Despite its known molecular heterogeneity in mouse and role regulating behavior, comprehensive profiling human LS has not been performed. Here, we conducted single-nucleus RNA sequencing (snRNA-seq) to generate transcriptomic profiles compared recently collected...
The dentate gyrus of the hippocampus is important for many cognitive functions, including learning, memory, and mood. Here, we present transcriptome-wide spatial gene expression maps human investigate age-associated changes across lifespan. Genes associated with neurogenesis extracellular matrix are enriched in infants decline throughout development maturation. Following infancy, inhibitory neuron markers increase, cellular proliferation decrease. We also identify spatio-molecular signatures...
Multiple algorithms are used to predict the impact of missense mutations on protein structure and function using algorithm-generated sequence alignments or manually curated alignments. We compared accuracy with native alignment SIFT, Align-GVGD, PolyPhen-2, Xvar when generating functionality predictions well-characterized (n = 267) within BRCA1, MSH2, MLH1, TP53 genes. also evaluated employed from these (except Xvar) supplied same four including automatically generated by (1) (2) Polyphen-2,...
TP53 is the most frequently altered gene in head and neck squamous cell carcinoma, with mutations occurring over two-thirds of cases, but prognostic significance these remains elusive. In current study, we evaluated a novel computational approach termed evolutionary action (EAp53) to stratify patients tumors harboring as high or low risk, validated this system both vivo vitro models. Patients high-risk had poorest survival outcomes shortest time development distant metastases. Tumor cells...
Between-sample normalization is a critical step in genomic data analysis to remove systematic bias and unwanted technical variation high-throughput data. Global methods are based on the assumption that observed variability global properties due reasons unrelated biology of interest. For example, some correct for differences sequencing read counts by scaling features have similar median values across samples, but these fail reduce other forms variation. Methods such as quantile transform...
Count data derived from high-throughput deoxy-ribonucliec acid (DNA) sequencing is frequently used in quantitative molecular assays. Due to properties inherent the process, unnormalized count compositional, measuring relative and not absolute abundances of assayed features. This compositional bias confounds inference abundances. Commonly normalization approaches like library size scaling/rarefaction/subsampling cannot correct for or any other relevant technical that uncorrelated with size.