Category Archives: josh_pub

Characterization of highly active mutational signatures in tumors from a large Chinese population

Abstract The majority of mutational signatures have been characterized in tumors from Western countries and the degree to which mutational signatures are similar or different in Eastern populations has not been fully explored. We leveraged a large-scale clinical sequencing cohort of tumors from a Chinese population containing 25 tumor types and found that the highly ……

Characterization and decontamination of background noise in droplet-based single-cell protein expression data with DecontPro

Assays such as CITE-seq can measure the abundance of cell surface proteins on individual cells using antibody derived tags (ADTs). However, many ADTs have high levels of background noise that can obfuscate down-stream analyses. Using an exploratory analysis of PBMC datasets, we find that some droplets that were originally called “empty” due to low levels ……

Matrix and analysis metadata standards (MAMS) to facilitate harmonization and reproducibility of single-cell data

A large number of genomic and imaging datasets are being produced by consortia that seek to characterize healthy and disease tissues at single-cell resolution. While much effort has been devoted to capturing information related to biospecimen information and experimental procedures, the metadata standards that describe data matrices and the analysis workflows that produced them are ……

Integrative genetic and genomic networks identify microRNA associated with COPD and ILD

Chronic obstructive pulmonary disease (COPD) and interstitial lung disease (ILD) are clinically and molecularly heterogeneous diseases. We utilized clustering and integrative network analyses to elucidate roles for microRNAs (miRNAs) and miRNA isoforms (isomiRs) in COPD and ILD pathogenesis. Short RNA sequencing was performed on 351 lung tissue samples of COPD (n=145), ILD (n=144) and controls ……

Interactive analysis of single-cell data using flexible workflows with SCTK2.0

Analysis of single-cell RNA-seq (scRNA-seq) data can reveal novel insights into heterogeneity of complex biological systems. Many tools and workflows have been developed to perform different types of analysis. However, these tools are spread across different packages or programming environments, rely on different underlying data structures, and can only be utilized by people with knowledge ……

A single-cell lung atlas of complement genes identifies the mesothelium and epithelium as prominent sources of extrahepatic complement proteins

To understand functional duality of the complement system in host defense and lung injury, a more comprehensive view of its localized production in the lung, and the impact of age on complement production are essential. Here, we explored the expression of complement genes through computational analysis of preexisting single cell RNA sequencing data from lung ……

Smoking Modulates Different Secretory Subpopulations Expressing SARS-CoV-2 Entry Genes in the Nasal and Bronchial Airways

Xu, K., Shi, X., Husted, C., Hong, R., Wang, Y., Ning, B., Sullivan, T., Rieger-Christ, K., Duan, F., Marques, H., Gower, A., Xiao, X., Liu, H., Liu, G., Duclos, G., Platt, M., Spira, A., Mazzilli, S., Billatos, E., Lenburg, M., … Beane, J. (accepted by scientific report) Abstract Background: SARS-CoV-2 infection and disease severity are ……

ExperimentSubset: an R package to manage subsets of Bioconductor Experiment objects

Motivation R Experiment objects such as the SummarizedExperiment or SingleCellExperiment are data containers for storing one or more matrix-like assays along with associated row and column data. These objects have been used to facilitate the storage and analysis of high-throughput genomic data generated from technologies such as single-cell RNA sequencing. One common computational task in many genomics analysis workflows ……

Comprehensive generation, visualization, and reporting of quality control metrics for single-cell RNA sequencing data

Single-cell RNA sequencing (scRNA-seq) can be used to gain insights into cellular heterogeneity within complex tissues. However, various technical artifacts can be present in scRNA-seq data and should be assessed before performing downstream analyses. While several tools have been developed to perform individual quality control (QC) tasks, they are scattered in different packages across several ……

Celda: a Bayesian model to perform co-clustering of genes into modules and cells into subpopulations using single-cell RNA-seq data

Single-cell RNA-seq (scRNA-seq) has emerged as a powerful technique to quantify gene expression in individual cells and to elucidate the molecular and cellular building blocks of complex tissues. We developed a novel Bayesian hierarchical model called Cellular Latent Dirichlet Allocation (Celda) to perform co-clustering of genes into transcriptional modules and cells into subpopulations. Celda can ……