Cellenium-a scalable and interactive visual analytics app for exploring multimodal single-cell data.

SUMMARY: Multimodal single-cell sequencing data provide detailed views into the molecular biology of cells. To allow for interactive analyses of such rich data and to readily derive insights from it, new analysis solutions are required. In this work, we present Cellenium, our new scalable visual analytics web application that enables users to semantically integrate and organize all their single-cell RNA-, ATAC-, and CITE-sequencing studies. Users can then find relevant studies and analyze single-cell data within and across studies. An interactive cell annotation feature allows for adding user-defined cell types. AVAILABILITY AND IMPLEMENTATION: Source code and documentation are freely available under an MIT license and are available on GitHub (https://github.com/Bayer-Group/cellenium). The server backend is implemented in PostgreSQL, Python 3, and GraphQL, the frontend is written in ReactJS, TypeScript, and Mantine css, and plots are generated using plotlyjs, seaborn, vega-lite, and nivo.rocks. The application is dockerized and can be deployed and orchestrated on a standard workstation via docker-compose.

Multipass open-path Fourier-transform infrared measurements for nonintrusive monitoring of gas turbine exhaust composition.

The detection limits for NO and NO2 in turbine exhausts by nonintrusive monitoring have to be improved. Multipass mode Fourier-transform infrared (FTIR) absorption spectrometry and use of a White mirror system were found from a sensitivity study with spectra simulations in the mid-infrared to be essential for the retrieval of NO2 abundances. A new White mirror system with a parallel infrared beam was developed and tested successfully with a commercial FTIR spectrometer in different turbine test beds. The minimum detection limits for a typical turbine plume of 50 cm in diameter are approximately 6 parts per million (ppm) for NO and 9 ppm for NO2 (as well 100 ppm for CO2 and 4 ppm for CO).