Emily Shen

All Publications

• Sub-Cluster Identification through Semi-Supervised Optimization of Rare-Cell Silhouettes (SCISSORS) in Single-Cell RNA-Sequencing. Bioinformatics (Oxford, England) Leary, J. R., Xu, Y., Morrison, A. B., Jin, C., Shen, E. C., Kuhlers, P. C., Su, Y., Rashid, N. U., Yeh, J. J., Peng, X. L. 2023

  Abstract

  MOTIVATION: Single-cell RNA-sequencing (scRNA-seq) has enabled the molecular profiling of thousands to millions of cells simultaneously in biologically heterogenous samples. Currently, common practice in scRNA-seq is to determine cell type labels through unsupervised clustering and the examination of cluster-specific genes. However, even small differences in analysis and parameter choosing can greatly alter clustering results and thus impose great influence on which cell types are identified. Existing methods largely focus on determining the optimal number of robust clusters, which can be problematic for identifying cells of extremely low abundance due to their subtle contributions towards overall patterns of gene expression.RESULTS: Here we present a carefully designed framework, SCISSORS, which accurately profiles subclusters within broad cluster(s) for the identification of rare cell types in scRNA-seq data. SCISSORS employs silhouette scoring for the estimation of heterogeneity of clusters and reveals rare cells in heterogenous clusters by a multi-step semi-supervised reclustering process. Additionally, SCISSORS provides a method for the identification of marker genes of high specificity to the cell type. SCISSORS is wrapped around the popular Seurat R package and can be easily integrated into existing Seurat pipelines.AVAILABILITY: SCISSORS, including source code and vignettes for example datasets, is freely available at https://github.com/jr-leary7/SCISSORS.SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

  View details for DOI 10.1093/bioinformatics/btad449

  View details for PubMedID 37498558

• Barriers and Facilitators for Population Genetic Screening in Healthy Populations: A Systematic Review FRONTIERS IN GENETICS Shen, E. C., Srinivasan, S., Passero, L. E., Allen, C. G., Dixon, M., Foss, K., Halliburton, B., Milko, L., Smit, A. K., Carlson, R., Roberts, M. C. 2022; 13: 865384

  Abstract

  Studies suggest that 1-3% of the general population in the United States unknowingly carry a genetic risk factor for a common hereditary disease. Population genetic screening is the process of offering otherwise healthy patients in the general population testing for genomic variants that predispose them to diseases that are clinically actionable, meaning that they can be prevented or mitigated if they are detected early. Population genetic screening may significantly reduce morbidity and mortality from these diseases by informing risk-specific prevention or treatment strategies and facilitating appropriate participation in early detection. To better understand current barriers, facilitators, perceptions, and outcomes related to the implementation of population genetic screening, we conducted a systematic review and searched PubMed, Embase, and Scopus for articles published from date of database inception to May 2020. We included articles that 1) detailed the perspectives of participants in population genetic screening programs and 2) described the barriers, facilitators, perceptions, and outcomes related to population genetic screening programs among patients, healthcare providers, and the public. We excluded articles that 1) focused on direct-to-consumer or risk-based genetic testing and 2) were published before January 2000. Thirty articles met these criteria. Barriers and facilitators to population genetic screening were organized by the Social Ecological Model and further categorized by themes. We found that research in population genetic screening has focused on stakeholder attitudes with all included studies designed to elucidate individuals' perceptions. Additionally, inadequate knowledge and perceived limited clinical utility presented a barrier for healthcare provider uptake. There were very few studies that conducted long-term follow-up and evaluation of population genetic screening. Our findings suggest that these and other factors, such as prescreen counseling and education, may play a role in the adoption and implementation of population genetic screening. Future studies to investigate macro-level determinants, strategies to increase provider buy-in and knowledge, delivery models for prescreen counseling, and long-term outcomes of population genetic screening are needed for the effective design and implementation of such programs. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020198198.

  View details for DOI 10.3389/fgene.2022.865384

  View details for Web of Science ID 000828384700001

  View details for PubMedID 35860476

  View details for PubMedCentralID PMC9289280