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Lang, O. W.

Publications and source records attributed to Lang, O. W..

2 recordsLinked to original sources

Multi-modal in situ profiling of human cells using the AVITI24 platform characterizes single-cell responses to acute stress

Cells begin to respond to stress within minutes, but how this early response depends on cell type, neighboring cells, or cell cycle phase has been difficult to determine, because bulk assays average across cells and synchronization can induce stress. We measured 338 transcripts, 48 proteins and phosphoproteins, and six cell paint stains in situ in 1.18 million single cells from four human cell lines exposed to H2O2, alone and in co-culture, and in A549 cells exposed to TNF-, cadmium, dithiothreitol or lipopolysaccharide. In A549 cells, five distinct stressors changed the same targets in the same direction within 15 min, differing mainly in magnitude, and modestly increased JNK phosphorylation. By 30 min of H2O2 treatment, immediate-early genes (FOS, JUN, DDIT3, DUSP1, NR4A1) were induced most strongly in HCT116 and A549 cells. These changes occurred across the whole cell population rather than in a responsive subset. Cell line-specific differences persisted in co-culture, and the response of MCF7 cells did not increase with the number of adjacent, strongly-responding A549 cells. Ordering cells along the cell cycle from the same measurements identified 106 cycle-associated transcripts, and the response varied more between cell lines than among cell cycle phases. Overall, the measured regulators respond to stress within 30 minutes through a largely shared program whose magnitude depends more on cell identity than on cell cycle state or neighboring cell type.

genomics↗

ScriptManager: a platform for scalable and reproducible high-resolution analysis of genomics datasets

BackgroundThe growing diversity of genomic and epigenomic assays has driven a parallel expansion in data formats, analysis workflows, and figure-generation tools. However, tools for analyzing data and assembling publication-quality figures are often specialized to a specific assay, dramatically limiting their interoperability and reproducibility. ResultsWe present the v1.0 release of ScriptManager, a Java-based framework for modular and reproducible analysis and visualization workflows of genomics and epigenomics data. Unlike existing tools specialized for individual assay types, ScriptManager provides a unified and extensible framework for cross-assay visualization and workflow reproducibility. The v1.0 release adds novel analytical modules, GUI session logging, automated unit and integration testing, tutorials, and expanded documentation. It also integrates with the broader reproducibility ecosystem through Singularity containers, Anaconda packaging, and Galaxy XML wrappers. We demonstrate ScriptManagers TagPileup scaling from local single-core execution to a 10,305-job analysis distributed across the Open Science Grid (OSG), with the full workload completing in <2 hours of wall-clock time. ConclusionsScriptManager v1.0 enhances workflow portability, transparency, and reproducibility across a diverse range of high-resolution genomic assays. By coupling a flexible module design with modern reproducibility standards, ScriptManager provides a bridge between exploratory data analysis and formal, publication-ready figure generation. These improvements enable researchers to build, share, and reproduce genomic analyses across diverse computational infrastructures with minimal configuration.

bioinformatics↗