Search the literature by keyword, topic, or author. Filter to articles with full text available.
1073 results
<h4>Summary</h4>Combinatorial barcoding technologies for single-cell nucleotide sequencing, such as split-pool ligation protocols, involve sequential rounds of cell barcoding to uniquely tag individual cells. The rapid adoption of combinatorial barcoding in recent years is due in …
Read PDF<h4>Motivation</h4>Advances in high-throughput chromatin conformation capture have provided insight into the three-dimensional structure and organization of chromatin. While bulk Hi-C experiments capture spatio-temporally averaged chromatin interactions across millions of cells, single-cell Hi-C experiments report on …
Read PDFThis letter comments on the recently published AICellType platform for large language model (LLM)-based cell type annotation in single-cell and spatial transcriptomics. While appreciating the authors' systematic benchmarking and practical contribution, concerns are raised regarding …
Read PDF<h4>Motivation</h4>Single-cell sequencing data analysis requires robust quality control (QC) to mitigate technical artifacts and ensure reliable downstream results. While tools like alevin-fry and simpleaf (and augmented execution context for the alevin-fry), offer flexibility and computational …
Read PDF<h4>Motivation</h4>Dimensionality reduction for single-cell RNA-sequencing (scRNA-seq) data involving multiple biological samples presents a significant analytical challenge.<h4>Results</h4>We introduce MUlti-Sample Trajectory-Assisted Reduction of Dimensions (MUSTARD), an innovative trajectory-guided dimensionality reduction method specifically designed for multi-sample, multi-condition scRNA-seq …
Read PDF<h4>Motivation</h4>Advances in single-cell sequencing have enabled multiomics profiling at unprecedented resolution; however, mass spectrometry-based single-cell proteomics (scMS) remains inherently destructive, precluding simultaneous transcriptomic capture. Unlike antibody-based methods such as CITE-seq, which permit paired profiling but …
Read PDF<h4>Motivation</h4>Quantitative analyses of epithelial-mesenchymal transition (EMT) have been widely used in several areas of biomedical sciences due to its importance in development and cancer progression, but its multi-contextual nature requires standardization and implementation of gene …
Read PDF<h4>Motivation</h4>Accurate prediction of drug response remains a major challenge in precision oncology, particularly at the single-cell level and in clinical settings, due to significant distribution shifts between preclinical models and real-world patient data. Existing approaches …
Read PDF<h4>Motivation</h4>Psoriasis is a chronic, immune-mediated disorder with an unmet need for effective treatments. To systematically prioritize therapeutic targets, we integrated proteome-wide Mendelian randomization (MR) with expression validation in blood/skin, genetic susceptibility analysis, differential gene expression …
Read PDF<h4>Motivation</h4>Single-cell sequencing technologies allow researchers to study cell-cell variation within a cell population. Variations between cells are driven by the underlying biological network, particularly gene regulatory networks (GRNs). GRNs rewire as cells evolve, and different …
Read PDF<h4>Summary</h4>Many single-cell transcriptomics datasets are stored in the HDF5-backed AnnData (H5AD) file format, as popularized by the Python scverse ecosystem. However, accessing these datasets from R, allowing users to take advantage of the strengths of …
Read PDF<h4>Summary</h4>GSEA is a standard approach for pathway interpretation, yet Python ecosystems lack a high-performance implementation aligned with the fgseaMultilevel rare-event estimator target, especially for trajectory-aware rolling-window analysis. Under matched inputs, PyFgsea remains near-identical for normalized …
Read PDF<h4>Motivation</h4>GEDI is a generative framework for multi-sample, multi-condition single-cell analysis that performs batch correction, latent representation learning, and clustering-free differential expression within a unified model. However, the original implementation suffered from prohibitive memory use and …
Read PDF