Researchers have developed a new open-source computational method, dubbed Spectra, which improves the analysis of single-cell transcriptomic data. By guiding data analysis in a unique way, Spectra can offer new insights into the complex interplay between cells — like the interactions between cancer cells and immune cells, which are critical to improving immunotherapy treatments.
Researchers at Memorial Sloan Kettering Cancer Center have developed a new open-source computational method, dubbed Spectra, which improves the analysis of single-cell transcriptomic data.
"I'm happy to discover new biology," she continues."And I'm just as happy -- perhaps happier -- to build a foundational tool that can be used by the wider community to make many biological discoveries."Along with researchers at MSK, teams from several institutions are already using Spectra to study a variety of diseases, Dr. Pe'er adds.Over the past decade, the"single-cell revolution" has transformed human understanding of health and disease.
The team Dr. Pe'er assembled -- led by co-first authors Russell Kunes, a doctoral student trained in statistics, and Thomas Walle, MD, a physician-scientist with expertise in immuno-oncology -- not only developed the improved method for guiding the data analysis, but they also created a user-friendly interface to facilitate its adoption by other scientists.
Additionally, the authors note, the ability to transfer gleanings from one data set directly to another will speed up and streamline discovery, allowing researchers to refine knowledge across single-cell sequencing studies without requiring complex data integration.A research team has recently made a significant discovery about the evolutionary age of different type of cells in a small animal called Caenorhabditis elegans . By using single-cell ...
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